NEXT-GEN ATTENDANCE SYSTEM WITH FACE RECOGNITION CAPABILITIES

Traditional attendance systems are often prone to inefficiencies such as manual errors, buddy punching, and timeconsumption. With the advancements in artificial intelligence and computer vision, automating attendancesystems using facial recognition has gained prominence. This project implements an automated attendance systemthat detects and recognizes faces from a live camera feed, marks attendance in a secure database, and provides anintuitive web-based interface for administration and monitoring. Additionally, email notifications are sent tocandidates upon successful attendance marking, ensuring transparency and confirmation. The system reducesadministrative workload and enhances security by preventing fraudulent attendance marking. By leveraging deeplearning and real-time video processing, the system ensures a seamless and efficient approach to attendancemanagemen