In this paper we propose an innovative architecture, called Mo.Re.Farming, for handling agricultural data in an integrated fashion and supporting decision making in the precision agriculture domain. This architecture is oriented to data analysis and is inspired by Business Intelligence 2.0 approaches. It is hybrid in that it couples traditional and big data technologies to integrate heterogeneous data, at different levels of detail, from several owned and open data sources; its goal is to demonstrate that such integration is feasible and beneficial in supporting situ-specific and large-scale analyses. The proposed architecture has been developed in the context of the Mo.Re.Farming project, aimed at providing a Decision Support System for agricultural technicians in the Emilia-Romagna region and to enable analyses related to the use of water and chemical resources. The architecture is fully deployed and serves as a hub for agricultural data in Emilia-Romagna; the integrated data are made available in open access mode and can be accessed through web interfaces and through a set of web services. The paper describes the architecture from the technological and functional points of view and discusses the Mo.Re.Farming project outcomes and lessons learnt.

Mo.Re.Farming: A hybrid architecture for tactical and strategic precision agriculture / Enrico Gallinucci, Matteo Golfarelli, Stefano Rizzi. - In: DATA & KNOWLEDGE ENGINEERING. - ISSN 0169-023X. - STAMPA. - 129:(2020), pp. 1-16. [10.1016/j.datak.2020.101836]

Mo.Re.Farming: A hybrid architecture for tactical and strategic precision agriculture

Enrico Gallinucci;Matteo Golfarelli
;
Stefano Rizzi
2020

Abstract

In this paper we propose an innovative architecture, called Mo.Re.Farming, for handling agricultural data in an integrated fashion and supporting decision making in the precision agriculture domain. This architecture is oriented to data analysis and is inspired by Business Intelligence 2.0 approaches. It is hybrid in that it couples traditional and big data technologies to integrate heterogeneous data, at different levels of detail, from several owned and open data sources; its goal is to demonstrate that such integration is feasible and beneficial in supporting situ-specific and large-scale analyses. The proposed architecture has been developed in the context of the Mo.Re.Farming project, aimed at providing a Decision Support System for agricultural technicians in the Emilia-Romagna region and to enable analyses related to the use of water and chemical resources. The architecture is fully deployed and serves as a hub for agricultural data in Emilia-Romagna; the integrated data are made available in open access mode and can be accessed through web interfaces and through a set of web services. The paper describes the architecture from the technological and functional points of view and discusses the Mo.Re.Farming project outcomes and lessons learnt.
2020
Mo.Re.Farming: A hybrid architecture for tactical and strategic precision agriculture / Enrico Gallinucci, Matteo Golfarelli, Stefano Rizzi. - In: DATA & KNOWLEDGE ENGINEERING. - ISSN 0169-023X. - STAMPA. - 129:(2020), pp. 1-16. [10.1016/j.datak.2020.101836]
Enrico Gallinucci, Matteo Golfarelli, Stefano Rizzi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/773131
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