Prevent Road Accident using Machine to Machine (M2M) Learning

Abstract

The number of road casualties is steadily rising, while the age of driverless vehicles on the road is rapidly coming. Machine-to-machine (M2M) communication and the use of Big Data created by M2M communication have enormous promise for improving road safety. A training dataset-less Deep Learning strategy that uses only a safety model and optimizes it sequentially through M2M learning over time can prevent a lack of suitable Knowledge Base while also improving the capacity to handle unpredictable scenarios. The article outlines an M2M learning model based on in-vehicle sensors that can be used to reduce traffic accidents.