Open Access
Subscription Access
An AI-Based Intelligent Exam Proctoring System for Secure and Fair Online Assessments
Abstract
With the growing demand for remote learning and online education, ensuring the security and fairness of online assessments has become a critical challenge. This paper presents an AI-Based Intelligent Exam Proctoring System (AI-EPS) designed to monitor and secure online assessments in real time. The system leverages advanced facial recognition, eye-tracking, posture analysis, and voice recognition technologies to detect suspicious behaviours, such as cheating attempts or unauthorized personnel in the testing environment. By integrating machine learning algorithms, AI-EPS provides real-time monitoring, automatic anomaly detection, and post-exam auditing, ensuring a secure and fair assessment process. The proposed system has been evaluated across different online exam platforms, demonstrating significant improvements in detecting potential cheating attempts and providing instructors with detailed reports. Results indicate a 90% accuracy in detecting irregular behavior, contributing to more reliable and credible online examination practices.
References
R. Anandan, S. Sridevi, Joyce C.K.Mani “Intellectual Road Traffic Monitoring System for Fire Fighting Vehicles Using Jade and IoT”, International Journal of Pure and Applied Mathematics Volume 116 No. 22, 2017, 435-445.
G.Bindu,S.Sridevi,Dr.R.A.Karthika ” Authentication for security in Vehicular Ad-Hoc Network using Cognitive Radio Technology” International Journal of Management, Technology And Engineering, 2018,2249-7455
S.Sridevi, G Bindu, R Anandan, Comparison and Detail Study Of Attacks And Detection Methods For Wireless Sensor Network, International Journal of Engineering and Technology(UAE), 2227-524X, Vol 7, No 2.21 Special Issue 21, 2018
Chandra Sekar P. and et.al(2022) “An Energy Efficient Architecture for Furnace Monitor and Control in Foundry Based on Industry 4.0 Using IoT”, Scientific Computing for Internet of Health Informatics Things ,Volume 2022 ,Article ID 1128717 , https://doi.org/10.1155/2022/1128717
Chandra Sekar, P &Mangalam, H (2018), ‘Third generation memetic optimization technique for energy efficient routing stability and load balancing in MANET’, Cluster Computing The Journal of Networks, Software Tools and Applications Published in online and DOI number is https://doi.org/10.1007/s10586-017-1524- x,ISSN1573-7543.(IF: 2.040).
Chandra Sekar, P &Mangalam, H, (2019)‘A power aware mechanism for energy efficient routing in manet’, International Journal of Networking and Virtual Organizations’ (Inderscience Publishers), 2019 Vol.21 No.1, pp.3 - 18. (IF: 1.09).
M. Thangamani, V. Ravindra Krishna Chandar, False Alarm Reduction in ICU Using Ensemble Classifier Approach, Intelligent Automation & Soft Computing, Volume 34, Iss No.1, Pp.165-181, https://www.techscience.com/iasc/v34n1/47339, IF. 1.647.
M. Thangamani, Pravin R. Kshirsagar , Hariprasath Manaoharan, Vineet Tirth, Saiful Islam, Sandeep Srivastava, Varsha Sahni, M. M. Khanapurkar and Venkatesa Prabhu Sundramurthy, Implementation of Whale Optimization for Budding Healthiness of Fishes with Preprocessing Approach , February 2022, Journal of Healthcare Engineering Volume 2022, Article ID 2345600, 7 pages, https://doi.org/10.1155/2022/2345, IF. 2.682
Hariprasath Manoharan, Sulaima Lebbe Abdul Haleem, S. Shitharth, Pravin R. Kshirsaga, Vineet Tirth, M. Thangamani, Radha Raman Chandan, A machine learning algorithm for classification of mental tasks, Computers and Electrical Engineering, Vol. 99, No.107785, 2022.
S.Sakena Benazer, M. Sheik Dawood, “Design of Rectenna for wireless sensor Networks” Elsevier, Materials Today: Proceedings, 2021, ISSN 2912-2915.
Refbacks
- There are currently no refbacks.