Facial Recognition-Based Attendance and Smart COVID-19 Norms Monitor

Attendance is an important part of the academic environment. The manual method of marking student attendance is time-consuming and also not accurate. So, the use of biometric attendance is a better alternative to the manual method. There are many biometric techniques that can be considered to design an automated system to mark attendance. Facial recognition is one such biometric technique that can be used. In this paper, we propose the implementation of facial recognition where the attendance is marked by recognizing the faces detected in the video feed from the classroom. We are in the midst of the once in a century crisis, ever since the COVID-19 pandemic broke out it has become imperative to accommodate certain behavioral changes in our day to day lives, one such major change which is essential to curb the spread of COVID-19 is to wear a face mask, and thus, the facial recognition-based attendance adds another advantage by recognizing the faces even though students would be wearing the masks. Another important measure that needs to be followed to contain the spread of COVID-19 is to ensure social distancing in all public spaces; hence, there is a need to ensure that social distancing norms are followed by the students. So, we propose implementation of a system to monitor the social distancing among the students. Further, we propose to implement a COVID-19 vaccination status monitoring system using which we can monitor the vaccination status of the individuals through the video feed from the classroom.