Abstract
Exams are the methods adopted by educational institutions to identify student’s knowledge. Students adopt various ways to cheat in exams like answer sheet exchanging, copying etc, students cheat their way into getting good grades. Detection of cheating manually may not be efficient to identify and prevent cheating during examinations. So, to avoid this the process of invigilation is made automatic. Automated invigilation offers the best method for keeping an eye on the kids and spotting instances of malpractice right away. The proposed work has three phases. In the first phase, the exam management does processes like publishing time table, allocating exam hall, allocating hall to staff etc. In the second phase the posture detection of the student present in the exam hall is done using Computer Vision and Media Pipe to detect whether the student has involved in the malpractice. In the third phase, the emotion analysis and face recognition of the student is done using the Haar Cascade Frontal Algorithm. The proposed work also helps to eliminate impersonation in the exam hall.
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