• Chaitanya Srusti
• Vibhav Deo
• Dr. Rupesh C. Jaiswal

In many nations, motorcycles are a common form of transportation. However, riding a motorcycle comes with a great risk when the correct safety equipment is not used. Therefore, wearing a helmet is highly recommended to promote safety while riding a bike. It is vital to build an autonomous helmet detection system that can identify the offenders on motorcycles in order to eliminate this manual dependency. Many riders choose not to wear helmets while riding two-wheelers or only do so when there are traffic police present. The goal of this study is to create a real-time autonomous system utilizing the YOLO deep learning method. A form of CNN called YOLO is suitable for real-time object detection.

"Helmet Detection Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 10, page no.d10-d17, October-2022, Available :http://www.jetir.org/papers/JETIR2210312.pdf

"Helmet Detection Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 10, page no. ppd10-d17, October-2022, Available at : http://www.jetir.org/papers/JETIR2210312.pdf