Piezoelectric-Based Smart Helmet Accident Detection System
Abstract
Motorcycle accidents remain a leading cause of preventable fatalities globally, particularly in developing nations where two-wheelers constitute the primary mode of transportation. The critical time window immediately following an accident—commonly referred to as the “golden hour”—plays a decisive role in determining survival outcomes for injured riders. Unfortunately, many accident victims remain undiscovered for extended periods due to the absence of automated detection and notification systems, leading to preventable deaths. This paper presents the design, development, and implementation of a Piezoelectric-Based Smart Helmet Accident Detection System that addresses the critical need for rapid accident detection and emergency response. The proposed system integrates a piezoelectric impact sensor with an MPU6050 accelerometer-gyroscope unit to achieve accurate and reliable detection of collision events through a dual-sensor fusion approach. A force-sensitive resistor (FSR)-based helmet-wear detection mechanism ensures the system activates only when the rider is wearing the helmet, thereby minimizing false detections and conserving battery life. Upon detecting a potential accident event exceeding predefined threshold values, the system initiates a 10-second warning phase comprising audible buzzer alerts and vibration feedback, allowing the rider to cancel the trigger in case of accidental activation. If the warning is not cancelled, the system confirms the accident, acquires precise geographical coordinates using the NEO-6M GPS module, and transmits an emergency SMS containing location details and a Google Maps link to predefined emergency contacts through the SIM800L GSM module. The developed prototype was extensively tested under various simulated accident scenarios, demonstrating reliable impact detection across a force range of 4.9N to 64.8N, successful GPS location acquisition with accuracy within 2.5 meters, and consistent GSM-based emergency alert transmission. The system achieved a detection accuracy of 95% with minimal false alarm rates, validating its effectiveness as a practical, cost-effective safety solution for motorcycle riders in developing countries.