The Development of Expert-Diagnostic System with the Scope to Improve the Quality Supervision of Meat Production Using Neural Network

The article provides an innovative approach to improving the quality control and safety of meat products using neural networks that accurately simulate biological processes. The Expert-Diagnostic System (EDS) combines machine learning and computer vision to precisely detect meat's defects, such as mechanical damage, texture abnormalities, color changes, and bacterial infections. A key element is the multi-agent system, which incorporates specialized agents. The interaction of agents is arranged through a coordination committee and consensus algorithms, ensuring high accuracy of assessments. A mathematical model of agent interaction is presented. Strategies for overcoming challenges such as scalability and agent coordination are proposed.