Flying path optimization in UAV-assisted IoT sensor networks

In this paper, we present an optimal flying path for unmanned aerial vehicle-assisted internet of things sensor networks using a location aware multi-layer information map considering different utility functions based on the sensor density, energy consumption, flight time, and flying risk level. The overall weighted sum of multi-objective utility functions is maximized using the genetic algorithm. The simulation results verify that the optimum solution points can be obtained by adjusting the weights while satisfying the required constraints.