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DEVELOPMENT OF A PROTOTYPE FOR VEHICLE ACCIDENT AVOIDANCE, DETECTION AND RESCUE ALERTING SYSTEM

The growing demand for automobiles has resulted in an increase in traffic congestion and accidents. Traffic-related deaths in cities are on the rise due to a range of circumstances. By giving timely medical care, these death rates can be considerably lowered. As the ambulance takes longer to reach at the accident scene and hospital, the victim's odds of dying increase. To address this issue, an intelligent automatic ambulance rescue system based on Machine Learning can be utilized to reduce fatalities caused by accidents, either by preventing or detecting and reporting them. If an accident occurs for whatever cause, such as the driver being intoxicated and falling asleep unexpectedly, this embedded system will be able to send a spontaneous message to the police, ambulance, or rescue team to assist the victims. Sensors such as a vibrating sensor, an ultrasonic sensor, and a camera are used to create such a system. All of the devices are connected to the Jetson nano board, which allows for data analysis utilizing machine learning and deep neural networks, as well as parallel processing and edge computing.