An IoT-Based Automatic Vehicle Accident Detection and Visual Situation Reporting System - Shehzad Aslam; Shahid Islam; Natasha Nigar; Sunday Adeola Ajagbe; Matthew O. Adigun (Journal of Advanced Transportation)
Road accidents are a major cause of injuries and deaths worldwide. Many accident victims lose their lives because of the late arrival of the emergency response team (ERT) at the accident site. Moreover, the ERT often lacks crucial visual information about the victims and the condition of the vehicles involved in the accident, leading to a less effective rescue operation. To address these challenges, a new Internet of Things (IoT)-based system is proposed that uses on-vehicle sensors to detect and report the accident to rescue operator without any human involvement. The sensor data are automatically transmitted to a remote server to create a visual representation of the accident vehicles (which existing systems lack), facilitating the situation-based rescue operation. The system tackles any false reporting issue and also sends alerts to the victim’s family. A mobile application has also been developed for eyewitnesses to manually report the accident. The proposed system is evaluated in a simulated environment using a remote-controlled car. The results show that the system is robust and effective, automatically generating visuals of accident vehicles to facilitate informed rescue operation. The system has the potential to aid the ERT in providing timely first aid and, thus, saving human lives.