Publication Date: 2024/01/06
Abstract: An AI based Online Proctoring System isn’t a new concept and many such capable exam portals do already exist. However, all of them have an unsolved design flaw which is server side processing. To detect any suspicious activity, the sites either take a snapshot of the examinee in regular intervals which is doable but is very weak, or they continuously send the video feed over to the server for processing which being comparatively more effective, is highly expensive. Sending video feeds of tens of thousands of students and processing them in real time can be very heavy on the server as well as costly for the client. To counter all these flaws, proposing an AI based proctoring system that securely works on the client side. Overall goal is to allow the face detection system and suspicious activity detection system to run on the client side which will significantly reduce the server load and dependency on the network. In this review paper we explored various algorithms for face verification, object detection, also reviewed pre-existing OPS systems and learned about their architecture.
Keywords: CNN (Convolution Neural Network), OPS (on- line proctoring system), TFOD (Tensorflow Object Detection).
DOI: https://doi.org/10.5281/zenodo.10464663
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23DEC1917.pdf
REFERENCES