AI-IoT Based Smart Helmet with Frequency Based Vehicle Control

This paper presents an AI - IoT based smart helmet system with machine learning enhancements aimed at improving motorbike safety. The helmet integrates the LeNet Convolutional Neural Network (CNN) to monitor rider fatigue by analyzing facial features in real-time, issuing alerts when signs of drowsiness, such as frequent blinking, are detected. The system also includes a vibration sensor to detect accidents and initiate emergency protocols, as well as a blind spot detection system using ultrasonic sensors to monitor a 180-degree area for potential collisions. Communication between the helmet and vehicle is facilitated by Zigbee technology, ensuring reliable real-time data exchange. This integrated solution addresses critical safety issues such as driver fatigue, accident detection, and blind spot awareness, offering a comprehensive approach to enhance rider safety.