Smart Attendance and surveillance systems

Smart attendance and surveillance system utilizes image processing technique so as to mark the attendance of the students and additionally provide surveillance of the Institute on a real-time basis. A face detector and recognizer will be developed so as to attain this by using the OpenCV and Face_re

Project Title

Smart Attendance and surveillance systems

Project Area of Specialization

Artificial Intelligence

Project Summary

Smart attendance and surveillance system utilizes image processing technique so as to mark the attendance of the students and additionally provide surveillance of the Institute on a real-time basis. A face detector and recognizer will be developed so as to attain this by using the OpenCV and Face_recognition library of Python. In order to attain far more accurate results for face recognition/classification, DEEP LEARNING technique has been used. Python’s TENSORFLOW and KERAS libraries were used for the architecture designing. This architecture will serve as the base for achieving the task of image classification. All the data concerning the students are made accessible on a completely editable database. The attendance, surveillance system, and also the database is incorporated in a web site where the teacher, and Administration representative will access it easily.

Project Objectives

Following are the major objectives that we will be achieved in our project.

Objective 1:

 REAL-TIME SURVEILLANCE SYSTEM:

 As the name suggests we will be developing a fully monitored system that will keep the track of intruders. In order for the surveillance system to work, we have to develop a face detector that will work in real time. This real-time face detector will be developed by using the OPEN CV library of PYTHON PROGRAMMING LANGUAGE. 

Objective 2: 

DIGITIZED ATTENDANCE SYSTEM:

The whole concept around which this project revolves is the facial recognition technique. In order for the attendance system to work appropriately, we will use MACHINE LEARNING to TRAIN our system.

The LetNet architecture is an excellent “image classifier” for Convolutional Neural Networks. Originally designed for classifying handwritten digits, we can easily extend it to other types of images as well. 

‘The LetNet architecture consists of two sets of convolutional, activation, and pooling layers, followed by a fully-connected layer, activation, another fully-connected, and finally a softmax classifier. We’ll be implementing this network architecture using Keras and Python.’

 DATABASE AND MANAGEMENT SYSTEM:

This task plays a vital role in the development of this project, the above-mentioned objectives depend upon the student database. In the student database the entire information of the students, as well as their photographs, will be present. The database is completely editable, this is due to the fact that when a student wishes to get some sort of information updated he/she can visit the administration department with a request to update their information and get it done within minutes.

Project Implementation Method

All the above-mentioned objectives namely the database and management system, attendance system and surveillance system will be incorporated into a fully functional website so that the task of marking attendance, monitoring video, and accessing student database can be performed easily.

Benefits of the Project

• The first beneficiary of this project will be our very own university since it will help the faculty members by saving their time which is almost certain to be lost either at the start, middle or the end of the class and will also put an end to fake attendance. It will furthermore help in controlling the security situation which has been increasing over the years, by keeping a close eye on who is entering the university premises and whether a certain person is an enrolled student or an intruder.

• This project can be implemented by institutions that keep a log of their employees, it will most certainly enhance their security measures by reducing the chances of corporate espionage.

• The government can implement this project in penitentiaries in order to keep track of the inmates. The logging system can be used to keep a record of the inmates.

• Also, this project can be implemented in large public gatherings in order to keep track of felons that may be present.

Technical Details of Final Deliverable

This project is a Smart Attendance and Surveillance System that uses Image Processing technique to mark attendance of the students through facial recognition and extracting useful information from images captured, also the images captured will allow to monitor surveillance of intruders/ students in the institute. This system works on real time data processing, continuous stream of input data will be provided to produce an output for a particular moment to achieve objectives of marking attendance and surveillance of the institute.

In order to obtain surveillance system to monitor intruders / students activities in the institute, a face detector will be developed that will work in real time, OPEN CV library of Python will be used to develop the face detector.

To achieve accurate working of the attendance system, we will use MACHINE LEARNING to train our system for image classification procedure. Python and Keras architecture will be implemented to accomplish image classification.

The attendance, and surveillance system depend on a student data base where entire information regarding the university students will be recorded, the database will be completely editable so that changes can be integrated easily.

All these objectives will be incorporated into a fully functional website so that the task of marking attendance, monitoring video, and accessing student database can be performed easily.

Final Deliverable of the Project

HW/SW integrated system

Type of Industry

Education , IT , Security

Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People, Quality Education

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com