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This paper presents SmartNutritionDiabetes, a novel smart data model designed to semantically integrate food intake, nutritional goals and glycemic response for enhanced diabetes mellitus management. Developed in alignment with the Smart Data Models initiative and building upon existing frameworks such as SAREF4HEALTH and HL7 FHIR, the proposed model addresses a critical gap in representing nutrition-related data within chronic disease monitoring systems. By leveraging linked data principles and semantic interoperability, the model facilitates real-time, context-aware decision-making in healthcare environments. The model is implemented and tested in a simulated environment, where its performance is evaluated against traditional approaches. Results demonstrate significant improvements in data accessibility, semantic expressiveness, and cross-domain interoperability, making it a valuable foundation for next-generation personalized healthcare applications.

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A Smart Data Model for Nutrition-Aware Diabetes Management in Healthcare Systems

  • 会议论文

  • 发表日期：

    2026年

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  • Simeon Tsvetanov,
  • Stela Dimitrova,
  • Albena Antonova

摘要

This paper presents SmartNutritionDiabetes, a novel smart data model designed to semantically integrate food intake, nutritional goals and glycemic response for enhanced diabetes mellitus management. Developed in alignment with the Smart Data Models initiative and building upon existing frameworks such as SAREF4HEALTH and HL7 FHIR, the proposed model addresses a critical gap in representing nutrition-related data within chronic disease monitoring systems. By leveraging linked data principles and semantic interoperability, the model facilitates real-time, context-aware decision-making in healthcare environments. The model is implemented and tested in a simulated environment, where its performance is evaluated against traditional approaches. Results demonstrate significant improvements in data accessibility, semantic expressiveness, and cross-domain interoperability, making it a valuable foundation for next-generation personalized healthcare applications.