Pariksha Nirikshak: Anti Cheating System for examination Hall

The educational system is facing a growing problem with the proliferation of exam cheating as a result ofnew forms of electronic communication and enjoyment. Most students nowadays are too busy worryingabout getting a passing grade to put in the time and effort necessary to really prepare for the test. Classicalexam surveillance has become outdated as a result of the emergence of multiple cheating strategies. Thismeans that automated cheating case identification using cutting-edge tech is an absolute need. By utilizingdeep learning and computer vision techniques to analyze the student's posture in real-time, this researchpresents an anti-cheating strategy that focuses on behavior analysis. To do this, we employ YOLO-Faciallandmark and media pipe models to extract domain information from video frames at a high level. Thenext step in predicting cases of cheating is to employ a decision tree classification model.