Journal of Intelligent Systems (Sep 2024)
An efficient node selection algorithm in the context of IoT-based vehicular ad hoc network for emergency service
Abstract
With the recent growth of global populations, main roads in cities have witnessed an evident increase in the number of vehicles. This has led to unprecedented challenges for authorities in managing the traffic of ambulance vehicles to provide medical services in emergency cases. Despite the high technologies associated with medical tracks and advanced traffic management systems, there is still a current delay in ambulances’ attendance in times of emergency to provide patients with vital aid. Therefore, it is indispensable to introduce a new emergency service system that enables the ambulance to reach the patient in the least congested and shortest paths. However, designing an efficient algorithm to plan the best route for an ambulance is still a global goal and a challenge that needs to be solved. This article introduces an Internet of Things emergency services system based on a real-time node rank index (NR-index) algorithm to find the best route for the ambulance to reach the patient and provide the required medical services in emergency cases. The proposed system design copes with the dynamic traffic conditions to guarantee the shortest transport time. For this purpose, a vehicular ad hoc network is employed to collect accurate real-time traffic data. In this article, we suggest two parameters to compromise distance and congestion level. The first is the distance between the patient and the surrounding ambulance vehicles, and the second determines the congestion level to avoid the path with high congestion traffic. The system employs a developed real-time NR-index algorithm to select a suitable ambulance vehicle to respond to emergency cases at a low travel cost with the fastest journey. Finally, our system makes it easier for ambulance vehicles to use the best route and avoid heavy traffic. This allows them to make their way to the patient quickly and increases the chance of saving lives. The simulation results show significant improvements in terms of average travel time, average travel speed, and normalized routing load.
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