Inhalation Device Heating Control From User Evaluation Data
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Solution Overview
Problem
Existing inhalation devices lack the ability to customize aerosol heating temperature effectively, which affects user experience in terms of flavor preferences.
Innovation Solution
An information processing device that generates control information for inhalation devices based on a generation model trained with multiple data sets, including user evaluations and preferences, to optimize aerosol heating profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a generation model trained with multiple data sets is used to generate control information, then user experience and flavor satisfaction are improved, but device complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by collecting training data sets and training the generation model in advance. The model is pre-trained with multiple data sets including control information, evaluation sets, and modified control information before actual use. This allows the complex processing to be completed beforehand, reducing real-time complexity while maintaining high customization capability.
Solution Approach 2:
The generation model acts as an intermediary between raw user preferences and optimized control information. Instead of directly complex processing during operation, the model serves as a pre-trained mediator that translates user inputs into optimized heating profiles, simplifying the interaction while maintaining adaptability.
2Measurement precision
If multiple training data sets are collected and processed, then control information accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs the computationally intensive tasks of collecting multiple training data sets and training the generation model in advance, before actual operation. This preliminary processing allows the model to be pre-trained with comprehensive data, ensuring high accuracy while minimizing real-time processing time during actual use.
Solution Approach 2:
The patent replaces real-time mechanical processing of multiple data sets with a pre-trained generation model that uses learned patterns. Instead of processing multiple data sets during operation, the system substitutes this with a neural network model that has already internalized the relationships, significantly reducing processing time while maintaining accuracy.
Data Source
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AI summary
[Problem] To provide a mechanism capable of further improving the quality of user experience. [Solution] An information processing device comprising a control unit (116) that generates control information used by an inhalation device (100) that heats an aerosol source to generate aerosol based on control information specifying parameters related to the temperature for heating the aerosol source, wherein the control unit collects multiple training data sets, each including a combination of first control information, an evaluation set for the first control information, and second control information to be generated based on the first control information and the evaluation set for the first control information, and generates the control information used by the inhalation device of a first user based on a generation model of the control information learned from the collected multiple training data sets.