Design Autonomous Drone Control For Monitoring Tea Plantation Using Dynamic Programming and Kruskal Algorithm

Abstract

Abstract

Indonesia is a country with the largest tea producers in the world, with a very large area needed tools to be able to help monitor the area of tea plantations as a whole. Unmanned Aerial Vehicle (UAV) wash chosen as a solution for the monitoring proses. Optimum flight path calculation is needed in order to produce good quality images, and also it influence to power consumption. The algorithm proposed in this study is Dynamic Programming and Kruskal Algorithm. Implementing these two network algorithms is expected to find the optimal path in aerial photography. The experimental results showed that the algorithm produced the optimum path , and more efficient power consumption than conventional lines. Image data obtained during tea plantation monitoring produced high-quality images, with the accuracy of each map above 90% and the assumption of errors below 5%. Keywords—Unmanned Aerial Vehicle UAV, Monitoring, Dynamic Programming, Kruskal, Mapping.