• Krushna Ingale
• Yash Repal
• Pratish Bamane
• Aniket Palkar
• Saurabh Parchande

The project PROCTOAI: Enhancing Exam Integrity with Machine Learning proposes the development and implementation of PROCTOAI, a cutting-edge system aimed at bolstering the integrity of examinations through the utilization of machine learning techniques. With the pervasive rise of remote and online assessments, maintaining exam integrity has become a pressing concern. PROCTOAI seeks to address this challenge by employing advanced machine learning algorithms to detect and deter academic dishonesty, including cheating, impersonation, and unauthorized aids. By leveraging sophisticated facial recognition, behaviour analysis, and anomaly detection, PROCTOAI aims to provide educators and institutions with a robust solution to safeguard the credibility and fairness of exams conducted in virtual environments. Through its proactive approach to monitoring and intervention, PROCTOAI strives to uphold the standards of academic integrity and promote a level playing field for all learners.

Machine Learning, Exam Integrity, Cheating Detection, Facial Recognition, Anomaly Detection

"PROCTOAI: Enhancing Exam Integrity with Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.j318-j320, April-2024, Available :http://www.jetir.org/papers/JETIR2404940.pdf

"PROCTOAI: Enhancing Exam Integrity with Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppj318-j320, April-2024, Available at : http://www.jetir.org/papers/JETIR2404940.pdf