Agro.Big.Data.Science
Using BIG DATA in the management of kiwi, pear and spinach production chains
The growing availability of advanced sensor technology capable of collecting a wide range of information across all stages of the agri-food supply chain enables us to address issues related to diagnosis, forecasting, and improvement of supply chains through a data-driven approach. The data science methodology employed in this project involves a multidisciplinary team (including IT specialists, statisticians, and agri-food experts) capable of both formulating problems, hypothesizing causes, and validating solutions, as well as analyzing data using specific algorithms.
The project intends to apply this data-driven approach to three production chains (kiwi, pear, and spinach) provided by the participating companies, fully equipped with the necessary sensors for real-time data collection. For data collection and analysis, a general-purpose technological platform for Big Data will be used.
Agro.Big.Data.Science, the outcome of this project, aims to become the foundation for developing specialized solutions for the agri-food domain and sets the following objectives:
- Address specific issues in the three selected supply chains;
- Validate the data-driven methodology in agri-food supply chains;
- Assess the maturity and improve the IoT systems already in use in the supply chains;
- Engineer a flexible Big Data platform specific to the agri-food sector, adaptable to supply chains beyond those considered in the project.
PARTNERSHIP
Research Partners
- CRPV lab – Capofila
- CRAST
- CIRI AGRO
- CIRI ICT
- CITIMAP
Industrial Partners
- APOFRUIT
- APO CONERPO
- OROGEL
- GranFrutta Zani
- Agrintesa
- Agribologna
- Pempacorer
- Agrisol
- ONIT
- Winet S.r.l.
- iFARMING
ADMINISTRATIVE DATA
Duration: 26/07/2019 - 25/02/2022
Stauts: Completed
Project website: https://www.agrobigdatascience.it/
Funding: POR FESR Emilia-Romagna 2014/2020, Axis 1, Action 1.2.2, 2018 Call, co-funded by the Cohesion Fund. Granted contribution: €785,054.75