International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Road accidents constitute a leading cause of mortality and injury globally, necessitating rapid detection and emergency response mechanisms. This paper presents the design and implementation of an Internet of Things (IoT)-based vehicle accident detection and automated emergency notification system. The proposed system integrates an MPU6050 accelerometer- gyroscope module and NEO-6 GPS receiver with an ESP32 microcontroller to enable real-time impact detection and precise location tracking. Upon detecting abnormal deceleration or collision events, the system activates an audible alert, allowing occupants to confirm their safety via a manual button. If unacknowledged within a predefined timeframe, the system automatically transmits GPS coordinates to a web-based monitoring platform using secure tunneling protocols. The implementation demonstrates reliable accident detection with minimal false positives, real-time location mapping, and automated emergency notification capabilities. Experimental results validate the systems effectiveness in reducing emergency response time while maintaining a compact, power-efficient design suitable for diverse vehicular applications. This holistic approach leverages IoT connectivity to bridge the gap between traditional passive safety features and modern emergency management systems, ultimately contributing to enhanced road safety and reduced fatalities. The system employs sophisticated threshold-based algorithms to distinguish genuine collision events from normal driving scenarios such as sudden braking or speed bumps, achieving a true positive detection rate of 94.7 percent while maintaining a false positive rate below 2.3 percent.

Power management is optimized through dual TP4056 charging modules managing parallel connected 3.7V lithium on batteries, enabling over 12 hours of continuous operation. The embedded firmware, developed using ESP-IDF framework, implements multi-threaded processing for concurrent sensor data acquisition, collision analysis, and wireless communication tasks. The web-based visualization platform utilizes Leaflet.js mapping library to provide dynamic, real-time tracking of vehicle location with sub-second update latency. Ngrok tunneling facilitates secure embedded-to-web communication, allowing the ESP32 to transmit incident data without requiring static IP configuration or complex network setup. System validation through controlled laboratory experiments and field testing confirms detection latency of less than 180 milliseconds from impact to alert activation, and end-to-end notification delivery within 600 milliseconds. The modular architecture supports easy integration with existing vehicles as a retrofit solution, requiring minimal installation effort and no modifications to factory-installed systems. This research contributes to intelligent transportation systems by demonstrating a scalable, cost-effective approach to vehicular safety that operates independently of external infrastructure. The proposed solution addresses critical limitations in current accident response mechanisms, potentially reducing emergency response time by up to 40

Keywords: IoT, accident detection, ESP32, MPU6050, GPS tracking, emergency notification, embedded systems, real-time monitoring

Downloads: | DOI: 10.17148/IJARCCE.2026.15109