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Author(s):

Mrs. N. Nagajothi | A. Akash | R. Dhillipan | K. Narasimha Rao
Keywords:

YOLO, Object Detection, Exam Monitoring, Facial Recognition, Automated Attendance, AI Surveillance
Abstract:
The Rise In Exam Malpractice Has Necessitated Innovative Solutions To Uphold Academic Integrity. Traditional Invigilation Methods Often Fail Due To Human Error And Limited Monitoring Capabilities, Allowing Students To Exploit Blind Spots And Use Prohibited Items. This Project Proposes A YOLO-based Visual Distance Fraudulent Detection System To Monitor Exam Halls In Real Time. Utilizing High-resolution Cameras And AI-driven Object Detection, The System Ensures Automated, Non-intrusive Supervision While Reducing Human Intervention. Future Enhancements, Including AI-based Behavior Analysis And Multi-camera Integration, Will Further Improve Accuracy, Making It A Scalable And Efficient Solution For Secure Examinations.

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