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Review Papers | Computer Technology | Volume 15 Issue 2, February 2026 | Pages: 1518 - 1523 | India
IoT based Helmet Detection System
Abstract: Motorcycle safety has become a pressing concern due to the alarming rise in accidents involving riders not wearing helmets. This review paper explores the developments in two-wheeler helmet detection systems, looking at different approaches and their efficacy. Research utilizing methods such as genetic algorithms, ALPR, and YOLO-based object detection for hyperparameter optimization is examined. When paired with genetic algorithms, the YOLOv5 model shows promise in enhanced accuracy and real-time detection capabilities. Still, there are problems with scalability, unbalanced data, and real-time implementation. These issues should be the focus of future studies in order to improve motorcycle safety and lower helmet non-compliance.
Keywords: YOLO (You only Look Once), ALPR (Automatic License Plate Recognition), CVPRW (Computer Vision and Pattern Recognition Workshops), Two-wheeler, Detection
How to Cite?: Seema Singh, "IoT based Helmet Detection System", Volume 15 Issue 2, February 2026, International Journal of Science and Research (IJSR), Pages: 1518-1523, https://www.ijsr.net/getabstract.php?paperid=SR26225145628, DOI: https://dx.doi.org/10.21275/SR26225145628