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Smart AI-powered Attendance and Engagement Monitoring System
This project presents a Smart AI-Powered Attendance and Engagement Monitoring System integrated with Artificial Intelligence and face recognition technology. The system automates attendance recording while improving accuracy, security, and classroom monitoring. It identifies registered students through real-time facial recognition and records attendance automatically without requiring manual intervention. The application uses a webcam and computer vision techniques to detect, recognize, and verify faces, ensuring that only authorized individuals are marked present. If an unregistered person is detected, the system identifies them as "Unknown", preventing proxy attendance and unauthorized access. Traditional attendance methods, such as manual registers, biometric devices, or RFID cards, are time-consuming, prone to human errors, and vulnerable to proxy attendance. These methods also require physical interaction and additional administrative effort to maintain attendance records. There is a growing need for an intelligent, contactless, and automated attendance management system that can provide accurate identification, minimize manual work, and maintain secure attendance records in real time. the proposed system is developed using Python, Flask, OpenCV, and the face_recognition library. Attendance data, including the student's name, date, and time, is automatically stored in a CSV file for future reference.
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