Akademy: A Unique Online Examination Software Using ML

Online examinations, tasks, or any kind of assessment done either by schools, colleges, or organisations are vital for the institute as well as for the growth of a student. The evaluation output provided by all the existing tools is only important when the examination is conducted fairly. There is a scope for improvement in the conduction of online examinations. However, the institutions are unable to do so with the existing tools. In this paper, an approach is proposed that includes the possible illegal practise mitigation solutions such as student focus detection, face detection, and face verification that are necessary for fair evaluation and the necessary features such as detailed analysis and team formation/chat for students and faculty. The MTCNN model’s participation is critical in enhancing the fairness of the examination. The continuous face verification and authentication will definitely change the performance of this tool’s examination conduction mechanism.