Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64913
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
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.
Computer Engineering
TSSM's Bhivarabai Sawant College of Engineering and Research
Computer Engineering
TSSM's Bhivarabai Sawant College of Engineering and Research
In order to preserve academic integrity and guarantee fair exams and online learning, the quick expansion of online education has made efficient proctoring systems necessary. For online tests and e-learning, traditional proctoring techniques like in-person invigilation are impractical. A computer vision-based automated proctoring system is suggested as a solution to this problem. This technology uses sophisticated computer vision algorithms to track and examine how applicants behave during online tests and learning. The Automated Proctoring System keeps an eye on the test environment in real time by using a webcam and screen recording. The examinee's face, gaze direction, eye movements, body posture, and suspicious activities are all detected and tracked using computer vision algorithms. Unusual patterns of behavior, including repeatedly averting one's gaze from the screen or displaying several faces in the camera frame, are recognized by machine learning models. The examiners receive alerts for more investigation as a result of these irregularities. Through the mitigation of academic dishonesty, such as cheating, impersonation, and unauthorized aids, the suggested system seeks to improve exam security and e-learning. It offers a scalable and non-intrusive way to supervise online tests and e-learning by utilizing computer vision.
KEYWORDS
In this paper, we have suggested and put into practice a computer vision-based automated proctoring system. The system supports the fair administration of exams, upholding the integrity of the process. This study shows how semi-automated proctoring based on vision and audio capabilities, as well as simultaneously monitoring many students, may prevent cheating in online exams. However, if someone is seated behind the laptop, the student can speak with them by reading the question to them. A 360-degree camera that monitors the student's whole room can address this.
1. Jay Mayekar1, Shubham Pal2, Aditya Pandey3, Bikra Pani4, Prof. Preeti Mishra5, "AUTOMATED PROCTORING SYSTEM",International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 10 Issue: 04 | Apr 2023. 2. Simon Wenig, Michael Suriyah, Freiber Rojas, Kevin Schönleber,ThomasLeibfried,"Simulation Framework for DC Grid Control and ACDC Interaction Studies Based on Modular Multilevel Converters", @ IEEE 2016. 3. Aiman A Turani,Jawad H Alkhateeb,AbdulRahman A. Alsewari,"Students Online Exam Proctoring: A Case StudyUsing 360 Degree Security Cameras",2020 Emerging Technology in Computing, Communication and Electronics (ETCCE) 4.AsepHadianSudrajatGanidisastra, YoanesBandung,"An Incremental Training on Deep Learning Face Recognition for M-Learning Online Exam Proctoring",The 2021 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob) 5."Automated Proctoring System using Computer Vision Techniques",Conference Paper · July 2021.DOI: 10.1109/ICSCAN53069.2021.9526411 6.RenukaDevi,GowriSrinivasa, "Detection of anomalous behavior in an examination hall towards automatedproctoring",https://www.researchgate.net/publication/321260760,2017. 7. YousefAtoum, Liping Chen, Alex X. Liu, Stephen D. H. Hsu, and Xiaoming Liu, "Automated Online Exam Proctoring",ACCEPTED WITH MINOR REVISION BY IEEE TRANSACTION ON MULTIMEDIA, DEC 30, 2015 8. YusepRosmansyah,"Impersonation Attack-DefenseTree", https://doi.org/10.3991/ijet.v15i19.12699 9. AdityaNigam,RhitvikPasricha,Tarishi Singh, PrathameshChuri, "A Systematic Review on AI‑based Proctoring Systems: Past,Present and Future",Education and Information Technologies (2021) 26:6421–6445,2021. 10. TejaswiPotluri1 &Venkatramaphanikumar S1 &Venkata Krishna Kishore K1, "An automated online proctoring systemusing attentive-net to assess studentmischievousbehavior",Multimedia Tools and Applications (2023) 82:30375–30404,2023.
Publication Date
6/13/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
2
Total views since publication
PDF Downloads
5
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...