Smart Student Attendance Management with Face Recognition

Attendance monitoring is necessary in schools to track student presence and participation. Manual methods, though accurate, are time-consuming and inefficient for big numbers of students. Automated systems like biometric identification have enhanced efficiency but tend to be time-consuming due to individual verification, causing delays. This project proposes a new attendance system based on face detection and recognition technology. A high-definition camera takes pictures of classrooms, and a face detection model detects multiple faces from the group photo. These faces are then compared to a student database based on a recognition model. The system generates attendance records automatically in Excel form for effective record-keeping once identified. The suggested system has been experimented with many group images with great accuracy and efficiency over manual processes. Through minimizing human input, this system presents a complete automatic attendance solution perfect for today's learning environments. It improves attendance tracking precision, streamlines administrative work, and is fully integrated with institutional management systems for enhanced data management