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AUTOMATED video surveillance addresses real-time observation of people and vehicles within a busy environment, leading to a description of their actions and interactions. The technical issues include moving object detection and tracking, object classification, human motion analysis, and activity understanding, touching on many of the core topics of computer vision, pattern analysis, and artificial intelligence. There are immediate needs for automated surveillance systems in commercial, law enforcement, and military applications. Mounting video cameras is cheap, but finding available human resources to observe the output is expensive. Although surveillance cameras are already prevalent in banks, stores, and parking lots, video data currently is used only “after the fact” as a forensic tool, thus losing its primary benefit as an active, real-time medium. What is needed is continuous 24-hour monitoring of surveillance video to alert security officers to a burglary in progress or to a suspicious individual loitering in the parking lot, while there is still time to prevent the crime. In addition to the obvious security applications, video surveillance technology has been proposed to measure traffic flow, detect accidents on highways, monitor pedestrian congestion in public spaces, compile consumer demographics in shopping malls and amusement parks, log routine maintenance tasks at nuclear facilities, and count endangered species. In my work till date, I have been designing a portable, economically viable alternative to manual surveillance that can find application in both civilian and military sectors. It demonstrates the Battery Operated Video Surveillance System Architecture. In this Architecture, Base station is connected to Repeaters via Wi-Fi connection. Client collects the Video data connected to the Repeater or Base Station. A server which displays Video data connected to the Base station. Base station synchronize Wi-Fi connections of Repeaters. The Client is a Beaglebone Black with Video capture device and Server is a PC connected to Base station. All these devices connected via Wi-Fi. The Bot has the following features: Streaming the Video over Wi-Fi Network architecture. Resolution 320 x 240. Frame-rate 20 fps. Compression JPEG/ FFMPEG Range around 30m covering. Low power ratings 210-460 mA @5 V Depending On Activity and Processor Speed The use of sensors provides a new dimension to the robot and increases the scope of its application. But the bot can be improved much further through some additional features. Some other future aspects can be- Using Mesh Network protocol for Wireless connection. Battery operated Network Router. Motion Activated recording and alerts. Power Optimization. Theft control Battery charge level update to Server.

SOP Grades

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Page 1: SOP Grades

AUTOMATED video surveillance addresses real-time observation of people and vehicles within a busy environment, leading to a description of their actions and interactions. The technical issues include moving object detection and tracking, object classification, human motion analysis, and activity understanding, touching on many of the core topics of computer vision, pattern analysis, and artificial intelligence. There are immediate needs for automated surveillance systems in commercial, law enforcement, and military applications. Mounting video cameras is cheap, but finding available human resources to observe the output is expensive. Although surveillance cameras are already prevalent in banks, stores, and parking lots, video data currently is used only “after the fact” as a forensic tool, thus losing its primary benefit as an active, real-time medium. What is needed is continuous 24-hour monitoring of surveillance video to alert security officers to a burglary in progress or to a suspicious individual loitering in the parking lot, while there is still time to prevent the crime. In addition to the obvious security applications, video surveillance technology has been proposed to measure traffic flow, detect accidents on highways, monitor pedestrian congestion in public spaces, compile consumer demographics in shopping malls and amusement parks, log routine maintenance tasks at nuclear facilities, and count endangered species. In my work till date, I have been designing a portable, economically viable alternative to

manual surveillance that can find application in both civilian and military sectors. It

demonstrates the Battery Operated Video Surveillance System Architecture. In this

Architecture, Base station is connected to Repeaters via Wi-Fi connection. Client collects the

Video data connected to the Repeater or Base Station.

A server which displays Video data connected to the Base station. Base station synchronize Wi-Fi connections of Repeaters.

The Client is a Beaglebone Black with Video capture device and Server is a PC connected to Base station. All these devices connected via Wi-Fi.

The Bot has the following features:

Streaming the Video over Wi-Fi Network architecture.

Resolution 320 x 240.

Frame-rate 20 fps.

Compression JPEG/ FFMPEG

Range around 30m covering.

Low power ratings 210-460 mA @5 V Depending On Activity and Processor Speed The use of sensors provides a new dimension to the robot and increases the scope of its application. But the bot can be improved much further through some additional features. Some other future aspects can be-

Using Mesh Network protocol for Wireless connection.

Battery operated Network Router.

Motion Activated recording and alerts.

Power Optimization.

Theft control

Battery charge level update to Server.

Page 2: SOP Grades

NATIONAL INSTITUTE OF TECHNOLOGY ROURKELA

GRADE CARD FOR INFORMATION OF STUDENT ONLY

BACHELOR OF TECHNOLOGY

Name : VISHAL MISHRA Branch : ELECTRONICS & COMMUNICATION ENGINEERING

Roll No. :

111EC0179 Joined : AY 2011-12

Graduated : AY

1st Semester

Subject Code

Subject Name L-T-P Credits Grade

CE 130 Environment and Safety Engineering

3-1-0 4 A

CY 101 Chemistry 3-1-0 4 B

EC 100 Basic Electronics Engineering 3-1-0 4 A

MA 101 Mathematics - I 3-1-0 4 B

PH 101 Physics I 3-1-0 4 B

CE 171 Engineering Drawing 0-0-3 2 Ex

CS 171 Computing Laboratory - I 0-0-3 2 A

CY 170 Chemistry Laboratory 0-0-3 2 A

WS 171 Workshop Practice I 0-0-3 2 A

EA 171 NCC-I 0-0-3 2 A

Semester Credits :

30 Semester Grade Point Average (SGPA) :

8.67

Total Credits : 30 Cummulative Grade Point Average (CGPA) :

8.67

2nd Semester

Subject Code

Subject Name L-T-P Credits Grade

CE 100 Engineering Mechanics 3-1-0 4 Ex

CS 102 Data Structures and Algorithm 3-1-0 4 B

EE 100 Basic Electrical Engineering 3-1-0 4 B

MA 102 Mathematics - II 3-1-0 4 A

PH 102 Physics II 3-1-0 4 A

CS 172 Computing Laboratory - II 0-0-3 2 Ex

ME 170 Machine Drawing and Solid Modeling

0-0-3 2 A

PH 170 Physics Laboratory 0-0-3 2 A

WS 172 Workshop Practice II 0-0-3 2 A

EA 172 NCC-II 0-0-3 2 Ex

Semester Credits :

30 Semester Grade Point Average (SGPA) :

9.00

Total Credits : 60 Cummulative Grade Point Average (CGPA) :

8.83

3rd Semester

Subject Code

Subject Name L-T-P Credits Grade

EC 201 Analog Electronics 3-1-0 4 B

EC 203 Networks 3-1-0 4 Ex

MA 201 Mathematics - III 3-1-0 4 Ex

ME 231 Total Quality Management 3-0-0 3 B

ME 250 Thermal Engineering 3-0-0 3 B

EC 270 Basic Electronics Laboratory 0-0-3 2 Ex

EC 273 Circuit Simulation Laboratory 0-0-3 2 A

MA 270 Numerical Methods Laboratory 0-0-3 2 A

ME 271 Thermal Engineering Laboratory 0-0-3 2 Ex

Semester Credits :

26 Semester Grade Point Average (SGPA) :

9.08

Total Credits : 86 Cummulative Grade Point Average (CGPA) :

8.91

4th Semester

Subject Code

Subject Name L-T-P Credits Grade

EE 202 Electrical Engineering 3-1-0 4 A

MA 202 Mathematics - IV 3-1-0 4 A

CS 333 Operating Systems 3-0-0 3 B

EC 202 Digital Electronics 3-0-0 3 A

EC 204 Semiconductor Devices 3-0-0 3 B

EC 274 Analog Electronics Laboratory 0-0-3 2 Ex

EC 276 Digital Electronics Laboratory 0-0-3 2 Ex

EE 270 Electrical Engineering Laboratory-I 0-0-3 2 B

HS 270 Language Laboratory 0-0-3 2 Ex

Semester Credits :

25 Semester Grade Point Average (SGPA) :

8.92

Total Credits : 111 Cummulative Grade Point Average (CGPA) :

8.91

Page 1 of 2Grade Card Report

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Page 3: SOP Grades

Name : VISHAL MISHRA Branch : ELECTRONICS & COMMUNICATION ENGINEERING

Roll No. :

111EC0179 Joined : AY 2011-12

Graduated : AY

5th Semester

Subject Code

Subject Name L-T-P Credits Grade

EC 311 Analog Communication Systems 3-1-0 4 A

EC 331 Control System Engineering 3-1-0 4 A

EC 300 Microprocessor 3-0-0 3 Ex

EC 341 Digital Signal Processing 3-0-0 3 A

PH 321 Physics of Semiconducting Materials

3-0-0 3 Ex

EC 371 Microprocessors Laboratory 0-0-3 2 Ex

EC 373 Analog Communication Laboratory 0-0-3 2 Ex

EC 375 DSP Laboratory 0-0-3 2 Ex

EC 377 Electronics Design Laboratory 0-0-3 2 A

Semester Credits :

25 Semester Grade Point Average (SGPA) :

9.48

Total Credits : 136 Cummulative Grade Point Average (CGPA) :

9.01

6th Semester

Subject Code

Subject Name L-T-P Credits Grade

NOT APPLICABLE

Semester Credits :

Semester Grade Point Average (SGPA) :

Total Credits : Cummulative Grade Point Average (CGPA) :

7th Semester

Subject Code

Subject Name L-T-P Credits Grade

NOT APPLICABLE

Semester Credits :

Semester Grade Point Average (SGPA) :

Total Credits : Cummulative Grade Point Average (CGPA) :

8th Semester

Subject Code

Subject Name L-T-P Credits Grade

NOT APPLICABLE

Semester Credits :

Semester Grade Point Average (SGPA) :

Total Credits : Cummulative Grade Point Average (CGPA) :

REMARKS : Performance GradeGrade Point

Performance GradeGrade Point

Performance GradeGrade Point

Excellent Ex 10 Fair C 7 Fail F 2

Very Good A 9 Average D 6Incomplete Assesment

I -

Good B 8 Pass P 5 Debarred X -

Date : 14-FEB-2014...........................................................................................................................................................................................................................................

National Institute of Technology, Rourkela-769008 (Orissa), Phone: 0661-2462031, Fax: 0661-2462033 Website : www.nitrkl.ac.in

Page 2 of 2Grade Card Report

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