Acceleration based black-box accident detection and warning system

Autor: Beladgham Mohammed, Dahmane Oussama, Kadri Boufeldja, Kadri Ibrahim
Rok vydání: 2021
Předmět:
Zdroj: Indonesian Journal of Electrical Engineering and Computer Science. 23:1838
ISSN: 2502-4760
2502-4752
DOI: 10.11591/ijeecs.v23.i3.pp1838-1846
Popis: The purpose of this research paper is to develop a black-box accident warning system that utilizes both global system for mobile communication (GSM) and global positioning system (GPS) technologies to identify and deliver a minimum set of data that includes critical data about the accident gathered via various sensors such as the type of accidents, geographic coordinates, time, and velocities (civil protection, hospitals, and police). Additionally, the system makes use of data collected via the OBD-II standard to provide a reliable method for detecting accidents based on vehicle acceleration. Clearly, this system appeared to be the best option for countries with significantly older average vehicle ages. The system was installed in a real vehicle in order to evaluate the collision detection algorithm through the use of abrupt medium-speed braking. The system also includes an image processing system for age and gender prediction based on the Rapsberry Pi and intel neural compute stick 2 (NCS2) that will be published in future work.
Databáze: OpenAIRE