Student Information System with Face Recognition Attendance

Abstract

This student information system is a platform that makes it possible for schools to efficiently and transparently manage student data. Currently, handwritten logs and paperwork are used to manage student records, which leads to various issues like data loss, data redundancy, data inconsistency, and other human errors in addition to being time-consuming and inaccurate. Our student information system can significantly reduce the majority of these issues. The system we have built is a student information system that holds a range of student data, such as academic, attendance, and personal data. This system makes use of deep learning and facial recognition to automate the attendance process. Facial recognition is chosen as the method of authentication and CNN algorithm is used for higher accuracy, robustness and in-variance. It uses the student entering time and leaving time to create a data log which is used to calculate the total time attended by the student. This system will also analyze the entry and exit times of students on a particular day and display the students that are present and absent in real time. The system will then use this information to display various charts about the student attendance and academics using a user-friendly interface with three different user modes: teacher, student and admin.