Personalized Food Element Classification via Physiological Data
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Solution Overview
Problem
Individuals face challenges in determining which food elements to acquire that align with their unique physiological needs, as existing methods often lead to sensory overload and fail to account for personal responses to food elements.
Innovation Solution
A system and method utilizing a processor to receive a food element descriptor, retrieve user physiological data, and employ a machine-learning algorithm to identify constitutional enhancing and advancing food elements, displaying these on a graphical user interface for informed decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive food element information is provided to users, then users can make informed decisions about their dietary choices, but users experience sensory overload and difficulty understanding labels
Solution Approach 1:
The system segments comprehensive food element information into personalized subsets based on individual physiological data. The processor divides the large set of food element descriptors into relevant and irrelevant categories for each user, presenting only the segmented information that matters to that specific user's health goals and physiological state.
Solution Approach 2:
The system applies local quality by customizing information presentation according to each user's specific physiological needs. Different users receive different levels and types of food element information based on their individual constitutional enhancing and advancing food elements, rather than providing uniform information to all users.
2Ease of operation
If generic food recommendations are provided, then information can be easily communicated to all users, but individual physiological responses to food elements are not accounted for
Solution Approach 1:
The system performs preliminary action by collecting and analyzing user physiological data before providing food recommendations. The processor pre-processes individual physiological information to identify constitutional enhancing and advancing food elements, so that when food element descriptors are presented, they are already tailored to each user's specific needs rather than using generic recommendations.
Solution Approach 2:
The system applies dynamics by making food recommendations adaptable and changeable based on individual physiological states. The personalized guidance dynamically adjusts according to each user's unique constitutional enhancing and advancing food elements, allowing the system to versatilely accommodate different physiological responses to food elements.
Data Source
AI summary
A system for informing food element decisions in the acquisition of edible materials from any source. The system includes a processor coupled to a memory configured to receive from a user client device a food element descriptor uniquely identifying a particular food element. The system retrieves from a physiological database at least an element of physiological data. The system identifies using at least an element of physiological data and a machine-learning algorithm user constitutional enhancing food elements and user constitutional advancing food elements. The system classifies using a food element classifier a food element descriptor. The system displays on a graphical user interface a constitutional enhancing food element or a constitutional advancing food element.