Personalized Dietary Platform Integrating Scattered Health Data
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Solution Overview
Problem
Current systems fail to effectively integrate and analyze scattered personal health data, leading to reduced user convenience and accuracy in health-related analysis and prediction, especially when considering health, genetics, and environmental factors for personalized dietary suggestions.
Innovation Solution
A personalized dietary suggestion platform that acquires health-related data, constructs a database using big data including food product, human physiology, and environmental data, and suggests tailored nutritional ingredients or food products through a learned dietary derivation model, executed by a processor and stored in a memory, considering health maintenance, disease prevention, and physiologically active ingredients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If personal health data are collected and managed separately across different sources, then data collection coverage is improved, but user convenience and analysis accuracy deteriorate
Solution Approach 1:
The patent merges scattered personal health data from multiple sources (hospital records, test results, wearable devices, family history, genetic data, microbiome data) into a unified data structure. This integration allows comprehensive data collection while maintaining high analysis accuracy through centralized processing and standardized formats, directly resolving the contradiction between data coverage and analysis precision.
2Adaptability or versatility
If scattered health data are managed separately, then data source diversity is improved, but user convenience deteriorates
Solution Approach 1:
The patent creates a universal health data management system that can handle multiple types of data sources (medical records, genetic data, wearable device data, family history) through a single integrated platform. This multi-functional approach maintains data source diversity while providing unified access and management, thereby improving user convenience without sacrificing versatility.
3Measurement precision
If comprehensive health data integration is implemented, then personalized dietary suggestion accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the comprehensive health data integration system into modular components: data collection modules for different data types, data processing modules for specific analysis tasks, and suggestion generation modules for dietary recommendations. This segmentation maintains high personalized suggestion accuracy by processing each data type appropriately while reducing overall system complexity through manageable, independent modules that can be developed and maintained separately.
Data Source
AI summary
Provided is a method and a system for providing personalized dietary suggestion platform and provides a method and a system for providing personalized dietary suggestion platform in which a complex system is constructed by using user's health-related data, food product data, human physiology data, and environmental data, and a user-personalized diet is derived by learning thereof.