Vehicle Accident Detection & Alert System using IoT and Artificial Intelligence
Akash Bhakat, Neetigya Chahar, V Vijayasherly
Abstract
As nations around the globe are becoming economically stronger and thus leading to more financially capable citizens, more people now own their personal vehicles. Although the road infrastructure has improved, it is still unable to cope up with the increasing population. With that, more and more road accidents are increasing. According to the Indian government, in 2019 about 151,000 people died in road accidents. In most cases, people die because they were not immediately provided medical assistance because there is no definite system that can do so. As technologies like IoT have advanced, there is now a need to develop a system that can immediately update the responsible authorities with all the relevant data on the occurrence of a road accident. This paper analyses and proposes a way IoT can be used in this regard in a way that can save thousands of lives. Along with IoT, we have incorporated machine learning methods and image processing to accurately identify a road accident. The sensors like accelerometer, gyroscope, camera, etc. provide data to a microprocessor which matches the sensor data with the machine learning model and determines if there is an accident or not and if it is, the device sends the related metrics to the server through the internet. Here, instead of using a central server topology, we have incorporated Edge computing which enables us to process requests faster locally. This further optimizes response time. Once the data is reached to an edge server, it determines the nearest hospitals, police stations by looking at the GPS data and sends a notification to them and to the registered phone number by the user. This way, it becomes a life-saving technology.