HDRT: Helmet Detection System using Convolutional Neural Network in Real Time

Motorcycle accidents have progressively increased in many nations over the years, as riders around the world regularly disregard road safety, resulting in road accidents and casualties. While many countries have made wearing of helmets compulsory, still there need to be special laws to promote safety of vehicle riders. Thus it is critical for motorcyclists to understand the need of wearing helmet to avoid fatal incidents. To enforce wearing of Helmet, in this work, an algorithm is developed using Convolutional Neural Network to enable the detection of helmets in real time. If either of rider is riding without a helmet, the proposed algorithm can accurately track the situation and proclaim a legal violation. The application may be deployed in entrance of offices, marts, schools, and universities, allowing people to enter the premises only if the helmet is detected on the rider. It would almost probably have an impact on the use of helmets, which could save lives.