Data model for an intelligent fish farm management system

Abstract

The article defines the importance of artificial cultivation of hydrobionts. The article analyzes the state of fish farming in Russia. The main trend of the industry is the need for digital transformation of processes that provide management, control and monitoring of hydrobiont farming processes. This requires the development and implementation of “smart” digital solutions based on data. The analysis of the subject area has shown that there is a large amount of heterogeneous data related to, for example, the microclimate of water bodies, the state of hydrobionts, the works performed, the sanitary condition, and so on. All this requires the creation of a unified data model that meets the requirements of integrity, consistency, redundancy and normalization. This defines the purpose of the work to be performed. The application of methods that allow to obtain a description of the key aspects of the subject area, provided the opportunity to use the methodology of relational database design. With its help, key entities, their key and non-key attributes, as well as relationships between them are developed. The developed data model provides the principles of data storage and management, scalability of the model and its integration with other specialized software solutions.