Smart Home Device Grouping via Linguistics Models
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Solution Overview
Problem
Smart home devices often require multiple commands to operate multiple accessory devices simultaneously, which can be inconvenient for users.
Innovation Solution
The system uses linguistics models, device-affinity models, and historical data to identify related accessory devices and recommend grouping them, allowing users to control multiple devices with a single command.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users control each smart home device independently, then device control precision is maintained, but user convenience deteriorates due to multiple commands required
Solution Approach 1:
The patent merges multiple accessory devices into a single device group that can be controlled by one command. The system analyzes usage patterns to identify which devices are frequently controlled together, then automatically creates groups (e.g., grouping lights in the same room) so users can control them simultaneously with a single voice command or button press, thereby improving ease of operation.
Solution Approach 2:
The system performs preliminary analysis of usage patterns to pre-identify and pre-group devices that are frequently controlled together. By analyzing historical control data beforehand, the system proactively creates optimal device groupings before users need to control them, eliminating the need for users to manually configure complex control relationships.
2Ease of operation
If the system automatically groups devices, then ease of operation improves, but measurement precision of device relationships deteriorates due to automated recommendations
Solution Approach 1:
The system continuously monitors and analyzes usage patterns to provide feedback on device grouping effectiveness. It tracks which devices are controlled together and uses this feedback to refine and adjust device groupings over time, ensuring that automated groupings remain accurate and relevant to actual user behavior while maintaining ease of operation.
Solution Approach 2:
The system provides automated device grouping recommendations but allows users to review and selectively accept or reject specific groupings. This partial automation approach maintains measurement precision by letting users verify device relationships while still providing the convenience of automated suggestions for obvious groupings.
Data Source
AI summary
Systems and methods for intelligent device grouping are disclosed. An environment, such as a home, may have a number of voice-enabled devices and accessory devices that may be controlled by the voice-enabled devices. One or more models, such as linguistics model(s) and/or device affinity models may be utilized to determine which accessory devices are candidates for inclusion in a device group, and a recommendation for grouping the devices may be provided. Device-group naming recommendations may also be generated and may be sent to users.