Smart real-time accident detection and alert system

Abstract

Road traffic accidents remain a major public safety concern, particularly in regions where emergency response times are slow due to poor infrastructure, communication barriers, or delayed reporting. To address this challenge, this project presents the design and implementation of a Smart Real-Time Accident Detection and Alert System that leverages Internet of Things (IoT) technologies to improve the speed, accuracy, and reliability of accident detection and emergency response. At the core of the system is the ESP32 microcontroller, a highly capable IoT device equipped with built-in Wi-Fi connectivity. It serves as the primary control unit, interfacing with several key sensors to collect critical data. An accelerometer and gyroscope module (such as the MPU6050) is used to detect sudden movements, shocks, or abnormal motion patterns that typically occur during a vehicle collision. Alongside this, a GPS module (such as NEO-6M) is used to capture real-time location data, ensuring that the exact position of an accident is accurately identified. Upon detecting an accident event, the ESP32 processes and packages the data, including impact readings and GPS coordinates. This information is then transmitted wirelessly using the RA01 LoRa module, which operates on low power while supporting long-range communication. LoRa is ideal for remote or rural deployments where traditional internet or mobile networks may be unreliable or unavailable. On the receiving end, a LoRa gateway (receiver node) captures the transmitted data and forwards it to a cloud-connected PHP-MySQL web server. The server stores the incoming data and displays it on a web-based monitoring dashboard. This interface allows relevant authorities to view accidents in real time, analyze incident trends, and make informed decisions for improving road safety. To enhance responsiveness, the system integrates IoT-based API services for alerting emergency contacts. Upon accident detection, SMS alerts are automatically sent via platforms like Collecto (Cissy Technologies), notifying emergency responders and family members with vital details such as the vehicle’s location and time of the accident. This project effectively demonstrates how IoT components—including sensors, microcontrollers, wireless modules, cloud servers, and APIs—can be seamlessly integrated to create a low-cost, efficient, and scalable accident detection and alert system. It is especially suited for areas with limited infrastructure but also urban areas are catered for and offers a practical approach to enhancing emergency communication, reducing response times, and ultimately saving lives. By combining real-time data acquisition, wireless transmission, cloud-based storage, and automated alerts, the system represents a significant advancement in smart transportation and public safety technology.