Online Examination And Proctoring System

The increasing demand for remote education and online assessments has necessitated the development of secure and reliable exam monitoring systems. This project presents an Online Examination And Proctoring System that ensures academic integrity by monitoring candidates in real-time through webcam and screen activity. Utilizing advanced technologies such as facial recognition, object detection, and behavior analysis, the system identifies and flags suspicious activities including presence of multiple faces, unauthorized device usage, and leaving the test environment. It offers a scalable and automated solution that reduces the need for human invigilators, thus enhancing accessibility and efficiency in digital examinations. The system is developed using Python, OpenCV, and machine learning models, and integrates seamlessly with popular learning management platforms.

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Publication Details

Journal
International jounal of information technology and computer engineering.
Published
2025-06-11
DOI
https://doi.org/10.62647/ijitce2025v13i2spp67-76
Primary Topic
Problem and Project Based Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Online Examination And Proctoring System

M A Bari, Ishrath Unnisa, Sadiya Baseer
International jounal of information technology and computer engineering.
Problem and Project Based Learning
article

Online Examination And Proctoring System

M A Bari, Ishrath Unnisa, Sadiya Baseer
article en

Abstract

The increasing demand for remote education and online assessments has necessitated the development of secure and reliable exam monitoring systems. This project presents an Online Examination And Proctoring System that ensures academic integrity by monitoring candidates in real-time through webcam and screen activity. Utilizing advanced technologies such as facial recognition, object detection, and behavior analysis, the system identifies and flags suspicious activities including presence of multiple faces, unauthorized device usage, and leaving the test environment. It offers a scalable and automated solution that reduces the need for human invigilators, thus enhancing accessibility and efficiency in digital examinations. The system is developed using Python, OpenCV, and machine learning models, and integrates seamlessly with popular learning management platforms.

International jounal of information technology and computer engineering.Vol. 13(2s)
Dean College (US), English and Foreign Languages University (IN)
Openalex Percentile: Top 85%
Problem and Project Based Learning
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