pictinc.orgpictinc.org/dyn.pdfBD-122 Detection and Classification of Diseases in T: omato Plants - - - 7 BD-123 Predicting Bus Arrival Time Using GPS And Mac: hine Learning. - - -

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 Womenâ€™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 ||:::


: - - - 5BD-117 Analysis of Sentiment Analysis Techniques

: - - - 6BD-118 Interview bot â€“ 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)



: - - - 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.



: - - - 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



: - - - 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



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



: - - - 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



: - - - 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



: - - - 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



: - - - 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



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



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 :




: 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 :




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 :




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 :




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 :




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 :




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 :




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 :




: 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 without 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 :




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 :




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 :




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 :




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 :




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 :




: 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 :




: 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 :




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 :




: 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 :




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 :




: 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 :




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 :




: 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 :




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 :




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 :




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 :




: 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 :




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 :




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 :




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 :




: 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 :




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 :




: 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 :




: 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 :




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 :




: 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 :




: 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 :




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 :




: 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 :




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 :




: 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 :




: 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 :




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 :




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 :




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 :




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 :




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.


10. Others


: 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 :


10. Others


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 :


10. Others


: 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 :


10. Others


: 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 :


10. Others


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 :


10. Others


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.


Impetus and Concepts’19

Marketing

Dr. S. S. Narkhede

Dr G. S. Mundada

Prof. P. R. Patil

Ashwin Rachha

Raj Rathi

Krishna Patel

Shreya Mahadik

Mayur Raut

Publicity

Dr. Emmanuel M.

Dr. R. C. Jaiswal

Prof. A. R. Buchade

Prof. P. S. Varade

Prof. Y. A. Handge

Prof. R. B. Murumkar

Poorvi Raut

Malvika Shirke

Rushikesh Patil

Design Team Head

Snehal Jadhav

Deepak Choudhary

Web

Prof. S. B. Deshmukh

Prof. M. W. Nimje

Shubham Mapara

Umesh Gaikwad

Judging

Prof. T. A. Rane

Prof. S. S. Pande

Prof. M.R. Khodaskar

Prof. S.D. Kale

Prof. Z.A.S. Mohammed

Prof. A.R. Sharma

Prof. D.T. Mane

Prof. P. J. Jambhulkar

Prof. H. S. Thakar

Prof. M. R. Jansari

Prof. S. Hake

Pratiksha Pawar

Ajay Gawade

Prajwal Chandak

VNL and Stage setup

Prof. R. S. Paswan

Prof. V. V. Bagade

Prof. J. K. Kamble

Prof. S. S. Suradkar

Prof. Reddy Sudhakar

Prof. N. J. Bhalani

Ms. A. M. Kulkarni

Mr. V. A. Manmode

Mr. S. Deokate

Prof. S. A. Jakhete

Prof. P.S. Joshi

Prof. N. R. Sodha

Prof. S. V. Mundhe

Prof. R. J. Sutar

Gaurav Kale

Printing

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Prof. B. D. Zhope

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Mr. G. L. Kirwale

Guest Invitation

Dr. M. P. Munot

Dr. S. C. Dharmadhikari

Prof. K. V. Sakhare

Prof. P. R. Makkar

Prof. S. P. Shintre

Finance

Prof. A. R. Deshpande

Prof. K. C. Waghmare

Prof. S. H. Chandak

Prof. N. B. Gawade

Prof. R. A. Kulkarni

Hardware & Software

Prof. V. R. Jaiswal

Prof. N. V. Buradkar

Prof. D. M. Shinde

Prof. A. D. Patil

Prof. A. S. Bhosale

Mr. D. M. Mankar

Mr. D. Tikekar

Mr. S. M. Savalkar

Mr. S. R. Shelar

Mr. D. P. Dabir

Kunal Hepat

Yash Pande

Jaideep Foujdar Impetus and Concepts Event Co-ordinators

Gaurav Vanmane Aman Goenka Parth Shah

Siddhant Dabadgaonkar

Co-Ordinator

Prof. M. R. Khodaskar

PASC Counsellor

Prof. G. V. Kale

Convener

Dr. G. P. Potdar

Principal

Dr. P. T. Kulkarni

PISB Counsellor

Dr. R. B. Ingle

Impetus and Concepts’19

Pradnya

Prof. D. D. Londhe

Prof. P. S. Vidap

Mrs. Katewal Bakul

Mr. A. N. Pujari

Abhishek Vishwakarma

Litesh Zambare

Sanved Joshi

Transport

Mr. A.V. Sapkal

Prof. V. B. Vaijapurkar

Prof. M. S. Chavan

Prof. P. D. Jadhav

Prof. R. R. Vardhaman

Prof. S.D. Hade

Prof. H.S. Khatri

Prof. S. A. Takwane

Mr. H. V. Kasar

Mr. B. Dhavale

PA Systems

Prof. L.P. Patil

Prof. A. M. Chavan

Mr. P. P. Parkhi

Mr. S. S. Shinde

Trophies + Memento +

Photos

Prof. N. P. Sapkal

Prof. K. R. Jadhav

Prof. K. Y. Dighotkar

Prof. R. R. Chajjed

Prof. S. M. Hosmani

Prof. S. K. Choube

Prof. H .J. Joshi

Mr. B. S. Jadhav

Mr. S. G. Renuse

Mr. L. M. Pawal

Capture the Flag

Prof. P. S. Game

Prof. H.P. Channe

Prof. A. A. Jewalikar

Mrs. Buradkar

Chaitanya Rahalkar

Anushka Virgaonkar

Tantra-Naipunya

Dr. G. V. Bansod

Dr. S. K. Moon

Dr. M. P. Turuk

Prof. R.G. Yelalwar

Prof. N. B. Gawade

Prof. N. B. Patil

Avina Ghate

Rajeshwari Sonkusale

Neha Bhosale

Tushar Sinare

Yukti

Prof. P. A. Jain

Prof. A. M. Deshmukh

Prof. H. M. Hiwase

Prof. D. D. Kadam

Prof. S. D. Shelke

Daksha

Dr. K. C. Nandi

Prof. R. R. Deshmukh

Prof. A. A. Bhandekar

Avni Soni

Aditi Laturkar

Pratibha

Prof. A. M. Bagade

Dr. G. V. Kale

Prof. A. G. Phakatkar

Kashmira Ingole

Rajat Sawant

Hospitality

Prof. A. A. Joshi

Prof. K. A. Sultanpure

Prof. U. S. Pawar

Ms. S. L. Rane

Ms. V. Deshpande

Ms. S. R. Badkas

Ms. J. N. Buradkar

Ms. P. D. Vanarase

Muskan Agarwal

Vrati Bansod

Bushra Inamdar

Student Volunteer

Committee

Prof. E. M. Reddy

Prof. A. M. Kulkarni

Prof. A. M. Gangarde

Prof. S. S. Shevtekar

Prof. V. B. Patole

Mr. R. V. Badekar

Canteen Arrangement

Prof. A. M. Kulkarni

Prof. R.V. Kulkarni

Prof. M. R. Kale

Prof. J. B. Jagdale

Mr. S. S. Metakari

Mr. S.H. Karsulkar

Mr. K. Bhosale

Concepts

Shashank Lonkar

Sania Shaikh

Sahil Nahar

Impetus

Shantanu Shinde

Ahmed Khwaja

Ayushi Agarwal

Documents

pictinc.orgpictinc.org/dyn.pdfBD-122 Detection and Classification of Diseases in T: omato Plants - - - 7 BD-123 Predicting Bus Arrival Time Using GPS And Mac: hine Learning. - - -