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Big Data in Smart Farming - A review

Fri, 12/08/2017 - 09:43

Smart Farming is a development that emphasizes the use of information and communication technology in the
cyber-physical farm management cycle. New technologies such as the Internet of Things and Cloud Computing
are expected to leverage this development and introduce more robots and artificial intelligence in farming.
This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be
captured, analysed and used for decision-making. This review aims to gain insight into the state-of-the-art of
Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed. Fol-
lowing a structured approach,a conceptualframework for analysiswas developedthat can alsobeusedfor future
studies on this topic. The review shows that the scope of Big Data applications in Smart Farming goes beyond
primary production; it is influencing the entire food supply chain. Big data are being used to provide predictive
insights in farming operations, drive real-time operational decisions, and redesign business processes for
game-changing business models. Several authors therefore suggest that Big Data will cause major shifts in
roles and power relations among different players in current food supply chain networks. The landscape of stake-
holders exhibits an interesting game between powerful tech companies, venture capitalists and often small start-
ups and new entrants.
At the same time there are several public institutions that publish open data, under the
condition that the privacy of persons must be guaranteed. The future of Smart Farming may unravel in a contin-
uum of two extreme scenarios: 1) closed, proprietary systems in which the farmer is part of a highly integrated
food supply chain or 2) open, collaborative systems in which the farmer and every other stakeholder in the chain
network is flexible in choosing business partners as well for the technology as for the food production side. The
further development of data and application infrastructures (platforms and standards) and their institutional
embedment will play a crucial role in the battle between these scenarios. From a socio-economic perspective,
the authors propose to give research priority to organizational issues concerning governance issues and suitable
business models for data sharing in different supply chain scenarios.

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