Automatic Attendance System
The present project will be revolving around creating an attendance-taking system using facial recognition as a medium to gather data on student presence in a way that is unobtrusive and does not disturb class proceedings. A web dashboard will also be built to monitor or edit gathered data.
This project is to address the conditions of the attendance taking system, where
Taylor’s University uses physical paper to record the attendance of each student. This traditional way of taking attendance is slow and disrupts the class flow where the students are required to write on the paper to confirm their attendance. This can also be easily fooled, as friends will be able to help each other out by signing it for them, and it is not always reliable. Lecturers will have to manually add the attendance in, and overall, it is an extra step for something that should not be such a hassle.
CAMs is not perfect as well, as it requires students to be connected to I-Xcess (Taylors wifi) and sometimes it can be highly congested. This leads to students being unable to access their Taylors mobile app, and unable to do the attendance. Not only that, but the act of revealing the attendance code and requiring students to manually key it in themselves can consume valuable class time.
Therefore, a facial recognition system is proposed to detect and recognize students entering and exiting a classroom in order to log attendance. This should be done seamlessly with cameras being out of the way to the point where taking attendance is an afterthought without any need for user/student interaction. A companion dashboard site would also be built to allow lecturers and admins to view the data gathered and make amendments where necessary.