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Applications of Raspberry Pi for Precision Agriculture—A Systematic Review

Author

Listed:
  • Astina Joice

    (Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58102, USA)

  • Talha Tufaique

    (Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58102, USA)

  • Humeera Tazeen

    (Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58102, USA)

  • C. Igathinathane

    (Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58102, USA)

  • Zhao Zhang

    (Key Laboratory of Smart Agriculture System Integration, Ministry of Education, China Agricultural University, Beijing 100083, China)

  • Craig Whippo

    (Northern Great Plains Research Laboratory, USDA-ARS, Mandan, ND 58554, USA)

  • John Hendrickson

    (Northern Great Plains Research Laboratory, USDA-ARS, Mandan, ND 58554, USA)

  • David Archer

    (Northern Great Plains Research Laboratory, USDA-ARS, Mandan, ND 58554, USA)

Abstract

Precision agriculture (PA) is a farm management data-driven technology that enhances production with efficient resource usage. Existing PA methods rely on data processing, highlighting the need for a portable computing device for real-time, infield decisions. Raspberry Pi, a cost-effective multi-OS single-board computer, addresses this gap. However, information on Raspberry Pi’s use in PA remains limited. This review consolidates details on Raspberry Pi versions, sensors, devices, algorithm deployment, and PA applications. A systematic literature review of three academic databases (Scopus, Web of Science, IEEE Xplore ) yielded 84 (as of 22 November 2024) articles based on four research questions and screening criteria (exclusion and inclusion). Narrative synthesis and subgroup analysis were used to synthesize the results. Findings suggest Raspberry Pi can be a central unit to control sensors, enabling cost-effective automated decision support for PA, particularly in plant disease detection, site-specific weed management, plant phenotyping, biomass estimation, and irrigation systems. Despite focusing on these areas, further research is essential on other PA applications such as livestock monitoring, UAV-based applications, and farm management software. Additionally, Raspberry Pi can be used as a valuable learning tool for students, researchers, and farmers and can promote PA adoption globally, helping stakeholders realize its potential.

Suggested Citation

  • Astina Joice & Talha Tufaique & Humeera Tazeen & C. Igathinathane & Zhao Zhang & Craig Whippo & John Hendrickson & David Archer, 2025. "Applications of Raspberry Pi for Precision Agriculture—A Systematic Review," Agriculture, MDPI, vol. 15(3), pages 1-31, January.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:3:p:227-:d:1572664
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