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Sentinel Roadway Oversight System: Emergency and Traffic Rule Violation System

by Gulnaz Thakur, Ojal Rane, Vaibhav Sarode, Ashutosh Deshmukh, Prerana Pensalwar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 61
Year of Publication: 2025
Authors: Gulnaz Thakur, Ojal Rane, Vaibhav Sarode, Ashutosh Deshmukh, Prerana Pensalwar
10.5120/ijca2025924377

Gulnaz Thakur, Ojal Rane, Vaibhav Sarode, Ashutosh Deshmukh, Prerana Pensalwar . Sentinel Roadway Oversight System: Emergency and Traffic Rule Violation System. International Journal of Computer Applications. 186, 61 ( Jan 2025), 1-7. DOI=10.5120/ijca2025924377

@article{ 10.5120/ijca2025924377,
author = { Gulnaz Thakur, Ojal Rane, Vaibhav Sarode, Ashutosh Deshmukh, Prerana Pensalwar },
title = { Sentinel Roadway Oversight System: Emergency and Traffic Rule Violation System },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2025 },
volume = { 186 },
number = { 61 },
month = { Jan },
year = { 2025 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number61/sentinel-roadway-oversight-system-emergency-and-traffic-rule-violation-system/ },
doi = { 10.5120/ijca2025924377 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-01-28T19:07:03.895094+05:30
%A Gulnaz Thakur
%A Ojal Rane
%A Vaibhav Sarode
%A Ashutosh Deshmukh
%A Prerana Pensalwar
%T Sentinel Roadway Oversight System: Emergency and Traffic Rule Violation System
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 61
%P 1-7
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The goal of this paper is to review past work on advanced monitoring systems, with a focus on the integration of technologies such as Raspberry Pi 4.0 and YOLOv8/Yolov9. These technologies are among the most widely used solutions for real-time monitoring due to their efficiency and accuracy. It is a leading object detection model that provides a powerful system for continuous tracking and automated observation. This paper explores how these technologies enhance road safety and traffic management by monitoring various vehicle behaviors, detecting irregularities, and facilitating swift responses to critical road situations. The objective of the system is to enhance road safety and optimize traffic management by monitoring vehicle behaviors, detecting irregularities, and facilitating quick responses to critical road situations. It tracks vehicle movements, identifies potential incidents, and automatically alerts relevant authorities when discrepancies or safety issues are detected. The alerting system is essential for providing the location and information about the vehicle to traffic control agencies, ensuring swift and accurate responses.

References
  1. Benjamin Coifman, David Beymer, Philip McLauchlan, Jitendra Malik (1998). A real-time computer vision system for vehicle tracking and traffic surveillance. Transportation Research Part C: Emerging Technologies, 6(4), 271-288. Elsevier.
  2. V. K. Muneer, A. Azil (2024). Study of an AI-Powered Vehicle Monitoring System: An Ensembled Approach for Intelligent Surveillance. International Journal of Engineering Science, 11(2), 51-59.
  3. Bo Wang, Yang Su, Mingshu Zhang, Junke Nie A deep hierarchical network for packet-level malicious traffic detection. IEEE Access, 8, 201728–201740.
  4. Neeraj Kumar Jain, R. K. Saini and Preeti Mittal (2018). A Review on Traffic Monitoring System Techniques. In Soft Computing: Theories and Applications (pp. 569–577). Advances in Intelligent Systems and Computing (AISC, Volume 742). Springer.
  5. Tamim Mahmud Al-Hasan, Victor Bonnefille, and Faycal Bensaali Enhanced YOLOv8-based system for automatic number plate recognition. Technologies, 12(9), 164.
  6. Saif B. Neamah, Abdulamir A. Karim (2024). Real-time traffic monitoring system based on deep learning and YOLOv8. ARO The Scientific Journal of Koya University, 12(1), 45-52.
  7. John Paul Q. Tomas, Jose Angelo M. Apdian, Alosius John S. Masacayan, Gerome Justin C. Riego. Detection of traffic density via YOLOv8 towards prediction via regularized LSTM network. In Proceedings of the Sixteenth International Conference on Digital Image Processing (ICDIP 2024) (Vol. 13274, 132740D). SPIE.
  8. Yusuf Gladiensyah Bihanda, Chastine Fatichah, Anny Yuniarti (2024). Multi-vehicle tracking and counting framework in average daily traffic survey using RT-DETR and ByteTrack. IEEE Access, 12, 121723–121737.
  9. Bo Wang, Yuan-Yuan Li, Weijie Xu, Huawei Wang. Vehicle– Pedestrian Detection Method Based on Improved YOLOv8. School of Automotive and Transportation Engineering, Wuhan University of Science and Technology, Wuhan 430065, China.
  10. Sriram Sai Krishna, Varshith Parisha, Bhupathiraju Uday Kaushik Varma, Chennupalli Srinivasulu (2024). Traffic light detection and recognition using YOLOv8. In Proceedings of the 2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) (pp. 123-128). IEEE.
  11. Murat Bakirci (2024). Enhancing vehicle detection in intelligent transportation systems via autonomous UAV platform and YOLOv8 integration. Applied Soft Computing, 152, 112015.
  12. Manishkumar Purohit, Arvind R. Yadav (2018). Comparison of feature extraction techniques to recognize traffic rule violations using low processing embedded system. In Proceedings of the 5th International Conference on Signal Processing and Integrated Networks (SPIN) (pp. 270-274). IEEE.
  13. Hemanth Mohan, Randhir Dinesh, Abhiraj Kumar, Anwin Mathai (2024). Enhanced YOLOv8-Driven Traffic Rule Violation Detection with ROS-Integrated Autonomous Drone Navigation. In 2024 IEEE Recent Advances in Intelligent Computational Systems (RAICS). IEEE.
  14. Ali Usman, Seungmin Oh, Junghoon Lee, Jinsul Kim (2024). Brands logo recognition with semi-supervised learning using a robust YOLOv8 detection model. In Proceedings of the 2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) (pp. 123-128). IEEE.
  15. Ștefan Liviu-Andrei, Cărbureanu Mădălina 2(2024). Integrated convolutional neural networks application for road traffic efficiency. Romanian Journal of Petroleum and Gas Technology, 5(1), 159-168.
  16. Xingyu Liu, Yuanfeng Chu, Yiheng Hu, Nan Zhao (2024). Enhancing intelligent road target monitoring: A novel BGSYOLO approach based on the YOLOv8 algorithm. IEEE Open Journal of Intelligent Transportation Systems, 5, 509–519. (2024). Multivehicle tracking and counting framework in average daily traffic survey using RT-DETR and ByteTrack. IEEE Access, 12, 121723–121737.
  17. Md Faysal Kabir, Sahadev Roy (2022). Real time vehicular accident prevention system using deep learning architecture. Expert Systems with Applications, 206, 117837.
  18. Lakshmi, A. V., Goud, P. A. K., Raj, G. M., and Rahul, K. (2023). Vehicle collision warning and accident detection using Raspberry Pi and SSD MobileNetV1. In Intelligent Communication Technologies and Virtual Mobile Networks (pp. 203–218). Springer.
  19. Mohammed Imran Basheer Ahmed, Reem Zaghdoud, Mohammed Salih Ahmed, Bashayr Adnan Albin Saad. (2023). A real time computer vision-based approach to detection and classification of traffic incidents. Big Data and Cognitive Computing, 7(1), 22.
  20. Priyam Rai, Eshan Eshwar Kothari, Megha Bhushan, Arun Negi (2023). Vehicle theft identification using machine learning and OCR. In Machine Intelligence Techniques for Data Analysis and Signal Processing (pp. 753–763). Springer.
  21. Adithya Krishna R, Sandeep P, Sonu. P (2024). Camera mounted helmet detection with YOLO v8 on custom dataset. In Proceedings of the 2024 Sixteenth International Conference on Contemporary Computing.
  22. Manimegalai (2024). Highway vehicle detection using YOLOv8 and computer vision techniques. Bulletin of Electrical Engineering and Informatics, 13(5), 2750-2760.
  23. Surya Kumaran S, Rokesh Kumar P, Hemalatha R. Traffic Violation Detection System Using a YOLOv3 Model Implemented on Raspberry Pi. Published in International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 14, No. 11, 2023.
  24. Long Cheng, Dan Zhang, Yan Zheng. Improved YOLOv8Based Algorithm for Vehicle Detection in Foggy Weather. Published in Endorsed Transactions on Intelligent Transportation Systems, 2024.
  25. Kamya Brata Debnath. (2023). Enhancing Safety in Transportation Systems Using ESP32 and Deep Learning Algorithms. Published in Proceedings of the International Conference on Innovative Technologies in Computing, 2024.
  26. Pooja Chaturvedi, et al. (2024). Automated system for monitoring traffic violations: Targeting triple riders on twowheelers using YOLOv8 and OCR. International Journal of Intelligent Transportation Systems, 12(3), 120-130.
  27. Ubon Thongsatapornwatana, et al. (2024). Framework for identifying suspect vehicles using sensor data and legal records. Transportation Security Review, 9(2), 234-245.
  28. Tao Gao, Zhengguang Liu, Shiguo Lian, Shihong Yue, Jun Zhang (2024). Crossing road monitoring system based on adaptive decision for illegal situation. Applied Soft Computing, 10(4), 1067- 1075.
  29. Luiz Alfonso Glasenapp, et al. (2024). Integration of OCR with IoT for automated detection of vehicles with irregular documentation. Journal of Traffic Enforcement and Safety, 10(2), 156165.
  30. Nagaraj P., et al. (2024). Improving traffic safety with YOLOv8 and OCR: Detection of speeding and unauthorized vehicle use. IEEE Transactions on Intelligent Transportation Systems, 15(1), 45-56.
  31. Fatma Nur Ortatas¸, Mahir Kaya (2023). YOLOv8 in traffic sign detection: A comparison with YOLOv5 and YOLOv7. Autonomous Systems Journal, 8(2), 123-134.
  32. Ahmed N. Nusari, Abdulfattah E. Ba Alawi, Ferhat Bozkurt,˙Ibrahim Yucel Ozbek .(2024). Comparison of YOLO algorithms for vehicle accident detection and classification. IEEE.
  33. Ahmed Naji Musleh Nusari, et al. (2024). YOLO-NAS for accident detection systems in urban areas. Journal of AI in Traffic Management, 13(1), 154-165.
  34. Xiyue Wang, Xinsheng Wang, et al. (2024). Lightweight CNN for real-time vehicle detection in UAVs: A comparison with YOLOv8n. IEEE Access, 12, 121723–121737.
  35. Shahriar Ahmad Fahim (2024). YOLOv9 model for vehicle detection in Dhaka, Bangladesh: Enhancing urban traffic management. International Journal of Intelligent Transportation Systems, 12(4), 233-245.
Index Terms

Computer Science
Information Sciences
Real-time Monitoring
Surveillance
Alerting Systems

Keywords

Raspberry Pi 4.0 YOLOv8 EasyOCR Real-time Emergency System

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