Vehicle Accident Detection, Prevention and Reporting System

Abstract: The Vehicle Accident Detection, Prevention, and Reporting System integrates alcohol sensing, drowsiness monitoring, accident detection, and alert mechanisms into a single low-cost platform. The alcohol sensor ensures that vehicle operation is prevented when the driver is intoxicated, while the eye-blink sensor continuously monitors drowsiness levels to reduce fatigue-related risks. The ADXL accelerometer reliably detects sudden impact forces, and the GPS enables immediate transmission of real-time accident location data through alerts with Google Maps links. The inclusion of the L298N motor driver ensures that preventive actions, such as restricting ignition, are enforced effectively. By combining prevention, detection, and emergency communication, the system functions as a comprehensive safety framework rather than a standalone monitoring tool. It addresses both pre-accident conditions and post-accident assistance, thereby reducing the chances of collisions and minimizing delays in emergency response. The use of Arduino as the central controller makes the system cost-effective, scalable, and adaptable to a wide range of vehicles, which is particularly beneficial in developing countries where road accidents remain a critical challenge. In its future development, the system can be expanded with cloud-based monitoring platforms, artificial intelligence for predictive accident analysis, and adaptive thresholding to improve accuracy on rough terrains. Large-scale implementation across vehicular networks will also allow integration with smart city infrastructure, enabling traffic authorities and healthcare providers to receive automated accident notifications. With these advancements, the proposed system holds strong potential to significantly improve road safety, reduce casualties, and contribute to the development of intelligent transportation systems..