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.
Partially supported by the Mo.Re.Farming Project (www.morefarming.it) funded by the POR FESR Program 2014–2020.
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Gallinucci, E., Golfarelli, M., Rizzi, S. (2019). A Hybrid Architecture for Tactical and Strategic Precision Agriculture. In: Ordonez, C., Song, IY., Anderst-Kotsis, G., Tjoa, A., Khalil, I. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2019. Lecture Notes in Computer Science(), vol 11708. Springer, Cham. https://doi.org/10.1007/978-3-030-27520-4_2
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