Open Access

ARTICLE

AI-Based Helmet Violation Detection for Traffic Management System

by Yahia Said^1,*, Yahya Alassaf², Refka Ghodhbani³, Yazan Ahmad Alsariera⁴, Taoufik Saidani³, Olfa Ben Rhaiem⁴, Mohamad Khaled Makhdoum¹, Manel Hleili⁵

1 Department of Electrical Engineering, College of Engineering, Northern Border University, Arar, 91431, Saudi Arabia
2 Department of Civil Engineering, College of Engineering, Northern Border University, Arar, 91431, Saudi Arabia
3 Faculty of Computing and Information Technology, Northern Border University, Rafha, 91911, Saudi Arabia
4 College of Science, Northern Border University, Arar, 91431, Saudi Arabia
5 Department of Mathematics, Faculty of Sciences of Tabuk, University of Tabuk, Tabuk, 71491, Saudi Arabia

* Corresponding Author: Yahia Said. Email:

(This article belongs to the Special Issue: Artificial Intelligence Emerging Trends and Sustainable Applications in Image Processing and Computer Vision)

Computer Modeling in Engineering & Sciences 2024, 141(1), 733-749. https://doi.org/10.32604/cmes.2024.052369

Received 31 March 2024; Accepted 28 June 2024; Issue published 20 August 2024

Abstract

Enhancing road safety globally is imperative, especially given the significant portion of traffic-related fatalities attributed to motorcycle accidents resulting from non-compliance with helmet regulations. Acknowledging the critical role of helmets in rider protection, this paper presents an innovative approach to helmet violation detection using deep learning methodologies. The primary innovation involves the adaptation of the PerspectiveNet architecture, transitioning from the original Res2Net to the more efficient EfficientNet v2 backbone, aimed at bolstering detection capabilities. Through rigorous optimization techniques and extensive experimentation utilizing the India driving dataset (IDD) for training and validation, the system demonstrates exceptional performance, achieving an impressive detection accuracy of 95.2%, surpassing existing benchmarks. Furthermore, the optimized PerspectiveNet model showcases reduced computational complexity, marking a significant stride in real-time helmet violation detection for enhanced traffic management and road safety measures.

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Keywords

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