Advanced Smart Helmet System for Rider Safety using IoT-Based Alcohol Detection and Accident Detection
Abstract
The large number of deaths occur due to alcohol consumption by riders and delayed emergency response. Riders under the influence of alcohol experience a reduced concentration, slow reaction time, and poor decision making ability, increasing the probability of crashes. Additionally, accident victims are often unable to communicate their location due to unconsciousness or severe injuries. This article proposes an Advanced Smart Helmet System for Rider Safety using Internet of Things (IoT) technology. The system integrates an MQ-3 alcohol sensor to detect alcohol through the rider’s breath and measure alcohol percentage in real time. If the alcohol level exceeds a predefined threshold, the system sends an SMS alert containing alcohol percentage details to a registered mobile number. The system also incorporates an accelerometer based crash detection mechanism. When a crash is detected, an emergency buzzer is immediately activated to alert nearby people and draw attention to the accident location. Simultaneously, a GPS module retrieves the real time location and a GSM module sends SMS alerts and initiates emergency calls. If the rider consumed alcohol and an accident occurred, the system sends alerts including alcohol percentage and exact GPS location. Our proposed system enhances rider safety, prevents drunk driving, reduces emergency response time, and provides a reliable and cost effective solution for real world implementation.