Advancing Road Safety: A Comprehensive Analysis of an Enhanced Traffic Violation Detection
Keywords:
Traffic Congestion, Urban Automobile Ownership, YOLOv7, Speed Limit EnforcementAbstract
In India and elsewhere, the gravity of traffic offenses has risen in recent years as rising urban automobile ownership has led to increased traffic congestion. As a result, there is widespread property damage and an increase in accidents, both of which pose a threat to human life. Yolov7-based traffic infraction detection technologies are required to address this urgent issue and avert the potentially catastrophic outcomes. This is why the system constantly monitors for violations of traffic laws and prosecutes offenders. Since police are always monitoring the highways, it is imperative that any system for detecting traffic violations be implemented instantly. Therefore, law enforcement officers will not only have an easier time enforcing safe roadways, but they will also be able to do it more quickly and effectively thanks to the traffic detection technology. In real time, this apparatus can identify infractions of traffic lights, speed limits, and helmet laws. User-provided video is required for system operation, monitoring of traffic, and enforcement of traffic regulations.
Downloads
References
G. Ou, Y. Gao and Y. Liu, "Real Time Vehicular Traffic Violation Detectionin Traffic Monitoring System,” I n 2012 IEEE / WIC/ ACM, Beijing, China, 2012.
X. Wang, L.-M. Meng, B. Zhang, J. Lu and K.-L.Du, "A Video-based Traffic Violation Detection System," in MEC, Shenyang, China, 2013.
J. Chiverton, “Helmet presence classification with motorcycle detection and tracking,” IET Intell. Transp. Syst., vol. 6, no. 3, pp. 259–269, 2012.
K. Dahiya, D. Singh, and C. K. Mohan, “Automatic detection of bikeriders without helmet using surveillance videos in real-time,” in Proc. Int. Joint Conf. Neural Netw. (IJCNN), Jul. 2016, pp. 3046–3051.
Subedha, V. ., Vivek, B. ., Venkata Sai, C. N. ., Vadana, A. S. ., & Dhanwanth, B. . (2023). A Novel Strategy for Streamlining Land Registration using Ethereum Blockchain. International Journal of Intelligent Systems and Applications in Engineering, 11(3), 104–111. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3147
N. C. Mallela, R. Volety, R. P. Srinivasa, and R. K. Nadesh, “Detection of the triple riding and speed violation on two-wheelers using deep learning algorithms,” Multimedia Tools Appl., vol. 80, no. 6, pp. 8175–8187, Mar. 2021.
V. Mandal and Y. Adu-Gyamfi, “Object detection and tracking algorithms for vehicle counting: A comparative analysis,” J. Big Data Anal.Transp., vol. 2, pp. 251– 261, Nov. 2020.
S. Kumari, D. K. Gupta, and R. M. Singh, “A novel methodology for vehicle number plate recognition using artificial neural network,” in Proc. 3rd Int. Symp. Comput. Vis. Internet, Sep. 2016, pp. 110–114.
Vivek, B. ., Nandhan, S. H. ., Zean, J. R. ., Lakshmi, D. ., & Dhanwanth, B. . (2023). Applying Machine Learning to the Detection of Credit Card Fraud. International Journal of Intelligent Systems and Applications in Engineering, 11(3), 643–652. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3267
Dhanwanth, B. ., Vivek, B. ., Abirami, M. ., Waseem, S. M. ., & Manikantaa, C. . (2023). Forecasting Chronic Kidney Disease Using Ensemble Machine Learning Technique. International Journal on Recent and Innovation Trends in Computing and Communication, 11(5s), 336–344. https://doi.org/10.17762/ijritcc.v11i5s.7035
Sai, C. N. V. ., Archana, E. ., Vivek, B. ., Dhanwanth, B. ., & K. S., V. . (2023). Enhancing Hairfall Prediction: A Comparative Analysis of Individual Algorithms and An Ensemble Method. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6s), 499–508. https://doi.org/10.17762/ijritcc.v11i6s.6958
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.