Age of Information in UAV-Assisted Real-Time IoT Systems with Obstacle Avoidance

This work investigates an unmanned aerial vehicle (UAV)-assisted real-time Internet of Things (IoT) system in a complex urban environment, where the UAV senses the status packets of multiple IoT devices and sends the sensory packets to the BS while navigating around obstacles. By using the age of information (AoI) to evaluate the timeliness of the sensory data, we devise a stochastic optimization problem to minimize the average energy cost under the constraint on the average AoI at the BS by jointly optimizing sensing, transmission, and 3D trajectory for the UAV. Then, we convert this complex stochastic problem into a per-slot deterministic one and develop an efficient Lyapunov optimization-based online algorithm to solve it. Finally, through simulations, we verify the efficiency of our proposed algorithm in reducing the energy cost and AoI.