AI-based Helmet Detection System for Enhanced Road Safety
Keywords:
Artificial intelligence (AI), Computer vision, Helmet violation detection, Object detection, Violation detectionAbstract
This study presents an innovative approach to motorcycle helmet violation detection by leveraging the power of artificial intelligence (AI) and deep learning techniques. The global increase in traffic accidents, especially those involving motorcycles, underscores the urgent need for effective helmet use enforcement. Traditional methods of monitoring helmet compliance are often labor-intensive and inefficient. This research explores the use of AI for automatic helmet detection, addressing the limitations of manual monitoring and aiming to improve road safety outcomes. The study builds upon previous research in the field, acknowledging the effectiveness of deep learning in various computer vision tasks, including object detection. Drawing on these advancements, the paper focuses on developing an accurate, efficient, and real-time system capable of identifying motorcycle riders who are not wearing helmets. This research holds significant implications for policymakers, traffic enforcement agencies, and road safety advocates, offering a promising solution for automated helmet violation detection and promoting safer roads for all.
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