Personalized Scent Models for Cross-Reality Scent Delivery

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Solution Overview

Problem

Existing virtual, augmented, and cross-reality immersions fail to effectively incorporate the sense of smell, relying on generic scent banks that do not account for individual user preferences and experiences.

Innovation Solution

A scent module captures scent experiences and associated data to create personalized scent models, which are used to generate and optimize scent experiences in cross-reality sessions, considering user preferences, sensitivities, and context.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If a generic bank of scents is used in virtual reality, augmented reality, and/or cross-reality environments, then the system complexity is reduced and ease of operation is improved, but the adaptability to individual user preferences and experiences deteriorates

Engineering Contradiction:

Improveease of operationVSAvoidadaptability

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

The system performs preliminary actions by capturing scent experiences and associated data before generating the scent model. The scent module captures scents at various times along with contextual information (geographic location, user activity, preferences) and stores this data for later model generation, enabling personalized scent delivery without real-time complexity

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by using captured user scent experiences and preferences to continuously refine and update the personalized scent model. The scent model is generated and updated based on feedback from multiple scent experiences, allowing the system to adapt to individual user preferences while maintaining operational simplicity through automated model updates

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If personalized scent models are generated based on individual user data, then the adaptability to user preferences and experiences is improved, but the device complexity and data processing requirements increase

Engineering Contradiction:

ImproveadaptabilityVSAvoiddevice complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the scent delivery function into separate components: a scent module for capturing scent data, a scent modeling service for generating and updating the scent model, and a cross-reality application for utilizing the model. This segmentation distributes complexity across multiple modules rather than concentrating it in a single device

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a scent modeling service as an intermediary between data capture and scent delivery. This service acts as a mediator that processes captured scent experiences, generates the scent model, and provides it to the cross-reality application, thereby managing data processing complexity centrally rather than at the device level

Inventive Principle:

Principle #24Intermediary (Mediator)

3Reliability

If scent experiences are captured and analyzed to generate scent models, then the realism and immersion of cross-reality experiences are improved, but the loss of time for data collection and processing increases

Engineering Contradiction:

ImproverealismVSAvoidloss of time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary data collection by capturing scent experiences and contextual information in advance before the actual cross-reality session. This allows the scent model to be pre-generated and updated, reducing real-time processing delays and enabling immediate personalized scent delivery when needed

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The scent model is continuously updated based on new scent experiences and feedback data. The system maintains continuous data collection and model refinement, ensuring the scent model remains current and accurate without requiring complete reprocessing of all historical data, thus reducing time loss while maintaining realism

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS12417589B2Creating scent models and using scent models in cross-reality environments

Publication Date: 2025.09.16 AT&T INTELLECTUAL PROPERTY I L P

AI summary

Creating scent models and using scent models in cross-reality environments can include capturing experience data identifying a scent detected and a context in which the scent was detected. The experience data can be provided to a scent modeling service to generate a scent model that can represent perceived scents and perceived scent intensities for a user. The scent model can be used to generate cross-reality session data to be used in a cross-reality session presented by a cross-reality device. The cross-reality device can include a scent generator and can generate the cross-reality session using data obtained from the user device. The cross-reality device can generate a further scent during the cross-reality session based on the scent model.