Discussion of the master’s thesis in the College of Computer Science and Mathematics -Department of (   computer Science   ) entitled:

Behavioral Monitoring And Cheating Detection Based On Video Analysis In Exam Hall

supervised by  Dr.   Ghassan Jasim Mohammed

The thesis addressed the phenomenon of examination cheating as one of the major issues affecting the integrity of the educational process and the credibility of academic assessment. The study focused on developing an intelligent system for detecting cheating incidents in examination halls by utilizing Artificial Intelligence (AI), Computer Vision techniques, and real-time video analysis.

The study reviewed traditional methods for detecting cheating and their limitations, then discussed recent developments based on artificial intelligence and deep learning. It also addressed algorithms used in computer vision, such as YOLO and MediaPipe, as well as object tracking and behavior analysis techniques.

The study aims to  develop an intelligent system for detecting cheating in exams using artificial intelligence, computer vision, and real-time video analysis techniques. This system tracks student movement, analyzes head orientation and distances between students, and identifies suspicious behaviors, with the goal of improving monitoring accuracy, reducing reliance on traditional human supervision, and enhancing academic integrity.

The discussion committee consists of

Dr.  Alaa Yassin Taha

Dr.  Elaf Osama Abdel-Majeed

Dr . Mohammed Abdul Ghani Taha

Dr. Ghassan Jasim Mohmmed