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@article{189267,
        author = {Tanisha Suresh Parmar and Tejal Bagul},
        title = {AI Online Exam Proctoring System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {8196-8198},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189267},
        abstract = {The AI Online Exam Proctoring System is an intelligent, automated solution designed to monitor and secure online examinations using advanced artificial intelligence technologies. It integrates real-time facial recognition, object detection, behavior analysis, and audio–video monitoring to identify suspicious activities such as candidate impersonation, device usage, eye movement anomalies, and unauthorized presence. The system ensures academic integrity by continuously tracking the test-taker’s environment and generating instant alerts for potential violations. It eliminates the need for human invigilators, enables scalable remote examinations, and provides detailed reports for exam administrators. By combining machine learning, computer vision, and secure exam delivery mechanisms, the AI proctoring system offers a reliable, efficient, and tamper-resistant framework ideal for universities, corporations, and certification bodies conducting high-stakes assessments.},
        keywords = {The key concepts explored in this study include artificial intelligence, online proctoring, remote examination security, computer vision, facial recognition, object detection, behavior analysis, academic integrity, cheating detection, machine learning, deep learning, real-time audio-video monitoring, automated invigilation, and secure exam environments.},
        month = {December},
        }