Abstract
We don’t prioritize safety. An estimated 44,660 people died from not wearing helmets. The WHO claims that correct helmet use can reduce the risk of fatal injuries by 42% and head injuries by 69%. Our idea is to detect riders without helmets in order to overcome this problem. The purpose of this paper is to propose a framework for detecting motorcycle riders without helmets in real time. This methodology identifies motorcycle rider using the camera, which was placed in the motorcycle. It checks whether the motorcycle rider was wearing a safety helmet or not using image classification techniques. If the rider is not wearing the helmet, then the internal circuits of the motorcycle will not be closed and the rider will not be able to start the motorcycle.
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Chythanya, K.R., Reddy, K.S., Rudroju, A., Racharla, S.J., Barigela, A., Katha, A. (2023). Deep Learning and IoT-Based Driver Helmet Detection and Bike Ignition. In: Kumar, A., Ghinea, G., Merugu, S. (eds) Proceedings of the 2nd International Conference on Cognitive and Intelligent Computing. ICCIC 2022. Cognitive Science and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-99-2746-3_2
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DOI: https://doi.org/10.1007/978-981-99-2746-3_2
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