A bibliographic study of integrating IoT and geospatial modelling for sustainable smart agriculture in developed countries: Focus on Australia
Integrating 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. • 172 IoT–geospatial agriculture studies reviewed for 2013–2023 across 7 nations. • Wheat and corn dominate; barley, canola, cotton and sugarcane receive less focus. • UAVs, RGB cameras and SAR are the core sensing platforms across applications. • Most work targets monitoring and estimation; resource management is underused. • Australia trails USA and Germany in UAV, RGB, SAR use and resource trials.
Authors
- Quazi Mamun (ORCID: https://orcid.org/0000-0003-2196-7651)
- Ryan H. L. Ip (ORCID: https://orcid.org/0000-0001-8636-1891)
- K M Shamsul Haque (ORCID: https://orcid.org/0000-0001-5927-9649)
- Asaduz Zaman
Institutions
- Charles Sturt University (AU)
- Auckland University of Technology (NZ)
- Monash University (AU)
Publication Details
- Journal
- Computers and Electronics in Agriculture
- Published
- 2025-12-02
- DOI
- https://doi.org/10.1016/j.compag.2025.111289
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 1.75