Big Data Privacy in Smart Farming: A Review

Mohammad Amiri-Zarandi, Rozita A. Dara, Emily Duncan and Evan D. G. Fraser
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Mohammad Amiri-Zarandi: Data Management and Privacy Governance Lab, School of Computer Science, University of Guelph, Guelph, ON N1G 2W1, Canada
Rozita A. Dara: Data Management and Privacy Governance Lab, School of Computer Science, University of Guelph, Guelph, ON N1G 2W1, Canada
Emily Duncan: Geography, Environment and Geomatics, University of Guelph, Guelph, ON N1G 2W1, Canada
Evan D. G. Fraser: Geography, Environment and Geomatics, University of Guelph, Guelph, ON N1G 2W1, Canada

Sustainability, 2022, vol. 14, issue 15, 1-18

Abstract: Smart farming aims to improve farming using modern technologies and smart devices. Smart devices help farmers to collect and analyze data regarding different aspects of their business. These data are utilized by various stakeholders, including farmers, technology providers, supply chain investigators, and agricultural service providers. These data sources can be considered big data due to their volume, velocity, and variety. The wide use of data collection and communication technologies has increased concerns about the privacy of farmers and their data. Although some previous studies have reviewed the security aspects of smart farming, the privacy challenges and solutions are not sufficiently explored in the literature. In this paper, we present a holistic review of big data privacy in smart farming. The paper utilizes a data lifecycle schema and describes privacy concerns and requirements in smart farming in each of the phases of this data lifecycle. Moreover, it provides a comprehensive review of the existing solutions and the state-of-the-art technologies that can enhance data privacy in smart farming.

Keywords: privacy; big data; security; smart farming; precision agriculture; Internet of Things; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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