Smart Vehicle Accident Detection and Reporting System

Abstract: Road accidents are a leading cause of injuries and fatalities worldwide, often exacerbated by driver drowsiness, delayed medical assistance, and inadequate real-time monitoring. This research presents the design and implementation of a Vehicle Accident Detection, Prevention, and Reporting System using the ESP32 microcontroller as the central processing unit. The system integrates an ADXL335 accelerometer to detect sudden vehicle impacts, an eye blink sensor to monitor driver alertness, and a GPSmodule for real-time location tracking and emergency alert transmission. The methodology involves continuous monitoring of vehicle motion and driver behaviour, automated detection of abnormal conditions, and immediate reporting to designated emergency contacts. Experimental testing demonstrates that the system can reliably identify accidents and drowsiness events, trigger preventive alerts, and send timely notifications with location data, thereby reducing response time in critical situations. The results indicate that the proposed system enhances road safety, minimizes potential accident-related injuries, and provides a practical framework for integrating IoT-based vehicle safety solutions. In conclusion, the ESP32-based approach offers a cost-effective, efficient, and scalable method for real-time accident detection and driver safety monitoring.