Next-Generation Artificial Intelligence for Sustainable and Intelligent Food Production Systems: A Review

Abstract

Artificial Intelligence has become an indispensable force in changing the public's perception of every field, turning sustainability into climate friendliness, with smart food production being one of the largest casualties of this transformation. In a world facing mounting environmental challenges and ever-increasing pressures to maintain the global food supply, artificial intelligence demonstrates characteristics which are especially beneficial for improving production efficiency, reducing waste and improving quality at each stage of an agricultural or food value chain. The article makes a systematic analysis of new developments in artificial intelligence applied to food systems, covering both resource optimization and waste reduction at the supply chain level; predictive analytics for livestock management and precision agriculture; as well as high-sensitivity food manufacturing processes. The paper shows that the integrated power of advanced technologies such as robotics, computer vision, deep learning (DL), machine learning (ML), and the Internet of Things (IoT) promotes smart and sustainable manufacturing systems. A lot of quantitative data suggest that artificial intelligence on the one hand can achieve monitoring today's crops, early discovery of diseases and pests in them, intelligent irrigation management and safety standards for food production. However, there are still significant obstacles that prevent widespread adoption of these technologies: shortages in infrastructure, weaknesses in managing data like that from IoT devices (which are usually generated on your premises), economic constraints linked with further investment and ethical issues associated with deploying algorithms in such sensitive environments.