A Facial Recognition Based-Attendance Monitoring System for Jesus Reigns Christian College Staff

Abstract

Artificial Intelligence (AI) has become one of the most significant technological advancements in modern society, improving automation, security, and operational efficiency across different industries. In educational institutions, attendance monitoring remains an essential administrative task; however, traditional attendance systems are often time-consuming, prone to human error, and vulnerable to attendance fraud. Facial recognition technology offers a modern solution by enabling automatic identification and verification of individuals through digital image processing. This study presents AttendScan, a Facial Recognition-Based Attendance Monitoring System developed for the staff of Jesus Reigns Christian College. The main objective of the system is to automate attendance recording and provide a centralized platform for monitoring and managing staff attendance records. The system utilizes facial recognition technology for real-time identification and verification of staff members during time-in and time-out procedures.AttendScan was developed using the Agile Software Development Life Cycle methodology. The system uses Python and Flask for backend development, HTML, CSS, and JavaScript for the web interface, OpenCV for facial detection and recognition, and MySQL for database management. The system includes features such as staff registration, facial data capture, attendance logging, and report generation.The implementation of AttendScan provides a more efficient, accurate, and secure attendance monitoring process compared to manual attendance methods. The system minimizes administrative workload, reduces attendance manipulation, and improves record accessibility through digital automation. The study concludes that facial recognition technology can significantly enhance attendance management in educational institutions by providing reliable and automated monitoring solutions.