UAVs path planning architecture for effective medical emergency response in future networks

With the advancements of the Unmanned Aerial Vehicles (UAV) technology for use in different environments, it can be easily substituted for traditional transportation in event of emergencies. In the medical domain, UAV can play a vital role in the fast and efficient delivery of first aid and medical supplies. In the current study, safe and smooth UAV navigation from the initial position to the medical emergency location was achieved with optimal path planning through a proposed algorithm. On the notification of patient about his health condition using GSM band, doctor drone was sent from the nearest hospital facility. To avoid traffic congestion the doctor drone provides medical assistance with minimum computational time and transportation cost. The vehicle routing was carried out through proposed algorithms i.e., capacitated Vehicle Routing Problem (CVRP), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Genetic Algorithm (GA). The comparison between the algorithms was carried out at different vehicle capacities and numbers. The CVRP was found to outperform other algorithms with a runtime of 0.06 sec and cost of 419 at vehicle capacity 10, which is 50% less having the same number of the vehicles but increasing the capacities to 20. The results indicate that the effective path planning method could be applied to provide medical aid in real-time with efficacy.