Article’s

Road accidents are a major global concern, particularly for two-wheeler riders who face a high risk of injuries and fatalities due to factors such as drowsiness, alcohol consumption, and improper helmet usage. Existing safety systems mainly focus on post-accident reporting and lack real-time preventive capabilities. This paper presents an IoT-based intelligent helmet system designed to enhance rider safety through continuous monitoring and automated control. The system is built around the ESP32 microcontroller, which integrates multiple sensors embedded within the helmet, including an eye blink sensor for detecting drowsiness, an infrared sensor to ensure proper helmet usage, and an MQ-3 alcohol sensor to identify alcohol levels in the rider’s breath. An ADXL345 accelerometer is also used to detect sudden impacts or abnormal tilts that may indicate accidents. The system ensures that the vehicle operates only under safe conditions by reducing speed during drowsiness and disabling ignition if alcohol is detected or the helmet is not properly worn. In case of an accident, the system sends the rider’s real-time GPS location to emergency contacts via a Telegram bot, improving response time and road safety.