AI based Online Proctoring Remote Monitoring Intruder, Emotion Detection and Distance Estimation

AI based online learning has undeniably surged in popularity over recent years. The COVID-19 pandemic has further accelerated the transition to online education, heightening the need for secure methods to authenticate and proctor online students. Today, a range of technologies offers varying levels of automation. In this paper, we present a comprehensive analysis of a specific solution that integrates multiple automated authentication technologies with an automatic proctoring system. The parameters that we used to achieve our goal are face detection, eye gaze tracking, multiple person detection, emotion detection, distance estimation and background noise detection. All these components help to maintain the exam integrity and to mitigate the existing limitation of e-exam proctoring software’s. Keywords— AI based online learning, Exam remote Monitoring integrity, Gaze tracking, Intruder, distance estimation.