An Improved Version of Student Attendance Management System based on RFID using Raspberry-pi

Student attendance monitoring is a routine but time-consuming task in higher education institutions. Existing systems often rely on manual processes or limited automation using RFID, biometrics, or mobile devices. This paper presents an improved attendance management system leveraging both RFID and real-time facial recognition. Enhancements have been made to the RFID hardware module and a user-friendly web interface for faculty operations. The proposed system integrates Raspberry Pi 3 and OpenCV to implement a five-stage face recognition pipeline: detection, preprocessing, training, recognition, and attendance logging. The system uses a modified Viola-Jones Haar Cascade for face detection, LBP histograms for recognition, and combines SQLite with MySQL for database management. Attendance is automatically recorded, and alerts are sent to guardians and the department in case of absences. This approach reduces human error, enhances security, and improves administrative efficiency.