In current educational settings, the process of disseminating exam hall details through offline means, such as notice boards, poses several challenges. The manual posting of exam schedules, seating arrangements, and related information on notice boards can lead to inaccuracies, delays, and potential information discrepancies.
This proposed development outlines a sophisticated solution for exam hall management and security. Employing Convolutional Neural Network (CNN) algorithms, the system ensures precise face detection within the exam hall, facilitating accurate identification of individuals. This technology not only enables secure authentication through facial recognition but also offers real-time monitoring of exam hall details, including attendance and behavior.
The CNN algorithm's efficiency enhances the reliability of the face recognition system, contributing to a comprehensive approach for exam hall management. By leveraging advanced computer vision techniques, the system provides a secure and transparent environment for examinations, promoting fairness and integrity in the assessment process.
Keywords – CNN, Facial Recognition And Detection, Secure Authentication, Real-Time Monitoring, Attendance Tracking.