Abstract: Road accidents continue to be a major cause of fatalities across the world, largely due to the delay in detecting accidents and the inability to communicate the victim’s location to emergency responders in time. In many critical situations, accident victims are unconscious or physically unable to seek help, which significantly increases the risk of severe injury or death. To overcome this challenge, this paper presents the design and development of an IoT-based Accident Collision Detection and Safety Alert System using an ESP32 microcontroller integrated with GPS and GSM communication modules and multiple safety sensors. The proposed system automatically detects collisions using a limit switch–based impact sensor and immediately stops vehicle movement to prevent further damage. Once an accident is detected, the system sends emergency SMS alerts and initiates call notifications containing real-time GPS location information to predefined emergency contacts, ensuring rapid response. In addition to collision detection, the system includes ultrasonic sensors for obstacle detection, smoke sensors for identifying fire hazards, and a manual SOS push button that allows users to request emergency assistance during medical or critical situations. Distinct audio and visual alerts are generated using a buzzer and LED to indicate different emergency conditions. Furthermore, the ESP32 hosts a Wi-Fi-based web control interface that enables remote vehicle operation and manual override, enhancing system usability and flexibility. Experimental observations confirm reliable accident detection, accurate location tracking, and fast alert delivery, demonstrating that the proposed system is a low-cost, scalable, and effective solution for smart vehicles, autonomous platforms, and intelligent transportation systems, thereby significantly improving road safety and emergency response efficiency.

Keywords: Accident Collision Detection, Internet of Things (IoT), ESP32 Microcontroller, GPS Tracking, GSM Communication, Safety Alert System, Intelligent Transportation System

Downloads: | DOI: 10.17148/IARJSET.2026.13109