AI-Driven Approaches to Energy Management in Agricultural Cold Chains

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.