A review of the use of artificial intelligence in renewable energy for food processing and preservation process optimisation, challenges, and future prospects

Abstract

Both industry and academia are interested in combining renewable energy with artificial intelligence (AI) ineffective food processing and preservation equipment. With a global push for sustainability, interest in technology is growing among affluent nations and others. Given the widespread usage of AI, microgrids, and renewable energy in various fields, it is critical to create a review that examines the optimisation techniques employed in previous studies and possible directions for future research. This review systematically explores the integration of AI and renewable energy technologies in food processing and preservation, focusing on solar, wind, and biomass energy sources. AI applications like machine learning and neural networks improve energy management, process optimisation, and quality control in energy-intensive operations like drying, refrigeration, and packaging. Bibliometric analysis of 827 publications from 2015 to 2025 shows a rapid rise in interdisciplinary research driven by environmental concerns and technological advances. AI integration offers benefits like energy efficiency, reduced greenhouse gas emissions, and improved food quality, but challenges like high initial costs, infrastructure limitations, and socioeconomic disparities persist. Case studies show AI automating laborious tasks and optimising processes powered by renewable energy. Standardised frameworks, economic evaluations, and lifecycle assessments are needed for sustainable implementation. As part of the future growth of AI technology, recommendations for additional studies have been underlined and advised. Therefore, food processors and legislators could benefit much from harnessing the potential of AI in renewable energy for sustainable development.

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