AI-Driven Approaches to Energy Management in Agricultural Cold Chains
Journal of Smart and Sustainable Farming
Received On : 02 March 2025
Revised On : 30 April 2025
Accepted On : 12 May 2025
Published On : 25 May 2025
Volume 01, 2025
Pages : 078-088
Abstract
Organizations operating within the cold chain logistics sector are adopting a strategic approach towards using big data in order to effectively navigate the substantial potential and challenges presented by Artificial Intelligence (AI) and Internet of Things (IoT). When used in the broader context of cold chain logistics, IoT technology enhances the traditional information transmission network. In recent years, there has been a notable emergence of research focused on technological breakthroughs in the field of Internet of Things. As technology progresses to a certain threshold, the model of application will undergo maturation, leading to an expansion in range of requisitions and an augmentation in their capabilities. This paper examines the prevailing concerns pertaining to energy consumption across the agricultural supply chain and asserts the indispensability of using AI as a means to address these challenges. Furthermore, this paper examines several aspects of energy system planning and operation, specifically focusing on the potential use of AI in addressing energy challenges within the cold supply chain. In conclusion, this study undertakes more research on the problems and potential of the next generation of super cold chain. Its aim is to establish a standard for the good expansion of cold-chain logistics within the agricultural industry, with major interest in minimizing carbon emissions.
Keywords
Super Cold Chains, Cold Chain Logistics, Artificial Intelligence, Internet of Things, Cold Chain Infrastructure, Cold Chain Industry.
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CRediT Author Statement
The author reviewed the results and approved the final version of the manuscript.
Conceptualization: Ting Li and Wan Fang; Methodology: Ting Li and Wan Fang; Software: Ting Li; Data Curation: Wan Fang; Writing-Original Draft Preparation: Ting Li; Validation: Ting Li and Wan Fang; Writing- Reviewing and Editing: Ting Li and Wan Fang; All authors reviewed the results and approved the final version of the manuscript.
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Author(s) thanks to Dr. Wan Fang for this research completion and support.
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Cite this Article
Ting Li and Wan Fang, “AI-Driven Approaches to Energy Management in Agricultural Cold Chains”, Journal of Smart and Sustainable Farming, pp. 078-088, 25 May 2025, doi: 10.64026/JSSF/2025008.
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© 2025 Ting Li and Wan Fang. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.