MotoWatch: Deep Learning based AI Assisted Helmet Wearing Detection System

MotoWatch system provides an effective and intelligent solution to enforce helmet usage, enhance road safety, and reduce accident-related risks for motorcyclists. In the proposed framework to improve motorcycle rider safety Deep Learning (DL) and Internet of Things (IoT) technologies are incorporated for effective detection of helmet wearing under different scenarios. The proposed system employs the deep learning-based YOLO v8 object detection model to detect helmet usage in real time. An IoT-enabled ignition control mechanism is integrated with DL model to prevent the vehicle from starting unless a proper helmet wearing by the rider is detected. The system automatically blocks the flow of an electrical current from the battery to the ignition system until helmet compliance is verified, ensuring the vehicle operates only under safe helmet wearing conditions. Custom dataset is utilized for helmet detection task whereby proposed model achieving high performance of 99.5% mean average precision (mAP), with 99.4% precision and 100% recall.