Reactive Deployment of Autonomous Drones for Livestock Monitoring Based on Density-based Clustering *

摘要: Previous research has established that drones could be an efficient tool for farming. In this paper, we study the problem of livestock tracking and monitoring using a group drones. The main objective is to deploy limited number track monitor maximum livestock, such as cattle sheep, in vast pasture while minimizing average drone-animal distance. We assume targeted have been fitted with GPS collars, mobility each animal cannot neglected. first introduce procedure performing sweep coverage by By deploying accomplish entire pasture, initial locations all animals can acquired. Then applied density-based clustering algorithm DBSCAN find deployment places centroids clusters. Furthermore, based on updated animals' locations, follow movement demonstrate our solution always yield lower distance higher covered animals, compared standard K-Means algorithm.