| KEYWORD |
Hyperspectral based study of vines diseases for agricolture 4.0 new decision support systems design
Thesis in external company
keywords AGRICOLTURE 4.0, ARTIFICIAL INTELLIGENCE, IMAGE PROCESSING, IMAGE SEGMENTATION, REMOTE SENSING, SMART AGRICULTURE, UAV, DRONES
Reference persons LORENZO COMBA
Thesis type SPERIMENTAL, SPERIMENTAL APPLIED
Description The proposed activity is in collaboration with DiSAFA (Department of Agricultural, Forest and Food Sciences) of UniTO, and it is within the framework of a research project NOVIAGRI (New applications Of Vegetation Indexes in AGRIculture) funded by EU FEASR. In 2021 and 2022, an extensive monitoring campaign has been conducted in two vineyards near Asti, collecting several dataset: in-field observations, spectral signature of hundreds of leaves (healthy and diseased) by handheld High Resolution Field Spectroradiometer, high-resolution aerial multispectral maps by Matrice 300 UAV and MAIA camera, together with many other sensors.
The aim of the Thesis is to process spectral data of several samples to automatically classify them in three category: health plants, “Flavescenza dorata” diseased and “Mal dell’esca” diseased plants. Results of the proposed activity will enable the development of new decision support system (DSS) for enhanced precision agriculture methodologies.
See also 03_noviagri.pdf https://www.linkedin.com/company/laboratorio-di-meccatronica-universit%C3%A0-di-torino/
Required skills Mathworks Matlab
Deadline 08/07/2024
PROPONI LA TUA CANDIDATURA