AUTOMATIC VEHICLE ACCIDENT DETECTION AND ENHANCED RESCUE MANAGEMENT SYSTEM

Paper ID: EIJTEM_2025_12_4_265-272

Author's Name: Chittula Ruchitha, Mr. M. Veeresh Kumar

Volume: 12

Issue: 4

Year: 2025

Page No: 265-272

Abstract:

Vehicle accidents, especially those caused by over speeding, remain one of the most significant contributors to road fatalities globally, with delayed emergency response exacerbating the loss of life. To mitigate this issue, this project presents an intelligent, IoT-based accident detection and emergency alert system designed to minimize response time through real-time data transmission. The system employs an Arduino Nano as the central processing unit, interfaced with a high-sensitivity impact sensor to detect collision severity and distinguish minor incidents from major accidents requiring urgent intervention. Integrated with a GPS module, the system pinpoints the exact geographical coordinates of the accident site, ensuring precise localization, while a Wi-Fi-enabled ESP8266 module facilitates seamless communication by transmitting critical data—including impact force, time of accident, and location—to the ThingSpeak IoT cloud platform, which then triggers instant notifications to hospitals, police, and nearby emergency services. Additionally, the system incorporates an infrared (IR) sensor to detect the arrival of ambulances or rescue teams, providing verification that help has reached the scene. To further optimize emergency response, the solution includes a navigation assistance feature that relays the fastest route to the accident site, reducing delays caused by traffic or unclear directions. By combining impact detection, real-time GPS tracking, cloud- based alerts, and ambulance verification, this system ensures a rapid, automated, and reliable emergency response mechanism that can be deployed in any vehicle, offering a cost-effective and scalable solution to enhance road safety and save lives through timely medical assistance and efficient crisis management.

Keywords: Thingspeak, Internet of Things, Accidents, Rescue Management, Vehicles.

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