Use of artificial intelligence for managing a livestock farm

The implementation of intelligent digital control systems is essential for achieving high performance in agricultural enterprises. The study applies the biomachine systems theory to livestock farm management to analyze the functional links between complex system components. The research justifies the structure and functionality of an artificial intelligence (AI) framework for managing livestock biomachine systems. In this model, the farm is represented as an undirected multigraph, where vertices represent the “Human-Machine-Animal-Product-Environment” (H-M-A-P-E) elements and edges represent their functional interconnections. The study examines localized biotechnological systems – specifically milking and primary processing, feed preparation and distribution, microclimate control, and manure removal – analyzing their functional relationships through a directed multigraph. The authors categorize AI functions within these localized systems and provide a structural-functional diagram illustrating the interaction between milking and feeding systems within the Internet of Things (IoT) framework. The direct exchange of signals between these local systems, independent of a centralized “control center” (workstation), enables autonomous functioning and effective coordinated management. The systematization of AI functions presented here facilitates the development of intelligent telecommunication systems for monitoring operators’ performance, machine efficiency, physiological condition of animals, and the overall economic and environmental sustainability of the enterprise.