An Enhanced Intelligent Attendance Management System for Smart Campus

Abstract

Digital attendance management system has found to be extensively efficacious in monitoring and tracking the entry of students and staffs in an organization. Conventional method of taking attendance is considered chronophagous and prone to errors. The authors pen down an ingenious method of taking attendance precisely and accurately using machine learning. The authors also make sure about the vulnerability of the system towards a larger group of students. The students will be tracked while going in and out of the classrooms. The systems is instilled with a Haar cascade for appropriate detection of the face. The faces are further recognized using Local Binary Pattern Histogram algorithm. The tkinter GUI interface is used for user interface purposes in the system. The attendance status of the students can be checked on logging with a personal user ID and password.