AI Powered Human Behaviour Detection and Monitoring

Saratha M., Aarthi B., Harshini M., Hemanth B., Vishnu Priya C.

2025

Abstract

Examination malpractice refers to any intentional misconduct that violates examination regulations, aimed at providing an unjustly favoured candidate. Essentially known as cheating, this unlawful activity involves students attempting to achieve favourable grades through dishonest means. Such malpractice represents a deviation from the established protocols governing the examination process. The prevalence of examination malpractice has adversely affected students, as many have abandoned their studies, relying instead on the deceptive practices they have come to depend on during assessments. Examination malpractice within the Nigerian educational system has been extensively examined and recognized as a significant obstacle not only for examination authorities but also for school organization, the broader educational framework, governmental bodies, and society as a whole. The identification of impersonators in examination environments is crucial for enhancing the examination management system, which can contribute to the reduction of malpractices occurring in examination centres. A biometric approach presents an effective strategy to combat examination malpractice through the detection of impersonators. Face Recognition Technology is increasingly utilized across various applications, allowing for the identification of candidates based on extracted facial features, which are processed using algorithms and other methodologies. To address this issue, a robust solution that requires minimal manpower is essential. With the progress in deep learning algorithms, resolving this challenge has become more feasible. This project aims to develop a framework for facial recognition and to analyze students' behavioural patterns, employing HAAR cascade and Convolutional Neural Network algorithms.

Paper Citation

in Harvard Style

M. S., B. A., M. H., B. H. and C. V. (2025). AI Powered Human Behaviour Detection and Monitoring. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 312-317. DOI: 10.5220/0013897200004919

in Bibtex Style

@conference{icrdicct`2525,
author={Saratha M. and Aarthi B. and Harshini M. and Hemanth B. and Vishnu C.},
title={AI Powered Human Behaviour Detection and Monitoring},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={312-317},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013897200004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - AI Powered Human Behaviour Detection and Monitoring
SN - 978-989-758-777-1
AU - M. S.
AU - B. A.
AU - M. H.
AU - B. H.
AU - C. V.
PY - 2025
SP - 312
EP - 317
DO - 10.5220/0013897200004919
PB - SciTePress