Traffic Signal Based on Real Time Helmet Detection Using AI

Ensuring road safety in modern urban environments is paramount, particularly in light of the frequent occurrence of motorcycle accidents leading to severe injuries or fatalities. Despite the convenience of motorcycles as a means of transportation, enforcing helmet regulations remains challenging. In response, authorities have implemented a visual-based system to detect ill-fitted helmets in real-time, leveraging advanced technologies such as the YOLOv5 model and deep learning methodologies. This innovative approach aims to bolster road safety by dynamically adjusting traffic signals based on helmet detection, with the system achieving an impressive precision map of 97% after thorough training. The ultimate objective is significantly reducing motorcycle accidents and creating safer roads for all commuters.