Emotion-Aware Action Control Using User State Prediction
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Solution Overview
Problem
Existing technologies struggle to execute appropriate actions corresponding to user emotions effectively.
Innovation Solution
An electronic device that includes a storage unit for user emotion data, an estimation unit for emotion prediction, a prediction unit for future emotional states, and a control unit for executing actions that promote positive emotional experiences, while considering user privacy and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user emotion data is stored and processed to execute appropriate actions, then the appropriateness of executed actions is improved, but the device complexity increases due to multiple units (storage, estimation, prediction, control)
Solution Approach 1:
The system is divided into distinct functional units: storage unit for emotion data, estimation unit for current emotion analysis, prediction unit for future emotion forecasting, and control unit for action execution. This segmentation allows each unit to specialize in specific tasks, improving overall reliability while managing complexity through modular design.
Solution Approach 2:
The prediction unit forecasts future emotional states in advance before actual interactions occur. By preparing prediction data beforehand, the control unit can select appropriate actions proactively, improving the timeliness and appropriateness of responses without requiring complex real-time processing during critical moments.
2Adaptability or versatility
If user emotion data is collected and processed, then the personalization of user experience is improved, but the security and privacy protection requirements increase
Solution Approach 1:
The storage unit maintains separate emotion data records for different users, with each user's data processed independently. This localized data handling approach enables personalized action selection for each user while minimizing cross-user privacy risks, as each user's emotional profile is kept distinct and processed individually.
Solution Approach 2:
The system implements predetermined privacy protection measures and security protocols before data processing occurs. By establishing security frameworks in advance, the system protects user information from potential breaches while still enabling personalized emotion-based interactions.
3Measurement precision
If continuous emotion monitoring is performed to predict future emotional states, then the accuracy of action selection is improved, but the energy consumption increases
Solution Approach 1:
The estimation unit performs emotion analysis at periodic intervals rather than continuously, balancing monitoring accuracy with energy conservation. This periodic sampling approach captures sufficient emotional state changes for accurate prediction while significantly reducing computational load and power consumption compared to continuous monitoring.
Solution Approach 2:
The system monitors only the most relevant emotional indicators necessary for accurate prediction, rather than analyzing all possible emotional parameters. This partial monitoring approach maintains sufficient prediction accuracy while minimizing the energy required for data collection and processing.
Data Source
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AI summary
An electronic device according to an embodiment includes a storage unit that stores, as data for deciding an emotion of each user, a relationship among an expression, a voice, a gesture, biometric information, and the emotion, for each user as a database.