Smart navigation system for emergency vehicles (SNSEV): utilizing fog and cloud computing technology for real-time traffic management

Smart navigation system for emergency vehicles (SNSEV): utilizing fog and cloud computing technology for real-time traffic management

연구 분야: Networking

학회: Neural Computing and Applications

The navigation of emergency vehicles is a critical component of effective emergency response in a smart city. To improve response time, it is necessary to have a navigation system that can predict the shortest path to the destination and adjust in real time to current traffic conditions. This paper proposes a smart navigation system for emergency vehicles (SNSEV), a real-time navigation algorithm for emergency vehicles in smart cities that utilize fog and cloud computing technology for real-time traffic management. IoT devices such as sensors and cameras collect real-time data on traffic conditions and roadblocks, which is then processed and analyzed using fog computing technology. Cloud computing technology is then utilized to provide emergency vehicles with real-time navigation and priority control, reducing response time and ensuring that they reach their destination as quickly as possible. This paper presents the proposed SNSEV algorithm and the system architecture and discusses its potential benefits and challenges. The results show that SNSEV can significantly improve the efficiency and effectiveness of emergency response in a smart city, leading to improved public safety and well-being. According to the findings of several experiments, SNSEV works better than its competitors because it allows for the highest possible throughput, the lowest possible bandwidth usage, and the shortest possible delay.