Vine disease is a major risk for viticulture, involving economic loss, yield quality reduction and environmental impact when using chemicals for treatment. MERIAVINO project advocates a multidisciplinary approach, which is based on several scientific fields to address the problem of disease and yield estimation in vineyard.
The proposed multi-scale methodology consists of inter-combining and implementing IoT, remote sensing and big data in order to interconnect the vineyard parcels, as well as to develop a non-invasive, eco-friendly and low-cost technology for vine disease detection/warning.
With the goal of reducing economic loss of both quantity and quality, and the environmental impact, various sensors, data fusion techniques, artificial intelligence (AI) with machine learning (ML) methods will be combined along with the development of reprintable sensors for effective vineyard monitoring.
The project results are then analysed and geo-visualised on compatible MobApp for end-users for decision-making and early prevention.
Project Τitle:
MERIAVINO: Multiscale Sensing for Disease Monitoring in Vineyard Production
Project Duration: 36 months (2021-2023)
Project Framework & Funding:
ICT AGRIFOOD 2020 https://ictagrifood.eu/node/44588?language=el
GSRT (General Secretariat for Research and Technology)
Total Budget 1.000.000 Euros
UNIWA Budget 200.000 Euros
Investigator (UNIWA): Emmanouil Oikonomou
Consortium – Partners:
- INSA (Institut National des Sciences Appliquees, France, PI)
- IFV (France
- ATOS (France)
- CMU (Constanta Maritime University, Romania)
- SCDVV Murfatlar (Romania)
- University of West Attica, Department of Surveying and Geoinformatics Engineering
