Dynamic User Interface Generation via Machine Learning

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Solution Overview

Problem

Current methodologies for user interface design and optimization rely on manual processes that fail to capture the full range of user interactions and responses in real-time, making it difficult to predict and adapt to user needs accurately and efficiently.

Innovation Solution

A system and method for dynamic user interface generation and management, which includes a computer device configured to capture user interaction data, prioritize it using a generated template, receive server feedback, and determine the current and optimal user interface states using machine-learning models, to generate an updated display data structure for a remote device.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual processes are used for user interface design and optimization, then design flexibility and control are maintained, but the ability to capture real-time user interactions and adapt efficiently deteriorates

Engineering Contradiction:

Improveability to adapt to user needsVSAvoidtime for interface design process

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system enables self-service by automatically generating and optimizing user interfaces through machine learning models that analyze user interaction data without requiring manual design intervention. The ML model autonomously adapts interface elements based on captured user behaviors, eliminating the need for continuous manual optimization while maintaining design quality.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical design processes with automated machine learning systems. Instead of designers manually analyzing and adjusting interfaces based on user feedback, the system uses ML algorithms to automatically process user interaction data and generate optimized interface configurations, substituting human cognitive work with computational processes.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If manual user research and usability testing are conducted, then design accuracy can be achieved, but the system cannot capture the full range of user interactions in real-time

Engineering Contradiction:

Improveaccuracy of user needs predictionVSAvoidrange of user interactions captured

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The system implements continuous capture and analysis of user interactions through automated tracking of user behaviors across the interface. Rather than conducting discrete usability studies, the ML model continuously processes user interaction data in real-time, maintaining an ongoing understanding of user needs and behaviors without interrupting normal usage.

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The system establishes a feedback loop where user interactions are continuously captured, analyzed by the machine learning model, and used to generate real-time optimizations. The model receives feedback from actual user behaviors and automatically adjusts interface elements accordingly, creating a closed-loop system that continuously improves based on measured user responses.

Inventive Principle:

Principle #23Feedback

3Ease of operation

If personalized and intuitive interfaces are provided, then user satisfaction and engagement are enhanced, but the complexity of designing and managing these interfaces increases

Engineering Contradiction:

Improveuser satisfaction and engagementVSAvoidcomplexity of interface design process

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system segments the complex task of interface design into manageable components handled by the machine learning model. The ML system breaks down interface optimization into discrete elements such as layout adjustments, element positioning, and interaction patterns, processing each segment independently based on relevant user data to create personalized interfaces without overwhelming design complexity.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250085990A1Method and system for systematic enhancement of human interaction capabilities via dynamic user interface management

Publication Date: 2025.03.13 THE LONDON OSTEOPOROSIS CLINIC LTD

AI summary

A system of dynamic user interface generation includes a computing device configured to capture user interaction data comprising osseous tissue data using the first input field, receive server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation, determine a current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data, select an optimal user interface state as a function of the prioritized user interaction data and the current user interface state and generate, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure for the remote device.