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@article{188620,
        author = {Ambika N R and Bharathkumar B S and Dr. Rajashekar K J and Dhanalakshmi S M and Faiza Tarannum and Sahana Basavaraj Kariger},
        title = {Online Exam Proctoring System Based On AI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {7},
        pages = {2519-2523},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188620},
        abstract = {The rise of remote learning has increased the need for secure, scalable online examination systems, as traditional methods are prone to academic dishonesty. This paper proposes an AI-based proctoring system that detects and prevents cheating using real-time vision and audio analysis. Key features include face recognition, mobile-phone detection, multi-person identification, gaze tracking, and object detection, with alerts and logs for verification. The system ensures fairness, transparency, and academic integrity through a secure, user-friendly Monitoring interface.},
        keywords = {Artificial Intelligence, Deep Learning, Remote Learning, Online Proctoring, Face Recognition, YOLO, OpenCV, CNN.},
        month = {January},
        }