Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)

<Previous Article In Volume
Next Article In Volume>

AI-Powered Institutional Discipline Monitoring: Automated Detection Of ID Card Compliance And Facial Grooming Using Yolov5

Authors
D. Sagar1, *, K. Sripal Reddy1, P. Namratha Sri1, B. Karthikeya1
1Department of ECE, Vardhaman College Of Engineering, Rangareddy, TG, India
*Corresponding author. Email: ds9515574535@gmail.com
Corresponding Author
D. Sagar
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-858-5_18How to use a DOI?
Keywords
YOLOv5; Compliance; Object Detection; Deep Learning
Abstract

Maintaining discipline in institutional environments is a significant challenge, often requiring manual monitoring methods that are time-consuming and error-prone. This paper presents an automated system that utilizes machine learning for real-time discipline monitoring, specifically detecting the presence of beards and ID cards. By leveraging the YOLOv5 deep learning model, the system ensures high accuracy and efficiency in detecting compliance violations. The methodology includes data set collection, annotation, training, and real-time deployment for institutions. Experimental results demonstrate a high detection accuracy of 95.4% with optimized inference times. The proposed system enhances institutional compliance monitoring, reduces human intervention, and provides a scalable solution for discipline enforcement.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series
Advances in Computer Science Research
Publication Date
4 November 2025
ISBN
978-94-6463-858-5
ISSN
2352-538X
DOI
10.2991/978-94-6463-858-5_18How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - D. Sagar
AU  - K. Sripal Reddy
AU  - P. Namratha Sri
AU  - B. Karthikeya
PY  - 2025
DA  - 2025/11/04
TI  - AI-Powered Institutional Discipline Monitoring: Automated Detection Of ID Card Compliance And Facial Grooming Using Yolov5
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 197
EP  - 203
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_18
DO  - 10.2991/978-94-6463-858-5_18
ID  - Sagar2025
ER  -