Proctor-Tool

 Proctor-Tool

1st PRANEETA

Roll-No:20211CSE0688

dept. CSE

2st MS. Kalpana K                              3nd Indira M

      Assistant Professor            Roll-No:20211CSE0687

        dept. CSE                                             dept. CSE

4rd Juveria Syed

Roll-No:20211CSE0665

dept. CSE

Abstract—The increasing adoption of online education has led to a growing need for secure and reliable examination systems. Traditional in-person examinations ensure integrity through physical invigilation, but with the rise of remote learning, maintaining exam security has become a significant challenge. Online exams are often vulnerable to cheating, impersonation, and unauthorized assistance, which undermines the credibility of assessments.

Existing online examination systems employ manual proctoring, where human invigilators monitor students via webcams. However, this approach is labour-intensive, expensive, and subject to human errors. To address these challenges, automated proctoring solutions have been introduced, integrating artificial intelligence (AI) and machine learning to detect suspicious behaviour.

In this research, we present Procto, an AI-based online proctoring system designed to ensure exam integrity through automated monitoring and real-time analysis. The system uses computer vision techniques to detect face absence, multiple people in the frame, mobile phone usage, and unauthorized objects. Additionally, it prevents tab switching, keyboard shortcuts, and right-click actions, further securing the examination process.

Procto is designed to be efficient, scalable, and user-friendly, making online assessments more reliable without requiring human invigilators. By leveraging advanced AI models, the system enhances security while reducing the administrative burden on educators. This research explores the need, implementation, and effectiveness of AIbased proctoring, offering a novel approach to securing online exams.