Two-Wheeler Helmet Detection System Using Object Recognition

A "helmet" is a protective cover worn while riding a two-wheeler, which is a safety measure for the rider and for the pillion. However, due to the negligence of people, helmets are not worn by most riders. According to the latest report of the National Crime Records Bureau (NCRB), as many as 1,55,622 people lost their lives due to road accidents in 2021, out of which around 70,000 people lost their lives in two-wheeler accidents.Proposed study is the perfect solution for this problem. We have made a smart machine learning-based system integrated in a two-wheeler that makes wearing a helmet mandatory as it monitors every second of the ride. The moment the rider removes the helmet, the vehicle is supposed to turn off and make the rider wear a helmet. There are some existing studies that cover different parts of helmet detection techniques but almost each of the studies are usable and limited to that helmet however this study focuses on how the system can be integrated into the two-wheeler itself to generalize the detection of helmets. The perfect implementation of this study is used to reduce accident rate.