Smart Attendance and Progress Management System

Abstract

Management of attendance may be a great burden on lecturers if done manually. This study focuses on finding an automated solution for taking attendance and keeping track of progress of a student in a smart way. The smart attendance system is generally using biometrics for identifying individuals. In this study, face recognition was considered for identification. The student's face is recognized and attendance is taken using face biometrics based on high-definition monitor camera. The images of the student are given as an input and image classification was done using CNN algorithm preventing duplicate entries for attendance. For tracking the progress of the student, the factors affecting the GPA are trained using Machine Learning algorithms. This research also aims to examine the effective progress of undergraduate students by taking past year records and find out the factors for their high and low output which will be helpful to improve their performance.