Facial Recognition-Based Smart Attendance System Using MongoDB and OpenCV

Attendance management is essential in institutions and workplaces but traditional methods like manual entries or biometric systems often face issues such as time consumption, errors, and fraud. This project introduces a Smart Attendance System using facial recognition to provide an efficient, accurate, and secure solution. By leveraging OpenCV and the face recognition library, the system captures multiple facial images, creates encodings, and matches them in real time against a MongoDB database for attendance logging. It includes modules for face detection, recognition, database management, and a user-friendly interface for seamless operation. Developed through iterative prototyping and rigorous testing, the system demonstrated high accuracy and low latency in real-world scenarios, showcasing its scalability for institutions. The Smart Attendance System offers a foundation for advancing automated attendance tracking solutions.