A Comprehensive IoT-Based Bike Crash Detection and Emergency Response System for Enhanced Road Safety

Motorcycle travel, deemed one of the riskiest modes of transportation, faces a staggering fatality rate, with 212.7 deaths for every million miles travelled. Unlike enclosed vehicles, motorcycles expose riders to their surroundings, heightening the need for proactive safety measures. This paper explores the development and implementation of a Motorcycle Crash Detection and Alert System (MCDAS) utilizing the Multi-axes accelerometer. The system is designed to detect when a motorcycle falls and promptly alert emergency services and contacts via Firebase cloud. The study delves into the challenges posed by two-wheeled vehicle dynamics and outlines a novel collision detection algorithm tailored for motorcycles. This algorithm is validated against experimental evidence, providing a robust foundation for crash detection systems in this unique context. Additionally, the paper introduces a novel method for vehicle detection and tracking, employing thresholding, mathematical morphology treatment, and original labelling to enhance accuracy and reduce artifacts. In the context of road accidents, especially prevalent among two-wheelers, the paper presents a system that combines accelerometer data and a user’s heartbeat sensor to assess the severity of accidents. This timely information triggers alerts to nearby medical centers and contacts through GSM and GPS modules, facilitating immediate medical aid. The Android application associated with the system not only sends text messages to medical centers and friends but also shares the precise accident location, significantly reducing response time. important contributions and heralds a new departure for the vehicle safety paradigm.