Witness System of Vehicle Accidents Based on the Internet of Things

Road traffic accidents become more of a problem as there are more automobiles on the road. Accidents are impossible to completely prevent, but there are techniques to lessen their impact and manage their aftereffects to limit harm. One of the biggest issues is exchanging car accident alerts with other vehicles on the road. A number of technologies are in use to prevent traffic collisions. It is planned to develop a system for detecting collisions between vehicles based on the vehicular ad-hoc network (VANET) concept. Additionally, it immediately alerts the neighborhood hospital and social media about the incident. The proposed technique uses a warning system supported by collision potential and is implemented on OpenStreetMaps and at locations of interest. We assess our system’s performance using the simulation of urban mobility (SUMO) software tool, which employs OpenStreetMap data to simulate vehicle-to-vehicle communication and accident detection. SUMO generates traffic on the road for our evaluation. To gauge the effectiveness of our system, we measure the size of messages exchanged within the VANET and demonstrate its feasibility. Furthermore, we compare our results with previously published works in the same field of study for reference.