Smart Helmet System: Enhancing Rider Safety through IoT and Sensor Integration

Abstract

Road safety is a crucial concern and reckless driving behaviors such as not wearing a helmet, single-hand driving, and driving under the influence of alcohol contribute significantly to road accidents. Every year, thousands of lives are lost due to preventable mishaps caused by negligence. This study, “Smart Helmet System: Enhancing Rider Safety through IoT and Sensor Integration,” proposes a smart and automated system to ensure safe riding by integrating IoT and sensor-based monitoring. The primary goal is to enforce safety measures that can reduce accidents and save lives. The system uses an ESP32 microcontroller to control various components, including an IR sensor for helmet detection, two additional IR sensors for single-hand driving detection, an MQ3 alcohol sensor, and an ADXL345 accelerometer for accident detection. These components work together to monitor rider behavior in real-time. Initially, the system verifies whether the rider is wearing a helmet. If the helmet is not detected, the vehicle will not start, preventing unsafe riding practices. Once the helmet is detected, the system checks for alcohol in the rider’s breath. Additionally, in the event of an accident, the system sends an alert message via Telegram.