doi: 10.17706/jsw.20.1.1-23
Applications and Platform Designs of Intelligent Sensing Technologies in Agriculture: A Systematic Review
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Jianhua Zhu
3,*
- 1 Institute of Data Intelligence and Smart Transformation, Ningbo University of Finance and Economics, Zhejiang Province, 315175, China.
- 2 College of International Economics and Trade, Ningbo University of Finance and Economics, Zhejiang Province, 315175, China.
- 3 Yangtze River Economic Belt Innovation and Green Development Think Tank, Beijing Province, 100071, China.
- Manuscript received November 19, 2024
- revised January 27, 2025
- accepted February 10, 2025
- published March 7, 2025
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.
How to 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. https://doi.org/ 10.17706/jsw.20.1.1-23
Copyright & License
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).