Meal Recommendation System Using Effective Age and Food Tolerance
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Solution Overview
Problem
Accurate identification of compatible meal options is challenging due to the complexity of analyzing multiple user demands and large quantities of data, particularly in relating user biological markers to food tolerance scores.
Innovation Solution
A system and method that utilize a processor to receive user dietary preferences, calculate effective age measurements using machine learning, and determine food tolerance scores based on biological markers, identifying compatible meal options that include supplements by correlating user body measurements with food tolerance scores through a food analysis module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple user demands and biological markers are analyzed to identify compatible meal options, then the accuracy of meal recommendations is improved, but the complexity of data analysis and processing increases
Solution Approach 1:
The system segments the complex meal recommendation task into distinct functional modules: a biological marker analysis module that processes user health data, a food database module that stores nutritional information, and a meal generation module that combines these inputs. This segmentation allows each module to handle specific aspects of the analysis independently, reducing overall system complexity while maintaining high accuracy through specialized processing in each segment.
Solution Approach 2:
The patent introduces an intermediary processing layer that translates complex biological marker data into simplified compatibility scores with food items. This intermediary module acts as a mediator between the raw biological data and the final meal recommendations, making the complex analysis results interpretable and actionable without requiring the entire system to handle the full complexity of raw data processing.
2Reliability
If large quantities of data are analyzed to locate compatible meal options, then the completeness of nutritional assessment is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and categorizing food items in the database according to their nutritional properties and compatibility profiles before they are needed for meal recommendations. Biological markers are also pre-analyzed and stored in standardized formats. This preliminary preparation ensures that when meal recommendations are generated, the system can quickly retrieve and match pre-processed data without performing complex analysis in real-time, thus maintaining completeness while reducing processing time.
3Adaptability or versatility
If user-specific biological markers are correlated with food tolerance scores, then the personalization of dietary recommendations is improved, but the difficulty of detecting and measuring tolerance levels increases
Solution Approach 1:
The patent replaces direct mechanical or laboratory-based measurement of food tolerance with a computational system that uses machine learning algorithms to infer tolerance levels from biological marker data. Instead of requiring complex physical or chemical measurements of tolerance, the system substitutes these with automated data processing and pattern recognition, making the measurement process more accessible and scalable while maintaining personalization through individualized algorithmic analysis.
Data Source
AI summary
A system for identifying compatible meal options. The system including a processor configured to receive a user selection identifying a dietary preference and select a meal option as a function of the dietary preference. The processor further configured to calculate a user effective age measurement using a first machine learning process trained with training data correlating a plurality of biological markers to a plurality of effective age measurements. The processor further configured to determine a food tolerance score as a function of the user effective age, wherein the food tolerance score relates to a user ability to tolerate a food item, wherein the food item is a supplement. The processor also configured to identify a plurality of compatible meal options as a function of the food tolerance score, wherein at least a compatible meal option of the plurality of compatible meal options includes at least a supplement.