Creation of digital twins of neural network technology of personalization of food products for diabetics
Andrey M. Vaskovsky, Marina S. Chvanova, Максим Ребезов
Abstract
The article discusses the problems of creating Digital Twin for use in neural network technology for personalizing food products for people with a genetic predisposition to diabetes. When designing an information system for personalizing food products, it is proved that the main direction of development is the modeling of a Digital Twin of the product and the consumer, as well as the determination of the technologies that form the basis of the personalized food model to create an accurate, correctly functioning system.
Topics & Concepts
PersonalizationArtificial neural networkProduct (mathematics)Computer scienceFood productsHuman–computer interactionArtificial intelligenceWorld Wide WebFood scienceGeometryMathematicsChemistryFood Industry and Aquatic BiologyRegional Economic Development and Innovation