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Research & Devlopment


Our machine learning helmet project aims to use computer vision and machine learning techniques to determine whether a person riding a bike is wearing a helmet or not. By analyzing video footage from cameras mounted nearby, the system can detect the presence of a helmet on the rider's head and make a determination about whether they are wearing one. The system is trained on a dataset of images and videos of people riding bikes, both with and without helmets, to learn the distinctive features of helmets and the absence of them.

The goal of this project is to promote safety and encourage the use of helmets while riding bikes. This technology can be used in a variety of settings such as traffic monitoring, bike-sharing systems, and personal safety applications. With the help of this technology, it can reduce the number of accidents and promote safety. Furthermore, the system can also be integrated with other technologies such as GPS, to track the location of helmet usage and areas where helmet usage is low, which can help authorities to create targeted awareness campaigns.