Exam Surveillance System using Machine Learning An exam surveillance system encompasses the automation of proctoring procedures within universities or colleges, aiming to enhance the efficiency of highly educated staff. By implementing such a system, the objective is to dissuade students from engaging in cheating behaviors during exams. This is achieved through the automation of the identification of potential cheating events, utilizing detailed logs. The system streamlines the review process for proctors, reducing the reliance on manual examination and enabling a more efficient detection and handling of academic dishonesty. Moreover, extending its utility beyond examinations, the system can also be seamlessly applied to interview process, providing a secure and monitored environment for virtual interviews.