Smart Light Color Control via Natural Language Intent
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Solution Overview
Problem
Traditional methods for controlling smart lights, such as smartphone applications and voice-controlled systems, are cumbersome and limited in their functionality, requiring multiple steps for basic operations and only allowing binary state changes like turning lights on or off, which restricts users' creative interactions with their smart lighting systems.
Innovation Solution
A natural language understanding (NLU) system is employed to interpret human intent through voice or text commands, determining object colors and light patterns, enabling users to control smart lights with more complex and creative commands, such as changing colors or emitting patterns, by utilizing a color database and learning customized commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If smartphone applications are used to control smart lights, then basic functions like changing brightness can be achieved, but the operation becomes cumbersome and time-consuming
Solution Approach 1:
The patent replaces manual smartphone application operations with voice-based natural language commands. Users can control smart lights by speaking commands like 'make the lights blue' instead of navigating through app interfaces, substituting mechanical/tactile interaction with acoustic interaction that is processed by speech-to-text and NLP systems.
Solution Approach 2:
The patent introduces natural language processing and speech recognition systems as intermediaries between the user and the smart light control system. This intermediary layer translates spoken commands into actionable control signals, eliminating the need for direct app interaction while maintaining precise control capabilities.
2Productivity
If simple voice commands are used to control smart lights, then the control process is speeded up, but the functionality is limited to binary states only
Solution Approach 1:
The patent implements a multi-functional voice control system that can handle diverse lighting commands beyond simple on/off states. The NLP system interprets various natural language expressions to control multiple parameters including color selection, brightness levels, and light patterns, making the system universally capable of handling different user intents through a single voice interface.
Solution Approach 2:
The patent enables dynamic changes of multiple light parameters through natural language commands. Instead of being limited to binary states, the system can adjust color temperature, brightness intensity, and operational patterns by interpreting parameters from user speech, allowing continuous adjustment across multiple dimensions of light control.
3Ease of operation
If traditional control methods are used, then the system is simple to operate, but creative interactions and desirable ways of using lights are limited
Solution Approach 1:
The patent transforms the static, predefined control interface into a dynamic, adaptive system. The NLP system learns from user interactions and adapts to individual preferences, allowing the control method to evolve and accommodate creative uses. The system dynamically interprets natural language to enable interactions that were not explicitly programmed, fostering creative experimentation with lighting.
Data Source
AI summary
According to one embodiment, in response to a text stream originated from a user at an electronic device (e.g., home device), a natural language processing (NLP) operation is performed on the text stream. An object described by the text stream is determined based on the NLP operation. One or more colors associated with the object are determined. A light control command is then transmitted from the electronic device to each of the smart lights to control a color of the smart light based on the one or more colors associated with the object, such that the smart lights are lit with the colors associated with the object. The text stream may be converted from a voice stream using a speech recognition process.