INDEXPICT, Pune Synopsis : Concepts-2019
01. Big Data/AI/DL/ML/Pattern Recognition
: - - - 1BD-101 Cognitive Reasoning Engine - Smart Teacher Assistance System based on student thinking and learning trends
: - - - 1BD-102 Increasing Accuracy of GPS using Multiple Receivers
: - - - 1BD-103 Stock Market Prediction : Effect of web-media on stock market
: - - - 1BD-104 VIDEO BASED INDIAN SIGN LANGUAGE RECOGNITION SYSTEM
: - - - 2BD-105 Contextual Recommendation and Summary of Enterprise Communication
: - - - 2BD-106 Missing Child Finder
: - - - 2BD-107 Alert System for Women’s Safety Using Spatio-Temporal Prediction of Criminal Hotspots
: - - - 3BD-108 Qualitative Assessment of Industrial Processes using Sound Analytics
: - - - 3BD-109 Securify "Jeevan"
: - - - 3BD-110 AI Buddy
: - - - 3BD-111 Automated Glaucoma Detection
: - - - 4BD-112 Fake News Detection for Twitter
: - - - 4BD-113 Pedestrian Detection System
: - - - 4BD-114 automated detection of autism
: - - - 5BD-115 Classifying Users and Identifying User Interests based on semantic and contextual analysis
: - - - 5BD-116 Comprehensive Developer Assistant
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
: - - - 5BD-117 Analysis of Sentiment Analysis Techniques
: - - - 6BD-118 Interview bot – A chat bot based approach for interview preparation
: - - - 6BD-119 Automatic detection of road conditions using inertial sensors and route prediction
: - - - 6BD-120 Extract Algorithm, Highlighted Content And Search Algorithm Using Machine Learning And Core Nlp With Scholar Big Data
: - - - 6BD-121 E-Commerce Product Rating Using Customer Review Mining
: - - - 7BD-122 Detection and Classification of Diseases in Tomato Plants
: - - - 7BD-123 Predicting Bus Arrival Time Using GPS And Machine Learning.
: - - - 7BD-124 Malware Classification using Deep Neural Networks
: - - - 8BD-125 Transport Vehicle Selection Predictor
: - - - 8BD-126 CosmoMind: Universal On-board Computing Platform for AI based Drone Payloads
: - - - 8BD-127 Autonomous Naviation in drones using Computer Vision and Artificial Intelligence
: - - - 9BD-128 Real Time Sign Language Translation in Video Sequence
: - - - 9BD-129 Stock Prediction using Mahout Framework
: - - - 10BD-130 Slack Integration with Simple App
: - - - 10BD-131 Artificial Intelligence Dietitian
: - - - 10BD-132 Smart assistant system using voice recognition for physically disabled
: - - - 11BD-133 Digitisation and analysis of invoices (A new approach)
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
: - - - 11BD-134 Classifying Re-admission of a diabetic patient using MKNN classifier
: - - - 11BD-135 Classifying Users and Identifying User Interests based on semantic and contextual analysis
: - - - 12BD-136 Comprehensive Developer Assistant
: - - - 12BD-137 Analysis of reception of government schemes and decisions by people
: - - - 12BD-138 Query based Car Make and Model Recognition System using Deep Learning
: - - - 13BD-140 Auto Painter: text to image synthesis
: - - - 13BD-141 BASS - Music for Your Mood!
: - - - 13BD-142 Detecting students Interest in lectures using Deep Learning
: - - - 13BD-144 Music Vidya - Piano Tutor App using DSP and ML
: - - - 13BD-145 Cognitive Reasoning Engine - Smart Teacher Assistance System based on student thinking and learning trends
: - - - 14BD-146 Content and metadata based YouTube tag generation
: - - - 14BD-147 A system for fashion outfit composition using deep learning method
: - - - 14BD-148 DIETOS: PRESONALIZED DIET COMPANION
: - - - 15BD-150 Classification and prediction of cardiac arrhythmia using machine learning
: - - - 15BD-151 Facial Emotion Recognition Based Human Computer Interaction
: - - - 15BD-152 Automatic estimation of age via face recognition
: - - - 16BD-153 Forward Engineering Tool Using Imageprocessing And Hadoop.
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
: - - - 16BD-155 Knowledge graphs for question answering system
: - - - 16BD-156 License Plate Recognition system for vehicles
: - - - 16BD-157 Image generation of Human faces from text description using Generative Adversarial Networks
: - - - 17BD-159 sss approach for crop selection based on Agro-Climatic Conditions
: - - - 17BD-160 Content and metadata based YouTube video tag generation
: - - - 17BD-161 Fake News Detection Using Machine Learning
: - - - 17BD-162 A Disease Prediction and Rectification System for Banana Leaf using CNN
: - - - 18BD-164 Conrod Object detection for right positioning
: - - - 18BD-165 Analysis of Machine logs to Detect patterns and Perform Auto-remediation
: - - - 18BD-166 Painting Recommendation using Apache Mahout Engine
: - - - 19BD-167 Prediction of Alzheimer's disease Using Machine learning Techniques
: - - - 19BD-168 Enhanced Knowledge Understanding and Querying for Commercial Applications
: - - - 19BD-169 Application for Fruit Classification and Grading System using Transfer Learning
: - - - 19BD-170 Medical waste detection
: - - - 20BD-171 Deep Learning in Medical Image Analysis
02. Database and Storage/System Application/Expert System
: - - - 21DS-201 Securing data in cloud
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
: - - - 21DS-202 School Recommendation System
: - - - 21DS-203 Cloud Based Linux and DevOps Skills Assessment Application
: - - - 21DS-204 Data logger
: - - - 22DS-205 Amigos Tracker Android Application
: - - - 22DS-206 Tool Calibration Traceability
03. Netwoking & Networking Application/Cloud Computing/Data Security/Cyber Security
: - - - 23NN-301 SISA: Securing Images by Selective Alteration
: - - - 23NN-302 Cryptobugs
: - - - 23NN-303 Iaas as a Platform
: - - - 23NN-304 Detection of Phishing Sites
: - - - 24NN-305 Smart Business Continuity Application
: - - - 24NN-306 Hybrid approach towards IDS,IPS and IRS using Reinforcement learning
: - - - 24NN-307 Optimized use of Memory to Increase Efficiency and Security in Cloud Computing
: - - - 25NN-308 Monitoring of network using an Open source Software MonIt
: - - - 25NN-309 Three Tier Architecture for Document Authentication
: - - - 25NN-310 E-Certificate Authentication System using Blockchain
: - - - 26NN-311 Autoscaled Instance Management
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
04. Blockchain Applications
: - - - 27BA-401 Electronic Healthcare record system
: - - - 27BA-402 LifeBlocks - A Blockchain based Insurance Platform
: - - - 27BA-403 Providing Access Control to IoT devices using Blockchain
: - - - 28BA-404 Secure Distributed Storage System for Large-scale IoT Data Using Blockchain
: - - - 28BA-405 Decentralized Crowdfunding Application on Blockchain
: - - - 29BA-406 Decentralized Voting System
: - - - 29BA-407 Ethereum based Blockchain implementation for peer review system.
: - - - 29BA-408 Health Data Exchange Platform using Blockchain
: - - - 30BA-410 Supply Chain Management for Automobile Industry
05. Augmented Reality / Virtual Reality
: - - - 31AR-501 2D to 3D Image Conversion System
: - - - 31AR-502 Gesture Controlled Car Driving Simulator
: - - - 31AR-503 Augmented reality application for home shopping in Mcommerce using Markerless Tracking
: - - - 31AR-504 Educat-AR: Dissemination of conceptualized information using Augmented Reality and Image Processing
: - - - 32AR-505 VR Space Explorer
: - - - 32AR-507 Fit-O-Fun
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
: - - - 32AR-508 Education using Virtual Reality
06. Multimedia/Image Processing/DSP
: - - - 33MI-601 Optical Coherence Tomography(OCT) Report Generator
: - - - 33MI-602 Automatic Generation of Highlights of a Cricket Match
: - - - 33MI-604 E-ticketing system for intercity public transport
: - - - 34MI-605 Smart E Stick for visually impaired using android application and cloud vision API
: - - - 34MI-606 Automated Self Monitoring Calorie Estimation on Food
: - - - 35MI-607 Analysis of ocular disease using multiple Informatics domain
: - - - 35MI-608 Human Activity based home automation and energy saving
: - - - 35MI-609 Human Activity based home automation and energy saving
: - - - 35MI-611 Smart drone implementing detection and tracking of Humans using ML
: - - - 36MI-612 HAIRCUT RECOMMENDATION SYSTEM
: - - - 36MI-613 Automating Data Entry Forms for Banks Using OCR
: - - - 36MI-614 Performance Evaluation of Feature Extraction Technique For Facial Analysis
: - - - 36MI-615 Automating Data Entry Forms for Banks Using OCR and CNN
07. Wireless and Mobile Communication/Wireless Sensor Netwoks
: - - - 37WM-701 LoRa based meters
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
: - - - 37WM-702 Distributed EM spectrum database based on Blockchain
: - - - 37WM-703 Fire detection & prevention with robot using WSN
: - - - 37WM-704 Spectrum sensing using machine learning for cognitive radio
: - - - 38WM-705 Orthogonal Frequency Divison Multiplexing
: - - - 38WM-706 Alamouti space time block codes
: - - - 38WM-707 Design and fabrication of multiband patch antenna for wireless application using HFSS.
08. VLSI/Embedded Systems/Communication Systems
: - - - 39VE-801 SITWELL- POSTURE MONITORING DEVICE
: - - - 39VE-802 Fall Detection Device for Senior Citizens
: - - - 39VE-803 Human tracking with a drone
: - - - 39VE-804 Advanced Driver Assistance System
: - - - 40VE-805 Characteristics validation of NiTino,through Joule Heating
: - - - 40VE-806 Smart E-Rationing System
: - - - 41VE-807 Waste Collection Management System
09. IOT/Industrial IOT/Smart Cities/Sustainability
: - - - 42IS-901 Portable Home Automation with machine learning
: - - - 42IS-902 Development of real time water monitoring system using IoT
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
: - - - 42IS-903 Internet of Things based Smart Parking System using RFID
: - - - 43IS-904 BIOMETRICS BASED STUDENT ATTENDANCE MONITORING SYSTEM
: - - - 43IS-905 Drone based Medical Service
: - - - 43IS-906 Emergency Vehicle Alert System
: - - - 44IS-907 Automated fogger system
: - - - 44IS-908 Wireless Charging of Electric Bus using Inductive Coupling Method
: - - - 44IS-909 IoT Based Smart Irrigation System
: - - - 45IS-910 Anti-Theft Vehicle Tracking System
: - - - 45IS-911 Automated Shopping System
: - - - 45IS-912 Intelligent System Using IoT for Women Safety
: - - - 45IS-913 Emergency Vehicle Alert System
: - - - 46IS-915 Real Time Drive Monitoring System for Drive Safety Using Machine Learning on IOV
: - - - 46IS-916 R-Notifier
: - - - 46IS-917 QR based school children safety enhancement
: - - - 46IS-918 Land Use Change Detection for solid waste management
10. Others
: - - - 48OT-101 Movie Review System
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
INDEXPICT, Pune Synopsis : Concepts-2019
: - - - 48OT-102 Quantitative Tool for Neuro-therapy
: - - - 48OT-103 Solar Hybrid Inverter With Sun Tracking Mechanism
: - - - 48OT-104 Computational module for the hearing-impaired
: - - - 49OT-105 Complaint Management System
: - - - 49OT-106 Product recommendation system
: - - - 49OT-107 Youtube Video Recommendation Based On User Comments And Its Statistical Analysis
: - - - 50OT-108 KrushiDhan
: - - - 50OT-109 Extending Csmith, a compiler testing tool for GCC C Extensions
: - - - 50OT-110 Autonomous Robot Mapping for Marine Inspection and Surveillance System
: - - - 51OT-111 Coconut Tree Climbing and Harvesting Robot
: - - - 51OT-112 Exoskeleton Arm
: - - - 51OT-113 Bio Medical Waste Management Audit Tool
: - - - 52OT-114 A framework for the enunciation of Sanskrit words and phrases
: - - - 52OT-116 Lyft please
: - - - 52OT-120 SMART USB CABLE
: - - - 52OT-121 Design and Prototyping of an Autonomous Underwater Surveillance
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||:::
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
: Different students have different abilities, backgrounds, interests, goals, priorities and
hence, "one size" education does not fit all students. Our project represents a new, unique and
indeed, much-needed direction that is complementary to the current trend of global education.
While current tools do assess students, they are based solely on the course-specific technical
skills. With the aim to provide more comprehensive analysis, our system computes the extent to
which the students’ cognitive skills such as aptitude, logical reasoning, seriousness and interest
influence the students’ learning and thinking patterns.
By integrating Bayesian Knowledge Tracing with knowledge-based clustering, the
proposed tool provides the teacher with an accurate periodic report and a detailed demographic
of the class. By adopting this probabilistic approach, we have countered the issue of any student
relying solely on guesswork as well as one making silly mistakes, thus accurately analysing the
extent to which the student has learned. The system also equips the teacher with specific
information and suggestions regarding each student. In addition to this, we formulated buckets
of students having similar knowledge and trends of learning through frequency clustering on
binary categorical data. Consequently, this system is capable of evolving individually for each
student as the course progresses, thus aiding the teacher to enhance the quality of education as
a whole.
Abstract
Cognitive Reasoning Engine - Smart Teacher Assistance System based on student thinking and learning trends
BD-101 :
: GPS is a technology that allows for accurate tracking of various parameters, namely
speed and locationToday's GPS technology is not accurate enough to provide useful data about
a vehicle speed and position with respect to something as restricted as sidewalk or in
battleground.Conventional GPS technology is theoretically accurate to about 10 meters which
is not sufficient enough for military applications as well as for the consumer use.Current
Technology like Differential-GNSS or WAAS (Wide Area Augmentation system) either requires
expensive equipment or more expensive and complex operations like launching more satellites.
The proposed system will give GPS position with minimum errors as well as positional accuracy
can be increased up to 2-3 meters.This proposed system will consist of multiple GPS receivers
which will communicate with each other to give more accurate results.Also, this system will
select probable position of object based on cluster elimination technique.
Abstract
Increasing Accuracy of GPS using Multiple ReceiversBD-102 :
: Stock market volatility is influenced by information release, dissemination, and public
acceptance. With the increasing volume and speed of social media, the effects of Web
information on stock markets are becoming increasingly salient. This report would focus on
analysing effects of news media and historical stock data on stock market prices. This will be
realised with the help of machine learning and deep learning algorithm such as Recurrent Neural
Network (RNN) to improve upon the existing prediction model.
Abstract
Stock Market Prediction : Effect of web-media on stock marketBD-103 :
: Hearing impaired people use sign language as their prime means of communications.
Developing a tool for interpreting signs in a video helps us to understand hearing impaired
people. We have developed a system that recognizes signs in a video. For processing purpose,
we have used Titan XP GPU that considerably reduces processing time. A database for 13
different video signs of animals is created consisting total 2340 videos. The temporal features of
a video-based gesture are extracted using backward predictions. The complete sign in a video is
represented in a single image. Matlab R2018b is used for complete programming of the project.
For getting maximum accuracy, deep learning is used for training the database. The database
containing 13 classes was trained using different transfer learning methods such as AlexNet,
GoogleNet, Vgg16 & Vgg19. AlexNet gives the maximum validation accuracy of 97.37%. Real
Abstract
VIDEO BASED INDIAN SIGN LANGUAGE RECOGNITION SYSTEMBD-104 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 1
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
time sign recognition accuracy is improved using two-stream CNN. This two-stream CNN takes
two different inputs, first a feature image formed using video input , and second, the random
frames selected from the recorded video. At present, the real time accuracy is approximately
92.3%. A stand-alone application is created. Moreover, since the proposed scheme compresses
the motion information of a video sign into a single image, it allows for using simple
convolutional neural networks where the temporal dimension is eliminated. This is actually
advantageous for both computational and storage requirements. Further the algorithm can be
modified for other static & dynamic gesture detection of Indian Sign Language.
: Employees in modern organizations employ communication and collaboration
platforms such as mailing lists, chat rooms, etc. Given the huge volume of messages exchanged,
it becomes difficult and time-consuming for a user to keep a track of the messages, especially if
the users span across time-zones. Also, team structures and boundaries in an organization are
dynamic and flexible. Current approaches are proprietary and cannot be modified to suit
corporate communication platforms in an organization. This project plans to address the above
problems using Deep Learning and Social Network analysis. Our aim is to make use of latest
research in Natural Language Processing to discover and recommend past communication
based on the context of messages and automatically generate a summary of user-relevant
information. The context includes the topic of communication as well as work-social
relationships between users in the conversation. We will build algorithms for this solution,
demonstrate their efficiency and create demo-able implementation using standard tools in
machine/deep learning ecosystem.
Abstract
Contextual Recommendation and Summary of Enterprise CommunicationBD-105 :
: Proposed System is composed of two modules, one will be an Android application which
will be based on community and another will be an algorithm to recognize faces.
For a human it’s easy to recognize faces but doing it simultaneously to multiple
locations and to remember all the faces is hard task. Face recognition is technology based on
deep learning makes this task easy. Our system will detect face from the photo submitted by
parents and train itself. After that if the child comes in contact with cameras or any person
captures the photo of the child then system will detect all the faces along with face of child from
the photo using HOG (Histograms of gradient method) and classify them using SVM or KNN
classifier. If the child’s photo is successfully classified then system will look after his details for
that we will be using CBIR(Content based image retrieval) method to search his details using
image instead of legacy search algorithms for efficiency and using those details and location
nearby police station and parent will get a notification.
Abstract
Missing Child FinderBD-106 :
: Crimes against women are a common social problem affecting the quality of life of
women. Crimes could occur everywhere. However, it is common that criminals work on crime
opportunities they face in most familiar areas for them. By providing a machine learning
approach to determine the criminal hotspots and find the type, location, and time of committed
crimes we hope to make our community safer for the women living there and the ones who will
travel there. With the increase of crimes, law enforcement agencies are continuing to demand
advanced geographic information systems and new machine learning approaches to improve
crime analytics and prediction to better protect their communities. We aim at building an alert
system for women’s safety using machine learning prediction models. These models will help to
achieve a deeper understanding of criminal hotspots. The alert system will function through an
Android application that will deliver alerts to women if and when the women enter a
neighbourhood susceptible to danger. The alerts will be based on a static database that is
obtained as an output of the machine learning prediction.
Abstract
Alert System for Women €™s Safety Using Spatio-Temporal Prediction of Criminal HotspotsāāāāBD-107 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 2
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
: Analytical models built using Machine Learning and Deep Learning techniques will
monitor sound from production line machinery with an aim to identify anomalies, assess the
quality of produced goods, classify patterns of equipment failure and predict issues before they
interrupt production.
This enables anticipation of problems with real-time alerts, reduction of unplanned
downtime with predictive analytics, and ensures that the produced goods meet the quality
standards.For advanced analytics using unstructured data such as sound, sending the raw data
to cloud infrastructure and getting the results back from the cloud could lead to significant
delays.This makes any real-time analytics using such unstructured data over cloud computing
platform infeasible.
Edge computing addresses this by using powerful tiny computers at the "edge" of the
IoT network (i.e. at the point of sensor deployment), and we run our Analytical Models on those
computers locally, without any need of communication with the cloud. This results in an instant,
real-time analytics based on audio-visual data with the results displayed right there and then.
Abstract
Qualitative Assessment of Industrial Processes using Sound AnalyticsBD-108 :
: The aim of the project is to secure women's life and make them feel safe. This project is
the combination of hardware and software. Biosensors are used in wearable device(Hexiwear)
to measure physiological parameters such as pulse rate, respiration rate, skin temperature,
heart rate and sweat level. Whenever there is some odd situation certain changes takes place in
the body like increase in sweat level, anxiety, etc. So, these readings will be sent to the android
application. The algorithm in the android application will check for abnormal readings and will
detect them. The normal and detected abnormal readings will be sent to the server machine and
then if there are abnormal ratings the security alarm will set on and simultaneously notification
messages will be sent to the contacts whose numbers are given as emergency contacts by the
user, otherwise if there are normal ratings, then no action will be taken just the data will be
stored. This application helps woman get help from the people who can reach to her with great
accuracy. Apart from women the system will also be useful to kids, elderly people and employees
at work place, especially the conditions where the employees are working at odd time. The
system will help in early detection of vulnerable situations and provide timely help.
Abstract
Securify "Jeevan"BD-109 :
: Chatbots can nowadays chat like a human being and they can learn from experience. At
initial stage rule-based chatbots rapidly changed to dynamic chatbots with development of
artificial intelligence (AI). The purpose of this research is to develop a chatbot which simulates a
human conversation. It uses recent NLP techniques to understand context of conversation in
basic language(English) and gradually progress towards dynamic responses.
Our model converses by predicting the next sentence given the previous sentence or
sentences in a conversation. The bot will level up, after sufficient learning at the current stage to
provide more friendly responses. These friendly responses help the person to always have a
friend chatbot with whom we communicate, sharing experiences of the day to day life, which
gives suggestions just like a friend. This model can be further extended into a product which will
work with multiple languages.
Abstract
AI BuddyBD-110 :
: Glaucoma is a debilitating optical degeneration disease that can lead to vision loss and
eventually to blindness. Given its asymptomatic nature, most people with Glaucoma aren’t even
aware that they have the disease. As a result, the disease is often left untreated until it is too
late. Detecting the presence of Glaucoma is one of the most important steps in treating
Glaucoma, but is unfortunately also the most difficult to enforce.A detailed literature survey of
Abstract
Automated Glaucoma DetectionBD-111 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 3
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
preprocessing, feature extraction, feature selection, Deep Learning (DL) techniques and data
sets used for testing and training purpose was conducted. Automated prediction of glaucoma is
very important and unfortunately a little work has been done in this regard and minimum
accuracy has been achieved. The application aims at bringing the pre-diagnosis to everyone
which will give a basis for the investigator to take further decisions regarding diagnosis and
treatment of patients. The mobile nature of the system will enable it to be used in rural and
inaccessible areas as well. The diagnosis equipment being expensive is not accessible to
investigators at pre-diagnostic level. So to provide a preliminary test of optic nerve damage and
analysis.
: The extensive spread of fake news has the potential for extremely negative impacts on
individuals and society. Therefore, fake news detection has recently become an emerging
research that is attracting tremendous attention.Twitter is often used to repeatedly spread false
information during and also after the elections. By using machine learning technique for the
detection of fake news on Twitter, we hope to provide the user an idea about the truthness of
the given tweet. We have generated our own dataset with the help of Twitter API. By cosidering
various text based features and user based features we have trained our machine learning
model. The user gives the URL of the specific tweet using ourwebsite and the back end
calculates and gives the percentage indication of the news being fake or real. Ensemble learning
is used to build the machine learning model after choosing the best suitable models for fake
news prediction.
Abstract
Fake News Detection for TwitterBD-112 :
: It happens in the blink of an eye. You’re driving and take your eyes off of the road to
reach for your coffee cup or turn around to tell your kids to quiet down, and when you look
ahead, a pedestrian is crossing the road right in front of you. You hit the brakes—but it may be
too late. Unfortunately, this scenario is all too common. One out of three vehicle-pedestrian
crashes involves a vehicle going straight as a pedestrian crosses the road. And fatalities involving
vulnerable road users, such as pedestrians, bicyclists, and motorcyclists, have increased over the
past decade.A vehicle’s pedestrian detection system acts as an extra set of eyes for motorists,
helping them avoid potentially catastrophic collisions.The main objective of this project is to
detect the pedestrian using image processing and machine learning techniques. In recent years,
deep learning and especially Convolutional Neural Networks (CNN) have made great success on
image and audio, which is the important component of deep learning. Artificial designed
methods of feature extracting has an imperfect description of pedestrian in the complex
background. In this project, we propose a pedestrian detection method based on deep
convolutional neural network with multi-layers.It can make full use of the advantages of deep
convolutional neural network and extract features from the database of pedestrian detection.
Till the date we have managed to run all the programs in openCV and literature survey to derive
the algorithm to be used which might be efficient and optimized to detect whether the picture
provided from the database consists of pedestrian or not.
Abstract
Pedestrian Detection SystemBD-113 :
: Autism Spectrum Disorder (ASD) is a group of heterogeneous developmental
disabilitiesthat manifest in early childhood. The diagnosis of ASD is often restricted to the
assessment ofthe behavioral and intellectual abilities of a child which is subjective, time
consuming and doesnot always provide conclusive evidence for its early detection. Diagnosis
based on MRI can beobjective, can help understand the brain alterations in ASD, and can be
suitable for earlydiagnosis. However machine learning techniques on MRI derived brain features
have beensuccessful with high classification accuracies (70%) for well-matched small datasets (n
< 200).The studies using the large dataset (n > 500) have reported low classification accuracies
(~60%).In this project, the dataset is first collected and further pre-processing is done on it
andfinally feature extraction is done followed by using machine learning algorithms for the
Abstract
automated detection of autismBD-114 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 4
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
detectionof autism. This project aims to improve the accuracy (>70%) of detection for a large
dataset (n >400) by using efficient machine learning algorithms like Random Forest.
: With the development of the Internet, a more personalised and customized service is
expected from service providers. The analysis of user behaviour and interests can be done to
achieve the same. Social networks can help provide a deeper insight into the user and his/her
activities, the knowledge of data mining is used to analyze the degree of the user interest. The
proposed system utilizes Natural Language Processing techniques to extract and process
relevant data from large user interaction datasets acquired from social networks. That data
further is used for accurate user behaviour and interest analysis by employing machine learning
techniques. We examine the conversations of every user to determine their interests in various
fields, as well as perform contextual analysis to infer about his/her stand in respective
conversations. Such behavioural information will be used for probabilistic classification of users
into predetermined buckets. User characteristics upon which classification is to performed is
obtained by supervised and unsupervised algorithms. After identifying the distinct categories to
classify users into, we can successfully segregate them. This proposed system is useful for
personalised notification feed generation according to behaviour and interests.
Abstract
Classifying Users and Identifying User Interests based on semantic and contextual analysisBD-115 :
: Chatbots and virtual assistants represent a potential shift in how people interact with
data and services online. Thus, they are a part of the evolution in user interface, which started
initially with command line, moved over to GUI (Graphical User interface) and further now has
moved on to Voice based Inter-faces i.e. Chatbots. Chatbots are machine agents that serve as
natural language user interfaces for data and service providers. Currently, chatbots are typically
designed and developed for Mobile messaging applications. The current interest in chatbots is
spurred by recent developments in artificial intelligence (AI) and machine learning . Chatbots are
seen as a means for direct user or customer engagement through text messaging for customer
service or marketing purposes, bypassing the need for special-purpose apps or webpages.
We propose to develop a voice based assistant aiding developers and coders to increase
the efficiency of their work by assisting in various trivial but consequential tasks like executing
terminal commands, resolving code related queries by providing concise and time efficient
solutions with integration with StackOverflow, automatic high level code summarization to
understand code snippets, executing commands like creating, forking, branching repositories
related to Version Control Systems like Github on voice input and creating Java based
documentation for a given Java code snippet.
Abstract
Comprehensive Developer AssistantBD-116 :
: Emergence towards valuing customer reviews and their opinions is the prime propelling
factor for any exploring business. Electronic Commerce has clinched the world, and the majority
preferring to buy products through these websites online. Due to the increase in demand for
e-commerce with customer’s preference towards online purchasing of products over physically
moving from shop to shop (offline purchasing), there is the huge amount of information being
shared to and fro. The e-commerce websites are loaded with immense volume of data and
customer reviews thus being generated. This huge volume of data is in its diversity and its
structural randomness. The customers face difficulty in precisely finding the review for a
particular feature of a product that they intend to buy. Also, there are mixtures of positive and
negative reviews thereby increasing the complexity for customers to find a cogent response. So
to avoid this confusion and make this review base more transparent and user friendly, a
technique to extract feature based opinion from a diverse pool of reviews and processing it
further to segregate it with respect to the aspects of the product and further classifying it into
positive and negative reviews using machine learning based approach. The analysis of the data
generated in huge amount holds the prime centred topic, underlying Data Analytics. This paper
proposes the study and analysis of obtaining the best methodologies on sentiment analysis of
Abstract
Analysis of Sentiment Analysis TechniquesBD-117 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 5
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
consumer reviews in context to the features of a product. The system aims at providing a
summary that represents the extent to which the consumers who had already bought the
particular product were or were not satisfied with the specific feature of the product. Due to
this sentiment analysis, there is a feedback environment being generated for helping customers
buy the right product and guiding companies to enhance the features of product suiting
consumer‘s demand.
: Preparing for job interviews is very difficult. A lot of candidates are not prepared for the
interviews and so they are not able to fetch their dream jobs. Mostly candidate's selection is
based upon the answers given in the interview. People will definitely hire those candidates who
show interest and positive attitude. Using neural network we are proposing an application
framework which would help candidates in preparing for the interviews. This involves neural
network working for predicting a section of an interview and providing real-time feedback and a
report. Using CNN, emotional analysis is performed on the video stream and realtime updates
on the emotion is provided by means of visualization, Candidate’s answers are evaluated based
on their sentiments . Further, AIML is utilized for chat-bot interaction during the process. The
chat-bot ask the questions to the candidate and candidate's response is recorded and analysis is
done and a simple report is generated. All these together will try to prepare the candidate for the
interview as a whole .
Abstract
Interview bot €“ A chat bot based approach for interview preparationāāāāBD-118 :
: Nowadays, drivers cannot avoid bumpy roads because of unfamiliarity with traffic
conditions, and poor visibility may cause traffic accidents. Therefore, the state of the roadways
and driving safety are important topics. To alleviate this problems mobile application can be
used, as mobile phone technology has evolved to enable miniature devices that has capability of
containing powerful sensors. The functionalities of these sensors, such as accelerometers,
present in smartphones is capable of automatically detecting potholes in real-time, monitoring
road traffic conditions and also they are used by GPS for plotting the location of potholes on
Google Maps.The aim is to evaluate a Pothole Detection System, which involves processing
sensor readings and judging the accuracy of the system using a neural network Clustering is
used to group potholes, and supervised learning algorithms is used to train the system.
Ultrasonic sensors are used to detect the potholes. This serves as a valuable source of
information to the government authorities and vehicle drivers. This play a proactive part in
improving road conditions in developing countries.
Abstract
Automatic detection of road conditions using inertial sensors and route predictionBD-119 :
: The world of computer science has more concepts with their algorithm. When some
new concept is built and then new algorithm should be build. There are n numbers of algorithm
stored in some document. Computer science people require searching some algorithm, and it’s
very difficult to find the relevant algorithm. To overcome this problem we are going to build a
system for algorithm searching and extracting highlighted points having best ranked algorithm.
We will identify and extract algorithm representations in a heterogeneous pool of intellectual
documents. In this system, the main formation/weight of PDF documents is calculated by
TF-IDF technique, each and every word having its weight based on that ranked up technique is
going to work. For developing purpose the real time PDF data will be downloaded from
CiteSeerX site.
Abstract
Extract Algorithm, Highlighted Content And Search Algorithm Using Machine Learning And Core Nlp With Scholar Big Data
BD-120 :
: Today E-commerce have become an important part of our day to day life and people are
getting dependent on these website products. The user reviews too, are becoming important for
customers. So, through this project we are building a algorithm, which rates the E-commerce
Abstract
E-Commerce Product Rating Using Customer Review MiningBD-121 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 6
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
products based on sentiment analysis of user reviews. With this shopping for customers will
become very convenient as well as time saving from reviewing large set of user reviews. The
Web has become an outstanding way of expressing opinions about all products and service.
Most of the Web sites containing such view are astronomically vast and it is promptly
incrementing. The buyer reviews in web sites are truly useful for product recommendation in
which fulfilled buyers tell other persons how much they like an originality of product
: India is widely considered to be an agrarian nation. It is the second largest producer of
wheat and rice which are the world’s major food staples. The agricultural system forms the
backbone of the Indian economy and the country stands second worldwide in agricultural
output and yet, this sector remains largely disorganized, underdeveloped and characterized by a
lack of penetration of technology. Crop diseases, in particular is a growing concern faced by
farmers these days as the weather and climate is becoming erratic and more unpredictable than
ever. There is a lack of proper infrastructure for detection and identification of crop diseases.
Farmers face significant losses as a result of destruction of crops due to various such diseases.
Our area of focus was classification of diseases in tomato plants. We intend to design
and build a system that identifies tomato plant diseases based on the input image of the plant
leaf. Using the novel technology of deep learning, higher accuracy can be achieved for a wider
range of diseases and larger datasets. There have been very few attempts to implement such an
application in real time although high accuracy has been achieved during training and testing. An
interactive image segmentation technique can be employed using Graph Cut algorithm.
Processing and storage constraints are eliminated with the help of Cloud platform. We also aim
to make the application more comprehensive by providing the farmer with remedies and
preventive measures stored on the Cloud, for the detected disease.
Abstract
Detection and Classification of Diseases in Tomato PlantsBD-122 :
: The bus companies generally provide bus timetables on the web. Such bus timetables
only provide limited information (e.g. operating hours, time intervals) which are not timely
updated according to instant traffic conditions. Although many commercial information
providers offer the real time bus arrival prediction information the service usually comes with
prestigious cost. State of the art systems provide this meta data by means of an in vehicle device
which accepts driver input, such as the current route, as well as by estimating arrival times based
on current vehicle location, past travel time and the official route schedule.
The main objective of our system is to develop an android application to provide real
time bus arrival information. This system use real-time vehicle tracking using a Global
Positioning System (GPS) technology module to receive the location of the vehicle. There will
also be an android application which will give real time schedule of buses. Also it can give quick
and real time replay for enquiry, via server. Also in case of bus failure or breakdown, the
notification will be sent to system, with Bus location. If a user don’t have a mobile phone he can
get information of buses at his bus stop for all the buses which are going from that bus stop, and
for the passengers inside the bus we are providing a screen on that screen we can display the
current bus stop, next bus stop and last stop.
We are using Haversine algorithm for distance calculation, Bearing algorithm for to
detect bus direction of travelling, k-Means for location clustering.
Bus monitoring system can help transportation authorities efficiently monitor all the
buses and improve the operational efficiency of the entire transportation system.
Abstract
Predicting Bus Arrival Time Using GPS And Machine Learning.BD-123 :
: The explosive growth of malware variants poses a major threat to information security.
Traditional anti-virus systems based on signatures fail to classify unknown malware into their
corresponding families and to detect new kinds of malware programs is another big challenge.
Accurate classification of .asm files of malware can in fact provide an early stage remedy as all
the malware classes’ treatments are known which are put forward roughly in a same way. So, a
Abstract
Malware Classification using Deep Neural NetworksBD-124 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 7
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
kind of resistance this classification can offer to any system. In this paper, a comparative analysis
on two different approaches has been done that can be used for more accurate classi?cation on
the dataset provided by Microsoft in” Microsoft Malware Classi?cation Challenge (BIG 2015)”.
In the first approach, grey scale images are taken that are formed by reading the assembly ?les of
malwares as binary ?les and converting them to grey scale image. Then a CNN model is applied
on these images for classifying them in their respective classes of malwares. In second approach
text classi?cation is used where the assembly ?les of malwares are taken and then features
extractions like count vector and ngram are used. We build a Deep Neural Network model on
these features for classi?cation.
: Vehicle Selection Predictor is a new and important concept in transportation studies. In
recent few years, prediction model was designed for the prediction of prices of vehicles. In this
project, we are trying to build a prediction model for vehicle selection based on its usage. In this
project, we consider the problem of vehicle selection for transportation using a multi-criteria
decision-making approach. The problem includes several conflicting factors which are economic
and technological factors. The vehicle has its own specifications/factors like load it can handle,
an average of the vehicle, design of vehicle etc. Based on these factors the transport agency
should choose a vehicle for a particular delivery. Hence, to predict the selection of vehicle
depending on its specifications, the system will be designed by using machine learning
algorithms. While designing the model feature selection is a very important aspect. This paper
mainly focuses on feature selection and building the predictive model.
Abstract
Transport Vehicle Selection PredictorBD-125 :
: Drone is used in various domains like agriculture, defence, mapping and surveying. With
the increase in applications, there is increase in payloads which apparently generates large
amount of data. Latency occurs while transferring data between the drone and ground stations
and further relays the processing and decision making. Thus, to eliminate the latency there is a
need of on-board processing which process data in real-time and take decisions with the help of
Artificial Intelligence quickly.
The proposed solution is to develop an on-board processing platform having AI
powered functionalities. CosmoMind comprises of hardware accelerator for AI workloads and
high-performance processor to take real-time decisions. With such high-speed processing and
AI specific software algorithms, CosmoMind eliminate the latency which occurs while data
transfer in traditional systems. With real-time Actionable Data and all the decisions taken
on-board, Drone/UAV’s Flight Control is guided for further flying instructions, all the decisions
taken on-board are immediately given to the flight controller for further traversing. CosmoMind
includes a universal connector which has ability to connect all types of drone payloads and
supports all communication protocols.
In CosmoMind, with the help of hardware accelerator one can execute machine learning
models like DNN, CNN, RES-NET 50, Inception V3, etc. The high-performance processor is
capable of implementing computational tasks based on RNN and ANN. CosmoMind has
on-board storage facility to store data locally and supports communication protocols like LORA,
Wi-Fi, Bluetooth, 4G-LTE, etc. Universal connector included in CosmoMind supports all types of
interfaces like USB3.0, USB2.0, RJ45, HDMI, Display Port, CSI, PCIe, 60 pin ex-HAT connection,
40 pin GPIOs.
Abstract
CosmoMind: Universal On-board Computing Platform for AI based Drone PayloadsBD-126 :
: Drones are widely being used in many industries and have impacted and also their cost
benefits are huge. Currently, most of the drone navigation systems are based on integrated GPS
navigation. This system allows a drone to navigate through pre-programmed waypoints.
Autonomous drone with only GPS navigation system may result in collisions with nearby objects
causing serious damages and injuries in the case of humans. To avoid such scenarios ultrasonic
sensor are being used. But the ultrasonic system is not reliable to avoid obstacle intelligently. To
Abstract
Autonomous Naviation in drones using Computer Vision and Artificial IntelligenceBD-127 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 8
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
overcome such dangerous scenarios drones needs to be equipped with intelligence capable to
visualize surroundings and take corrective measures in real-time.
Computer Vision is a technique to sense environmental information. Big amount of
information that can be sensed by this technique. Our system focuses on the development of a
technique that allows drones to fly autonomously with surrounding visual information. With this
visual information and Intelligence, drones can fly autonomously in GPS denied environment or
whenever signal dropouts occur, or when tracking visual targets like moving objects without
knowing their exact GPS location.
Our system uses computer vision techniques for drones like stereo-based visual
navigation, image processing, AI-based SLAM navigation, AI-based Path Planning algorithms,
Object Detection. The stereo vision system can detect an obstacle by implementing the
Semi-Global Matching or Semi-Global Block Matching Algorithm (SGM/SBGM). To avoid an
obstacle, the concept of a collision cone is used. SLAM (Simultaneous Localization And Mapping)
is used to navigate the environment and generate the map of the drone's surrounding and locate
the drone on the map at the same time. With this real-time visual navigation and extracted
information, our AI enabled system plans the optimal path to reaches the desired destination.
: The count of differently-abled people around the globewho communicate with the help
of sign languageis substantially large. Learning sign language for communicating with them is
atedious task. Moreover, it poses a challenge for them to live a normal life like others.
Contemporary approaches to this problem employ the use of gesture recognition by segmenting
the hand using colour masks. Such approaches carry with them a limitation of using the system
where the hand colour is different from other parts of the scene and pre-knowledge of the
colour of hand of the user is also required. In this project, we formulated the given problem as
video classification to classify the user’s actions. We employ Inception 3D architecture to train
the Convolutional Neural Network model to classify the gestures in a given video by calculating
the optical flow between the video frames. The model learns spatiotemporal features in the
video for the classification and achieved an accuracy score of 95% on the ChaLearn dataset. As
there are many different forms of sign-language for communication which differs
geographically, therefore in addition to the above contribution, we have created our own “Indian
Sign Language Dataset”, which contains 105 gestures performed by 21 individuals each. The
dataset would be publicly released soon. We aim to implement the model on our own dataset
and observe the results accordingly.
Abstract
Real Time Sign Language Translation in Video SequenceBD-128 :
: A neural networks based model have been used in predicting of the stock market. One
of the methods, as an intelligent data mining, is artificial neural network (ANN). In this paper
represents how to predict a NASDAQ's stock value using ANNs with a given input parameters of
share market. We used real exchange rate value of NASDAQ Stock Market index. This paper
makes use generalized feed forward networks. The network was trained using input data of
stock market price in between 2012 and 2013. It shows a good performance for NASDAQ stock
market prediction. In a financially volatile market, as the stock market, it is important to have a
very precise prediction of a future trend. Because of the financial crisis and scoring profits, it is
mandatory to have a secure prediction of the values of the stocks. Predicting a non-linear signal
requires advanced algorithms of machine learning. The literature contains studies with different
machine learning algorithms such as ANN (artificial neural networks) with different feature
selection. The results of this study will show that the algorithm of classification SVM (Support
Vector Machines) with the help of feature selection PCA (Principal component analysis) will
have the success of making a profit. We will use C4.5 classifier for learning and testing purpose.
We will compare results of our implementation with SVM and other classification techniques
mentioned in our base paper. We will implement item based collaborative filtering technique
using Apache Mahout Prediction and recommendation library.
Abstract
Stock Prediction using Mahout FrameworkBD-129 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 9
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
: Many platforms are available for searching incomprehensible or inconceivable data for
e.g. Quora,Google etc.But none of them is integrated with Slack.Slack software is cloud-based
collaboration software and is designed to enable users to communicate easily and eliminate the
app fatigue associated with using multiple communication applications.While communicating, if
user finds something incomprehensible or inconceivable then user have to switch to another
platform for scrutinizing the solutions and then user have to put a lot of efforts to find an
optimum solution which generally leads to diminishing returns. Slack is an acronym for
Searchable Log of All Conversation and Knowledge.Slack is a collaboration chat bot used both in
and out of organizations to help teams communicate and coordinate in a more effective
manner.Slack achieves this is by segregating a team into Channels which can be specialized for
different uses as needed. Slack was the first hosted app to allow integrations on its platform.
This was what gave slack its significant growth rate.Vizerto is a Software Application designed
and developed by Digital Main. Vizerto is specially designed to get high quality answers to our
questions.User can ask any question in Vizerto and application will respond by providing
relevant and best answers of that question.If user is not satisfied with the answers,then user can
submit their questions to the expert team of Vizerto.And expert team will response within 24
hours. We can integrate these two platforms using APIs.The Slack Conversations API provides
your app with a unified interface to work with all the channel like things encountered in Slack,
public channels, private channels, direct messages, group direct messages, and our newest
channel type, Shared Channels.Similarly,Vizeto API provides your app with a unified interface to
get the search results in no time.
Abstract
Slack Integration with Simple AppBD-130 :
: This project aims to present the study and implementation of artificial intelligence
dietitian which can simulate the experience of a human dietitian. The main aim is to recommend
to the users a perfectly planned diet according to their body parameters and their day to day
activities using artificial intelligence. The online artificial dietician is a bot with artificial
intelligence about human nourishments. It acts as a diet specialist similar to an actual dietitian.
We have also taken under consideration the health status of the user. We have used artificial
intelligence as the driving technology. To select the diet of user it has to check various
parameters and there can be various food items that pass the criteria. So to select the best
among all, we take the help of Genetic Algorithm. Genetic Algorithm is our key algorithm,
besides the Na veļ Bayes algorithm. Genetic algorithm keeps on finding the best option from the
pool of options while Na veļ Bayes is used for the purpose of classification.
Abstract
Artificial Intelligence DietitianBD-131 :
: This proposed system provides a system based on voice that uses instant Message and
voice commands to create two way communication between human and our machine. This is the
desire of man in the 21st century. Our motive is to give a voice control intelligent system that
gives ability to control our machine for its operation. Our system is for enabling the impaired or
disabled people to use appliances or machine. Existing technologies in these fields are
depen-dent on displays and keyboard which are very costly and not affordable. As we know,
navigating through any site or webpage users click generates large volume of clickstream logs.
Our major goal is to reduce clicks and minimum use of keyboard to give input to the machine.
Our system is hands-free yet accurate way to communicate with the application. System
compatibility problems that are generated in existing technologies will overcome in this system.
Our system is capable of providing maximum functionalities with- out internet connectivity
which is necessary in existing systems like Google SIRI, Alexa and Microsoft Cortana which are
not open source software. This intelligent system would provide the blind and physically
challenged people access to computer without click of buttons. In future It will soon be used in
small and big devices like washing machine too. As per the implementation details we are going
to use google engine for voice to text feature. The text obtained from google engine can be
Abstract
Smart assistant system using voice recognition for physically disabledBD-132 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 10
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
further processed for assistant. This system works on the principle of data mining and semantic
analysis in which for one voice input it gives more than one matching results and the data
dictionary recognizes the best matched results and performs the particular task. For this we are
going to use xml parsers to store predefined commands.
: Digitization of the commercial invoice can be thought in two principal directions. (1)
transforming the non-searchable document to searchable one and (2) extracting invoice
information in summarized form. Such tasks are achieved by (non)commercial optical character
recognition (OCR) techniques. But output generated from OCR is plain - loses the original
semantics from the document.There aremany commercial approaches/ solutions, but they either
lack the accuracy required or onlywork on basic sets of invoices. The main goal is to create a
prototype with the ability to evaluate data from invoices. To achieve this goal, we first evaluate
existing OCR engines on how they perform in terms of number of correctly recognized words in
invoices. Then we apply pattern matching using Regx to extract data from plain textwhich
follows a pattern and also correct the OCR generated errors. Later we use the concept of
comparing edit distances between lines in text format invoice to recognize and extract table in
.csv file output. Thus, at the end we successfully extract summary of information from invoice
which include the structured data and table information. Few complex invoices documents had
multiple pages and nested tables we have developed a script that correctly extract these nested
tables also.
Abstract
Digitisation and analysis of invoices (A new approach)BD-133 :
: Hospital re-admission is now-a-days a high-priority health care quality measure. It can
be used as target for cost reduction. In spite of broad interest in readmission, relatively little
research has focused on patients with diabetes. The diabetes burden among hospitalized
patients, however, is substantial, growing, and costly, and readmissions contribute a significant
portion of this burden. Reducing readmission rates of diabetic patients can greatly reduce health
care costs while simultaneously improving care. Risk factors for readmission in the hospital in
this population include lower socioeconomic public insurance, co morbidity burden, status,
racial/ethnic minority, emergent or urgent admission, and a history of recent prior
hospitalization. Hospitalized patients having diabetes may be at higher risk of readmission than
those who don’t have diabetes. Ways to reduce re-admission risk are - specialty care, inpatient
education, co-ordination of care, better discharge instructions, and post-discharge support.
More studies are needed to test effects of these interventions on the re-admission rates of
patients with diabetes and without diabetes.
Abstract
Classifying Re-admission of a diabetic patient using MKNN classifierBD-134 :
: With the development of the Internet, a more personalised and customized service is
expected from service providers. The analysis of user behaviour and interests can be done to
achieve the same. Social networks can help provide a deeper insight into the user and his/her
activities, the knowledge of data mining is used to analyze the degree of the user interest. The
proposed system utilizes Natural Language Processing techniques to extract and process
relevant data from large user interaction datasets acquired from social networks. That data
further is used for accurate user behaviour and interest analysis by employing machine learning
techniques. We examine the conversations of every user to determine their interests in various
fields, as well as perform contextual analysis to infer about his/her stand in respective
conversations. Such behavioural information will be used for probabilistic classification of users
into predetermined buckets. User characteristics upon which classification is to performed is
obtained by supervised and unsupervised algorithms. After identifying the distinct categories to
classify users into, we can successfully segregate them. This proposed system is useful for
personalised notification feed generation according to behaviour and interests.
Relevant mathematics associated with the Project:To predict user properties we train
attribute classifiers F(u) using two feature types f (u) :
Abstract
Classifying Users and Identifying User Interests based on semantic and contextual analysisBD-135 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 11
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
I. Context-based features learned from user interests f (u) i , II. Content-based
features learned from user data f (u) t . We define F(u) as a function mapping a user to the most
likely attribute value assignment: F(u) =argmaxaP(A(u) = a|f (u) ). We quantify a user’s degree of
interest in an area as the proportion of followed accounts that deal with the interest i, given by:
|F i u | |Fu| Since P i |F i u| |Fu| = 1, we can talk of the proportional interest of a user in an
interest area.
Names of at least two conferences where papers can be published: KDD 2018 ACM
Cods-Comad 2019 IEEE Indicon 2019
: Chatbots and virtual assistants represent a potential shift in how people interact with
data and services online. Thus, they are a part of the evolution in user interface, which started
initially with command line, moved over to GUI (Graphical User interface) and further now has
moved on to Voice based Inter-faces i.e. Chatbots. Chatbots are machine agents that serve as
natural language
user interfaces for data and service providers. Currently, chatbots are typically
designed and developed for Mobile messaging applications. The current interest in chatbots is
spurred by recent developments in artificial intelligence (AI) and machine learning . Chatbots are
seen as a means for direct user or customer engagement through text messaging for customer
service or marketing purposes, bypassing the need for special-purpose apps or webpages.
We propose to develop a voice based assistant aiding developers and coders to increase
the
efficiency of their work by assisting in various trivial but consequential tasks like
executing terminal commands, resolving code related queries by providing concise and time
efficient solutions with integration with StackOverflow, automatic high level code
summarization to understand code snippets, executing commands like creating, forking,
branching repositories related to Version Control Systems like Github on voice input and
creating Java based documentation for a given Java code snippet.
Abstract
Comprehensive Developer AssistantBD-136 :
: Due to the multilingual and mixed script nature of social media data, analysis of such
texts is difficult. However, it is very important to understand what exact meaning and
sentiments these texts carry as this data is of great potential for researchers, companies. While
efforts have been made to understand multilingual sentiment analysis based on a range of
informal languages, no significant advances have been made for sentiment analysis of mixed
texts. This project will accurately analyse the reception of government schemes/decisions like
Demonetisation, Pension scheme etc. by the common people, which will help government get
the correct feedback from people and can work upon them. People may belong to different
geographical locations and hence may use different languages to express their opinion towards
the schemes. The project can analyse all the opinions in Hindi and English language present on
the social media platforms to form a generalised feedback towards schemes and present it to the
required authorities.
Abstract
Analysis of reception of government schemes and decisions by peopleBD-137 :
: Pune, or India in general, has been seeing an increase in the number of vehicle related
crimes. This includes robbery, missing vehicles, kidnapping,etc. In the event that a vehicle needs
to be tracked, going through hours of CCTV footage is the usual solution, which of course is time
consuming and requires manual efforts. No such systems exist in India to automate this process.
Our System has two parts, First part uses Deep Learning to detect and classify cars based on
their Make, Model and colour and store it in the database for future queries. The Second part
enables the user to query the database using simple set of dropdowns. The system is able to
output all the candidate frames of the suspected car from the footage. Image processing
techniques have low scalability. Our CNN based model is trained on our recorded Indian data so
that the model is robust for Indian traffic conditions such as high traffic density, occlusions and is
Abstract
Query based Car Make and Model Recognition System using Deep LearningBD-138 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 12
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
highly scalable.
: Automatic synthesis of real images from text would be interesting and useful, but
current systems are still far from this goal. However, in recent years generic and powerful
recurrent neural network architectures have been developed to learn discriminative text
feature representations. Meanwhile, deep convolutional generative adversarial networks
(GANs) have begun to generate highly compelling images of specific categories, such as
faces, album covers, and room interiors. In this work, we develop a novel deep architecture and
GAN formulation to effectively bridge these advances in text and image modeling, translating
visual concepts from characters to pixels.
Abstract
Auto Painter: text to image synthesisBD-140 :
: Creating and managing large playlists and selecting songs from these playlists according
to user’s mood is an extremely difficult and time consuming task. It would thus be very
convenient for the user if the music player itself generates a playlist that is suitable for the user’s
current mood. The proposed application will minimize the efforts of managing playlists. In this
application the mood of the user will be automatically detected using a facial expression
detection system in OpenCV. A camera will be used to capture the image of the user, which in
turn will be passed under different stages – detection of a face from an image, facial feature
extraction and facial expression classification. The image classification for mood will use a
Convolutional Neural Network classifier. The application also includes the facility of sorting
songs based on mp3 file audio properties like danceability, energy, instrumentalness, liveliness,
tempo, etc classified according to a Convolutional Neural Network so that they can be added
into appropriate playlists according to the mood. The playlist will be generated randomly and
recommended to the user.
Abstract
BASS - Music for Your Mood!BD-141 :
: The project aims to provide teachers with a proper feedback of the percentage of
interested students in the online tutorial which will assist the teachers to determine in if there is
any need of change in any teaching methodology. The system will be able to recognize the state
of students. The focus of the system is to detect the engagement of students in tutorials.
Student’s engagement in lecture is determined by facial orientation. This will be done by CNN
based approach successfully. The deep learning approach provides satisfactory results on a
challenging, real-world dataset with significant occlusion, lighting and resolution constraints.
Abstract
Detecting students Interest in lectures using Deep LearningBD-142 :
: From beginner to pro, gain all the essential skills you need to make your musical dreams
come true. Whether you want to learn piano on your own, or you’re starting from scratch, Music
Vidya will guide you so you can play the songs you love. It works with any piano or keyboard,
your device listens to which notes you’re playing through the microphone and provides
real-time feedback.
Music Vidya is a Machine Learning based mobile platform to learn your favourite
musical instrument anytime, anywhere. We combine age-old Digital Signal Processing
Techniques along with the latest breakthroughs in Machine Learning to solve the Automatic
Music Transcription problem for mobile devices. We propose a hybrid platform of Native
Android and a 2D gaming framework called libgdx which is tightly coupled with a deep learning
algorithm to accomplish this task.
Abstract
Music Vidya - Piano Tutor App using DSP and MLBD-144 :
: Different students have different abilities, backgrounds, interests, goals, priorities and Abstract
Cognitive Reasoning Engine - Smart Teacher Assistance System based on student thinking and learning trends
BD-145 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 13
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
hence, "one size" education does not fit all students. Our project represents a new, unique and
indeed, much-needed direction that is complementary to the current trend of global education.
While current tools do assess students, they are based solely on the course-specific technical
skills. With the aim to provide more comprehensive analysis, our system computes the extent to
which the students’ cognitive skills such as aptitude, logical reasoning, seriousness and interest
influence the students’ learning and thinking patterns.
By integrating Bayesian Knowledge Tracing with knowledge-based clustering, the
proposed tool provides the teacher with an accurate periodic report and a detailed demographic
of the class. By adopting this probabilistic approach, we have countered the issue of any student
relying solely on guesswork as well as one making silly mistakes, thus accurately analysing the
extent to which the student has learned. The system also equips the teacher with specific
information and suggestions regarding each student. In addition to this, we formulated buckets
of students having similar knowledge and trends of learning through frequency clustering on
binary categorical data. Consequently, this system is capable of evolving individually for each
student as the course progresses, thus aiding the teacher to enhance the quality of education as
a whole.
: A large portion of video content on the internet is present on YouTube. It is always
flooded by new content every second by content creators or so-called YouTubers. As they
upload new content every day, they add certain ‘tags’ to their video description which allows
users to search with relevant words when the actual title is unknown. These tags on YouTube
video classify the content based on region, language, age and most importantly used as search
keywords. Essentially making tags the second most important search criteria after the actual
title of the video. Proper tagging of the videos ensures the right content is being delivered. The
marketing schemes and the rapidly rising YouTube culture pressures these YouTubers to tag
their videos with trending or very common phrases which ensure more viewers by perplexing
the peers.
The suggested system here fundamentally solves the problem by generating relevant
tags to ensure that true content is delivered rather than the content getting more views for the
sake of popularity or marketing schemes. The suggested system will scan the video, its
metadata, audio track and description by the content developer whereon it will look for relevant
keywords common throughout this information and generate descriptive and legit tags for the
content. Video classification is achieved through CNN and NLP is used to extract keywords from
audio track, caption and description. Relevance to these factors is verified by means of image
processing over arbitrary frames of the video. The system is expected to generate a plethora of
tags for the video significant enough for it to top the search results as expected.
Abstract
Content and metadata based YouTube tag generationBD-146 :
: The fashion industry has evolved in many fields and its growing and making a huge
market in garment companies and e-commerce entities. The challenging task for IT industry in
fashion is to model a predictive system with the domain of data mining. Our project deals with
such a system which will result in composing fashion outfits. Meaning, while choosing the cloth
this system will recommend the other products (like the bag, footwear, etc.) with it. Our
approach is to first implement an end-to-end system of encoding visual features using a deep
convolutional network for complicated visual contents of a fashion image because it is
impossible to label or even list all possible attributes for every clothing image. Secondly, we
propose a multi-modal deep learning framework for rich contexts of fashion outfit. Since, we
must consider not only the pixel information but also the context information in the fashion
outfit.
Abstract
A system for fashion outfit composition using deep learning methodBD-147 :
: In India, the numbers of mobile phone users are increasing at an enormous rate. As
Android becamepopular, there is a radical shift in the mobile phone market. On the other hand,
Abstract
DIETOS: PRESONALIZED DIET COMPANIONBD-148 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 14
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
users have become more health-conscious and dietitians or nutrition experts are gaining
prominence. Nevertheless, people care about their family's health. So to converge all these
paths into one, it seemed that if a user can get information about a food product that the user
comes across in a supermarket, a suggestion that can help to make decision whether to buy the
product and use it or not. This can be done using a mobile phone supported with Android. Our
goal is to create android application system which recommends diet to user. Obesity is a global
issue and has a direct impact on the public and private health care system. Our goal is to design
and implement a system that can recommend the daily diet for individual users according to the
current health parameters like age, gender, height, weight etc.
: Heart disease is the most common cause of death globally. According to a recent study
by the Indian Council of Medical Research (ICMR) near about 25% of deaths between the ages of
25-69 years cause due to of different heart-related problems. The cardiovascular diseases are
the highest increased diseases. The shortage of specialists and high wrongly diagnosed cases has
necessitated the need to develop a fast and ef?cient detection system. Again heart disease
prediction using data mining is one of the most interesting and challenging tasks. So we should
also have jumped on techniques and methods used for alertness and care to avoid the sudden
death of the people because of the heart attack. By using sensor we can sense the real-time ECG
values. Firstly, evaluating the real time ECG values and the other parameter related to heart
disease in trained dataset and by applying data mining technique i.e. Support vector machine
prediction of the disease can be done.
Abstract
Classification and prediction of cardiac arrhythmia using machine learningBD-150 :
: Emotions play an important role not only in our relations with other people but also in
the way we interact with computers. Emotional state of a person may affect concentration, task
solving and decision-making skills. The objective is to create a system, which will recognize
human emotions and influence them in order to enhance productivity and effectiveness of
working with computers. Proposed facial expression emotion recognition-based
human-computer interaction (FEER-HCI) system will recognize human emotions and will
generate facial expression for adapting to human emotions. Firstly, the facial images are
captured by using camera, which will be passed to classification model for classification of face
emotion. Then the response will be generated according to the emotion identified. The system
will recognize and generate 7 different emotions like happy, sad, angry, surprise, fear, disgust
and neutral. AffectNet dataset is used for training the Emotion Recognition model. There are
various applications of proposed system like customer service, home service, health service etc.
It can be used in digital education, as it can understand which content of the learning system
causes boredom and the educators can modify the content.
Abstract
Facial Emotion Recognition Based Human Computer InteractionBD-151 :
: An algorithm for age-group recognition from frontal face image is presented. Estimating
human age from images is a problem that has recently gained attention from the computer
vision community due to its numerous applications as well as the challenges that face a
satisfactory solution. The algorithm classifies subjects into different age categories in four key
stages: Pre-processing, facial feature extraction, face feature analysis, and age classification. In
order to apply the algorithm to the problem, a face image database focusing on peoples age
information is required. Beside traditional challenges in captured facial images under
uncontrolled settings such as different lighting, varying poses and expressions, aging effects on
appearance depends on many other factors such as life style. In this thesis, an automatic age
estimation framework is proposed. A single image is required as input for the subject of interest
to estimate his/her age.
Abstract
Automatic estimation of age via face recognitionBD-152 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 15
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
: Nowadays,the significance of automated code generation of Java code from UML class
diagram has increased due to its benefits such as cost reduction,and accuracy.Consistency
checking between UML class diagrams,and ensuring accuracy and completeness of the
generated code are the main concern in this area.The UML class based approach provides
abstraction to deal with high complexity of embedded application and when combined with
Model-Driven Engineering can also provide automation through automatic code generation.The
method for this approach is the the embedded application are modeled using UML class diagram
to give a structural view and several sequence diagram to represent the behaviour.From the
class diagram the structural code is generated from each class , a java file is generated describing
its attributes and methods signature.The code generation also includes the relationship between
classes and interfaces.The approaches uniquely sequence diagram to capture behaviour and
validate a development of tool whose input is UML class diagram model and after capturing the
model ,it must be transformed in Java code and also generate database query called DDL
statement.
Abstract
Forward Engineering Tool Using Imageprocessing And Hadoop.BD-153 :
: Since the introduction of knowledge graph in 2012 by Google to enhance their search
engine, knowledge graph has found applications in multiple fields to help store not just content
but context in the form of relationships among entities. By storing unstructured text in
knowledge graphs as the brain for Question Answering systems, the user's intent can be better
understood and by semantic correlation right answers can be provided to the users which can
prove as a major step in boosting performance to use semantic analysis instead of sentiment
analysis which is more prominently used in current chatbots or QA systems. By implementing
Machine learning and NLP algorithms to construct and query knowledge graphs it is intended to
exploit the strength of knowledge graphs in QA domain.
Abstract
Knowledge graphs for question answering systemBD-155 :
: Automatic recognition of car license plate number has become very important in our
daily life because of the unlimited increase in cars and transportation systems which makes it
impossible to be fully managed and monitored by humans. The recognition of License Plates of
Vehicles from videos is a challenging task in computer vision as it is difficult to recognise due to
different colour backgrounds, occlusion, existence of multiple plates in an images, variance in
illumination etc. The main objective is to design an efficient automatic vehicle license plate
identification system which works for real time videos and specific to the Indian Standard types.
Our system will use Deep
Leaning techniques for detection of license plates. The developed system first captures
the videos and extracts the frames to detect the vehicles. Once the vehicles have been detected
the license plates will be localised for the detection of the characters. Experiment results
confirms that our system can detect license plates with a high accuracy and short running time.
Abstract
License Plate Recognition system for vehiclesBD-156 :
: Synthesizing high-quality images from text descriptions is a challenging problem in
computer vision and has many practical applications like criminal sketching, product designing,
photo editing, etc. There have been previous works on the generation of images of birds, flowers,
human poses, etc. from text descriptions. Work on face to text description has also been done in
the past. In our project, we use Generative Adversarial Networks (GAN) to generate human face
images using a natural language text description of the face as input to the model. Our effort is
to generate clear recognizable face features with maximum accuracy.
Abstract
Image generation of Human faces from text description using Generative Adversarial Networks
BD-157 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 16
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
: Agriculture helps to meet the basic needs of human and their civilization by providing
food, clothing, shelters, medicine and recreation. Hence, agriculture is the most important
enterprise in the world. Very high proportion of working population in India is engaged in
agriculture. Crop production is highly dependent on factors such as temperature, humidity,
precipitation, moisture, solar radiations, wind velocity etc. One of the reasons for the shortage
of food across the country can be selection of unsuitable crop for cultivation. The proposed
project will contain information of different crops and will suggest the farmers crop which is
suitable for cultivation based on the climatic conditions such as temperature, moisture and
humidity by making use of different sensors.
Abstract
sss approach for crop selection based on Agro-Climatic ConditionsBD-159 :
: A large portion of video content on the internet is present on YouTube. It is always
flooded by new content every second by content creators or so-called YouTubers. As they
upload new content every day, they add certain ‘tags’ to their video description which allows
users to search with relevant words when the actual title is unknown. These tags on YouTube
video classify the content based on region, language, age and most importantly used as search
keywords. Essentially making tags the second most important search criteria after the actual
title of the video. Proper tagging of the videos ensures the right content is being delivered. The
marketing schemes and the rapidly rising YouTube culture pressures these YouTubers to tag
their videos with trending or very common phrases which ensure more viewers by perplexing
the peers.
The suggested system here fundamentally solves the problem by generating relevant
tags to ensure that true content is delivered rather than the content getting more views for the
sake of popularity or marketing schemes. The suggested system will scan the video, its
metadata, audio track and description by the content developer whereon it will look for relevant
keywords common throughout this information and generate descriptive and legit tags for the
content. Video classification is achieved through CNN and NLP is used to extract keywords from
audio track, caption and description. Relevance to these factors is verified by means of image
processing over arbitrary frames of the video. The system is expected to generate a plethora of
tags for the video significant enough for it to top the search results as expected.
Abstract
Content and metadata based YouTube video tag generationBD-160 :
: The rise of internet in 21st century has given both advantages and disadvantages.
People get access of information at very negligible rate and at very short time. On the internet
no one is confined to anything. So, everyone is free to express their ideas and stance. Because of
this few people take advantage of this and propagate the false stories or news article. “Fake
news detection” is de?ned as the task of categorizing news along a continuum of veracity, with
an associated measure of certainty. For detecting the fake news we use different machine
learning algorithm like SVM, RANDOM FOREST, RANDOM TREE, ANN etc. The result is
generated by combining all the algorithm. Here we use the majority system. Among this
algorithm, if the majority of algorithm detected the news as true or false that result is consider.
Also, the use of Ensemble learning helps to connect different Technologies. Though scheming a
fake news detector is not a direct problem, we plan in use rules for a possible fake news
detecting system. The nature of online news publication has changed.
Abstract
Fake News Detection Using Machine LearningBD-161 :
: Banana is one of the major and economically important fruit crop in India. In India
banana is grown below various conditions and production systems. This system focuses to
identify, detect and rectify the diseases in banana leaf and also continue providing updates
about the diseases in the leaf of the banana plant to the farmer. Here, the system will be
Abstract
A Disease Prediction and Rectification System for Banana Leaf using CNNBD-162 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 17
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
provided with the input as regular images of banana leaf captured through different image
capturing media, and the system will further process those images to detect the disease ( mosaic,
black sigatoka etc. ) ,if any and then notify the farmer as well. The system uses the Convolutional
Neural Network( for feature extraction) and KNN algorithm (for classifying the diseases).The
system also guide the farmer about the further actions to be taken such as suggesting him with
the right pesticides, fertilizers to use and farming techniques so that diseases will be cured and
would not corrupt the crops nearby. Therefore, the further yield of his crop will reach the
maximum level and the disease would not replicate in the future.
: Many problems in computer vision were saturating on their accuracy before a decade.
Efficient and accurate object detection has been an important topic in the advancement of
computer vision systems for Industrial purpose. With the advent of deep learning techniques,
the accuracy for object detection has increased drastically. One of the problem was detecting
the correct side of the Con Rod. The more complicated problem of this project involves both
classification and localization. In this case, the input to the system will be a image, and the output
will be abounding box corresponding to all the objects in the image, along with the class of object
in each box.The project aims to incorporate accurate positioning of Conrod( which connects
crankshaft) for object detection with the goal of achieving high accuracy with a real-time
performance. A major challenge in many of the object detection systems is the dependency on
other computer vision techniques for helping the deep learning based approach, which leads to
slow and non-optimal performance. In this project, we use a completely deep learning based
approach to solve the problem of object detection in an end-to-end fashion. The network is
trained on the most challenging i.e our own dataset. The resulting system is fast and accurate,
thus aiding those applications which require object detection at industry level.
Abstract
Conrod Object detection for right positioningBD-164 :
: Log data is an important and valuable resource for understanding system status and
performance issues. Machine logs record system states and significant events at various critical
points to help debug performance issues and failures, and perform root cause analysis.
The log format is the standard log format which contains timestamp, process name,
message, log type, id etc. These logs are analysed to detect any sequence of events which
provide us with the patterns necessary for further implementation. From these patterns future
critical situations like memory issues, network down, machine shutdown etc. are found. After
detecting these critical situations auto remediation is done by sending alert messages or
notifications which state the solutions like system restart, code re-execution etc. which will help
in avoiding these future critical situations and help protect the system.
Abstract
Analysis of Machine logs to Detect patterns and Perform Auto-remediationBD-165 :
: Recommendation system is an information filtering technology. It is used in our painting
website to present paintings that are likely to be of interest to the customer. The
Recommendation system uses details of the registered users’ profile, opinions and habits of their
whole community of users and compares the information to reference. Our project uses Apache
Mahout Recommender Engine. This engine uses Collaborative Filtering (CF) technique to
recommend which helps recommending to the users items based on his/her
preferences.Collaborative filtering (CF) approaches consider the notion of similarity between
items and users. No features of product or properties of users are considered here. The purpose
of this project is to show various similarity techniques being used for recommendation and to
discuss various challenges especially for the web media sites.
Thus the objective of this website is to provide platform interface between the artist
and the customers. Our website will fulfill the needs of customer by personalized
recommendation and provide the artist with a platform to sell her paintings according to the
customer demand.
Abstract
Painting Recommendation using Apache Mahout EngineBD-166 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 18
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
: Alzheimer's disease is a progressive and neurodegenerative disorder which involves
multiple molecular mechanisms. One of the most common signs of Alzheimer’s disease,
especially in the early stage, is forgetting recently learned information. Intense research during
the last years has accumulated a large body of data and the search for sensitive and specific
biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and
the current tests do not accurately detect the process leading to neuro-degeneration. Motivated
by this, we thought of developing a system that detects the disease at early stage. To achieve
this we are considering patient’s daily routine and his personal details. The system will have a
questionnaire and each answer will have a certain weightage. To calculate the final prediction
we will use classification algorithm as SVM, DNN and Naive Bayes algorithm. The predicted
result will be final percent prediction. Depending on this percent further medical suggestions
will be suggested by the system.
Abstract
Prediction of Alzheimer's disease Using Machine learning TechniquesBD-167 :
: There is large amount of data available in all the businesses such as modern
banking,e-commerce,finance etc.To utilize this information properly, we need proper and
thorough understanding of the domain. For this, there already exist many solutions based on
nested conditional loops non-decisions and necessary natural language processing.This methods
can be improved using Knowledge Graphs.
Use of structural information in commercial documents to understand the ontology of
the domain and relationships between various terms in a domain . Knowledge graphs are used to
represent and understand this information . Utilizing this information in knowledge graph to
query for the most relevant topics in the knowledge graph and the relationships with other
terms are the direct benefits of this approach . This approach extends the conventional
approach with added benefits of structural information , flow of information as well as domain
knowledge understanding with the help of knowledge graphs .
Abstract
Enhanced Knowledge Understanding and Querying for Commercial ApplicationsBD-168 :
: When we go into market to buy fruits we choose according to their quality,size,etc.
Sometimes it can happen that we might get confused about its quality. So we have designed an
application which will classify fruits and grade them according to their quality. In this we have
made use of transfer learning,which is a machine learning method where a model developed for
a task is reused as the starting point for a model on a second task.We then retraind it on a similar
problem. Deep learning from scratch can take days, but transfer learning can be done in short
order. We have made use of tensorflow,which is an open source library for numerical
computation, specializing in machine learning applications.We have also used tflite to convert
classifier into an android application.
Abstract
Application for Fruit Classification and Grading System using Transfer LearningBD-169 :
: It is every individual’s desire to have their home as well as vicinity clean and tidy. It
creates a fresh aura in the surroundings which enables a healthy and hygienic of living. People
dump all types of garbage including medical waste anywhere in the city without proper
segregation, which is not environment friendly. However, this illegal dumping can also include
hazardous waste which poses a big threat to the surroundings, such as introducing health issues.
Our system proposes the method to detect the medical waste using object detection model
YOLOv3 (You Look Only Once). The camera captures image of the object to be thrown, if it is
not a medical waste then the system will notify the end user by ringing alarm in max 10 sec.
Because the system suggests that the dustbin is specifically meant for medical waste. This
System is user friendly and implicit in nature. It will improve the detection and sorting of the
medical waste easily. The system generates appropriate responses relative to the input waste
Abstract
Medical waste detectionBD-170 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 19
01. Big Data/AI/DL/ML/Pattern Recognition
PICT, Pune Synopsis : Concepts-2019
there by making it interactive and efficient.
: The application of Deep Learning in digital pathology yields promising results and poses
its own challenges in spotting the correct region of interest for extracting features from the
training images and working with the complexities of medical science. Cancer diagnosis and
treatment is a field where Deep Learning has the potential to provide tremendous scope for
targeted large scale interventions. However, the number of pathologists in India, experienced in
oncology (study and treatment of tumors) are few, nearly as much as one in thousand patients
suffering from cancer, which leads to delay in cancer diagnosis and treatment. Motivated to
bridge this gap between the number of patients and pathologists, we have developed a
web-based virtual digital pathologist to speed up the diagnosis process. By employing a
121-layer DenseNet architecture on Chest X-Rays, we have verified the importance of domain
specific weights for transfer learning and have obtained 88% test accuracy in detection of
Pneumonia. The application also enables pathologists to classify lymphoma into its subtypes
with an accuracy of 97.33% using the power of Deep Learning. Additionally, we have used the
segmentation technique followed by Convolutional Neural Networks (CNN) on Lung CT Scan
images to diagnose lung tumor. Our results show that 2D and 3D segmentation of cancerous
regions followed by CNNs provide better results than using CNN alone. Our deep learning
models outperform the accuracy of existing state-of-the-art models and our application portal
enables users to upload cellular pathology images to receive a diagnosis. We have thus moved
one step closer towards the universal goal of introducing automation in medical science using AI.
Abstract
Deep Learning in Medical Image AnalysisBD-171 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 20
02. Database and Storage/System Application/Expert System
PICT, Pune Synopsis : Concepts-2019
: As we know the cloud is huge and complex structure which is used to maintain the
heavy data and to compute the same. And now a day’s cloud becomes the lifeline of all the
applications and software. This leads to huge and gigantic data streaming inside the data
warehouse where actual cloud is deployed. So these data warehouses employees large number
of engineers to handle this cloud, So cloud is always under the threat for its data from both
internal persons and external hackers. So to maintain the security of the data at the cloud end
proposed model uses attribute based encryption scheme where secret key and public key are
generated based on the random character selection from the hash key generated by the
personal attributes of the user profile. And proposed model generates public and private keys
based on these random characters, Which is powered with the reverse circle cipher algorithm to
provide more and more secure encryption model for the uploading data of the user at the cloud
end.
Abstract
Securing data in cloudDS-201 :
: Recommendation Systems are the sort of data separating frameworks intended to
assist clients with finding their way through the present huge data spaces. The objective of a
Recommendation System is to produce proposals to clients. This will be useful for offering
suggestions to data searcher. Analyzing Recommendation of School for Users. The objective of
this project is to develop an web based application which will help users to find best, nearest and
affordable primary and secondary school.
Now a days in this current running world people do not have time to visit every school
personally and collect all the information regarding school admission process. Parent are
expecting to be get an whole information at one place, so that they can get required information
about best school. There are so many resources are available on internet regarding college
information but not for school so we are proposing this system which will help the user to find
out their affordable school.
Abstract
School Recommendation SystemDS-202 :
: Now a day’s many online tools are available to test the programming knowledge of the
person like codechef. But in order to test the knowledge of the DevOps there is no such online
tool available. So the aim is to develop the cloud based infrastructure to test the knowledge of
DevOps of the examinee. The questions related to the DevOps will be given to the candidate
along with the access to the terminal. The candidate has to do all the steps required to solve the
problem given. The terminal Provided to the candidate is the communication link between the
candidate and the allotted container. We are using containers rather than VMs, because
containers are small,light-weighted and fast, one application can be packed in each container
image. The Kubernetes will manage the containerized applications such as database storage and
user specific command across a set of containers or hosts and provides mechanisms for
deployment, maintenance, and application-scaling. The container runtime packages,
instantiates, and runs user commands on containerized application. The output generated will
be stored in a temporary file which will be verified with the desired output stored in a database.
Abstract
Cloud Based Linux and DevOps Skills Assessment ApplicationDS-203 :
: Log data is an important and valuable resource for understanding system status and
performance issues. Machine logs record system states and significant events at various critical
points to help debug performance issues and failures, and perform root cause analysis.
The log format is the standard log format which contains timestamp, process name,
message, log type, id etc. These logs are analysed to detect any sequence of events which
provide us with the patterns necessary for further implementation. From these patterns future
critical situations like memory issues, network down, machine shutdown etc. are found. After
Abstract
Data loggerDS-204 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 21
02. Database and Storage/System Application/Expert System
PICT, Pune Synopsis : Concepts-2019
detecting these critical situations auto remediation is done by sending alert messages or
notifications which state the solutions like system restart, code re-execution etc. which will help
in avoiding these future critical situations and help protect the system.
: In past five years, social networking applications had gained a lot of support and
popularity all over the world. ”The world is a global village “; this terminology has proven true in
this aspect. So taking this thought into consideration, we are developing an application which
would be a different view point in social networking world. An application named “Amigo
tracker” will serve its users with a new picture of social networking. Generally in such(Social
Networking) applications, people stay in touch through posting and sharing their comments,
pictures, videos, and much more. There are times, when people like to know the current location
of his/her friend/(s) or colleague/(s), apart from staying in touch, which we do in social
networking applications. Taking this thought into consideration, we are planning to develop an
application which will behave as follows:
This application will provide user with his/her friends location using GPS (Global
Positioning System). It will provide global position of that device itself the user is holding, and
through satellite. It also facilitates user to make new friends that are using that particular
application and are connected through internet.The application offers an ability to work with
location sensitive information. It will allow the user to login/register to the system. The user can
also make friends by searching the application users and sending request to them. He/she can
also accept or reject the request received by him/her from other application users.He can select
particular friend from his friend list and can trace his/her current location, provided that he
owes Android GPS based mobile phone GPS Should Be Activated .Application gives surety that
user’s personal and location based information is never shared without users permission. For
accessing this application, user has to be connected through internet.
Abstract
Amigos Tracker Android ApplicationDS-205 :
: Calibration is necessary, no matter the application or weighing instrument. Proper
calibration ensures the traceability, reliability and accuracy of the results obtained from a scale
or balance. In manufacturing and assembly world, tightening , controlling , and measuring torque
is a crucial job for efficiency of the tool.Wide range of tools are available for controlling and
measuring but we should always select a tool which is suitable for our material. Safety should
be mandatory while work on assembly line. According to the need and recommendation of the
manufacturer.Some organizations may recommend six (6) month calibration intervals, while
others may schedule it at twelve (12) months. Elimination of Human Errors Using Traceability.To
scan tools and check their functionality.To notify the expert about calibration of tool and take
proper measure regarding tool’s health.
Abstract
Tool Calibration TraceabilityDS-206 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 22
03. Netwoking & Networking Application/Cloud Computing/Data Security/Cyber Security
PICT, Pune Synopsis : Concepts-2019
: With an increase in the popularity of mobile and camera devices, personal life is being
continuously documented in the form of images and so the risk of losing it to eavesdroppers is a
matter of grave concern. Our work is concerned with the security of images which are mostly
stored in the secondary storage.While image encryption is the best tool to ensure image
security, full image encryption and decryption is a computationally intensive process. Moreover,
image quality and thus the pixel density have increased substantially, making image encryption
and decryption more expensive. We thus propose selective encryption or blurring of images
based on the region of interest i.e. instead of altering the entire image we only encode selected
regions of the image. This will reduce the overhead without compromising security. The
applications utilizing this technique will be more usable as the decryption time is reduced.
Blurred images are more readable than encrypted ones allowing us to define the level of
security. Machine learning algorithms like Fast-RCNN and YOLO have set new benchmarks for
object recognition. We leverage these ML algorithms to select the region of interest. We
develop an end-to-end system to demonstrate our idea of selective encryption.
Abstract
SISA: Securing Images by Selective AlterationNN-301 :
: Crypto-currency exchanges platforms allow user to trade in crypto-currencies for other
assets, these assets can be conventional fiat currency, or trading between any different digital
currencies. For this purpose it uses inter-net, and when internet comes in scenario it produces
security threats and vulnerabilities to the system . In this project we evaluate the weaknesses,
possible threats and strengths in the crypto-currency exchange platform, likea Intrusion
Detection System(IDS), mainly focused on Block-chain Technology used in Crypto-currency
exchanges.
Abstract
CryptobugsNN-302 :
: The advent of Cloud computing offers different ways both to sell and buy resources and
services according to a pay-per-use model. Thanks to virtualization technology, different
Cloud providers supplying cost-effective services provided in form of Infrastructure as a Service
(IaaS) have been rising. Currently, there is another perspective which represents a further
business opportunity for small/medium providers known as Cloud Federation. In fact, the Cloud
ecosystem includes hundreds of independent and heterogeneous cloud providers, and a possible
future alternative scenario is represented by the promotion of cooperation among them, thus
enabling the sharing of computational and storageresources.
This abstract documents the program and outcomes of multi-cloud providers.It's the
choice of a business to distribute its assets, redundancies, software and applications and
anything it deems worthy not on one cloud hosting environment, but rather across several. This
can be done using an interface between client and cloud providers. The interface will provide the
users/clients an opportunity to distribute its data and resources over multiple cloud providers
that is authoried by middleware application in a simple and efficient manner.
We conclude the abstract with the benefits of providing federation as per their
requirement such as high availability, reliability and more importantly privacy to users data.
Abstract
Iaas as a PlatformNN-303 :
: Phishing is a fraudulent technique that is used over the Internet to deceive users with
the goal of extracting their personal information such as username, passwords, credit card, and
bank account information. There are various ways found to detect phishing sites,But the fraud
rate is increasing all way. Phishers are finding new ways for creeping a personal information to
tackle this problem and make network surfing more secure for everyone we aim to design
system to detect phishing site and save user from getting in to trap and losing his personal
Abstract
Detection of Phishing SitesNN-304 :
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03. Netwoking & Networking Application/Cloud Computing/Data Security/Cyber Security
PICT, Pune Synopsis : Concepts-2019
information to third party. Inproposed system we develop new security server which will work
as an gateway for internet access of devices in organisation .Modules used in proposed system
are Alexa Ranking , Web Crawler , Spam detection ,Neural Networks and Fuzzy logic.Module
Alexa Ranking and Wed Crawling is for early classification depending on previously available
data . Module Neural Network and Fuzzy Logic isfor training machine and making system ready
to detect new phishing sites depending on properties of detected phishing sites.Fuzzy logic is an
integral part to take most accurate decision.
: Smart business continuity application deals with the continuation of business in adverse
circumstances. The system consists of two parts: business continuity planning and disaster
recovery planning. Business continuity involves the processes and procedures an organization
must implement to ensure that mission-critical functions can continue during and after a
disaster. Disaster recovery comprises specific steps an organization must take to resume
operations following a disastrous incident. A business consists of entities like people, assets,
services, etc. When incidents like fire, flood, network failure, breach of cyber security, etc. occur,
these entities can get affected and may take indefinite time to resume working. This can disturb
the continuity of the processes they are associated with.
Every organization must have predefined business continuity plans for its projects. In
the traditional framework, these plans are documented manually. The admin has to keep
monitoring the assets and services of all the projects himself. When a disaster occurs, he has to
first refer to the BCP document and then give instructions accordingly. This consumes time and
the continuity of projects is disrupted.
Here, we propose a Smart Business Continuity Application which shall allow an end user
to store the BCPs for various projects of an organization in an Information Technology Service
Management (ITSM) server. As soon as an asset or a service goes down due to a disaster, its
backup, as mentioned in the project’s BCP, takes over its working. The admin of the organization
is automatically notified of such incidents and he can check status of impacted projects at a
glance. There is a provision to trigger BCPs for severely impacted projects by a single click.
Abstract
Smart Business Continuity ApplicationNN-305 :
: System security is of essential part now days for huge organizations. The Intrusion
Detection frameworks (IDS) are getting to be irreplaceable for successful assurance against
assaults that are continually changing in size and intricacy. With information honesty, privacy
and accessibility, they must be solid, simple to oversee and with low upkeep cost. Different
adjustments are being connected to IDS consistently to recognize new assaults and handle
them. This work proposes a semi-supervised model based on combination of Intrusion Detection
System (IDS), Intrusion Prevention System (IPS), Intrusion Response System (IRS) for network
traffic anomaly detection. As most IDS try to perform their task in real time but their
performance hinders as they undergo different level of analysis or their reaction to limit the
damage of some intrusions by terminating the network connection, a real time is not always
achieved. In this research, we are going to implement intrusion detection system (IDS) using
anomaly intrusion detection method for misuse as well anomaly detection. The proposed
framework is a multiple classifiers, whose information base is demonstrated as a administer, for
example, "if-then" and enhanced by a hereditary calculation. The system is tried on the
benchmark KDD’99 and NSL KDD intrusion dataset and contrasted and other existing methods
accessible in the writing. The outcomes are empowering and show the advantages of the
proposed approach.
Abstract
Hybrid approach towards IDS,IPS and IRS using Reinforcement learningNN-306 :
: Cloud computing enables on-demand network access to a shared pool of con?gurable
computing resources such as servers, storage and applications. These shared resources can be
rapidly provisioned to the consumers on the basis of paying only for whatever they use. Cloud
storage refers to the delivery of storage resources to the consumers over the Internet. Private
Abstract
Optimized use of Memory to Increase Efficiency and Security in Cloud ComputingNN-307 :
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03. Netwoking & Networking Application/Cloud Computing/Data Security/Cyber Security
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cloud storage is restricted to a particular organization and data security risks are less compared
to the public cloud storage. Hence, private cloud storage is built by exploiting the commodity
machines within the organization and the important data is stored in it. When the utilization of
such private cloud storage increases, there will be an increase in the storage demand. It leads to
the expansion of the cloud storage with additional storage nodes. During such expansion,
storage nodes in the cloud storage need to be balanced in terms of load. In order to maintain the
load across several storage nodes, the data need to be migrated across the storage nodes. This
data migration consumes more network bandwidth. The key idea behind this Application is to
develop a dynamic load balancing algorithm based on deduplication to balance the load across
the storage nodes during the expansion of private cloud storage.
: Network Monitoring is a basic requirement in an organization with enormous number of
servers working within a network. To manually monitor those servers and their services is
nearly impossible for an average human being. Thus, the concept of monitoring servers through
software arose. One can monitor and analyze various servers and their services in one place i.e.
on single main server. Nagios has been providing the same. However, Nagios does not complete
the user’s needs. Thus, software better than Nagios is required. The software will be open
source, along with several nodes already added to it to monitor the performance of the system in
a better and less time-consuming way. The data will be collected, and real time statistics will be
provided. Various reports can be generated to analyze the performance of the system offline.
The main motive of the system is to make a better network monitoring open source software
tool, by adding basics as well as important plugins, making the GUI more interesting, reducing
the backend operations and making the system more efficient and easy for layman.
Abstract
Monitoring of network using an Open source Software MonItNN-308 :
: As we know QR(Quick Response) codes becoming the major transition routes for the
authentication of the applications and the process. Quick response codes are most reliable and
fastest way of authentication in today's world. These authentication can be used in implicit or in
an explicit way to ensure the security instead of passwords. Many quick response code
authentications are single tier, where they involve only QR codes and this may be the reason for
lower security in many paradigam . so to overcome this some two tier QR code authentication
systems are existed where secret passwords are being hidden in the QR codes to provide double
security for authentication. So to enhance this process proposed methodology presents three
tier security of QR code authentication where a document is encrypted using Reverse circle
cipher encryption algorithm with a random key. This key is catalyzed by RSA asymmetric
algorithm . A Reversible data hiding technique is used to store this two different keys in two QR
code Strings for their respective least significant bits. These QR code Strings are created by
using the random pattern evaluation method. And whole model provides fine tuned security for
the data authentication in three tier level.
Abstract
Three Tier Architecture for Document AuthenticationNN-309 :
: Nowadays, we often notice that the educational certificates can be duplicated easily.
The credibility of paper certificates is reducing. The duplication of certificates is possible
because of the lack of effective anti-forge mechanism. In order to solve this problem of
counterfeiting of certificates, an E-certificate generation and authentication system based on
the blockchain technology is proposed. Blockchain provides incorruptible, encrypted and
unmodifiable data features. Thus, by using blockchain, an E-certificate with features like
anti-counterfeit, anti-forge and verifiability can be generated. Through all these features of
blockchain, the system will help to solve the problem of fraud certification by enhancing the
credibility of the certificates. Also, electronically, the loss risks of the certificates will be
reduced. The system will work as follows: An electronic file of the certificate i.e. an E-certificate
is generated with the help of student’s data. Blockchain makes use of the hash value for each
block to create a chain of blocks which will store the student’s data. The proposed system will
Abstract
E-Certificate Authentication System using BlockchainNN-310 :
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03. Netwoking & Networking Application/Cloud Computing/Data Security/Cyber Security
PICT, Pune Synopsis : Concepts-2019
also create a related QR code or unique serial number which is provided to the student with the
electronic certificate. And then, the demand unit can check the authenticity of the electronic file
using the QR code or unique serial number which was provided earlier to the student.
: Cloud computing is an emerging concept combining many fields of computing. Cloud
has mainly two sorts , private and public cloud. The aim is to provide an opportunity to industry
to build a hosting architecture which is completely open source and scalable and to provide a
solution to manage their private cloud. The objective is to set up a model of private cloud using
OpenStack cloud operating environment for providing Infrastructure As a Service model.
OpenStack is open source platform for cloud computing and is easily available to users to deploy
their own cloud. In OpenStack , virtual OS is provided in the form of an instance. This instance is
provided by using customer stated requirements. In IT industry , automation is booming and it
helps to reduce the task of administrator. Here,when the instance reaches its threshold value,
automatically an instance will be launched. This automation will be acheived by using HEAT
template of OpenStack.
Abstract
Autoscaled Instance ManagementNN-311 :
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04. Blockchain Applications
PICT, Pune Synopsis : Concepts-2019
: Healthcare industry is one of the highest grossing industries in the world.However data
security for healthcare applications has been a grave concern .Also the current systems used by
the healthcare providers is not patient centric and provides little control to the patients on who
uses their data . Another important concern is the lack of interoperability between the
healthcare providers becomes a roadblock in emergency cases where patient history can
provide useful insights. All these concerns combined with the usability of blockchain can prove
to solve some of the problems mentioned above.
Abstract
Electronic Healthcare record systemBA-401 :
: Blockchain allows to have a distributed peer-to-peer network where non-trusting
members can interact with each other without a trusted intermediary, in a verifiable manner.
Blockchain is currently being used to implement peer-to-peer electronic cash systems, optimize
supply chain management, keep track of land records digitally and provide digital degrees. The
current insurance system in India involves the insurance providers, health centers and clients to
deal with intermediaries and third parties such as reinsurers, insurance agents and credit
monitoring agencies for customer verification, policy servicing and claim settlement. The system
in its current form depends on these intermediaries for transparency in the life cycle of
insurance process. The entire process is complex, tedious and archaic and is also not
cost-efficient for the insurance providers as they have to employ multiple intermediaries.
Premium facilities like quick claim settlements, cashless insurance and on-site KYC are provided
only through tie-ups between insurance providers and top tier health centers thus limiting
access to such facilities to a certain class of society. Blockchain helps in streamlining the existing
insurance system and makes it accessible to more people. A decentralized insurance platform
where the healthcare centers, insurance providers and clients participate in a trustless,
peer-to-peer network where the medical records and policy details of the clients are encoded
and stored on the blockchain. These records are accessed only by the parties involved in the
policy-servicing agreement. KYC, policy-servicing and claim settlement can be handled in a
quick and efficient manner through smart contracts. All transactions in the system are verified
using Proof-of-Authority (PoA) protocol ensuring transparency in the system. This can also help
in reducing fraud related to the integrity of a policy or claim. Blockchain will minimize
counterfeiting, double booking, document or contract alterations. However, use of the
Blockchain does not mitigate the risk associated with the majority of first party and third-party
frauds.
Abstract
LifeBlocks - A Blockchain based Insurance PlatformBA-402 :
: Internet of Things is unarguably the most disruptive technologies of the century. It is
quite obvious that in the coming years the things that are not themselves computers will have
some kind of computer inside them so that they can be connected to each other for
communication and data exchanging purposes. It is quite easy to form an IoT network with the
help of some cheap sensors and communication protocols and this data sharing will be at a
higher granularity level but as the size and confidentiality level of the IoTnetwork to be formed
increases we can’t ignore the security factor anymore. Sectors like smart city, smart healthcare,
etccan’t afford to let the data of their organization be visible to anyone who wishes to view it
since if one decides to misuse the data these organizations are generating then one will have
pose a grave threat to these organizations financially as well as ethically. On one hand, this data
can be used to offer a range of personalized services to the users. On the other hand, embedded
in this data is information that can be used to construct a virtual biography of our activities,
revealing private behavior and lifestyle patterns. This shows the lack of fundamental security
and privacy factors in the existing IoTarchitecture. A huge number of security and privacy
vulnerabilities have already been identified in the existing IoTsystems like smart locks, smart
cars, etc. Several intrinsic features of a typical IoT architecture amplify the security and privacy
challenges like: low storage and power capabilities, single point authentication, multiple attack
Abstract
Providing Access Control to IoT devices using BlockchainBA-403 :
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04. Blockchain Applications
PICT, Pune Synopsis : Concepts-2019
surfaces, context-aware and situational nature of risks, and scale. In some papers people have
tried to introduce distributed access control but they could not overcome the overheads and
excessive delays that come with it. In many instances the benefit of IoT network and data
sharing features cannot outweigh the risks of privacy and security. There is thus a need of
security-aware sharing of data through IoT networks without compromising the privacy of the
users. In this paper, we present that the answer may lie in the fundamental technology that
underscores emerging cryptocurrencies which is the Blockchain, an immutable public record of
data secured by a network of peer-to-peer participants. However, adopting Blockchain in IoT is
not straightforward and will require addressing the following critical challenges: Mining is
computationally expensive and time consuming and in IoT architecture low latency is expected
which is difficult to provide using Blockchain. Blockchain scales poorly as we increase the
number of nodes in the network and IoT networks contain a large number of nodes. IoT devices
are bandwidth limited and certain miners may create a lot of traffic. The main aim of this paper is
to introduce a Blockchain-based architecture for IoT devices and networks that delivers
lightweight and decentralized security and privacy. The architecture retains the benefits of
Blockchain while overcoming the challenges in integrating Blockchain with IoT. It helps to
uniquely identify every nodes of IoT ecosystem with the help of Blockchain virtues of
addressing.
: The Internet of Things refers to the ever-growing network of physical objects that
feature an IP address for internet connectivity, and the communication that occurs between
these objects and other Internet-enabled devices and systems.IoT can connect a variety of
physical objects, to reach common goals. In some of the IoT applications data can be stored in
distributed hash tables while the DHTs stored address can be stored in Blockchain. IoT devices
have low computational powers coming and they are not capable of conducting complex
computations. In a traditional cloud-based IoT structure, a centralized cloud server collects and
controls all the data, which brings two drawbacks: The cloud server needs very high storage
capacity to store the IoT data and Sensitive data can be easily leaked from the server. The
Development of the internet of things has made extraordinary progress in recent years. Storing
and protecting this huge volume of IoT data has become a significant issue. Traditionally, cloud
based IoT structure were used but they lead to high computation and storage demands on the
cloud servers. Due to centralized servers, there were many trust issues. To solve these
problems, we have proposed a distributed data storage scheme employing Blockchain and
certificate less cryptography. Blockchain serves as an unchangeable ledger that allows
transactions take place in a Decentralized manner. To the best of our knowledge, this is the first
work designing a secure and responsible IoT storage system using Blockchain.
Abstract
Secure Distributed Storage System for Large-scale IoT Data Using BlockchainBA-404 :
: The initial thing about crowdfunding is that we have to have trust in the party that we
are funding. Which takes out the factor of rookies. Very less amount of starters have a good
backing. So the current crowdfunding platform has the major drawback of building trust
amongst the campaign owner and the backers.
We are envisioning to create a Blockchain based Decentralised Application (DApp) for
crowdfunding projects, as well as unique startups. The goal of this project is to have a fully
transparent crowdfunding service for projects and startups alike. This service is destined to
cover up certain flaws that other centralised crowdfunding services like Kickstarter, or
IndieGoGo have. Ultimately, the whole system will be built upon transparency, thereby
providing an inherent trust factor to the backers.
Solution:
The decentralised version of this crowdfunding model overcomes the issue about the
building of trust. In our Decentralised Application (DApp) which is based on Blockchain we
overcome the problem of trust. In this case the contributors who contribute to a certain
campaign are responsible for maintaining the trust in the system. The manager of the campaign
Abstract
Decentralized Crowdfunding Application on BlockchainBA-405 :
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04. Blockchain Applications
PICT, Pune Synopsis : Concepts-2019
whenever wants to spend certain amount of money to the vendor has to create the spending
request. The request is then viewed by all the contributors who have contributed to that
campaign and they can vote whether the manager should spend the money or not. If the
spending request has enough votes (in our case simply more than 50%) then and only then the
manager can pay the amount to the vendor. Also since the system is based on Ethereum’s
Blockchain platform the money is then directly transferred to the vendor’s wallet, without any
middleman interference.
This model helps in keeping the transparency of all the transaction made by the
manager. Also all the contributors of the campaign are well aware of the fact about how their
money is being spent by the manager.
: There is no doubt that the revolutionary concept of the blockchain, which is the
underlying technology behind the famous cryptocurrency Bitcoin and its successors, is
triggering the start of a new era in the Internet and the online services. While most people focus
only at cryptocurrencies; in fact, many administrative operations, and everyday services that
can only be done offline and/or in person, can now safely be moved to the Internet as online
services. What makes it a powerful tool for digitalising everyday services is the introduction of
smart contracts, as in the Ethereum platform. Smart contracts are meaningful pieces of codes, to
be integrated in the blockchain and executed as scheduled in every step of blockchain
updates.E-voting on the other hand, is another trending, yet critical, topic related to the online
services. The blockchain with the smart contracts emerges as a good candidate to use in
developments of safer, cheaper, more secure, more transparent, and easier-to-use e-voting
systems. Ethereum and its network is one of the most suitable ones, due to its consistency,
widespread use, and provision of smart contracts logic. An e-voting system must be secure, as it
should not allow duplicated votes and be fully transparent, while protecting the privacy of the
attendees. In this work, we have implemented and tested a sample e-voting application as a
smart contract for the Ethereum network using the Ethereum wallets and the Solidity language.
After an election is held, eventually, the Ethereum blockchain will hold the records of ballots and
votes. Users can submit their votes directly from their Ethereum wallets, and these transaction
requests are handled with the consensus of every single Ethereum node. This consensus creates
a transparent environment for e-voting.
Abstract
Decentralized Voting SystemBA-406 :
: In recent years, many organizations have sprung up which publish journals submitted to
the conferences organized by them. Such prestige system is a complex socio-economic system
perpetuated by journals and researchers themselves by rewarding publication in prestigious
journals and punishing a lack thereof. It is self-reinforcing and is very difficult to remove. Hence
there is a need of a new reputation ecosystem which can assure the credibility of the papers
published and gain the trust of the people who will be referring such papers for their research.
The system allows reputation to be accrued by users and uploaded academic papers by creating
a reputation ecosystem that can be drilled down into the show the number of papers uploaded
and their quality, number of citations the paper receives, number of reviews performed and their
quality, number of decisions participated in and what decision was made. The system aims at
creating Decentralised Autonomous Organisation which encourages peer review and creates its
own reputation ecosystem to provide an alternative to the current prestige system that
dominates academic publishing with detrimental consequences. Information is stored on the
Ethereum blockchain to allow version control of documents and provide redundancy and
resiliency to the information in the network.
Abstract
Ethereum based Blockchain implementation for peer review system.BA-407 :
: We propose a Decentralized P2P data exchange system for Healthcare Records as an
alternative to current Health Information Exchange(HIE) systems. The systems have a limited
scope for exchange due to which patient data may not be accessible or may not be up to date.
Abstract
Health Data Exchange Platform using BlockchainBA-408 :
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04. Blockchain Applications
PICT, Pune Synopsis : Concepts-2019
Some HIE systems are centralized, due to which, the system is vulnerable to data breaches and
tampering. Our blockchain based system improves the security of the system with its properties
immutability of origin & integrity. Blockchains can also allow incentivization of data being
exchanged. A blockchain can also be used for auditing malicious attempts to access data, vital in
the HealthCare space. The system is created as a consortium blockchain, built using
Hyperledger.
: The traditional centralised supply chain management technologies have issues like lack
of transparency between the stakeholders of the supply chain, limitations in quality inspection,
inability to track the product right from raw material to the final product and tracing the
malicious member of the supply chain. We propose a Blockchain based supply chain
management system to address these problems. Blockchain based system will maintain the
complete data on a distributed immutable ledger, enhance transactional security and maintain
trust between the members of the chain by making a transparent system. In our proposed
system we are considering Supply Chain for Automobile Industry.
Abstract
Supply Chain Management for Automobile IndustryBA-410 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 30
05. Augmented Reality / Virtual Reality
PICT, Pune Synopsis : Concepts-2019
: In recent years, the development of high techniques in the field of computer graphics,
computer vision, and images processing has been widely studied and applied in geometric
modeling. Especially, in the field of 3D modeling and reconstruction of a 3D object from 2D
images. There has been recently a significant increase in the number of available 3D displays and
players. Nevertheless,the amount of 3D content has not increased in the same magnitude,
creating a gap between 3D offer and demand. To reduce this difference, many algorithms have
appeared that perform 2D-to-3D image conversion.
Abstract
2D to 3D Image Conversion SystemAR-501 :
: Virtual Reality is an emerging trend in computer technology. However, a lack of realistic
low-cost control results in limited applications of this technology. Using Vuforia’s Augmented
Reality support, our project aims to track an image target in the real world and convert it into
input commands. Our purpose is to create a low-cost solution to allow human interaction within
the virtual environment in the form of hand gestures and virtual buttons. This can see
applications as an improved user interface in several areas of virtual reality such as VR games
and VR media. Through our project, the user can interact with the Simulator through a system
created to track an image target and generate an input command based on change in position of
the image. The project will also allow inexperienced drivers to obtain real-time experience of
driving a vehicle in various environments. Rather than having to actually drive on the road, they
can use this simulator from the safety of their homes, in a risk-free environment. Using Unity3D
and Vuforia we wish to create a VR Car Driving Simulator, experienced through a Head
Mounted Display, which will recognize gestures made by the user as input commands to interact
with the environment.
Abstract
Gesture Controlled Car Driving SimulatorAR-502 :
: Augmented reality brings components of the digital world into a person's perception of
the real world. Mcommerce is constantly changing and those wanting to get ahead in the market
need to have their finger on the pulse. More than half number of shoppers abandon their carts
before completing a purchase or return a particular product saying that it was not as expected.
This indicates that retailers need to do a lot more to convince customers to follow through with
their choice and purchase items online. Augmented reality has the potential to reshape the
world of retail.
The Augmented Reality Application for Home Shopping will help users to get a better
view of the product by providing it’s virtual representation. It gives the user a mocked-up
version of how their home could look when fitted out with various items or products. The major
problems that Mcommerce sites face is user’s feedback that the product was not as expected.
The entire scene that users see is a virtually generated version of a home, and the immersive
experience allows them to become spatially aware of how various products would appear. The
current market works on Marker-based Tracking which hampers the true value of Augmented
Reality. The proposed methodology provides an idea of using Markerless Tracking which is more
efficient and requires less effort from user’s side as compared to Marker-based Tracking.
Abstract
Augmented reality application for home shopping in Mcommerce using Markerless TrackingAR-503 :
: In the current date scenario, technology is leveraged in all domains to help humans
achieve a better perspective about their day to day needs. EducatAR is a mobile application that
facilitates and promotes interactive and better conceptual learning. The application will scan
the image from a textbook (as a source for now) and fetch an equivalent 3-D model for it from
the cloud. The overall functionality of the application will help the students to understand the
topic better. The main aim of this application is to ease the process of learning amongst students.
Our application provides a user-friendly, interactive experience. An in-built camera in the
Abstract
Educat-AR: Dissemination of conceptualized information using Augmented Reality and Image Processing
AR-504 :
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05. Augmented Reality / Virtual Reality
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application will scan the image from the textbook. We have usedVuforia and Unity engine to
build our app and Blender to design our 3-D models. The 3D models will be kept on cloud. A
trained Convolutional Neural Network(CNN) will recognize the image and fetch an equivalent
model from the cloud. Once the model is fetched, the user would be able to interact freely with
the 3D model and get a crystal clear learning experience of the topic using Augmented Reality. It
thus enables the students and the entire educational field to achieve a better understanding.
: Why is so, that in the era of such huge development where everything is automated and
we use internet for our daily needs, we still use traditional teaching methods?That is, we still
depend on books for theorotical knowledge,
when it is scientifically proven that humans tend to understand things more clearly
when learnt through visual ways. Maybe thats why most students prefer youtube instead of
reference books.
What if there was a way that students could learn their favorite subjects through
immersive extensible visualised platform ?Thats what we want to achieve through our project ,
where we will be creating such a astronomical representation of solar system that you'll fell you
are in the space for real, and not only that, you can travel to every planet and actually feel what
the atmosphere at that planet is like along with all the astrophysical projections of the same.
Abstract
VR Space ExplorerAR-505 :
: Nowadays, we see the unhealthy behaviour of the people around us. Without proper
and sufficient exercise we see the degradation of health. Irrespective of knowing this fact people
still donot change their perspective of leading a healthy life. Some donot get time to go to gym or
walk or to do a little exercise while others find it hectic to do so. So, we come up withan idea to
inspire people to do some exercise with entertainment. With this approach they will enjoy the
exercise with little fun.
Our approach is to develop a VR game in android which will receive the information
throungh wireless motion sensors and the same actions will be reflected in the game. Our game
will have different actions corresponding to different body parts exercise. Therefore, by playing
the game the person can do the daily exercise at home or at any convenient place with
enjoyment.
This will help in the mental refreshment of the user along with the benefits of exercise.
Throung our project we inspire people to stay healthy and to lead a healthier life with
entertainment.
Abstract
Fit-O-FunAR-507 :
: This project aims to spread awareness about the importance and provide basic free
education to rural parts of the country. The project consists of a mobile application which
simulates the environment for virtual reality and can be viewed using a virtual reality headset.
The use of virtual reality in education allows us to create an immersive learning experience
which results in a better learning experience than conventional learning methods.
The application essentially works by using simulating a virtual reality environment using
Unreal Engine 4 and the main coding is done using Java and Unreal Script. The application uses
the Accelometer and the gyroscope present in the mobile phone to send the tilt and movement
input to the mobile phone which is processed by the engine to allow the user to interact with the
environment. The idea is to keep the application free so that even poor people can have access
to the educational content. All the user is going to need is an internet connection to access the
content for the application. The application will be made is such a way that it will be able to run
on even on low end devices.
Abstract
Education using Virtual RealityAR-508 :
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06. Multimedia/Image Processing/DSP
PICT, Pune Synopsis : Concepts-2019
: Optical Coherence Tomography(OCT) is a noninvasive imaging technology used to
obtain high resolution cross-sectional images of the retina. OCT testing has become a standard
of care for the assessment and treatment of most retinal conditions. The number of technician;
who perform OCT diagnosis is far less than the number of eye patients.
The "OCT Report Generator" (OCTRG) aims at, analyzing and deriving features
corresponding to symptoms of various ocular diseases; analyzes and visualizes retinal micro
architecture as cross-sectional or tomographic volumetric data in form of OCT scans (B-scan)
for detecting the early onset of a variety of eye conditions and eye diseases- Macular Hole, Wet
Age-related Macular Degeneration(AMD), Macular Edema - with the purpose of discarding the
need of a technician as a mediator.
The system presents the level of eye condition as an indicator of severity of ocular
diseases. It detects various features as an indicator of specific disease and determines its specific
score of probability. However, the system won’t hold any personal information in the form of
database. The web based application will enable it to be used in rural areas with lack of
technicians and will provide a ease of access to report. The scope, however, is restricted to the
NIO environment currently.
The proposed work is aimed at saving a considerable time consumed in generating
report, post OCT scan and will help in delivering immediate and more accurate results. It is sure
to reduce the cost of diagnosis and in fact provide a speedy environment.
Abstract
Optical Coherence Tomography(OCT) Report GeneratorMI-601 :
: Nowadays, each ball of a cricket match is manually classified as highlight/non-highlight
or labelled as a Four or a Six. This project presents ways to automatically classify each ball of a
cricket video, and thus extract highlights automatically from a full-length video.
A video contains vast amount of information, which if extracted helps in breaking down
the video to generate specific information which is helpful to a viewer. A cricket video for
instance contains both the cricket and the advertisements. A typical viewer here would like to
omit the advertisement part while watching the video again. There is much more information to
extract out of cricket video than just separating out ads from cricket. Event discovery in a cricket
match is also a vital part of the highlight detection pipeline. Motivated by such design
specifications, we aim to study various features of the video and audio of a Cricket match to
deliver diverse results. We have generated a model pipeline which contains 3 approaches. The
first one is based on audio analysis and obtaining an ad-free video. In the second approach we
aim to classify a cricket ball on the basis of event discovery. The videos are temporally
decomposed into a series of events based on an unsupervised event discovery and detection
framework. The last approach is used to label a ball with its outcome(Eg. 4/6 runs or wkt etc) to
generate event specific highlights (Eg. Display only Fours/Sixes/Wkts).
Abstract
Automatic Generation of Highlights of a Cricket MatchMI-602 :
: Transportation is the fundamental factor of any developing country.Increasing
population has stressed the transportation. Hence proper management is required.There are
situations when bus is overcrowded and conductor is not able to keep record of every passenger
whether they have issued ticket or not which leads to malpractises by passangers.Therefore we
intend to provide a solution by developing a system which has the capability of monitoring
passengers even in crowed situations .it will not required any manual control. The project
involves the use of Arm-7microcontroller,Fingerprintmodule,Globalsystem for mobile
communication(GSM)module,matrix keyboard and personal computer(PC).The system uses
image processing algorithms for the purpose of identification based on its color and send to
mobile phone via gsm modem.
Abstract
E-ticketing system for intercity public transportMI-604 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 33
06. Multimedia/Image Processing/DSP
PICT, Pune Synopsis : Concepts-2019
: With increase in population around the world, the number of people affected by vision
loss has increased substantially over the years. Blindness or visually impaired is a term used for
completely blind or partially blind people. Visual impairment may cause people to face
difficulties while performing daily activities such as driving, reading, socializing, walking, etc.
Hence this paper presents a system to aid the blind people to try and make their life
easier.Presently, the visually impaired use a simple stick as an aid to perform their daily chores.
But the use of this stick does not make them completely independent while performing their
daily tasks. To address this problem, we are presenting a smarter e-stick approach where a
microcontroller based automated hardware will act like an artificial vision and alarm unit for the
blind. The main aim is to provide a simple, affordable yet an efficient solution for the visually
impaired. The smart e-stick is an IoT-based project that has Ultrasonic Sensors for the detection
of objects, potholes, staircases (up and down) and other low-lying obstacles.It uses buzzers
which will buzz with changing frequencies according to the varying distance of the obstacle. It
also has water sensors for detecting wet surfaces and LDRs for vehicle detection. The smart
blind stick is interfaced via Bluetooth with the user’s smartphone to introduce GPS navigation
for the complete independent navigation of the visually impaired. Live location tracking of the
blind will be facilitated to the nearest help centers or their relatives in case of any emergency
situations. General communication features like placing calls or sending messages will also be
incorporated in the android application using voice commands.Images will be captured using the
camera module on the stick and object detection and recognition will be performed using the
cloud vision API. Therefore important objects such as traffic signals, road-side signs, zebra
crossing etc will be detected for the further high-level guidance of the blind. Also text
recognition will help the blind to read machine printed as well as handwritten text from these
images through voice output modules. Landmark identification, face detection as well as
emotion sensing features will be incorporated for the ease of the blind.Also, if the smart stick
itself gets misplaced, then stick tracking mechanism has also been incorporated. All these
functionalities will be provided using a microcontroller and android application which will
function completely via Natural Language Processing (Speech-to-Text and vice-versa) and voice
commands.Thus, keeping the design of the stick structurally similar, advanced functionalities
have been added to generate a simple, affordable yet an efficient solution for the visually
impaired.Hence this system enables the blind to move with the same ease and confidence as the
normal sighted people.
Abstract
Smart E Stick for visually impaired using android application and cloud vision APIMI-605 :
: The lifestyle of people is changing day by day across the globe. Now-a-day, people are
diverted toward junk food instead of healthy food making themselves fall into disease prone
zone(i.e obesity, diabetes, heart disease, etc ). Therefore we intend to provide a solution through
the web-based application “Automated Self Monitoring Of Calorie Estimation on Food” which
will help people to self monitor their calorie intakes without investing for any nutritionist or
dietitian. The system requires the user to upload the image of eatables which will be used to
calculate calories gained by the individual. As a prerequisite of the project, training of different
food samples are done on the dataset. This training is done using four layers of CNN algorithm.
After training, we got various features of the images i.e height, width, and color which is stored
in the database in the form feature vector. To use services, the user needs to register by filling
form and login into the system using his/her credentials. The health parameters i.e height,
weight, age, and activeness are accepted for further calculation of BMI . According to the
calculated BMI the required calorie intake is displayed.The image of food is uploaded by the user
from the device. After uploading, the image is redrawn and resized into a specific dimension(i.e
500*500). The new image is fed into CNN and features are extracted to predict the food item.
The feature vector of the uploaded image is compared with the feature vectors of trained
images. The Euclidean Distance of the uploaded image vector with the trained image feature
vector is calculated and the item with minimum distance is selected and the item is classified to
that category. To obtain more accurate result we used Naive Bayes classifier. The features from
Abstract
Automated Self Monitoring Calorie Estimation on FoodMI-606 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 34
06. Multimedia/Image Processing/DSP
PICT, Pune Synopsis : Concepts-2019
CNN are given to classifier to predict the appropriate food category. The calorie of food
category detected is subtracted from the required calorie intake and accordingly a generalized
diet plan is generated.
: Many researches have been done to improve ocular disease screening and diagnosis
using advanced image and data analysis techniques. However, the developed systems are not
widely used because they are usually offline and separated from medical devices. Here, we
introduce a platform that connects medical devices, ophthalmologists, and intelligent ocular
disease analysis systems through a cloud-based system. The retinal fundus images and patients’
personal data can be uploaded to the system and automatic analysis and assessment will be
performed using advanced pattern classification algorithms such as CNN and SVM. Further, the
analysis report will be made available so that patients can access their own report through
mobile applications or web portals.
Abstract
Analysis of ocular disease using multiple Informatics domainMI-607 :
: This System is based in creating computer vision at night as well as at day, In this project
we are using different method of capturing and processing images, traditional image processing
use 2D images for image processing 2D provides pixel value in color bits. We are using 3D
images for processing so that the camera output provided in distance that means in pixel provide
its value in millimeters for recognizing gestures and further processing done on Raspberry
PI/Latte Panda Board.The project contain 3D camera that track user skeleton and human
activities, depending on human activities system decides how much light intensity should be
used so that human activity done , system should be able to track human activity andand take
appropriate decision so that energy should be saved.
Abstract
Human Activity based home automation and energy savingMI-608 :
: This System is based in creating computer vision at night as well as at day, In this project
we are using different method of capturing and processing images, traditional image processing
use 2D images for image processing 2D provides pixel value in color bits. We are using 3D
images for processing so that the camera output provided in distance that means in pixel provide
its value in millimeters for recognizing gestures and further processing done on Raspberry
PI/Latte Panda Board.The project contain 3D camera that track user skeleton and human
activities, depending on human activities system decides how much light intensity should be
used so that human activity done , system should be able to track human activity andand take
appropriate decision so that energy should be saved.
Abstract
Human Activity based home automation and energy savingMI-609 :
: Real time human detection and tracking on a drone under a dynamic environment is the
key technique in the field of intelligent transport. A new lightweight real-time onboard human
tracking approach with multi-inertial sensing data is proposed. The first thing built is the drone
and its hardware consists of an embedded system that is used as the flight controller (Ardupilot).
The peripherals include brushless direct current motors, electronic speed controller, frame and
radio receiver, transmitter, and ultrasonic sensors and GPS module. The flight controller
calculates the Yaw, pitch and roll of the drone at an interval and by using PID values it calculates
the corrections to be made to the drone in order to keep it stable. Another more powerful
embedded system Raspberry Pi is also used to implement the smart features of the drone such
as image processing and taking the decisions to track the human in frame. Drone would be able
to perform features such as human tracking using image processing, nearby obstacle detection
and tracking using ultrasonic sensors on board. The user interface consists of a Radio
Transmitter and a web interface that is used for selection of the target human to be tracked.
The image processing is done using ssd_mobilenet algorithm.
Abstract
Smart drone implementing detection and tracking of Humans using MLMI-611 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 35
06. Multimedia/Image Processing/DSP
PICT, Pune Synopsis : Concepts-2019
: THE modern trend of diversification and personalization has encouraged people to
boldly express their differentiation and uniqueness in many aspects, and one of the noticeable
evidences is the wide variety of hairstyles that we could observe today. Given the needs for
hairstyle customization, approaches or systems, ranging from 2D from automatic to manual,
have been proposed or developed to digitally facilitate the choice of hairstyles. However, nearly
all existing approaches suffer from providing realistic hairstyle synthesis results. By assuming
the inputs to be 2D photos, the vividness of a hairstyle re-synthesis result relies heavily on the
removal of the original hairstyle, because the co-existence of the original hairstyle and the newly
re-synthesized hairstyle may lead to serious aritifact on human perception. We resolve this issue
by implementing the functionality of extracting the hairstyle for a given photo, which makes our
work more complete.
Abstract
HAIRCUT RECOMMENDATION SYSTEMMI-612 :
: Digitalization of money transfer is a must in the current state of banking operations.
Clients have various ways to perform transactions, such as credit, wiring money, and so forth.
However, depositing cash requires physical presence of the depositor at the bank, and cashier
need to enrol the transaction into the system, which slows down the rate of money deposit and
teller’s activity. To accelerate the process, banks around the world have to adopt and construct
guidelines for a digital deposit.
To accurately digitize and transmit deposit slip information from smart phones to the
bank, a scheme called as “Automating Data Entry Forms for Banks Using OCR and CNN”. The
deposit slip scanner algorithm is based on input from Smartphone camera.
Abstract
Automating Data Entry Forms for Banks Using OCRMI-613 :
: The Facial Expression Recognition, due to its wide research areas become active
research topic , and it relies on advancements in Image Processing and Computer Vision
techniques. Such systems have a variety of interesting applications, from human-computer
interaction, to robotics and computer animations. Their aim is to provide robustness and high
accuracy, but also to cope with variability in the environment and adapt to real time scenarios.
This project aims at constructing an facial expression recognition system, capable
of distinguishing the six universal emotions: disgust, anger, fear, happiness, sadness and surprise.
It is designed to be person independent and tailored only for static images. The system uses
uniform Local Binary Patterns for feature extraction and Support Vector Machine classifier is
first trained using known input images and then classifies unknown input images. After being
able to recognize facial expressions of normal images we will try to recognize the facial
expression of makeup images. We will compare the difference between normal and makeup
images.
Abstract
Performance Evaluation of Feature Extraction Technique For Facial AnalysisMI-614 :
: Digitalization of money transfer is a must in the current state of banking operations.
Clients have various ways to perform transactions, such as credit, wiring money, and so forth.
However, depositing cash requires physical presence of the depositor at the bank, and cashier
need to enrol the transaction into the system, which slows down the rate of money deposit and
teller’s activity. To accelerate the process, banks around the world have to adopt and construct
guidelines for a digital deposit.
To accurately digitize and transmit deposit slip information from smart phones to the
bank, a scheme called as “Automating Data Entry Forms for Banks Using OCR and CNN”. The
deposit slip scanner algorithm is based on input from Smartphone camera
Abstract
Automating Data Entry Forms for Banks Using OCR and CNNMI-615 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 36
07. Wireless and Mobile Communication/Wireless Sensor Netwoks
PICT, Pune Synopsis : Concepts-2019
: Traditional metering operations are labor intensive and utilize subjective measurement
by field personnel. Additionally, meters are often located in dense urban environments, indoors
or even underground, which can be difficult or impossible to reach by many wireless
technologies. By implementing a smart metering infrastructure comprised of sensors and
gateways embedded with LoRa Technology, utility companies can collect data remotely and use
personnel more efficiently to streamline operations. LoRa is wireless communication technology
which uses low power and provides long range of communication. Meters such as flow meter
and energy meter are provided with LoRa transmitter module. Meters continuously monitors
consumption and send data to gateway through LoRa. LoRa receiver is connected to raspberry
pi gateway. Up to 1000 LoRa devices can be connected to one gateway. Gateway sends data to
thingspeak cloud. Server can monitor data on cloud through webpage and user can check their
consumption using android app.
Abstract
LoRa based metersWM-701 :
: Spectrum is a very precious resource and thus underutilization of a large part of
allocated spectrum is not affordable. With an increasing demand for wireless applications,
allocated spectrum utilization is found to be very low. While Cognitive Radio is proposed as a
promising solution for increasing spectrum utilization and thereby helping to mitigate spectrum
scarcity, implementing it securely is a crucial task. By manipulating radio sensor inputs, an
adversary can affect the beliefs of a cognitive radio and subsequently its behaviour. To
overcome this difficulty Blockchain, a highly secure technology can provide a better solution. In
this project, we propose a blockchain verification protocol as a method for enabling and securing
spectrum sharing in moving CR networks. We use an auction mechanism based on
first-come-first-served basis. A cryptocurrency named Crubs is introduced for facilitating
transactions between primary and secondary users. Blockchain being a distributed database
system, the database is visible to all and any node can volunteer to update the blockchain. It will
lead to a decentralized, secure dynamic spectrum access with no cost of security. The proposed
auction mechanism improves the efficiency of current media access methods in case of
small-scale fading.
Abstract
Distributed EM spectrum database based on BlockchainWM-702 :
: Wireless Sensor Networks (WSNs) can be used for many applications, such as industrial
automatic control, remote environmental monitoring and target tracking. The similar system is
promising applications in fires can make a real-time monitoring and detection.
Wireless sensor network consists of numerous small nodes in most situations, which
small nodes are deployed in remote and inaccessible hostile environments or over large
geographical areas. The large number of small nodes sense environmental changes and report
them to cluster head node over network architect, which the deployment and maintenance
should be easy and scalable. The proposed approach can provide faster and efficiently reaction
to fires while consuming economically WSN’s energy, which has been validated and evaluated in
extensive simulation experiments.
Abstract
Fire detection & prevention with robot using WSNWM-703 :
: Bandwidth is a very precious resource. In today’s developing era, communication is the
backbone of almost all sectors in the industry. So, bandwidth has to be efficiently used due to its
low availability. Cognitive radio is a band allocation device which senses the spectrum for
availability of band for the secondary user. It uses many methods for this spectrum sensing, and
majorly performs two functions- Spectrum sensing and Spectrum Allocation.
In this project we propose a spectrum sensing technique for wideband signals which is
basically an eigen-values based technique but the threshold (which specifies the value of test
Abstract
Spectrum sensing using machine learning for cognitive radioWM-704 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 37
07. Wireless and Mobile Communication/Wireless Sensor Netwoks
PICT, Pune Synopsis : Concepts-2019
statistic above which signal is present) is replaced by an efficient classifier. Weather the
spectrum can be allocated to the secondary user or not will be the result of our project.
: Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier system where
data bits are encoded to multiple subcarriers, while being sent simultaneously. This results in the
optimal usage of bandwidth. A set of orthogonal sub-carriers together forms an OFDM symbol.
To avoid ISI due to multi-path, successive OFDM symbols are separated by guard band. This
makes the OFDM system resistant to multipath effects.
Basically, the OFDM is the technology derived from the FDM that is the carriers are
harmonics in OFDM i.e., the integral multiple of the fundamental frequency and system can be
implemented by one of the modulation schemes like QPSK, BPSK or QAM for the betterment of
the OFDM signal and effective use of bandwidth.
Abstract
Orthogonal Frequency Divison MultiplexingWM-705 :
: In wireless mobile communication systems, antenna diversity is one of the most
important techniques to improve the performance. Codes suitable for antenna diversitywhich
achieve full diversity, full rate and good coding gains are preferred when thereare a small
number of parallel channels. Since the Space-time block Codes (STBCs)is invented by Alamouti
and Tarokh in 1998, STBCs have gained much attention asthey are able to integrate the
techniques of spatial diversity and channel coding, andcan provide significant capacity gains in
wireless systems. As an effective transmitdiversity technique, STBC can be embedded into many
existing digital communication systems to combat fading,such as orthogonal frequency division
multiplexing(OFDM) systems or code division multiple access (CDMA) systems.
Abstract
Alamouti space time block codesWM-706 :
: This project report entitled to Design and fabrication of multiband patchantenna for
wireless application using HFSS. Multiband antenna for mobilephone application is designed and
analysed. For the design and simulation of thisantenna we used High Frequency Structure
Simulator(HFSS) software. The antennawas designed on a FR4 epoxy substrate with relative
permittivity 4.4 and dielectric loss tangent of 0.02 with a thickness of 0.8 mm. The performance
of antennawas evaluated based on return loss, operational bandwidth, gain, and VSWR
andradiation pattern characteristics. During measurement, return loss was measuredby seeing
the S11 port reflection constant parameter and it was found to be -18dB,-12dB, -14dB and
-24dB. The operating frequency bands of the proposed antennadesign are 2360 MHz, 2500
MHz, 2700 MHz and 3420 MHz having VSWR 2.3dB,4.6dB, 3.7dB and 1.2dB respectively.
Abstract
Design and fabrication of multiband patch antenna for wireless application using HFSS.WM-707 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 38
08. VLSI/Embedded Systems/Communication Systems
PICT, Pune Synopsis : Concepts-2019
: We’ve all seen the statistics: millions of working days lost per year due to back and neck
problems; arthritis on the rise; children spending less time outdoors than prisoners. Bad posture
is a nationwide epidemic. We sit hunched at desks all day, from school and university and into
working life. A poor posture over a prolonged period may not always lead to musculoskeletal
issues, but it often does, putting a considerable strain on the NHS.Maintaining a good posture
has become an utmost necessity in the part and parcel of our lives to avoid temporary and
permanent health issues. Bad posture has not only affected professionals in the IT industry but
with the growing influence of technology in the lives of teenagers, college students, and
professionals in the field of education, science and technology are increasingly subjected to neck
and back aches, and spinal cord related issues.
SITWELL is a device of great significance. It’s a “posture monitoring” device that’s
designed to indicate the wrong posture and therefore reduce pain and strengthen core – it could
even boost confidence and improve body language. This device will be mounted on the back and
interfaced wirelessly to the user’s laptop through BLE. Each time the device detects slouch, it
will notify the user. Slouch detection will be done using 3-axis accelerometer for accurate
results.
The user will be notified each time the device detects a wrong posture on the laptop
screen through a software interface. When the user is away from his laptop, slouch detection
will be notified by mild vibration to the user.
Abstract
SITWELL- POSTURE MONITORING DEVICEVE-801 :
: In line with today’s generation, falls represent a significant threat to the health and
independence of adults 65 years of age and older. It is becoming increasingly necessary to detect
when an individual has fallen, a need to analyze and synthesize ways to intimate the concerned
individuals for the quick and critical response. Our project aims at designing a device that could
be worn as a waist belt and helps us to detect fall of a person and then send this information over
the internet using WebRTC protocol. In absence of internet, the intimation would be sent
through SMS facility.
The sent information would include the nature and location of fall. This allows the
concerned family members to take necessary actions and avoid a fatal accident or even loss of
life.
Abstract
Fall Detection Device for Senior CitizensVE-802 :
: Human tracking is very important component of the computer vision system. It has
multiple applications in video surveillance, navigation, 3D image reconstruction, robotics etc. It
has attracted many researchers in this field. This project is aimed to continuously track a human
using a movable camera mounted on a quadcopter and instruct it to move towards and follow
the human. This project will incorporate algorithms used for object tracking, hardware setup of
movable camera on quadcopter and software required for this task. Most of the object tracking
quadcopters present today use off-board computers for image processing, estimating position of
the object and for implementing the computationally heavy algorithms for the same. In this
project we plan to process the video feed and implement the algorithms on a portable computer
like Raspberry Pi on-board the drone itself and directly generate the commands for drone
motion after processing the input. This will reduce the processing delay and also reduce the
communication and propagation delay drastically, resulting in fast and accurate human
detection and tracking.
Abstract
Human tracking with a droneVE-803 :
: The advances in Information Technologies have led to more complex road safety
applications. These systems provide multiple possibilities for improving road transport. The
Abstract
Advanced Driver Assistance SystemVE-804 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 39
08. VLSI/Embedded Systems/Communication Systems
PICT, Pune Synopsis : Concepts-2019
integrated system that this project presents deals with two aspects that have been identified as
key topics: safety and efficiency. To this end, the development and implementation of an
integrated advanced driver assistance system (ADAS) for rural and intercity environments is
proposed. It allows real time detection and classification of obstacles, and the identification of
potential risks. The driver receives this information and some warnings generated by the
system. In case, he does not react in a proper way, the vehicle could perform autonomous
actions (both on speed control or steering maneuvers) to improve safety and/or efficiency. the
system is designed to warn the driver if a risk is detected and, if necessary, to take control of the
vehicle.
The applications developed include: adaptive cruise control with consumption
optimization, overtaking assistance system in single-carriageways roads that takes into account
appropriate speed evolution and identifies most suitable road stretches for the maneuver;
assistance system in intersections with speed control during approximation maneuvers, and
collision avoidance system with the possibility of evasive maneuvers. To this end, mathematical
vehicle dynamics models have been used to ensure the stability, and propulsion system models
are used to establish efficient patterns, Artificial Intelligence and simulation are used for
experimentation and evaluation of algorithms to be implemented in the control unit. Finally, The
system has been implemented on a passenger car and has been tested in specific scenarios on a
test track with satisfactory results.
: NiTinol is a Nickel-Titanium alloy which is considered part of the shape memory alloy
class which means that it goes through the shape memory effect. When the material is held at
low temperature, it is in a very ductile form known as Martensite. This allows for the NiTinol
wire to be bent in any shape. When the material is heated up past its transition temperature, it
becomes much more rigid as it enters its Austenite form. When NiTinol wire enters the
Austenite state, it returns to its original shape regardless of any deformation that occurred at
lower temperatures, therefore it is referred to as a shape memory alloy. When the material is
cooled and re-enters its Martensite state, it does not return to its deformed shape until a load is
put on the wire.The ability of SMA to reversibly respond to external temperature changes and
change their physical/mechanical properties has enabled them to find many application. In
thermoelectric system, SMAs can be used as combined sensors and actuators where they can
sense the changes in external stimuli and monitor certain desired functions. Motivated by such
unique property, we aim to study, validate the different behavioural models of SMA and design
the testbench for the same and design the GUI in LABVIEW and interfacing the sensors used in
the experimental setup for verification with respect to research papers published
previously.Also to implement equations of modelling structures of NiTinol which includes the
parameters such as Resistance, Current, Temperature and Voltage applied with respect to time.
Abstract
Characteristics validation of NiTino,through Joule HeatingVE-805 :
: Government provides various facilities to poor and people below poverty line but such
facilities do not reach up to needy and poor people due to corruption present in the chain. One
of such facility provided by government is rationing material distribution. All the people having a
ration card to buy the various materials (sugar, rice, oil, kerosene, etc.) from the ration shops.
This material has to be taken from the shopkeeper at one time. If it is not taken by any card
holder then there is no monitoring of such unused material. So the shopkeepers are doing miss
use of these things by selling in the market and doing the fraud. So a central monitoring system
is required which is to be linked with government offices, shopkeeper and the ration card holder.
In this paper we proposed one such system which is developed by using Smart Card based on
EPROM ,Wi-Fi Module ,Android Application and PIC Microcontroller. Which will take care of
all the activities related for avoiding illegal work made by authorized people and help to
overcome the problems in this concern area.
Abstract
Smart E-Rationing SystemVE-806 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 40
08. VLSI/Embedded Systems/Communication Systems
PICT, Pune Synopsis : Concepts-2019
: Recently, it is seen that dustbins placed at a various places like public places such as
hospitals,educational Institutes and Industries are overflowing. This overflowing of garbage bins
create unhygienic condition which can spread the diseases. Also rapid increase in population
waste give rise to improper waste management.
To avoid this situation, we proposed new systemWaste Collection Management
System. In the recent decades, Urbanization has increased tremendously. At the same time there
is an increase in waste production. Waste management has been a crucial issue to be considered.
This paper is a way to achieve this good cause. smart bin is built on a microcontroller based
platform Raspberry pi Uno board which is interfaced with GSM modem and Ultrasonic sensor
And also the weight Sensor which is used for calculating the weight of the dustbins.
The Weight Sensor is placed at the Bottom of the dustbins which will measure the
weight of the dustbins and also the Ultrasonic sensor is placed at the top of the dustbin which
will measure the status of the dustbin. The threshold limit is set as 10cm. Raspberry will be
programmed in such a way that when the dustbin is being filled, the remaining height from the
threshold height will be displayed. Once the garbage reaches the threshold level ultrasonic
sensor will trigger the GSM modem which willcontinuously alert the required authority until the
garbage in the dustbin is squashed. According to the location, authority will sends the message
to the respective operator, garbage vehicle cancollect the garbage, which is done with the help
of robot mechanism.
Collect all the readings of every container of filling ratio, and give input to genetic
algorithm.Execute all the input population.GA will terminate it will find the vehicle root.GA will
provide the optimized path we will verify the real time accuracy.
Abstract
Waste Collection Management SystemVE-807 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 41
09. IOT/Industrial IOT/Smart Cities/Sustainability
PICT, Pune Synopsis : Concepts-2019
: This invention proposes an efficient implementation for IoT used for monitoring and
controlling home appliances using android application. To operate appliances which are
connected to analog switches in the home, the user needs to manually press the switch to turn
ON or OFF any appliance. This hassle of manually operating a switch is replaced by a smart
technology which involves operating the switches using the Android application. Smart switches
already exist in the market today, but they are very expensive and requires additional devices
like hubs for their working. The current work makes use of an Android application and a Cloud to
control the operation of the appliances. Also IR based devices like Tv, Ac etc. can also be
controlled directly through the Android application. The user communicates with the database
through the Android application, then corresponding changes made in the database which are
further detected by Raspberry Pi. After that processor sends a corresponding IR signal to the
appliances based on the changes received from the user, this ensures the portable usage of the
device. Also Raspberry Pi collects data from DHT22 sensor and stores into the database,
whenever the user makes changes in AC temperature. After the collection of sufficient data
raspberry pi will train the ANN (Artificial Neural Network) on collected data to predict the ac
temperature required by the user. Once the ANN model is trained on collected data periodically
prediction of ac temperature is done by the system automatically.
Abstract
Portable Home Automation with machine learningIS-901 :
: Undoubtedly, water is one of the important resources on entire globe. No one including
human beings, animals, plants or insects can live without water. Water is a scarce resource and it
may deplete over coming years due to overuse. The bad quality, overflowing water from tanks,
leakage in pipes, and inefficient usage of water are the main cause which leads to the wastage of
water. So it is necessary have control on water wastage and usage as well by introducing or
building a system which will overcome the water related issues using Internet of Things (IoT). So
we are building a system which will check the quality of water and notify to the users, equal
distribution of water, detect the leakage in pipes, control the usage of water, water level
detection, soil moisture detection in farms. This will help in control the wastage of water, health
issues by checking the quality, etc.
Abstract
Development of real time water monitoring system using IoTIS-902 :
: From last two decades there is a tremendous increase in density of vehicles on road.
Hence, there is increase in demand of parking space. Creating new parking slots is expensive in
today’s world, which leads to shortage of parking slots. This leads to congestion and finding a
parking spot is tedious task in high density traffic, in the era of smart city there is need of smart
parking systems (SPS).A parking lot should provide customers enough spaces to park their car
since car plays a huge role in transportation, there is need of finding out parking area to park the
vehicles.The common method of finding a parking space is manual where the driver usually finds
a space in the street through luck and experience. This process takes time and effort and may
lead to the worst case of failing to find any parking space if the driver is driving in a city with high
vehicle density. The alternative is to find a predefined car park with high capacity. However, this
is not an optimal solution because the car park could usually be far away from the user
destination.By creating a new system, it can help manage and reducing the road traffic. A new
system helps customers to save time in finding a parking spot. The Internet of Things is about
installing different sensors like ultrasonic sensors; active and passive RFID, IR, etc. connect to
the internet through different protocols. Using IoT, Smart City can be established by integrating
these features for IoT development. The SPS is based on several innovative technologies and can
automatically monitor and manage car parks.Furthermore, in the proposed system, each car
park can function independently as atraditional car park. Additional to this we will check
improper parking, this happenswhen a car is parked in such a way that it occupies two parking
slots rather thanone and charge extra amount for careless parking. Also, the reverse parking
assistwill be provided at the parking slot for ease in parking the vehicle in reverse gearand led
Abstract
Internet of Things based Smart Parking System using RFIDIS-903 :
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09. IOT/Industrial IOT/Smart Cities/Sustainability
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light track follow line will be constructed to show the parking slot to provide ease in navigation.
Thus, SPS will enable the user to find the nearestparking slot and avoid unnecessary traveling
through filled parking slots in parkingarea and system will bring ease in parking and reduce the
fuel consumption which reduces carbon footprints in atmosphere.
: In this project, The Biometric Access Control System based is designed and
implemented on IOT. These system can be used for security purpose of an environment so that
only the authorized persons are allowed to pass or also for attendance measuring purposes.
Biometric confirmation is the best among security frameworks. These frameworks are included
biometrics, like , unique mark, iris, and so on. Unique mark based biometric framework is a
decent mix of minimal effort and high precision. Assessment of individual's confirmation is
finished by refreshing time, participation and all related data to a Web server. Biometric
understudy participation framework builds the effectiveness of the way toward taking
understudy participation. This paper shows a basic and compact way to deal with understudy
participation as an Internet of Things (IOT) based framework that records the participation
utilizing unique mark based biometric scanner and stores them securely on the cloud. This
framework plans to robotize the bulky procedure of physically taking and putting away
understudy participation records. It will likewise anticipate intermediary participation,
subsequently expanding the unwavering quality of participation records. The records are
securely put away and can be dependably recovered at whatever point required by the
educator.
Abstract
BIOMETRICS BASED STUDENT ATTENDANCE MONITORING SYSTEMIS-904 :
: Disaster and accidents are uncontrolled human events which needs to be combatted in
the bestpossible way. Such events cause huge loss of life and property due to unavailability of
necessaryservices. Medical aid is one of the most important factor which fails to reach at the
desireddestination due to road transport failure. With the advancement in technology day by
day theurge to cope with other industries has increased drastically. In the past few years’
drones(Unmanned Aerial Vehicle) have transformed from a geeky hobbyist affair to a full-on
culturalphenomenon. The market is absolutely saturated with them due to their availability in
any shape, size or configuration as per one’s will. The future use of drones in healthcare also is
very thought provoking. Several thousands of people die day to day due to the time lag taken by
the Ambulance service to reach the accident spot. This happens due to traffic jam, congestion in
the city. A prototype of an emergency drone which can reach the fatal cases faster than a normal
ambulance which saves time is designed and it also measures the different health parameters
using its measuring devices. This can be used to provide aid to people in case of disasters where
road transport is time consuming. The rapid delivery of vaccines, medications and supplies right
to the source would aid the affected person. The proposed system consists of a UAV which
provides immediate & necessary medical services to the needy. The user needs to send a
request for the medical services he/she requires through web portal/ mobile application. The
consent hospital operators will receive the request and load the necessary medical services on
the drone. The drone will track the request location & navigate using a GPS and reach the
destination thus providing aid to the user. Further the drone will return to its initial source after
the medical service has been unloaded by the user. This system would thus provide a faster and
efficient way of overcoming the loss of time generally observed by road based ambulance.
Abstract
Drone based Medical ServiceIS-905 :
: Recommendation Systems are the sort of data separating frameworks intended to
assist clients with finding their way through the present huge data spaces. The objective of a
Recommendation System is to produce proposals to clients. This will be useful for offering
suggestions to data searcher. Analyzing Recommendation of School for Users. The objective of
this project is to develop an web based application which will help users to find best, nearest and
affordable primary and secondary school.
Abstract
Emergency Vehicle Alert SystemIS-906 :
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09. IOT/Industrial IOT/Smart Cities/Sustainability
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Now a days in this current running world people do not have time to visit every school
personally and collect all the information regarding school admission process. Parent are
expecting to be get an whole information at one place, so that they can get required information
about best school. There are so many resources are available on internet regarding college
information but not for school so we are proposing this system which will help the user to find
out their affordable school.
: To manage the greenhouse ,the weather condition is the most important factor. The
main goal of automated fogger system is to manage all weather condition factors such as
temperature, humidity, soil moisture level etc. and also provide the access to these system
remotely. The greenhouse can be monitored automatically without physical presence of farmer.
In this the sensor reads information simultaneously of greenhouse and sends it to the raspberry
pi, The raspberry pi will check the sensor’s value with standard database value maintained for
the particular crop. after comparison if the threshold value maintained for the particular crop
increases/decreases then accordingly action will takes place. These actions are as follows- If
the temperature get increases then exhaust fan will get started. If the moisture level of soil
get reduce then water supply will be provided. A greenhouse provides an environment to grow
plants all year around, even on cold and cloudy days. However, extreme environmental factors
inside the greenhouse such as high temperatures and a high humidity can negatively impact on
the plants. The automated fogger system is based on the programming a raspberry pi using
Python language to act as the central hub that manages the various sensors. The main goal of
this system is to analyze and maintain the greenhouse temperature in a desired range for
optimal plant growth using a temperature control system. We have planned to finish this project
as soon as possible but for the betterment of the performance we need more time. Therefore
this project can be extend to 1 or 2 weeks if any case. we assure you we will give you a finished
product.
Abstract
Automated fogger systemIS-907 :
: In the age of wireless technology and increasing use of non-renewable energy resources
there is a constant increase in the demand for wireless technology which is environment
friendly. Due to the problems caused by the gasoline engine on the environment and people, the
automotive industry has turned to the electric powered vehicle. Our project focuses on
implementation of wireless charging of battery for Electric Bus by inductive coupling method.
Whenever the bus arrives on the Bus Stop, the RFID sensor gives an indication that the bus has
arrived, then the controller switches the relay to begin the charging through transmitter and
receiver coils by Inductive Coil coupling method.For charging the battery on the Bus Stop we
have used Solar as well as AC mains supply but the first preference will be for Solar supply itself,
only in the absence of Solar Energy i.e. during night times or in rainy season the AC mains supply
would be used. Continuous monitoring of Solar power received in whole day would be done by
IoT. Results obtained of the Solar charging would be plotted in graphical format on the web
which will be observed by the concerned person in the Bus Depot to do the monitoring of all Bus
stops.
Abstract
Wireless Charging of Electric Bus using Inductive Coupling MethodIS-908 :
: Ever since the dawn of mankind, agriculture has been the only source of survival.The
traditional methods of irrigation were favourable when planet earth was not water scarce. Now
when the world has come down to so many nature related issues, an automated and sustainable
irrigation method was something to look upon being responsible global citizen. Our irrigation
system primely focuses on the conservation of water and hence save the fertile soil from further
salinity. We have approached the aforementioned problem via a moisture sensors, that tells us
about the moisture content of the soil. This extracted information drives the whole idea of our
proposed work. The purpose of our idea is noble yet the optimised and advanced version of a
tradition technology. It will drive the field of agriculture into a whole different and new level
Abstract
IoT Based Smart Irrigation SystemIS-909 :
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09. IOT/Industrial IOT/Smart Cities/Sustainability
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where things are modern yet eco-friendly. To make the system smart, we have interfaced Wifi
module along with the microcontroller.
: A vehicle tracking system is proposed which track the vehicle and offers to incarcerate
the vehicle in minimum period of time when it is lost. Vehicle tracking system has a Global
Positioning System (GPS) and a Global system for Mobile Communication (GSM). Owner can
send an edict anytime to the device which is in the vehicle. Vehicle tracking system is the
technology, which is habituated to track the vehicle and send the location to the owner.
Abstract
Anti-Theft Vehicle Tracking SystemIS-910 :
: Automation has become a new trend in today’s world. People always appreciate
automation everywhere. We know that purchasing and shopping at big malls in traditional way
has become a tedious job for the employee and also the billing process is lengthy. We propose an
automated shopping system in which the customer scans the products, place it on the conveyor
belt through which all the products will be packed in bags and will be ready for the customers at
the exit door. For this, an application is developed in which the customer must register himself
into the system. After registration each customer will get a barcode which will uniquely identify
him and must be logged in to use the system. After taking all the products into the cart, the
customer would go to checkout counter which is attached with a conveyor belt. The customer
scans the unique barcode from the application and then scans each product and places it on the
belt. If a product is placed without scanning on the belt, weight sensor will detect the extra
weight and the belt will halt. The scanned products would be placed in the customers bag and bill
is generated on customers app through which he/she can pay directly. At the exit door, the user
need to show the OTP generated after the billing to ensure security. The app also shows the
previous shopping list and can also navigate through the mall using the indoor navigation system
in the app. Thus making an IoT based automated system for better shopping experience.
Abstract
Automated Shopping SystemIS-911 :
: In today’s era women are entering in industrial area but a biggest question is how to
provide security to them and protect them. An important issue is to provide a safe atmosphere
to every women so this application is beneficial in this case. This is an easier technique specially
designed for the women. The system expects to a wireless strategy as embedded device
specifically Raspberry Pi for women providing a way of communicating with secure stations and
it captures the HD video using R-pi camera. Also in the circumstance of women security the
system proposes location monitoring facilities using GPS, GSM and GPRS. The enhance feature
of this system is video recording. We have utilized diverse sensors like temperature sensor. The
system involvesa heartbeat sensor which measures the heartbeat of victim. The algorithm used
in this system is “Decision tree”, which will compare the sensor value (predicted) and the actual
threshold value set by the system.
Abstract
Intelligent System Using IoT for Women SafetyIS-912 :
: Vehicular traffic is endlessly increasing everywhere in the world and can cause terrible
traffic congestion at intersections. The vast majority of the movement lights today highlight a
settled green light succession; in this way the green light grouping is resolved without
considering the nearness of the crisis vehicles. Along these lines, crisis vehicles, for example,
ambulances, squad cars, fire motors, and so on stuck in a congested driving conditions and
postponed in achieving their goal can prompt loss of property and profitable lives. This
document present an approach to plan crisis vehicle in travel. The approach combine the
dimension of the space among the crisis vehicle as well as an junction through visual sense
method, vehicle counting as well as time responsive alert broadcast inside the sensor network.
The space among the crisis vehicle also the junction is considered for association using Euclidean
Abstract
Emergency Vehicle Alert SystemIS-913 :
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09. IOT/Industrial IOT/Smart Cities/Sustainability
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distance, Manhattan distance and Canberra distance techniques.
: As per the latest data, in 2017, a total of 464,910 road accidents were reported in India,
claiming 147,913 lives and causing injuries to 470,975 persons, which translates into 405 deaths
and 1,290 injuries each day from 1,274 accidents. To reduce these numbers we are proposing a
real time alert system for the drivers for drive security.In today’s world the internet is a
necessity. In this world everyone and everything is getting connected with IOT (Internet of
Things). We used same connection network known as IOV (Internet of Vehicles) through which
we are connecting the vehicles to their drivers phone to provide real time alerts. We used OBD
II (On Board Diagnostic) port for gathering the sensor data from the vehicles. This data is then
transferred to cloud using Rasberry Pi through a working internet connection. Then the Machine
learning algorithms will execute on gathered data and the monitoring of the drive is done. And
also the driver will be updated with the real time data and features like gear shift alerts, rash
driving alerts.
Abstract
Real Time Drive Monitoring System for Drive Safety Using Machine Learning on IOVIS-915 :
: Imagine you run a restaurant that is jam-packed on a Friday night, and you have
customers waiting for the attendant to come and take their order (or get them the check when
they're done) only to realise that your waiters are too busy attending other patrons. After
countless hand-waving and calling attempts, they run out of patience and the irritability is
attributed to the service quality. A common scenario, isn't it? So how can service businesses
ensure that each and every customer is attended to in the best possible manner? Well, that's
where the R-Notifier by ReckonPlus comes into the picture.
A remote and receiver (with a range of 100 metres), this easy-to-install and
user-friendly system makes the communication between your staff and the customer faster,
streamlined and highly responsive. The remote is basically a small device (with buttons) that can
be placed on the restaurant table (or say, next to a hospital bed). When the user presses a
button, a unique wireless code is sent to the receiver, notifying the table number or room
number (that flashes in the form of an LED light on the receiver's front panel). It also comes
pre-loaded with a voice announcement feature. Your service team can instantly get alerted
about the call and the customer's request can subsequently be fulfilled efficiently.
Abstract
R-NotifierIS-916 :
: The project proposed a bus safety system which is designed to control the
entering/exiting of students from the bus. This system does several tasks, including identifying
personal information (E.g. Student id, Name, Class and Mobile Number) of each student using
QR Code, and displaying each student name into Android app display. Though not within strictly
in the scope, the same data can be used to assess the time of departure and arrival.
The problem definition for the system is to develop software for School Children
Security for the schools based on features- QR Code Techniques ,in which school buses can be
tracked on the way and software also maintain database of students. School Principal has
authority for login and make changes in the students database. Android app will send mobile
SMS to their parents about its successful departure and arrival and live tracking also provided.
Abstract
QR based school children safety enhancementIS-917 :
: Uncontrolled growth of the urban population in developing countries in recent years
has made solid waste management an important issue. In fact it is a global environmental issue
which concerns about a very significant problem in today’s world. To tackle this problem GIS can
be used as a decision support tool for proper planning of waste management. The model will be
implemented on the Aurangabad city’s current waste disposal areas and the results will suggest
some modification in the existing system which is expected to reduce the waste management
Abstract
Land Use Change Detection for solid waste managementIS-918 :
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09. IOT/Industrial IOT/Smart Cities/Sustainability
PICT, Pune Synopsis : Concepts-2019
workload to a certain extent. Significance of the project is as follows:
GIS can be used to identify the land areas where waste is being disposed and what
changes has occurred in those areas over a period of last 10 years. In this study a GIS optimal
routing model is proposed which can compute minimum cost and distance required for efficient
collection of waste.This model will also suggest the path for transporting the solid wastes to the
landfill. The proposed model can be used as a decision support tool by municipal authorities for
efficient management of the daily operations for transporting solid wastes, managing fuel
consumption, load balancing within vehicles and generating work schedules for the workers and
vehicles. Data is provided as output in the format of land area used in the form of maps and
tables where quantitative data is present to represent the change detection.Land Change is
done between years 2005 to 2015.Remote sensing (RS) and ? Geographic Information System
(GIS) are now providing effective tools for advanced land use change detection.The collection of
remotely sensed data facilitates the synoptic analyses of Earth – system function, patterning,
and change at local, regional, and global scales over time; such data also provide an important
link between intensive, localized change detection research and regional, national and
international conservation and management of population.
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10. Others
PICT, Pune Synopsis : Concepts-2019
: Sentiment analysis uses natural language processing and machine learning techniques
to find statistical and/or linguistic patterns in the text that reveal attitudes. It has gained
popularity in recent years due to its immediate applicability in the business environment, such as
summarizing feedback from the product reviews, discovering collaborative recommendations.
or assisting in election campaigns. The focus of our project is the analysis of the sentiment in the
short website comments.
Internet and social networking play a vital role in research field. It contains massive
diction about what people think. Twitter is a micro blogging site where people post their views
and preferences related to their interests. In this project we try to create a generalized review
projection web app to project aggregate public review about a movie by analyzing the hype
created amongst the mob. We use sentiment analysis of twitter data for the same. To display the
output we show number of positive as well as negative tweets about the movie along with
average public opinion.
Abstract
Movie Review SystemOT-101 :
: Clinical Depression also known as melancholia can often occur due to variety of reasons
which could be dejection, sadness, despondency, anger, fear, delusion and obsession. Depression
cycle can last for both long and short durations, depending on factors responsible for it. Anxiety
is a general term for several disorders that cause nervousness, fear, apprehension and worrying.
Approx. 50 million people in India suffer from depression and 30 million from anxiety according
to report by the WHO.
The project involves development of hardware systems along with the quantitative tool
for early diagnosis and treatment of this disorder. MRI scanning is expensive and is not possible
in semi-urban and rural areas. The cost of an MRI scan increases cost of therapy sessions
significantly. Therefore, there is a need to develop a low cost and effective tool for quantification
of the therapy being administered to the patients. This could be done by monitoring basic
biomarkers from the body non-invasively before and after the treatment, which is co-related to
the MRI data.
In this project, major study and experimentation is done on two major biomarkers –
ECG and EDA. Various features of the signal such as hear rate variability (hrv) from ECG and the
phasic component of EDA signals are extracted to give a quantitative data for analysis. Use of
cvxEDA algorithm is employed for separation of the phasic component from the EDA signal.
Standard deviation of normal to normal R-R intervals (sdNN) is employed to project hrv curve.
Abstract
Quantitative Tool for Neuro-therapyOT-102 :
: The current solar inverter modules which are being sold in the Indian market are
basically comprising of either the inverter section or the charge controller section. Our project
intends to develop a system that has both of these in a single product and also aim to have
healthy increase in efficiency of the system by introducing the sun tracking mechanism and
hence increase the effective output of the solar panel throughout the day.
Another important aspect that our project encompasses is that of the buck boost
converter and the CMOS IC based inverter section (low power consumption). Current systems
basically rely on the PWM concept of the charge control , but we intend to develop a derivative
of MPPT algorithm.
So overall this project is compartmentalized into three parts :Sun tracking ,buck-boost
charge controller (derivative of MPPT algorithm) and the inverter section.
Abstract
Solar Hybrid Inverter With Sun Tracking MechanismOT-103 :
: Sign language is an important mode of communication for the hearing impaired. Hand
gesture recognition is one of the methods used in sign language, which is also the most
Abstract
Computational module for the hearing-impairedOT-104 :
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10. Others
PICT, Pune Synopsis : Concepts-2019
commonly used method by deaf and dumb people for communicating with each other. A lot of
research and standardization has been done in ASL(American Sign Language) as compared to
ISL(Indian Sign Language). Also interactive ways of teaching are being developed for normal
schools, where as no efforts are being made for hearing-impaired students. The proposed
system aims to standardize ISL and develop an interactive computational module for teaching
and testing purpose of deaf students. This HCI module recognizes standard ISL hand gestures of
0 to 9 number system using transfer learning, a deep learning technique. A teaching and testing
module with interactive GUI is developed for hearing-impaired students to perform better in
their academics, it performs various mathematical operations on the recognized image, captured
using the webcam. The module is implemented using MATLAB.
: There is often a communication gap between the corporation, the working staff & the
civilians. The issues of the civilians take a long time to be processed & many a times it so
happens that the issues are not even conveyed properly. Due to this delay, the complaints take a
long time to be worked on. The Application ‘Complaint Management System’ has 3 users. First
user is the ‘Admin’ who has the rights to create a new user id for higher authorities of the
corporation. Second user is the ‘Civilian’ who notices faults & can notify the corporation of the
issues, he/she has by adding a text & uploading a picture. Third user is the ‘Worker’ who again
has 7 roles that differ as per the issue category. These categories can be ‘Garbage’ , ‘Drainage’ or
‘Civil’. Each of the user roles can either Complete the work on the issue or forward it to the next
responsible official. Under the ‘Garbage’ category, the initial request goes to the Corporate.
When he approves it, the request is forwarded to the ‘Worker’. If the ‘Worker’ forwards the
request, it is sent to the ‘Sanitary Engineer’ & then to the ‘Ward Officer’. In case of ‘Drainage’ or
‘Civil’ categories, the flow of request goes as Corporate, Deputy, Executive & lastly to the
Commissioner. The ‘Civilian’ who has raised the issue can track the current status of the
complaint with date and timestamp.
Abstract
Complaint Management SystemOT-105 :
: One of the ?rst things to do while purchasing a product form e-commerce website is to
go for a good e-commerce website. Buying a product form e-commerce website can be an
overwhelming task with tons of e-commerce websites to choose from, for every speci?c product.
Motivated by the importance of these situations, we decided to work on the task of
recommending e-commerce websites to users. We used multiple e-commerce websites
recommendation dataset, which has a variety of features that helped us achieve a deep
understanding of the process that makes a user choose certain websites for purchasing speci?c
product over others. The aim of this product recommendation task is to predict and recommend
some websites clusters to a user that he/she is more likely to buy given hundred distinct clusters.
Abstract
Product recommendation systemOT-106 :
: YouTube is most popular video sharing platform around the world due to which
YouTube has become most preferred choice of users. With the current level of complexity of
YouTube ,obtaining users behavior and choices automatically became a crucial task. Current
personalize recommendation system is based on users watch and search history is not adequate
factor for most appropriate video suggestion. To minimize this issue of irrelevant
recommendation,we are proposing the YouTube recommendation system based network of
user comments and their sentiment analysis.Depending on users comments they will be added
into only relevant recommendation network.We are considering that comments might be useful
source to gain information about video quality and relevancy. Therefore,in this system we are
using sentiment analysis approach for relevant video recommendation. YouTube dataset
contains different attributes such as likes,dislikes,comments and views which can provide useful
insights to the uploader using statistical analysis. We are also interested in determining the
change in rate of recommendation by using our improvised approach rather than the
conventional recommendation of YouTube
Abstract
Youtube Video Recommendation Based On User Comments And Its Statistical AnalysisOT-107 :
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10. Others
PICT, Pune Synopsis : Concepts-2019
: Due to excessive use of chemicals and pesticides the crops produced are harmfulfor our
health .So, The KrushiDhan Company took an initiative to provide organicproducts .Here, we
need to develop a platform where the organic products can besold and there will be ease in
transactions.
Considering the requirements-”readily available, all time access, online shopping”, we
found the most suitable field to deploy our application.Due to easy mobility andinternet access,
Mobile phones are the most sought after and targeted devices for theadvertisements and
softwaredeployment. In this application we will consecutivelyuse android for operating
environment, cloud based servers forData storage anddatabase services .In the front end
android will be used for UIdesign and for the backend we will use Azure cloud to provide the
database and hosting services. Now, comes the problem of enlisting the products. Many times
thedevice size varies among androids which might result in the disfigurement of the layout .So,
we will require an image conversion tool i.e. Picasso.
Abstract
KrushiDhanOT-108 :
: Csmith is a compiler testing tool which generates random C program based on standard
C. It is useful for stress testing the compiler. It is also called fuzzer testing. Csmith only generate
standard C without GCC C Extensions. The goal of this project is to extend codebase of Csmith
to cover GCC C Extensions and run it against compiler to find compiler bugs.
Extended Csmith i.e. adding GCC C Extensions in Csmith can be used in -
1. Linux Kernel
2. Airplanes autopilot verification
3. Mission Critical Systems
4. Embedded System Compiler
and almost where ever GCC compiler is used.
In Csmith, 12 GCC C Extensions are added which led to find 4 bugs in GCC compiler and
increased code coverage of GCC compiler.
Percentage gain in code coverage of GCC compiler -
[% GAIN] -
Line - 0.5%
Function - 0.7%
Branch - 0.4%
Abstract
Extending Csmith, a compiler testing tool for GCC C ExtensionsOT-109 :
: Significant advances in Robotics and marine technologies hold promise to create the
autonomous navigation and inspection of physical structure fault in the shipping environment
and surveillance system of unknown human interaction in the orlop deck. The contribution of
this paper is to develop a system with an Autonomous Mapping which performs an inspection
and surveillance of the ship’s orlop deck using Simultaneous Localization and Mapping (SLAM).
By developing an integrated deck mapping and monitoring solution using the 2D SLAM.
Comprehensive experimental tests have been carried out with Robot Operating System (ROS)
and a map made by teleoperation is used as the base map against which subsequent maps that
are generated based on machine learning algorithm which is compared in order to detect
anomalies. The occurrence of any irregularities is reported to the operator thereby preventing
lethal accidents. This process is both time and labour intensive due to the demand for absolute
accuracy failing which the performance and safety could be compromised and disastrous
consequences could unfold. The presence of narrow spaces in the ship’s orlop deck burgeons
inaccessibility. The bot will be able to access such spaces easily due to its compact size and look
for necessary faults. The goal of the autonomous robot inspection and control system is to
follow linear trajectories and stay in the lanes by correcting the lateral deviation to reach the
destination point. The bot will also facilitate the process of reducing the presence of onsite
support staff resulting in a more cost-effective approach.
Abstract
Autonomous Robot Mapping for Marine Inspection and Surveillance SystemOT-110 :
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10. Others
PICT, Pune Synopsis : Concepts-2019
: In this age of staggering development of technology, many problems go unnoticed by
common people and world leading corporations. So, we thought about the industries in India
where technology can help improve the performance. Agriculture was the most obvious sector.
To help farmers and agriculture facilities, not many initiatives are taken. We want to contribute,
as small as it may be.
In the first version we will design a robot which has manual climbing and cutting
controls. 4 clamps will be enough for the basic climbing mechanism with 2 clamps for pushing
and 2 clamps for pulling. For cutting a blade can be mounted with repeated linear motion for safe
cutting/harvesting of the coconuts. Positioning of the blade will be achieved using a motor.
Manual cutting/harvesting and climbing won’t require any image processing.
Once we have achieved this, we will move on to introducing automation in this bot. This
will be one of the major challenges in our project. For this, we will need MATLAB and a good
quality camera.
Abstract
Coconut Tree Climbing and Harvesting RobotOT-111 :
: This project was undertaken for the advancement of the methods/technology used in
Physiotherapy Treatments. Most of the patients who are undergoing through Physiotherapy
treatment have to perform exercise with the help other human.So, we wanted introduce
robotics in Physiotherapy treatment. We thought of a method which improves recovery time
from the treatment and reduce the physical strain the Physiotherapypatients face. We created
an Exoskeleton arm which is placed on an adjustable stand and act as amplifier that augment,
reinforce or restore human performance. User can perform exercise for both of his Arms in
Elbow, in shoulder and rotational movement of shoulder. Physiotherapy treatmentincludes a
great deal of repetitive, precise and special work postures. An Exoskeletal mechanism can assist
in the wearer's work like performing physical exercise guided by Doctor, lifting heavy stuff for
treatment and assist to keep your hands in air without any strain.
We have designed an exoskeleton arm on stand with 3 motor to support the movement
of shoulder, rotation of elbow and movement of arm below elbow. A joystick is used to control
the movement of all motors, and then arm moves accordingly.
Abstract
Exoskeleton ArmOT-112 :
: The term “biomedical waste” has been defined as “any waste that is generated during
diagnosis, treatment or immunization of human beings or animals, or in the research activities
pertaining to or in the production or testing of biological and includes categories mentioned in
schedule I of the Government of India’s Biomedical Waste (Management and Handling) Rules
2016 [1]. Hazards arising from waste disposal from clinical practices can be divided into two
main areas. First, there is the environmental burden of a variety of hazardous products and
second, the more immediate risks of potentially infectious material that may be encountered by
the individuals handling waste most notably being needle stick injury [2]. The severity of the
threat is further compounded by the high prevalence of diseases such as human
immunosuppressive virus (HIV) and Hepatitis B and C [3].
Although, there is an increased global awareness among health professionals about the
biomedical waste hazards and also appropriate management techniques but the level of
awareness in India is found to be unsatisfactory [4,5].Careless and indiscriminate disposal of this
waste by healthcare establishments and research institutions can contribute to the spread of
serious diseases such as hepatitis and AIDS (HIV) among those who handle it and also among the
general public. [6] Also the rate of Needle stick injuries among health care workers handling
waste in the hospital setup is as high as 18% due to improper segregation of waste. [7] Thus
there is a need for regular audit at the institutional level not only to prevent mixing of biomedical
waste but also to prevent needle stick injuries to the health care workers. Audit requires huge
amount of documentation as well as communication to different departments which makes it
difficult to implement. Availability of biomedical waste management audit tool as a mobile
Abstract
Bio Medical Waste Management Audit ToolOT-113 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 51
10. Others
PICT, Pune Synopsis : Concepts-2019
application will not only make the complete process of audit easy and paperless but also provide
online services to communicate different departments and compiling the monthly reporting.
: Sanskrit shlokas have been clinically proven to have a cathartic effect on the mind and
soul. But due to lack of teachers, not many of us are able to tap these resources which are a part
of our rich heritage and culture. Enunciating Sanskrit words helps in improving the grey matter
concentration. Hence we propose a framework which enables the user to enunciate Sanskrit
shlokas. The first step towards enunciation is Sandhi Spitting for which we have come up with a
rule-based approach based on the melody of the shloka. The final step is the enunciation of the
shloka using a seq2seq model with attention.
Abstract
A framework for the enunciation of Sanskrit words and phrasesOT-114 :
: We proposed and developed a bike sharing system that accept by passengers real time
ride request send from smart phone and schedules proper bikes to pick up then via ride sharing,
subject to time,capacity,and monetary constraints. The monetary constraints provide incentives
for both passengers and bike drivers.passangers will not pay more compared with no ridesharing
and get repayment if their travel time is long or extended due to ride sharing; bike drivers will
make money for all the long way around distance due to ride sharing or they contribute money
for petrol. While such a system is of important social and environmental benefit, e.g. saving
energy consumption and satisfying people commute, getting minimum vehicles, saving petrol,
saving environment, relieve traffic jam. real-time bike sharing has not been well studied yet. To
this end, we plan a mobile cloud architecture based bike sharing system. Bike riders and bike
drivers use the bike sharing service provided by the system via a smart phone app. The GPS first
finds candidate bike quickly for a bike ride request using a bike searching algorithm. We are
using Android as an Frontend and SQL as an Backend as well as we are using API's(Geolocation
API)for getting current location of User.Real time bike sharing system is very effective means to
reduce pollution and the congestion of vehicles in cities. It also provides an eco-friendly way to
travel. It also provides an opportunity to meet new people. System saves the total travel
distance of bikes when delivering passengers. Our system can enhance the delivery capability of
bikes in a city so as to satisfy the commute of more people. The system can also save the bike
fare for each individual rider while the profit of bike drivers does not decrease compared with
the case where no bike sharing is conducted.
Abstract
Lyft pleaseOT-116 :
: Present paper discusses the Charging Colour Changing Cable occurrence & its relevant
parameters in charging cable. In the proposed system its being visualize the different colour
changing of the cable as per the charging of Cell phone .The Cable is operated with the adapter
along with switched mode power supply.The ESP8266 Controller will help to control the
charging & WIFI controlled device. Switch-mode power supplies are a popular and sometimes
necessary choice for DC-DC power conversion. These circuits offer distinct benefits and
tradeoffs when compared to alternative methods of converting DC power. This system helps to
avoid the over current & over voltage charging of Cell Phone. This cable will visualize the
changing of cable colour with Charging of Cell Phone.
Abstract
SMART USB CABLEOT-120 :
: Earth, the blue planet is made up of nearly 70% of water out of which 95% is still
unexplored. To spread and advance the research of the oceans it is imperative that autonomous
underwater vehicles are advanced at a faster pace. Chakra is an AUV developed by a multi-
disciplinary student group at Maharashtra Institute of Technology, Pune to perform many tasks
which can’t be done by humans due to underwater constraints. Our aim is to test the basic
functionality of the AUV and make it compliant to work for underwater tasks such as ecological
Abstract
Design and Prototyping of an Autonomous Underwater SurveillanceOT-121 :
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 52
10. Others
PICT, Pune Synopsis : Concepts-2019
study, military surveillance, topological mapping etc. Chakra uses seven thrusters to achieve 6
degrees of freedom. Out of these, three vertical thrusters are used to control roll, pitch and
heave of the AUV and from the remaining four thrusters two are used to move the AUV in the
forward and backward direction while the other two are used to move the AUV laterally. The
electronics system is designed keeping in mind the navigation and the different tasks which
needs to be performed in a robust and power efficient manner. It focuses upon the verticals of
simplicity, stability and modularity within a distributed architecture. The high level system
architecture of chakra consists of two boards, a Jetson Tx1 which us used as the main board and
an Arduino mega which is used as the peripheral board. The main board runs the control logic of
the AUV and the peripheral board controls the 7 thrusters to produce the desired motion.
Localization is performed by the main board using ZED (stereo camera), an Inertial
Measurement Unit and pressure sensor. A PID control loop is implemented on the main board to
make the entire feed-back system a closed loop one. Using the images of ZED, image processing
algorithms are implemented to identify various objects.
:::|| Pune Institute of Computer Technology Impetus and Concepts 2019 ||::: 53
Impetus and Concepts’19
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