Sensoring and AI Algorithms for Early Crop Disease Detection
Using digital technologies to produce risk maps so as to facilitate the early detection of plant pests.
This Flagship Innovation Experiment (FIE) aims to leverage digital technologies for the early detection of plant pests in three different crops: grapevines, cork trees and olive trees. In order to identify the symptoms of plant pests, which can at times be similar for different diseases, at an early stage, the FIE combines key technologies for crop observation such as remote sensors, Artificial Intelligence (AI) algorithms and weather forecast models. Their synergy helps to establish data patterns of symptoms, thereby creating risk maps which support farmers in mitigating the negative environmental impacts of production.
On top of that, the analysis of gathered information identifies and characterises the conditions under which certain diseases are most likely to appear in the relevant crops. To facilitate a solution with operational performance, this FIE strikes a balance between the amount of data needed for automatic algorithms to work precisely and the fast coverage of large areas to ensure an early detection of contamination.