Live Multi Persons Attendance System

This Project is based on Live or Real-time Face Recognition System . We have used this technique for creating an attendance system. Real-time scanning faces enables fast and efficient Attendance System. Tradition Attendance System has raised many problems. Calling each students roll no. is

Project Title

Live Multi Persons Attendance System

Project Area of Specialization

Computer Science

Project Summary

This Project is based on Live or Real-time Face Recognition System . We have used this technique for creating an attendance system. Real-time scanning faces enables fast and efficient Attendance System. Tradition Attendance System has
raised many problems. Calling each students roll no. is time wasting as it takes up to 15 minutes to take
the attendance. Even Online Attendance finds same problem. Sometimes Absent students get their
attendance marked. And some don’t get their attendance marked because they were absent at the time
of attendance. Thus it is obvious to solve this problem. Real-time Face recognition is the efficient way to
identify the students and enlist the attendees. We have used Machine/Deep Learning to solve this issue.
Machine Learning Model can easily validate the image and save list of attendees into data base. It will
be fast, easy and efficient way to make students obligated for being in class to have their attendance
marked. We will train the Model using CNN . On Runtime Faces will be scanned and found with the help
OpenCV Library in Deep Learning to accomplish this goal. Thus we can have a system to take attendance
of whole class with one Click.

Project Objectives

1. To Use Face Recognition technique to take Attendance efficiently
2. To find  real-time Faces and identification with maximum accuracy
3. To enable Teacher to take Attendance of students on one Click
4.  To avoid time consumption and disturbance on attendance
5.  To get every one's attendance marked on the same time.
6. To let students (present in class) never miss their Attendance.
7. To compel students to be in class otherwise they will be marked as absent..

Project Implementation Method

We will use Computer Vision in Machine/Deep learning which is used for Visual Data.For any Machine/Deep Learning Model major ingredients are 1. Data Sets 2. Machine/Deep Learning Algorithms
We will use these building blocks to train the Model for our project.
We will collect images of students of a class, label each image, pass it through Processing and Model
training.
We will make Image Data available to tackle the Classification through Supervised Learning Method.
Camera will be accessed through OpenCV library in python.
Students’ faces will be scanned and Model will compare the scanned faces with images on data base.
If the faces match the recorded image data, Face scanned will be recognized and its label will be saved in
data base denoting date and time of Attendance and list of labels will be saved as List of Attendees.

Steps for training Model
1. Preprocessing: Image data will be stored in data base and all images will be given LABELS.
2. Model Training: CNN (Convolutional Neural Network) in Deep Learning will be used to train
the Model on given images Data.
3. Application will access Camera and it will be done through python code from OpenCV(Fixed
Camera in Class or Mobile Camera)
4. Camera will scan whole the class and will find the Faces with the help of OpenCV Library in
Python
5. Found Faces will be matched with Trained Data
6. Classify The Faces and Enlist Labels of matched Faces and mark them as Present.
7. Attendance List will save in Excel File and will be sent to Student Attendance Cell.

Resources
1. For Image Data Sets We will collect 10 images of every student of the class.
2. We will apply the algorithms of Model Training from
a. Github Open Source Repository
b. Kaggle
c. Google
d. YouTube

Hardware: Cameras
Two types of Cameras may be functional in this project.
1. May be Fixed in Class
2. Mobile camera with required specification
Camera Specification
a. Range of camera
b. Quality (MP)
c. Rotatable and Zoom able
d. Enough Resolution to fetch faces from 40 ft.
e. Bluetooth connectivity enabled.

Benefits of the Project

1. This project will enable Teacher to take Attendance of students on one Click.
2. Time consumed on attendance will be put into lecture and disturbance because of attendance
will be avoided.
3. All students will get their attendance marked on the same time.
4. Students present in class will never miss their Attendance.
5. Students will find it compulsory to be in class otherwise they will be marked as absent.
6. Student cannot be marked absent if student present in class.
7. Student will not get attendance if they are absent in class.

Limitations

1. Teacher may need to scan class portion wise to avoid blurred and low quality coverage if quality of Camera is not up to the mark.
2. Teacher may need to scan more than once to get finer results.
3. Due to Low quality of camera Students unidentified may need to be scanned again.
4. Due to Low quality of Camera, completely unidentified student may be called to sit in front to get him identified.
5. Students with genuine reason will not be getting Attendance.( Yet they have 25% Leave Slot beyond that they are termed back)
6. Student cannot be marked absent on account of punishment.

 Future Innovation

1. This Project may be later advanced to take attendance automatically of every student who was present in class for minimum of 75% duration of Lecture.
2. In such case Camera will be all time Live to track time of presence of Student.
3. Storage of such camera will be automatically deleted once attendance is marked.
4. Teacher may still be able to review attendance in last 5 minutes and check if any students found blurred. System will suggest him names of blurred students so He will manually allow his attendance to be marked.
5.  New Students will have to have their Images saved and enrolled themselves in Data base in Student Attendance Cell.

Technical Details of Final Deliverable

1. Our Project will have a Desktop or Mobile Application.
2. Teacher will sign in and Find his/her Classs.
3. Scan Button will enable Teacher to scan whole class.
4. Scanned faces will be validated with the datasets.
5. Recognized Faces will be enlisted in Attendance.
6. Blurred or unidentified faces will be scanned again .
7. Teacher will get the excel file to download or directly uplaod the file to Students Attendance Management Cell
8. Final Attendance submits this way.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Education

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Quality Education, Industry, Innovation and Infrastructure, Partnerships to achieve the Goal

Required Resources

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