Data-Driven Agriculture : Unveiling the Power of Internet of Things and Data Analytics For Transformative Farming Practices

Zulfadli Hazim, Zul Azlan and Syahrul Nizam, Junaini and Adnan Shahid, Khan and Wan Azani, Mustafa (2025) Data-Driven Agriculture : Unveiling the Power of Internet of Things and Data Analytics For Transformative Farming Practices. Journal of Sensors, 2025. pp. 1-38. ISSN 1687-7268

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Abstract

As the global population is projected to reach 10 billion by 2050, the urgent need for advanced agricultural technologies becomes increasingly apparent. The Internet of Things (IoT) and data analytics stand at the forefront of this technological revolution, offering unprecedented enhancements in real-time monitoring and decision-making to optimize farm productivity. However, there is a significant gap in the literature regarding the extensive application of IoT and data analytics in agriculture. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, this review carefully examines the current landscape, highlighting the benefits and challenges of integrating IoT and data analytics into agriculture. From an initial pool of 1166 studies identified in Scopus and Web of Science (WoS), 28 pivotal studies were selected. Collectively, these studies provided deep insights into eight major research trends, underscored nine essential benefits, and articulated 14 significant challenges. This review not only proposes five methodologies to evaluate the effectiveness of these technologies but also introduces a robust conceptual model and framework, based on the analyzed literature, designed to guide future research and support the development of innovative and integrated agricultural solutions. As agriculture transitions to a digital and data-driven future, understanding the full spectrum of IoT and data analytics applications becomes crucial. This review addresses the current knowledge gap and provides a foundation for data-informed decision-making to enhance the sustainability and efficiency of agricultural practices.

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