Enhancing Motorcycle Safety and Security Using Biometric Verification and Helmet Detection Through AI and ML Integration

The automotive industry, like many others, has had to adapt to newer technologies, including biometrics, AI, and Machine Learning (ML) over the years. In this chapter, a sophisticated technique directed on improving vehicle security through biometric verification and helmet detection is described using TensorFlow and a custom-built Arduino-based system. A notable factor contributing to fatalities in these motorcycle accidents is lack of helmet use among riders. Ensuring that riders put on helmets before they get on their motorcycles is done through monitoring with CCTV cameras or by manually supervising traffic intersections by police. These methods however entail high levels of manual labor. Through these approaches, some motorcycle riders without helmets have been tracked, and their license plates captured via CCTV cameras. In this methodology, the algorithm first identifies moving objects as motorcycles or non-motorcycles. Moreover, the system assesses whether classed helmeted riders are wearing helmets. If not, the device applies an OCR technique to capture the license plate