Nutritional Analysis System Using Image Recognition and Database Querying
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Solution Overview
Problem
Obtaining accurate nutritional information for food items is challenging due to diverse food preparation methods, varying portion sizes, hidden ingredients, and limitations in food databases, particularly for restaurant food where local establishments lack resources for comprehensive nutritional analysis.
Innovation Solution
A nutritional analysis system that aggregates data for each ingredient of a food item, receives user input including images, text, and other forms of data, and queries internal and external databases to determine nutritional information, generate nutritional scores, and provide recommendations for improving dietary value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive nutritional analysis is performed for restaurant food items, then measurement precision of nutritional information is improved, but device complexity and cost increase significantly
Solution Approach 1:
The system segments the nutritional analysis process into distinct modules: image capture, ingredient identification, database querying, and nutritional calculation. Each module handles a specific aspect of the analysis, making the overall system more manageable and less complex while maintaining high measurement precision through specialized processing at each stage.
Solution Approach 2:
The patent introduces an intermediary database layer that stores pre-collected nutritional data for thousands of ingredients. This intermediary structure allows the system to avoid performing complex real-time nutritional calculations, instead simply querying stored data based on identified ingredients, thereby reducing device complexity while preserving measurement accuracy.
2Measurement precision
If manual nutritional analysis is performed by dietitians, then measurement precision is improved, but productivity decreases due to time-consuming processes
Solution Approach 1:
The system enables self-service nutritional analysis where users simply capture an image of the food item and the system automatically performs ingredient identification, database matching, and nutritional calculation without requiring manual input or expert intervention. This automation maintains high measurement precision through algorithmic consistency while dramatically improving productivity by eliminating time-consuming manual processes.
Solution Approach 2:
The patent replaces the mechanical system of manual nutritional analysis by dietitians with an automated computational system using image recognition and database querying. This substitution maintains measurement precision through consistent algorithmic processing while improving productivity by performing analyses in seconds rather than minutes or hours.
3Measurement precision
If detailed ingredient information is collected for all food items, then measurement precision of nutritional data is improved, but loss of time in data collection increases
Solution Approach 1:
The system performs preliminary action by pre-collecting and storing nutritional information for thousands of ingredients in a comprehensive database before they are needed for analysis. When a food item is analyzed, the system simply queries this pre-prepared database rather than collecting ingredient data in real-time, thereby maintaining high measurement precision while eliminating time-consuming data collection during the analysis process.
Data Source
AI summary
A system can process an indication of user data, wherein the user data comprises a food item including at least one recipe having one or more ingredients, and a query, wherein the query is associated with at least one ingredient, and generate, based at least in part on the query, nutrition data associated with the at least one ingredient, wherein the nutrition data comprises preparation data, sourcing data, delivery data, and a list of nutrients for the at least one ingredient. The system can further estimate, based at least in part on the nutrition data associated with the least one ingredient, a nutritional score, then compare the estimated nutritional score to a threshold, and based on the compared nutritional score, generate one or more instructions to cause an indication of the nutritional score on a user device.