Home Scene Automation Using Learned Device Control Patterns
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Solution Overview
Problem
Existing home control systems require manual interaction with physical devices or remote controls for activating or adjusting home environments, lacking automation for scene creation based on user habits and preferences.
Innovation Solution
A distributed system of home device controllers that utilize touch and voice inputs, machine learning, and historical data analysis to recognize user patterns and automatically execute scenes based on triggers such as time, context, and device activation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual interaction with physical devices or remote controls is used for activating or adjusting home environments, then users can directly control home systems, but the process requires significant user effort and time
Solution Approach 1:
The system performs scene creation automatically without requiring user intervention. The controller monitors device states and environmental conditions, then autonomously activates or deactivates devices to create scenes based on learned user preferences and current context, eliminating manual operation requirements
Solution Approach 2:
The system pre-learns user preferences and habitual scene creation patterns through machine learning algorithms. By analyzing historical data and user interactions, the system prepares scene configurations in advance, enabling automatic execution when triggering conditions are met, thus saving user time and effort
2Extent of automation
If automated scene creation using machine learning is implemented, then user convenience is enhanced, but system complexity increases
Solution Approach 1:
The controller is designed as a multi-functional device that combines traditional device control capabilities with machine learning processing, historical data analysis, and automatic scene creation functions. This universal approach consolidates multiple functions into a single device, managing system complexity through integration rather than proliferation of separate components
Solution Approach 2:
The system introduces an intelligent controller as an intermediary between users and home devices. This mediator handles the complexity of machine learning algorithms, data analysis, and automated decision-making, while presenting a simplified interface to users and standard control protocols to devices, thus isolating and managing system complexity
Data Source
AI summary
A distributed system of home device controllers can control a set of home devices. A home device controller of the system can determine a set of configurations for a set of home devices being repeatedly configured by a user. The controller can automatically display a selectable feature indicating a suggested scene corresponding to the set of configurations for the set of home devices. The system can receive one or more inputs to select the suggested scene, and based at least in part on the one or more inputs, associate the suggest scene with a set of triggers. In response to detecting the set of triggers, the controller can automatically transmit a set of commands that correspond to the suggested scene to the set of home devices to execute the suggested scene.