Machine Vision System of Emergency Vehicle Detection System Using Deep Transfer Learning

Accidents can happen at any time and in any location, so emergency vehicles are essential in any emergency or life-threatening circumstance. However, due to lots of people owning cars, traffic jam is a severe problem in many cities. These traffic jams have an impact on emergency vehicles, particularly ambulances, as well as other vehicles such as fire trucks and police cars. The purpose of this research is to develop an emergency vehicle detection system that will assist law enforcement in mandating traffic when emergency vehicles are on the road. The researcher used deep learning, specifically the YOLov3 technique in developing the detection system wherein it will utilize CNN in implementation. The highest mAP value out of 25 models was obtained by the detection system is 98.78% by model 21.