Sensory Environment Personalization for Activity-Specific Performance

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Solution Overview

Problem

Existing technologies fail to optimize sensory environments for individuals performing specific activities, leading to inefficiencies, inaccuracies, and increased stress due to suboptimal sensory conditions.

Innovation Solution

Systems and techniques that determine and provide an optimal sensory environment by receiving user data, selecting knowledge pyramids based on user attributes and desired outcomes, and generating an optimal sensory environment output that includes details for visual, auditory, tactile, olfactory, gustatory, and kinesthetic stimuli.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If a person performs an activity in a non-optimized sensory environment, then the person can complete the activity, but the performance efficiency and accuracy deteriorate and stress increases

Engineering Contradiction:

Improveactivity performance efficiencyVSAvoidactivity performance accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system changes sensory environment parameters (lighting intensity, color temperature, sound levels, ambient temperature) based on the specific activity type and user characteristics. For example, it adjusts lighting to different color temperatures for different times of day and activity types, and modifies sound levels based on task requirements, thereby optimizing both efficiency and accuracy simultaneously

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system proactively adjusts the sensory environment before the user begins an activity based on predicted needs. It analyzes the scheduled activity, user profile, and current environment to pre-configure optimal sensory conditions, preventing performance degradation before it occurs

Inventive Principle:

Principle #10Preliminary action

2Productivity

If the sensory environment is optimized for each specific activity, then performance outcomes improve, but the complexity of determining and adjusting the environment increases

Engineering Contradiction:

Improveactivity performance outcomeVSAvoidsensory environment adjustment system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system segments the sensory environment into distinct controllable components (lighting, sound, temperature, air quality) and manages each independently with specialized controls. This modular approach simplifies the overall complexity by breaking down the complex optimization problem into manageable subsystems that can be adjusted separately

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system automatically determines and adjusts optimal sensory environments without requiring manual user intervention. It uses machine learning models and sensors to autonomously analyze activity requirements and environmental conditions, then makes adjustments automatically, eliminating the need for complex user-configurable interfaces

Inventive Principle:

Principle #25Self-service

3Measurement precision

If detailed user data is collected to determine optimal sensory environment, then the accuracy of optimization improves, but the time and information required from the user increases

Engineering Contradiction:

Improveuser preference accuracyVSAvoiduser input time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system collects and processes user data in advance to build comprehensive user profiles before they need them. It pre-analyzes user responses, preferences, and behavioral patterns during onboarding and日常 usage, so that when optimization is needed, the system already has the information required to make accurate recommendations without requiring additional user input

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously gathers feedback from user responses, usage patterns, and performance outcomes to refine its understanding of user preferences. This ongoing feedback loop allows the system to improve measurement precision over time while requiring minimal additional user input, as the model becomes increasingly accurate through automated learning

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250076831A1Optimal sensory environment

Publication Date: 2025.03.06 HAMILTON ROGER MARK

AI summary

Systems and techniques for determining and providing an optimal sensory environment include steps of receiving a request for the optimal sensory environment, the request indicating the one or more users having optimal situation model attributes and including a desired outcome for a user activity to be performed by the one or more users, determining an optimal situation model by selecting one or more knowledge pyramids from a knowledge pyramid catalog based on the optimal situation model attributes of the one or more users and the desired outcome of the one or more users, determining the optimal sensory environment based on the determination of the optimal situation model, generating an optimal sensory environment output that comprises details of the optimal sensory environment, and sending the optimal sensory environment output to a source of the request for the optimal sensory environment.