Path Planning Algorithm for UAV Based Water Quality Monitoring

This study is about the development and application of Unmanned Aerial Vehicles (UA Vs) efficient water quality monitoring in aquaculture. The primary objective is to enhance the monitoring process with the help of Unmanned Aerial Vehicle Water Quality Monitoring System (UAVWQMS), which is specifically designed to collect critical water quality data from aquaculture ponds. The UAVWQMS aims to reduce the labor costs and to help in continuous monitoring, essential for optimizing fish growth and harvest. To achieve accurate and efficient data collection, the UAVWQMS Path Planning Algorithm (UPP), was developed and tested. A dataset was created to show how the sampling points are distributed throughout the ponds UPP was compared against Google Linear Optimization Package (GLOP), Greedy Traveling Salesman Problem Algorithm (GTSP) and a Graph Attention Model (AM). UPP, on the other hand, performed better than all the other algorithms in solution quality and runtime across every size of pond designed.