Abstract
The rapid advancement of the Internet of Things (IoT) has revolutionised precision agriculture by enabling real-time monitoring of soil health and optimising resource utilisation. This systematic review assesses the benefits of IoT in precision agriculture, focusing on its effectiveness in soil health monitoring and resource optimisation techniques. A comprehensive literature search was conducted across Scopus, Web of Science, IEEE Xplore, and SpringerLink, targeting studies published between 2020 and 2025. A total of 2,108 articles were initially retrieved. After applying inclusion and exclusion criteria such as language, relevance, publication year, and experimental validation, 200 articles were selected for final review. The review examines the accuracy, scalability, and practical implementation of IoT devices in precision agriculture, identifying key datasets and evaluation metrics. Findings highlight the significant role of IoT in improving soil health assessment through sensor networks, big data analytics, and machine learning integration. Additionally, resource optimisation techniques such as variable rate technology (VRT) and remote sensing demonstrate substantial efficiency in reducing environmental impact and enhancing crop yield. However, challenges such as high implementation costs, internet connectivity issues, and the need for specialised expertise hinder widespread adoption, particularly in developing regions. The review underscores the necessity for policy support, cost-effective IoT infrastructure, and training programs to facilitate the adoption of precision agriculture technologies. Future research should explore AI-driven predictive models, edge computing solutions, and enhanced IoT interoperability to further optimise agricultural productivity and sustainability.
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CITATION STYLE
Iluno, C., & Nwaogwugwu, C. J. (2025). IoT in precision agriculture: A systematic review of soil health monitoring and resource optimisation techniques. Journal of Agricultural Science and Practice, 10(3), 42–49. https://doi.org/10.31248/jasp2025.533
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