Faculty presence detection and alert system

The exponential growth of inspection systems has increased the demand for efficient and cost-effective solutions. This project introduces a faculty verification system that uses the webcam of the system and OpenCV for real-time facial recognition. The system integrates a Flask-based web interface to provide an intuitive and dynamic user experience. The key features are live detection and system-level video capture by using the Haar Cascade classifier. It gives more importance to accessibility and user-friendliness. Unlike some solutions that work on an external camera or even a Raspberry Pi module, this system works on solely built-in resources. Therefore, the value is guaranteed. The study evaluates performance in face recognition under varying conditions. Focus has been laid on accuracy, responsiveness, and scalability.