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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM24840
Volume:
7 |
7 |
Jul 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Distance and on- line mastering ( or e-learning) has emerge as a norm in schooling and education due to a ramification of benefits similar as effectiveness, flexibility, affordability and ease of use. Insulation requirements. however, tracking participants and scholars throughout training, specifically assessments, is a major task for on- line systems due to the dearth of physical presence. strategies and technologies need to be advanced that offer sturdy equipment for detecting unfair, unethical and unlawful conduct for the duration of the study room requirements. We suggest in this paper a new online surveillance system that uses deep learning to continuously monitor physical locations without the need for a physical examiner. The system makes use of biometric strategies which includes face sensor OpenCV DNN and the eye tracking algorithm OpenCV. further, the machine consists of person and phone detection. To make sure equity for the duration of examinations, the device can also recognize devices including cell telephones, laptops, iPads and books.
KEYWORDS
Publication Date
7/27/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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