Smart Helmet for Two Wheeler

Abstract

Road safety for two-wheeler riders has become a critical concern due to the increasing number of accidents caused by helmet non-compliance, alcohol-impaired driving, rider fatigue, and delayed emergency response. This paper presents a Smart Helmet Safety System that integrates multiple sensors and Internet of Things (IoT) technology to enhance rider safety through automated monitoring, accident detection, and real-time emergency communication. The proposed system is designed to enforce helmet usage, prevent vehicle operation under unsafe conditions, continuously monitor rider status, and provide immediate assistance during emergencies.

The system is built around a Raspberry Pi Pico W microcontroller, which acts as the central processing unit and interfaces with an Infrared (IR) sensor, MQ-3 alcohol sensor, MPU-6050 accelerometer, SW-420 vibration sensor, heartbeat sensor, NEO-6M GPS module, and SIM800L GSM module. During operation, the IR sensor verifies whether the rider is wearing the helmet properly. If the helmet is not detected, vehicle ignition remains disabled. Once helmet authentication is successful, the MQ-3 sensor analyzes the rider’s breath for alcohol content. If alcohol concentration exceeds a predefined threshold, the ignition system is blocked to prevent unsafe riding.

After successful authentication, the system continuously monitors rider movement and health conditions. The MPU-6050 accelerometer and SW-420 vibration sensor analyze acceleration and impact patterns to identify accident events, while the heartbeat sensor tracks the rider’s physiological condition in real time. Upon detecting a severe impact or abnormal motion indicative of an accident, the controller immediately activates the GPS module to obtain the rider’s live location coordinates. These coordinates are then transmitted through the GSM module as an emergency SMS alert to pre-registered contacts and emergency responders. Simultaneously, a 16×2 LCD display provides real-time status information such as helmet detection, alcohol status, heartbeat monitoring, vehicle readiness, and accident alerts.
Experimental testing demonstrated reliable performance in helmet detection, alcohol sensing, accident identification, and emergency communication. The proposed system is compact, cost-effective, energy-efficient, and suitable for practical deployment. By combining embedded systems, sensor fusion, and IoT-based communication technologies, the Smart Helmet Safety System enables faster emergency response, promotes responsible riding behavior, and contributes to the development of intelligent transportation and road safety solutions.

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