Personalized Food Influence Modeling for Individual Nutrition Advice
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Solution Overview
Problem
Existing systems struggle to provide personalized food advice due to the need for pre-prepared databases, failing to account for individual user differences.
Innovation Solution
An information processing system that includes a prediction model storage unit for user-specific dietary component intake analysis, a food database, and an influence amount calculation unit to determine how foods affect individual physical data, allowing for personalized food recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If pre-prepared advice database is used, then system complexity is reduced, but adaptability to individual users deteriorates
Solution Approach 1:
The system dynamically generates personalized advice by calculating influence amounts based on individual user characteristics and dietary component contents, rather than using static pre-prepared advice databases. This allows the system to adapt to each user's unique needs while maintaining manageable complexity through automated calculations.
Solution Approach 2:
The system changes the parameter of advice generation from fixed pre-prepared categories to dynamic calculations based on user-specific parameters including individual characteristics, physical data, and dietary component analysis. This enables personalized advice tailored to each user's specific situation.
2Adaptability or versatility
If personalized prediction models are created for each user, then adaptability to individual users is improved, but device complexity increases
Solution Approach 1:
The system segments the personalization process into distinct functional modules: a prediction model storage unit that stores pre-built models, a food database that stores dietary component information, and an influence amount calculation unit that performs calculations. This segmentation allows personalized advice generation without overwhelming system complexity, as each module handles a specific aspect of the task.
Data Source
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AI summary
Optimal food information can be provided to individual users. An information processing system includes: a prediction model storage unit that stores, for each user, a prediction model that predicts physical data regarding a body of the user based on intake amounts of a plurality of dietary components taken by the user, the prediction model including a degree to which each dietary component improves or deteriorates the physical data; a food database that stores a content of the dietary component contained in a food; and an influence amount calculation unit that calculates an influence amount which is an amount by which the food improves or deteriorates the physical data of the user based on the content of the dietary component included in the food and the degree related to the dietary component.