Electronic Device Contextual Behavior Prediction Through User Feedback
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Solution Overview
Problem
Existing IoT devices struggle to accurately suggest behavior patterns tailored to individual user situations without causing errors due to incorrect situation recognition.
Innovation Solution
An electronic device that obtains situation information, determines behavior patterns, and updates mapping relationships based on user inputs to virtual buttons, allowing for refined pattern adjustments through reliability value comparisons and error prevention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the device automatically determines behavior patterns based on situation information, then the automation level is improved, but the reliability deteriorates due to potential errors in situation recognition
Solution Approach 1:
The patent implements a feedback mechanism where the device provides situation information and proposed behavior patterns to the user, and receives user feedback through virtual buttons. The user can confirm the situation information, correct errors, or adjust the proposed behavior patterns. This feedback loop allows the system to learn from user corrections and improve its situation recognition accuracy over time, thereby resolving the contradiction between automation and reliability.
Solution Approach 2:
The device performs preliminary actions by pre-determining behavior patterns based on recognized situations before presenting them to the user. The system proactively identifies situations using sensors and historical data, and pre-formulates appropriate behavior patterns, then presents these for user confirmation. This preliminary action reduces the need for real-time user intervention while maintaining high reliability through user verification.
2Adaptability or versatility
If the device provides detailed feedback for each factor in behavior pattern determination, then the adaptability is improved, but the device complexity increases
Solution Approach 1:
The patent segments the behavior pattern determination process into distinct factors or elements. Each factor (such as situation type, time, location, user state) is separately identified and presented to the user with its corresponding reliability value. This segmentation allows the user to provide targeted feedback on specific factors without overwhelming them with the entire complex decision process, thereby improving adaptability while managing complexity through structured presentation.
3Measurement precision
If the system updates mapping relationships based on user input, then the measurement precision is improved, but the loss of time increases due to feedback collection
Solution Approach 1:
The system performs self-service by automatically updating its mapping relationships between situation information and behavior patterns based on user feedback. The device learns from user corrections and confirmation patterns, continuously refining its situation recognition accuracy without requiring manual reconfiguration. This self-service mechanism improves measurement precision over time while minimizing the time loss associated with feedback collection, as the system operates autonomously in the background.
Data Source
AI summary
The present disclosure relates to an electronic device and control method. The method includes obtaining situation information through a pre-defined situation recognition method; determining any one of a plurality of behavior patterns as a predicted behavior pattern on the basis of the situation information; generating a main query on the basis of at least one of the situation information and the predicted behavior pattern; outputting, on a display, a first virtual button corresponding to the situation information, a second virtual button corresponding to the predicted behavior pattern, and the main query; on the basis of receiving a negative response to the main query, activating the first virtual button and second virtual button; and on the basis of a user input on the first virtual button or second virtual button, updating any one of a mapping relationship between the situation information and the predicted behavior pattern, and the situation recognition method.