Smart Home Dialog Engine for Multi-Modal Device Control
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Solution Overview
Problem
Existing home automation systems have complex and difficult-to-use user interfaces, lacking multi-modal interaction capabilities and the conversion of input signals into location-specific normalized queries, which hinders seamless human-device interaction.
Innovation Solution
A multi-modal dialog interaction engine that processes input signals from various modalities (voice, images, gestures, etc.) and converts them into semantic queries using a domain-specific and location-specific vocabulary, enabling intuitive control of home devices through a unified interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional user interfaces are used for home automation control, then device control functionality is achieved, but user interface complexity and difficulty of use increases
Solution Approach 1:
The patent replaces traditional mechanical/physical interfaces (buttons, switches, dials) with voice-based acoustic input. Users speak natural language commands instead of manually operating complex physical controls, substituting mechanical interaction with acoustic field interaction. This resolves the contradiction by simplifying user operation while maintaining comprehensive device control capability.
Solution Approach 2:
The patent introduces a voice recognition system and natural language processing intermediary between the user and the home automation devices. This intermediary translates spoken commands into device control signals, shielding users from the underlying system complexity while enabling sophisticated device control. The intermediary layer handles the complexity internally while presenting a simple voice-based interface to users.
2Measurement precision
If multi-modal interface with location-specific vocabulary is implemented, then interaction accuracy and relevance is improved, but system complexity increases
Solution Approach 1:
The patent implements location-specific vocabulary and context-aware processing tailored to each user's environment. The system learns and adapts to local preferences, device placements, and usage patterns specific to each household. This allows accurate interpretation of voice commands in context while managing complexity through localized adaptation rather than universal complexity.
Solution Approach 2:
The system performs preliminary learning and vocabulary building during initial setup and ongoing usage. It pre-processes and learns location-specific terms, device names, and user preferences before they are needed for command interpretation. This preliminary action reduces the complexity of real-time processing by having the system already prepared with context-specific knowledge.
Data Source
AI summary
A smart home interaction system is presented. It is built on a multi-modal, multithreaded conversational dialog engine. The system provides a natural language user interface for the control of household devices, appliances or household functionality. The smart home automation agent can receive input from users through sensing devices such as a smart phone, a tablet computer or a laptop computer. Users interact with the system from within the household or from remote locations. The smart home system can receive input from sensors or any other machines with which it is interfaced. The system employs interaction guide rules for processing reaction to both user and sensor input and driving the conversational interactions that result from such input. The system adaptively learns based on both user and sensor input and can learn the preferences and practices of its users.