ML-Driven Automated Professor Presence Monitoring Using GPS Geo-Fencing and Face Liveness Detection

This project proposes a Machine Learning-Driven Automated Professor Presence Monitoring System that combines GPS geofencing and face liveness detection to ensure accurate and fraud-proof attendance. When a professor enters a predefined geofenced area, their presence is detected automatically, eliminating manual check-ins. To prevent spoofing through photos, the system uses real-time liveness detection (e.g., blink or head movement) powered by machine learning. Additionally, models like Random Forest and Linear Regression are used to predict arrival times based on past behavior and traffic patterns. A web-based dashboard provides real-time data visualization, attendance logs, and automated reporting. This mobile-first solution enhances security, improves efficiency, and offers a smart, scalable approach to attendance monitoring in academic environments