Student Authentication and Proctoring System Using AI and the IoT

Abstract

The alarming spread of COVID-19 has caused significant social, economic, and commercial changes globally and has altered education. It highlighted the significance of an alternative education model that maintains health and safety during pandemics without disrupting learning. With this rapid transition to distance learning, it became fundamental to ensure the reliability of academic results is maintained through an online exam proctoring tool, providing user authentication, and examinees' monitoring, while ensuring maximum student convenience. In this paper, we propose an AI-powered proctoring system that adequately detects and reports academic malpractice and tackles the most significant distance learning deficiency, which is verifying the online learner's identity. The proposed solution is based on a computing unit equipped with an HD camera running computer vision pipelines that uses the student identification details for user authentication. The system aims to eliminate the possibility of running into technical problems while maintaining minimal human intervention. Hence, it offers a reliable, low-cost, user-friendly solution that saves time and resources. © 2022 IEEE.

Keywords: Artificial intelligence, COVID-19, Online learning, Proctoring