A Survey of IoT-Based Smart Helmet Technologies for Motorcycle Rider’s Safety

Riding a motorcycle presents serious safety concerns because of its lack of structural protection and high accident rate, with alcohol usage and inappropriate helmet use being two of the main contributing causes. In order to improve rider safety, especially for delivery riders, this study provides the design and assessment of a smart helmet prototype based on the Internet of Things. Using an ESP32 microcontroller with MQTT communication, the helmet incorporates sensors such as a GPS, gyroscope, accelerometer, alcohol sensor, and rearview camera that transmit data in real time. 90% accurate crash detection, 88% accurate alcohol monitoring, and automated emergency warnings with GPS location tracking are some of the key features. Real-time management notifications and logistics tracking are made easier by a mobile application created with Firebase and Bubble.io. Positive feedback from delivery riders confirms that the prototype's ergonomic sensor placement and lightweight materials guarantee rider comfort. This research provides a scalable strategy for lowering accident-related mortality by tackling important safety issues and advancing IoT applications in personal safety equipment.