Path Plan Optimisation for UAV Assisted Data Collection in Large Areas

Integrated systems that combine wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) are emerging as state-of-the-art solutions for large-scale remote sensing. In order to achieve an energy-efficient path plan, this paper highlights the importance of considering parameters from sensor nodes beyond just UAV travel distance. For example, residual battery and buffer size of sensor nodes are equally important in enhancing data collection, reducing energy consumption, minimising data loss and extending the lifetime of WSNs. The paper presents an extract from a proposed algorithm that demonstrates how to generate UAV path plans based on the dynamic resources of the WSN. This algorithm harnesses parallelism by dividing WSN into clusters. The path plans only include a subset of sensors that interact with the UAV, serving as waypoints in the traversal process. The cost of each path plan is assessed by our proposed system model, which considers the energy-consuming actions the sensors can perform. Graph theory is used to map the problem of UAV path plan generation to the Travelling Salesman Problem (TSP).