Customized Food Badges Using Cohort and Biological Data

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Solution Overview

Problem

Existing methods for providing nutritional information about food items are limited in scope and accessibility, leading to incomplete or outdated data, which impedes informed dietary choices and adherence to health or sustainability standards.

Innovation Solution

A system and method for generating customized badges using advanced data analytics and machine learning algorithms to provide personalized and comprehensive information about menu items and food products, integrating cohort data, alimentary array data, and user biological data to create tailored digital badges.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If paper menus, product labels, or nutrition fact panels are used to provide nutritional information, then information is provided to consumers, but the information is limited in scope, accessibility, and may be outdated

Engineering Contradiction:

Improvecompleteness and accuracy of nutritional informationVSAvoidaccessibility and personalization of information

Core Design Contradiction:

Loss of informationVSAdaptability or versatility

Solution Approach 1:

The patent implements a dynamic digital badge system that updates in real-time based on changing cohort data, alimentary array data, and user biological data. Unlike static paper labels, the digital badges continuously adapt to reflect current nutritional information, certification status, and personalized user metrics, ensuring information remains current and relevant.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the parameters of information delivery by transitioning from fixed, standardized nutritional labels to dynamic, multi-dimensional digital badges that can be customized based on user preferences, biological data, and real-time food composition analysis. This allows the same food item to display different badge information for different users based on their specific dietary needs and health goals.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If traditional certification methods are used for menu items or products, then health or sustainability standards can be verified, but the process is labor-intensive and prone to errors or inconsistencies

Engineering Contradiction:

Improveaccuracy of health and sustainability certificationVSAvoidefficiency of certification process

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system implements self-service certification through automated data collection and analysis. The badge generation process automatically retrieves cohort data, alimentary array data, and user biological data, then uses machine learning algorithms to assess compliance with health and sustainability standards without requiring manual review, thereby eliminating human error and increasing processing efficiency.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual, mechanical certification processes with automated computational systems. Machine learning models and algorithms substitute for human reviewers, automatically analyzing food composition data, sourcing information, and nutritional content to generate certification badges, thereby dramatically increasing productivity while maintaining or improving reliability through consistent algorithmic application.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Ease of operation

If generic nutritional information is provided to all users, then information delivery is simple, but it does not account for individual dietary preferences, health goals, or ethical considerations

Engineering Contradiction:

Improvesimplicity of information deliveryVSAvoidpersonalization to user needs

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

The system applies local quality by customizing badge information for each individual user based on their specific biological data, dietary preferences, health goals, and ethical considerations. Rather than providing uniform information to all users, the digital badges are locally optimized for each user's unique needs, displaying relevant nutritional metrics, certification badges, and recommendations tailored to their personal context.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system performs preliminary action by collecting and analyzing user biological data, dietary preferences, and health goals before generating personalized badge information. This advance preparation allows the system to pre-customize badge content for each user, making personalized information delivery efficient and scalable without adding complexity to the actual information presentation.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250278768A1Systems and methods for generating a customized badge

Publication Date: 2025.09.04 KPN INNOVATIONS LLC

AI summary

A system and method for generating a customized badge is disclosed. The system comprises at least a processor and a memory to receive cohort data, receive alimentary array data, generate a cohort digital badge for the alimentary item of at least alimentary array data as a function of the cohort data, receive user data wherein the user data comprises biological extraction data, update the cohort digital badge to a user digital badge as a function of the biological extraction data, and display the user digital badge.