Automated Helmet Detection System Using RT-DETR for Real-Time Monitoring of Motorcyclist Safety

This paper presents a real-time helmet detection system designed to enhance safety in workplaces and traffic environments. Utilizing deep learning models like YOLO (You Only Look Once), the system detects whether individuals are wearing helmets in live video feeds or images. Trained on a diverse dataset, the system achieves high accuracy and efficiency, making it suitable for deployment in safetycritical areas. The paper highlights its potential applications, challenges, and future improvements, such as IoT integration and edge computing, to further enhance performance and scalability. This work contributes to leveraging AI for safety enforcement and accident prevention.