Combination of Deep Learning and Graph Theory to Facilitate Traffic for Emergency Vehicles

In this paper, we present an innovative approach to facilitating the movement of emergency vehicles on urban roads. Using advanced artificial intelligence techniques and the Internet of Things, we have developed a system that detects emergency vehicles in real time and modifies traffic lights accordingly. Our methodology combines the use of strategically placed cameras with a deep learning model to identify emergency vehicles in dense traffic conditions. In addition, we have applied graph theory to model urban intersections and optimize the routes for emergency vehicles. Initial tests show a significant improvement in traffic flow for emergency vehicles, reducing their response time and potentially saving lives. This study offers a promising first step towards the realisation of an intelligent, responsive urban road network focused on society's priorities.