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A Bibliographic Study of Integrating IoT and Geospatial Modelling for Sustainable Smart Agriculture in Developed Countries: Focus on Australia

aut.relation.articlenumber111289
aut.relation.endpage111289
aut.relation.journalComputers and Electronics in Agriculture
aut.relation.startpage111289
aut.relation.volume241
dc.contributor.authorMamun, Quazi
dc.contributor.authorZaman, Asaduz
dc.contributor.authorIp, Ryan HL
dc.contributor.authorHaque, KM Shamsul
dc.date.accessioned2025-12-03T20:59:24Z
dc.date.available2025-12-03T20:59:24Z
dc.date.issued2025-12-02
dc.description.abstractIntegrating the Internet of Things (IoT) and geospatial modelling technologies is pivotal for advancing sustainable smart agriculture, particularly in resource-constrained environments like Australia. This systematic literature review examines the adoption and impact of these technologies in agriculture across Australia and select developed countries. Through an extensive analysis of 172 peer-reviewed articles published between 2013 and 2023, this study identifies key technological advancements such as unmanned aerial vehicles (UAVs), consumer-grade cameras (RGB cameras), and satellite platforms (Sentinel-2, LANDSAT-8) that have significantly influenced agricultural practices. The findings reveal Australia’s progress in adopting these technologies but also highlight gaps compared to countries like Germany and the USA, especially in using UAVs, Synthetic Aperture Radar (SAR) and RGB cameras. The study underscores Australia’s need to enhance its technological capabilities, particularly resource management, to foster more efficient and sustainable agricultural practices. This review provides valuable insights for policymakers, researchers, and technology providers, aiming to drive innovation and improve agricultural outcomes in the face of growing environmental challenges.
dc.identifier.citationComputers and Electronics in Agriculture, ISSN: 0168-1699 (Print); 1872-7107 (Online), Elsevier, 241, 111289-111289. doi: 10.1016/j.compag.2025.111289
dc.identifier.doi10.1016/j.compag.2025.111289
dc.identifier.issn0168-1699
dc.identifier.issn1872-7107
dc.identifier.urihttp://hdl.handle.net/10292/20259
dc.languageen
dc.publisherElsevier
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S016816992501395X?via%3Dihub
dc.rights© 2025 The Authors. Published by Elsevier B.V. Creative Commons. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.
dc.rights.accessrightsOpenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject3002 Agriculture, land and farm management
dc.subject4602 Artificial intelligence
dc.subject07 Agricultural and Veterinary Sciences
dc.subject08 Information and Computing Sciences
dc.subject09 Engineering
dc.subjectAgronomy & Agriculture
dc.subject30 Agricultural, veterinary and food sciences
dc.subject40 Engineering
dc.subject46 Information and computing sciences
dc.subjectIoT
dc.subjectGeospatial modelling
dc.subjectPrecision agriculture
dc.subjectSustainability
dc.titleA Bibliographic Study of Integrating IoT and Geospatial Modelling for Sustainable Smart Agriculture in Developed Countries: Focus on Australia
dc.typeJournal Article
pubs.elements-id747221

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