Computer vision for unmanned aerial vehicles in agriculture: applications, challenges, and opportunities

Abstract

Unmanned Aerial Vehicles (UAVs), commonly called drones, have gained significant attention in agriculture due to their potential to revolutionize traditional farming practices. This paper explores the integration of computer vision techniques with UAV technology to enhance agricultural processes. The fusion of these two domains has the potential to provide farmers and agronomists with valuable insights for optimized decision-making. The primary focus of this research is to showcase the various applications of computer vision for UAVs in agriculture. The paper begins by presenting an overview of the challenges faced by modern agriculture, such as resource optimization, crop monitoring, disease detection, and yield prediction. It then delves into the technological advancements in UAVs and their suitability for addressing these challenges.