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@article{196904,
        author = {DR NELLUTLA SASIKALA and B.Sahithya Varshini and Ch.Abhigna and G.Kavya and B.Manideep and D.Akhil},
        title = {MEISS: MALPRACTICE IDENTIFICATION AND EXAMINATION SURVEILLANCE SYSTEM USING MULTIMODAL SENSING AND IMAGE PROCESSING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {5424-5430},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196904},
        abstract = {Examinations are important for academic evaluation of a structure and maintaining their integrity is very important .Traditional invigilation methods depend on human supervision which can lead to limited attention difficulty in monitoring large examination hall simultaneously with the rapid advances in AI and computer in SIM technologies there is scope to automate and enhance the invigilation process  This project proposes an AI based intelligent invigilation system that assists invigilators by continuously monitoring student behavior  and detect suspicious actions in real time this project focuses on maintaining discipline during  examination which requires continuous monitoring of students behavior frequent head movements such as looking left right or behind may indicate unfair behavior Manual observation will be limited and difficult which is prove to error thus project automatically monitors and analyses head movements of student using computer vision This AI-enabled automated proctoring system utilizes computer vision, image processing, and deep learning to monitor online exams in real-time, detecting cheating via facial recognition, eye-tracking, object detection (e.g., phones, books), and audio analysis. It automatically logs violations; tracks head pose and behavior, and ensure integrity. AI-enabled automated proctoring systems use computer vision, machine learning, and image processing via webcams to ensure exam integrity 
 AI-enabled automated proctoring systems leveraging image processing and computer vision have revolutionized remote assessment by replacing manual invigilation with real-time, scalable, and objective monitoring. Tracks gaze, head pose, and body movement to detect looking away, are leaving the seat or multiple people in the frame.},
        keywords = {Eye-Tracking, Computer Vision, Exam Integrity, Gaze, Online Exams},
        month = {April},
        }