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@article{186333,
        author = {Vaishnavi Vijay Taware and Sakshi Dagdu Raut and Suknya Vithal Late and Ritika Satish Jadhav},
        title = {Suspicious Activity Detection in Exam Hall},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {857-861},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186333},
        abstract = {This project, titled “Suspicious Activity Detection in Exam Hall Using CNN,” aims to automatically detect and alert exam supervisors about suspicious behavior during examinations. The system uses video input from a camera and processes it through image preprocessing and feature extraction techniques. A Convolutional Neural Network (CNN) model is trained using a dataset of normal and suspicious activities to identify unusual behavior such as cheating or using mobile phones. When suspicious activity is detected, the system captures the image and sends an email alert to the examiner. This project helps to ensure a fair and transparent examination process by reducing manual monitoring and improving accuracy and reliability through artificial intelligence.},
        keywords = {},
        month = {November},
        }