AI-Based Exam Malpractice Detection Using Machine Learning and Computer Vision
Author : T Alamel Praba and R Nithya
Abstract :
Artificial Intelligence (AI) has significantly transformed educational assessment systems by enhancing transparency and integrity. Exam malpractice remains a major concern in both offline and online examinations, leading to unfair evaluation and academic dishonesty. This study proposes an AI-based exam malpractice detection system that utilizes computer vision and machine learning techniques to monitor candidate behavior during examinations. The system captures real-time video input, detects suspicious activities such as head movement, multiple persons in frame, use of mobile devices, and abnormal eye movement using deep learning models. By automating invigilation, the system ensures fairness, reduces human supervision burden, and improves reliability in examination processes.
Keywords :
Artificial Intelligence, Exam Monitoring, Machine Learning, Computer Vision, Deep Learning, Facial Recognition, Online Examination, Malpractice Detection.
