Abstract
In this paper we present a platform that implements a BI 2.0 architecture to support decision making in the precision agriculture domain. The platform, outcome of the Mo.Re.Farming project, couples traditional and big data technologies and integrates heterogeneous data from several owned and open data sources; its goal is to verify the feasibility and the usefulness of a data integration process that supports situ-specific and large-scale analyses made available by integrating information at different levels of detail.
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CITATION STYLE
Gallinucci, E., Golfarelli, M., & Rizzi, S. (2019). A Hybrid Architecture for Tactical and Strategic Precision Agriculture. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11708 LNCS, pp. 13–23). Springer. https://doi.org/10.1007/978-3-030-27520-4_2
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