gholamreza Abdi

The implementation of Artificial Intelligence (AI) in the food sector is increasing worldwide to enhance industrial functionalities. This technology improves effectiveness, product quality, and environmental sustainability, as well as speeds up the process. It forecasts inadequacies, reduces waste, and assists in resource exploitation. This chapter focuses on AI-driven twin technology applications in different real-world food systems after a brief introduction of these technologies. AI-driven twin technology highlights the combination of deep neural networks and deep convolutional neural networks designs. This chapter explores the current state of AI implementation in the food sector, demonstrating how this innovation is central to modern food production. These food sectors include dairy, beverages, and fruit and vegetable processing. It also provides an overview of emerging applications of AI in intelligent food packaging, personalized nutrition, and nutrient composition analysis. Besides its remarkable prospects, this study debates several raised challenges and offers future recommendations for sustainable food processing and manufacturing.