International Journal of Analog Integrated Circuits

DressCode Monitoring System

  1. Amal S. Panikar ✉
  2. Tanuja Patil
  3. Bhausaheb E. Shinde

Abstract

This project aims to develop a dress code monitoring system using YOLO v5 object detection technology. Thesystem utilizes a camera to capture images or video footage of individuals entering a specific area and then uses YOLO v5 todetect their clothing and ensure that it complies with the predefined dress code standards. The system utilizes a deep learningalgorithm to accurately recognize various clothing items and differentiate between compliant and non-compliant attire. Byleveraging YOLO v5's advanced capabilities, the system can detect multiple objects in real-time, providing efficient andaccurate dress code monitoring. The proposed system has potential applications in various settings, such as schools,businesses, and public areas, to ensure compliance with dress code policies and maintain a professional environment.

References (24)

  1. Wang Zhiqiang and Liu Jun. A Review of Object Detection Based on Convolutional Neural Network, Proceedings of the
  2. th Chinese Control Conference July 26-28,(2017), Dalian, China. US: IEEE Press; 2017.
  3. Nadia Jmour, Sehla Zayen, Afef Abdelkrim. Convolutional Neural Networks for image classification 2018 International
  4. Conference on Advanced Systems and Electric Technologies (IC_ASET). 22-25 March 2018; Hammamet, Tunisia. US:
  5. IEEE Press; 2018.
  6. Chien-Yao Wang, Alexey Bochkovskiy, HongYuan Mark Liao. Scaled-YOLOv4: Scaling Cross Stage Partia
  7. Network (2021), Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.
  8. N. H. Abas, N. Yusuf, N. A. Suhaini, N. Kariya, H. Mohammad, and M. F. Hasmori, “Factors Affecting Safety
  9. Performance of Construction Projects: A Literature Review,” in IOP Conf. Series: Materials Science and Engineering 713
  10. W. Fang, L. Ding, B. Zhong, P. E. D. Love, and H. Luo, “Automated detection of workers and heavy equipment on
  11. construction sites: A convolutional neural network approach,” Adv. Eng. Informatics, vol. 37, pp. 139–149, Aug. 2018
  12. Seungjun Roh, Zeeshan Aziz, Feniosky Peña-Mora. An object-based 3D walk-through model for interior construction
  13. progress monitoring. Automation in Construction. Volume 20, Issue 1, January 2011, Pages 66-75.
  14. Boddu, Praveen, Face Recognition and Pattern Recognition Based Dress-Code Monitoring for Students (February 20,
  15. . International Journal of Advanced Science and Technology, 2020, Available at SSRN:
  16. https://ssrn.com/abstract=3580777
  17. Karwan Jacksi, Falah Ibrahim, Shahab Ali. Student Attendance Management System. Scholars Journal of Engineering and
  18. Technology. Feb 2018; 6(2): 49-5. 10.21276/sjet.2018.6.2.1
  19. Aayush Kumar, Amit Kumar, Avanish Chandra Dubey, Indira Adak. Custom Object Detection and Analysis in Real
  20. Time: YOLOv4. Ijraset Journal for Research in Applied Science and Engineering Technology.
  21. https://doi.org/10.22214/ijraset.2022.43303
  22. Zhihua Feng, Xin Luo, Tao Yang, Kenji Kita. An object Detection System Based on YOLOv2 in Fashion Apparel. 2018
  23. IEEE 4th International Conference on Computer and Communications (ICCC). 07-10 December 2018; Chengdu, China.
  24. US: IEEE Press; 2019.

Read more of it

Subscribe to one journal or build your own list of several. One invoice, one payment, access for a full year.

Subscribe to journals →

Publish your article

Peer-reviewed journals across every subject, with open access options. Send your manuscript to the right editor today.

Publish with us → Calculate your APC
Support