IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i15p9120-d871261.html
   My bibliography  Save this article

Big Data Privacy in Smart Farming: A Review

Author

Listed:
  • 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)

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.

Suggested Citation

  • Mohammad Amiri-Zarandi & Rozita A. Dara & Emily Duncan & Evan D. G. Fraser, 2022. "Big Data Privacy in Smart Farming: A Review," Sustainability, MDPI, vol. 14(15), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9120-:d:871261
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/15/9120/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/15/9120/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohammad Amiri-Zarandi & Mehdi Hazrati Fard & Samira Yousefinaghani & Mitra Kaviani & Rozita Dara, 2022. "A Platform Approach to Smart Farm Information Processing," Agriculture, MDPI, vol. 12(6), pages 1-18, June.
    2. Keith H Coble & Ashok K Mishra & Shannon Ferrell & Terry Griffin, 2018. "Big Data in Agriculture: A Challenge for the Future," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 40(1), pages 79-96.
    3. Raymond Hubbard & Brian D. Haig & Rahul A. Parsa, 2019. "The Limited Role of Formal Statistical Inference in Scientific Inference," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 91-98, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martina Šestak & Daniel Copot, 2023. "Towards Trusted Data Sharing and Exchange in Agro-Food Supply Chains: Design Principles for Agricultural Data Spaces," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
    2. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    3. Haoling Ren & Jiangdong Wu & Tianliang Lin & Yu Yao & Chang Liu, 2023. "Research on an Intelligent Agricultural Machinery Unmanned Driving System," Agriculture, MDPI, vol. 13(10), pages 1-19, September.
    4. Komarek, Adam M. & De Pinto, Alessandro & Smith, Vincent H., 2020. "A review of types of risks in agriculture: What we know and what we need to know," Agricultural Systems, Elsevier, vol. 178(C).
    5. Robert Finger, 2023. "Digital innovations for sustainable and resilient agricultural systems," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(4), pages 1277-1309.
    6. Schroeder, Ted C. & Tonsor, Glynn T. & Coffey, Brian K., 2019. "Commodity futures with thinly traded cash markets: The case of live cattle," Journal of Commodity Markets, Elsevier, vol. 15(C), pages 1-1.
    7. Rim Lassoued & Diego M. Macall & Stuart J. Smyth & Peter W. B. Phillips & Hayley Hesseln, 2021. "Expert Insights on the Impacts of, and Potential for, Agricultural Big Data," Sustainability, MDPI, vol. 13(5), pages 1-18, February.
    8. Keith H. Coble, 2020. "Relevant and/or Elegant Economics," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 392-399, March.
    9. Cara Stitzlein & Simon Fielke & François Waldner & Todd Sanderson, 2021. "Reputational Risk Associated with Big Data Research and Development: An Interdisciplinary Perspective," Sustainability, MDPI, vol. 13(16), pages 1-13, August.
    10. Oksana Hrynevych & Miguel Blanco Canto & Mercedes Jiménez García, 2022. "Tendencies of Precision Agriculture in Ukraine: Disruptive Smart Farming Tools as Cooperation Drivers," Agriculture, MDPI, vol. 12(5), pages 1-15, May.
    11. Rabhi, Loubna & Jabir, Brahim & Falih, Noureddine & Afraites, Lekbir & Bouikhalene, Belaid, 2023. "A Connected farm Metamodeling Using Advanced Information Technologies for an Agriculture 4.0," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 15(2), June.
    12. Emily Duncan & Alesandros Glaros & Dennis Z. Ross & Eric Nost, 2021. "New but for whom? Discourses of innovation in precision agriculture," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(4), pages 1181-1199, December.
    13. Omar Abu Hassim & Ismah Osman & Asmah Awal & Fhaisol Mat Amin, 2024. "Navigating the Path to Equitable and Sustainable Digital Agriculture among Small Farmers in Malaysia: A Comprehensive Review," Information Management and Business Review, AMH International, vol. 16(2), pages 173-188.
    14. Zhikai Ma & Kun Chong & Shiwei Ma & Weiqiang Fu & Yanxin Yin & Helong Yu & Chunjiang Zhao, 2022. "Control Strategy of Grain Truck Following Operation Considering Variable Loads and Control Delay," Agriculture, MDPI, vol. 12(10), pages 1-14, September.
    15. Amanda M. Nelson & Nicolas E. Quintana Ashwell & Christopher D. Delhom & Drew M. Gholson, 2022. "Leveraging Big Data to Preserve the Mississippi River Valley Alluvial Aquifer: A Blueprint for the National Center for Alluvial Aquifer Research," Land, MDPI, vol. 11(11), pages 1-17, October.
    16. Kumar, Parveen & Hendriks, Tim & Panoutsopoulos, Hercules & Brewster, Christopher, 2024. "Investigating FAIR data principles compliance in horizon 2020 funded Agri-food and rural development multi-actor projects," Agricultural Systems, Elsevier, vol. 214(C).
    17. Ayorinde Ogunyiola & Maaz Gardezi, 2022. "Restoring sense out of disorder? Farmers’ changing social identities under big data and algorithms," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 39(4), pages 1451-1464, December.
    18. Mpho Neo Chuma & Joshua Ebere Chukwuere, 2024. "Investigating the Use of Big Data in Fast Food: A Case of Mahikeng," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 98-114.
    19. Kyrgiakos, Leonidas Sotirios & Kleftodimos, Georgios & Kremantzis, Marios Dominikos & Vlontzos, George & Pardalos, Panos M., 2023. "Assessing efficiency differences in a common Agriculture Decision Support System - A comparative analysis between Greek and Italian durum wheat farms," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 14(01), January.
    20. Gunter, Ulrich & Önder, Irem & Smeral, Egon, 2019. "Scientific value of econometric tourism demand studies," Annals of Tourism Research, Elsevier, vol. 78(C), pages 1-1.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9120-:d:871261. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.