A smart attendance system using facial recognition and data analytics

This project proposes a Smart Attendance System that uses facial recognition technology to automatically mark student attendance in real time. The system captures student faces in the classroom and identifies them using computer vision techniques. It integrates with existing student databases and applies data analytics to identify attendance trends, defaulter students, and class-wise performance patterns. Real-time dashboards and notification systems provide timely updates to teachers and parents, thereby improving transparency, reducing manual effort, and enhancing overall attendance management efficiency in educational institutions.