International Research Journal of Education and Technology

The AI-based smart exam monitoring framework using yolo algorithm is designed to ensure fairness and integrity in online examinations. With the rapid growth of e-learning, conducting secure remote exams has become a major challenge. This system uses artificial intelligence, computer vision, and machine learning techniques to monitor candidates during online exams in real time. It analyzes facial recognition, eye movement, head position, multiple face detection, and suspicious behavior to identify potential cheating activities. The system automatically flags violations such as looking away frequently, presence of unauthorized persons, use of mobile phones, and abnormal behavior patterns. It also records exam sessions for review by administrators. By reducing the need for manual invigilation, the proposed system provides a cost-effective, scalable, and reliable solution for secure online assessments, ensuring transparency and trust in digital examinations.Audio monitoring is incorporated to identify unusual background noises or conversations. The system maintains detailedactivity logs and video recordings, which are securely stored and can be reviewed by exam administrators for further validation. Real-time alerts are generated when abnormal behavior crosses predefined thresholds.By automating the invigilation process, the proposed system significantly reduces human effort and operational costs while improving exam security. It is scalable, reliable, and suitable for educational institutions, certification bodies, and corporate assessments.Overall, this system enhances trust, transparency, and integrity in online examinations.