SMART ARTIFICIAL INTELLIGENCE BASED ONLINE PROCTORING SYSTEM

Abstract

Since COVID 19, there have been significant
advancements in the field of teaching and learning.
Academic institutions are going digital to provide their
students more resources. Due to technology, students
now have more alternatives to study and improve skills
at their own pace. In terms of assessments, there has
been a shift toward online tests. The absence of a
physical invigilator is perhaps the most significant
impediment in online mode. Henceforth, online
proctoring services are becoming more popular, and
AI-powered proctoring solutions are becoming
demanding. In this project, we describe a strategy for
avoiding the physical presence of a proctor during the
test by developing a multi-modal system. We captured
video using a webcam along active window capture.
The face of the test taker is identified and analysed to
forecast his emotions. To identify his head pose, his
feature points are identified. Furthermore, aspects
including a phone, a book, or the presence of another
person are detected. This combination of models
creates an intelligent rule-based inference system
which is capable of determining if any malpractice took
place during the examination