REAL-TIME VEHICLE CRASH DETECTION AND AUTO ALERT SYSTEM USING SENSORS AND GPS

Abstract

Road accidents remain a significant issue of concern in the world, as they normally cause serious injuries and loss of life because of late detection and reaction. In this paper, a Real-Time Vehicle Crash Detection and Auto Alert System is described that makes use of multi-sensors data and smart communication to achieve the delivery of emergency help as timely as possible. This system uses a gyroscope, accelerator, and GPS sensor to track the dynamics of the vehicle and record impacts of the collision, and the mobile based interface delivers real time messages via SMS, cloud server or satellite connection. To prevent any abnormal braking or an unexpected collision, the system activates automatically to identify the severity of the accident and forward the whereabouts of the vehicle to emergency contacts and authorities that have been pre-registered. The machine learning algorithm is implemented to reduce false alerts and enhance detection accuracy depending on the road conditions. The suggested solution is a framework on intelligent accident detection and quick emergency response with scalable and cost-effective and network-independent framework, that will improve overall road safety and reliability both in urban and rural regions.