UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management

Nowadays, UAV is widely used in several research and industrial fields. One of the highly beneficial features is that it is able to be utilized to capture aerial images in high-resolution for environmental study or detecting disaster phenomena quickly. This paper presents a multispectral image analysis system for aerial images that captured by multispectral camera, which are mounted on an unmanned autonomous vehicle (UAV) or Drone, and discusses an application of semantic computing system for agricultural health condition monitoring and analysis. In our experiments, we analyze multispectral images to detect healthy and unhealthy conditions of agricultural area and interpret the keyword of plant health conditions for user. We also propose the SPA process for real-time farming area management. As a case study, we conducted an experiment on rye fields in Latvia.