Anthropomorphic Lighting Control via Self-Learning Persona
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Solution Overview
Problem
Current lighting systems lack the ability to provide a personalized and engaging user experience, as they typically respond to user interaction in a lifeless and inanimate manner, failing to adapt and learn from user behavior to modify their persona over time.
Innovation Solution
A lighting system comprising a source of light, a sensor, a storage device, and a processor that detects user activity and learns to adjust lighting conditions and outputs to create a perceptible persona, using anthropomorphic control to change physical characteristics, sound, and lighting parameters based on user interaction and historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional lighting control methods (simple switches, occupancy sensors, ambient light detectors) are used, then the system is easy to operate and has low device complexity, but the system lacks adaptability and cannot learn from user behavior to modify its persona
Solution Approach 1:
The lighting system performs self-learning by automatically observing user interactions and occupancy patterns over time, building a persona model without requiring explicit user programming. The system serves itself by autonomously adapting its behavior based on accumulated data from sensors and user responses.
Solution Approach 2:
The system implements continuous feedback loops where sensor data about user interactions (manual overrides, occupancy patterns, ambient light adjustments) is fed back to the processor, which updates the persona model accordingly. This feedback mechanism enables the system to learn and adapt its lighting behavior based on observed user preferences and behaviors.
2Ease of operation
If advanced speech recognition and gestural sensing technologies are incorporated, then the system gains better user interaction capabilities, but the device complexity and difficulty of detecting and measuring user intent increase
Solution Approach 1:
The lighting system integrates multiple sensing modalities (occupancy sensors, ambient light detectors, speech recognition, and gestural sensing) into a single unified platform. This multi-functional approach allows the system to detect various types of user interactions through different channels, making it easier for users to interact with the system in their preferred manner while the processor synthesizes inputs from all sensors to determine user intent.
3Adaptability or versatility
If portable user devices (remote controls, smartphones, tablets) are used for control, then the system gains remote control capability, but the device complexity increases and the system becomes more dependent on external devices
Solution Approach 1:
The system incorporates a communication interface that acts as an intermediary, enabling the lighting system to receive and process control commands from portable user devices (smartphones, tablets, remote controls) while maintaining its own autonomous decision-making capabilities. This intermediary layer allows seamless integration with external devices without making the lighting system dependent on them, as the processor can still independently interpret sensor data and adjust lighting based on observed user behavior.
Data Source
AI summary
An example of an intelligent lighting device or system is configured to control one or more parameters of light output, such as intensity, shape or distribution, color characteristics and position or orientation of light output (e.g. via a motorized luminaire control). The device or system may have other controllable output capability, e.g. display projection or audio. Sensors or other input devices are responsive to the user. Responsive to user input, the device or system, controls its light and any other output capabilities so as to present a defined persona to the user or other occupant(s) of a space illuminated by the intelligent lighting device or system.