Emotion Inference via Multi-Product Personality Profiles
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Solution Overview
Problem
Existing emotion inference devices face limitations in precision due to reliance on limited data from single products or devices, which restricts accurate emotion detection and inference, especially outside of specific usage contexts.
Innovation Solution
An emotion inference system that utilizes a combination of multiple products connected to a communication network to form an individual personality based on user data, incorporating machine learning and artificial intelligence to detect emotions with higher precision by comparing base and individual personalities, and adjusting actions accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If emotion inference is performed using data from a single product, then the device complexity is low, but the measurement precision of emotion detection is insufficient
Solution Approach 1:
The patent combines data from multiple products (vehicle, smartphone, wearable device) to create a comprehensive user profile that integrates various types of information including driving behavior, communication patterns, and physiological data. This merging of data sources significantly improves emotion detection precision by providing a multi-dimensional view of user emotional states.
Solution Approach 2:
The server is designed to handle multiple functions: collecting data from various products, creating user profiles, detecting emotions, and providing support actions. This multi-functional approach allows the system to improve measurement precision without proportionally increasing device complexity, as the same infrastructure serves multiple purposes.
2Measurement precision
If emotion inference is performed using data from multiple products, then the measurement precision of emotion detection is improved, but the device complexity increases
Solution Approach 1:
The server acts as an intermediary that centralizes data collection, processing, and emotion detection functions. By placing the complex processing logic in the server rather than in each individual product, the patent reduces the complexity burden on endpoint devices while still achieving high measurement precision through multi-source data integration.
Solution Approach 2:
The system segments the emotion detection functionality into separate modules: data collection by individual products, data aggregation and user profile creation by the server, emotion detection based on the user profile, and support action generation. This segmentation allows each component to be optimized independently, managing overall system complexity while maintaining high detection precision.
3Measurement precision
If a user profile is created based on long-term data from multiple products, then the emotion detection precision is improved, but the loss of time for data collection increases
Solution Approach 1:
The system performs preliminary actions by continuously collecting data from multiple products and maintaining an up-to-date user profile in advance. This pre-established profile containing user characteristics, behavior patterns, and emotional responses enables rapid emotion detection when needed, reducing the time loss associated with data collection during actual emotion inference events.
Data Source
AI summary
An emotion inference device and an emotion inference system that are capable of inferring a user's emotion with higher precision. A motorcycle includes an individual personality that is configured on the basis of information on a user from a plurality of products associated with the user, connected to a communication network, and including the motorcycle, an automobile, a rice cooker, a vacuum cleaner, a television receiver, and a refrigerator, the individual personality forms a base personality, and the motorcycle includes an emotion detecting section that detects an emotion.