The continuous development of technology has a strong effect on all the heterogeneous research areas and contexts including production agriculture. As a result, precision farming technologies have been increasingly recognized for their potential ability for improving agricultural productivity, reducing production cost, and minimizing damage to the environment. In this context, the main goal of this paper is to present a methodology that can be applied in order to extract semantic information, more specifically some vegetative indices from plants, in order to further improve the vegetation representation and health by means of a specific semantic robotic system.
|Titolo:||A Methodology for Improving Vegetation Representation and Health Exploiting a Semantic Robotic System|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|