Profit Maximization for UAV Trajectory Planning in Time-Constrained Data Collection

In this work, we use unmanned aerial vehicles (UAVs) to collect data from IoT devices on the ground. Each device has an amount of data that can be sent to the UAV during a specific time window. Our objective is to maximize the total profit that the UAV can collect the data from the IoT devices. Since the problem is NP-hard, we propose a heuristic algorithm in three stages to solve the problem. We solve the traveling-salesman problem (TSP) in the first stage to find the UAV's flying trajectory. In the second stage, we propose an algorithm to change the visiting order or remove IoT devices from the flying trajectory if we cannot satisfy their time constraints. In the third stage, we improve the UAV's flying distance established in the second stage. The simulation results show that the proposed algorithms outperform some baselines in terms of total profit and execution time.