Machine learning-based intelligent accident detection and notification system in IoT network

The number of traffic accidents is increasing every day as the number of cars increases. It is said that 3 million people die each year worldwide and 55 million people are injured. Lack of emergency medical care at the scene of an accident or long post-accident response times are the leading causes of death. Cognitive aids can be used to detect incidents and alert traffic watchers or rescue teams, reducing waiting times for lifesaving operations. Transportation systems have received considerable attention from industry and academia due to the growing demand for urban exploration and have been seen as a way to improve road safety in these areas. In this study, an IoT and machine learning-based intelligent rescue team accident detection model was presented. An IoT module has been developed that can recognize an accident, collect all accident data such as position, pressure, force and speed, and transmit all relevant data to the cloud. Machine learning models are used in the cloud to validate IoT module data and activate emergency modules after a failure is detected.