Revolutionizing Agricultural Efficiency: Leveraging AI Neural Networks and Generative AI for Precision Farming and Sustainable Resource Management

Abstract

This essay addresses the applicability of emerging innovative technologies in the area of agriculture. In particular, this essay focuses on the application of AI neural networks as well as one of the applications of generative AI in this field. AI neural networks are shown to be best suited for application in precision farming, especially when it is necessary to find dependencies between a large number of factors and external applications. Generative AI can be used as a tool to assist in data analysis. The essay stresses the importance of systematic and rational use of resources. It is noted that preliminary data processing is the "weakest link" in any production process and hence, in the agricultural sphere as well.
The creation of tools for identifying dependencies between indicators and their influence on productivity is of great theoretical and practical interest in terms of human and animal health, increasing the efficiency of living standards, and the rational use of the Earth's resources. Sustainable resource management and the development of the agricultural industry are included in the list of Sustainable Development Goals and are given first place since about 80% of the world's antibiotics are used in animal husbandry, which is dangerous in terms of the appearance and distribution of antibiotic resistance. This essay proposes an approach to the application of innovative technologies to solve the stated problem and provides examples of the practical application of proposed algorithms in this study. The main attention is paid to the issues of practical work in the field of preliminary data processing. Furthermore, the essay also provides three presented results of studies using the proposed methods.