Automation of the process of managing the production of organic products by means of an intelligent system

The transition to organic agriculture can help overcome environmental problems in Russia and preserve natural resources for future generations. Also, the development of organic agriculture contributes to improving the quality of food products and can lead to an improvement in the health of the nation. One of the key factors that contributes to the development of organic agriculture in Russia is the presence of vast expanses of unused land. In light of this, the Russian Government is taking measures to stimulate the development of organic agriculture.

The measures taken include support and subsidies for organic farmers, the creation of special programs and projects, as well as the development of appropriate legislation.

The presented article is devoted to the study of the process of managing the production of organic products, automation of its main stages. The authors describe the development of a hybrid intelligent system for improving the process of managing the production of organic products for the development of organic crop production as a high-tech direction of agriculture. Information, behavioral models and a model of components of an intelligent system are presented.

The main modules of the hybrid intelligent information system are the knowledge base, the executive system, and the intelligent interface. For integration with other systems, it is possible to enable the integration module. The role of the intelligent interface is to form concepts used to make decisions about the possibility of producing organic products. In turn, the knowledge base, or concept repository, receives the extracted concepts and fragments of texts. The tasks of the executive system are visualization, statistics maintenance and search for associative rules of organic production factors within the framework of the considered level.

The developed system allows you to change input parameters and conditions by region, socio-economic situation and climatic conditions, adjust user requests to obtain the most optimal proposed solutions.

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