Abstract—This study systematically examines the critical challenges confronting global agriculture, including resource scarcity, environmental degradation, and the increasing demand for food production driven by population growth. The research aims to investigate the application of intelligent sensing technologies, encompassing the Internet of Things (IoT), Artificial Intelligence (AI), and big data analytics, in addressing these challenges. The study's primary objective is to design and evaluate an integrated smart agricultural platform that leverages these technologies to enhance productivity, optimize resource efficiency, and support sustainable rural development. Through a synthesis of 50 peer-reviewed studies published between 2015 and 2023, selected based on relevance, methodological rigor, and impact, this review demonstrates that IoT-based systems improve water-use efficiency by up to 30%, while AI-driven crop monitoring reduces pesticide usage by 25%. These findings propose a conceptual framework for the deployment of intelligent sensing technologies, advancing precision agriculture and sustainable food systems.

Keywords—Artificial Intelligence (AI), big data analytics, intelligent sensing technologies, Internet of Things (IoT), precision agriculture, smart agricultural platforms, sustainable agriculture

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Cite: Jiuhong Yu, Tianying Jiang, Bu Li, and Jianhua Zhu, "Applications and Platform Designs of Intelligent Sensing Technologies in Agriculture: A Systematic Review," Journal of Software, vol. 20, no. 1, pp. 1-23, 2025.


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