EXAM CHEATING DETECTION USING WEBCAM FEED

Abstract

Academic integrity is now a major concern due to the quick rise of remote exams and online learning. Automated solutions are becoming more popular because traditional proctoring techniques are frequently ineffective, expensive, and inappropriate for large-scale digital exams. A real-time test cheating detection system that uses camera feeds with computer vision and machine learning algorithms is presented in this study. The system uses object detection to find prohibited items like books, smartphones, or other people, gaze and head pose estimation to track candidate attention, and facial recognition to confirm identity.