BigDataGrapes
Responsible Partner: Agricultural University of Athens (AUA)
Pilot description
Table and Wine Grapes Pilot aims to denote correlations between precision agriculture information and phenological data and grape and wine chemical analysis. Another goal is to associate the aforementioned data with earth observation data in order to examine the effectiveness of applying machine learning techniques and eventually train the relevant machine learning components.
AUA will continuously collect and monitor sensor, farming and phenological data derived from all test sites located in Greece. Soil properties, climate conditions and cultivation techniques constitute significant variables, which affect the quality of the final product. In particular, soil data affect both crop quality data and crop quantity data. Deriving meaningful knowledge from many relevant, yet heterogeneous data sources is very important and will act as the basis for future decision-making processes.
Specific Goals
Some of the goals to be achieved through sensor and farming data collection, is to denote correlations between precision agriculture information and phenological data and grape and wine chemical analysis. Finally, the ultimate goal is to correlate the aforementioned data with earth observation data in order to examine the effectiveness of applying machine learning techniques and eventually train the relevant machine learning components.
Site Description
Three test sites have been chosen for data collection. These are situated in the regional unit of Corinthia, in the north-eastern part of Peloponnese, Greece. In particular,
- Palivou Estate and Kontogiannis Estate for winemaking production
- Fasoulis Estate for table grapes production
Expected Timeline
Measurements related to the Table and Wine Grapes pilot will take place during the whole duration of the project. Emphasis will be given during the summer months, May through September, while grapevines grow and produce grapes.
Envisaged Outcomes
The expansive and diverse collection of datasets for BigDataGrapes will serve as the basis for carrying out research and technical work. These data assets will contribute to a data marketplace demonstrator that will serve as the project’s experimentation environment. The streams will be used as the testbed for enabling the implemented technical components to efficiently handle the volume and intricacies of these data clearly acquired from realistic in-field conditions. As the project progresses, the data pool will be continuously enriched in volume and range, in accordance with the needs and requirements of the covered use cases.
