Human-Centric Lighting With Ambient Light Feedback
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Solution Overview
Problem
Current human-centric lighting systems lack the ability to accurately adjust lighting parameters to influence human emotions due to the high cost and limitations of using functional Magnetic Resonance Imaging (fMRI) systems and electroencephalogram (EEG) methods, which are either too expensive or inconsistent in determining emotional states, making it difficult to create effective light recipes for emotional adjustment.
Innovation Solution
A system and method that uses fMRI to determine the blood oxygen-level dependent (BOLD) contrast responses and EEG brainwave patterns to establish a multispectral lighting situational database, allowing for the development of an intelligent human-centric lighting system that adjusts lighting parameters such as CCT, illuminance, and circadian action factors to match desired emotional responses, and employs ambient light sensors and smart lamp groups to dynamically adjust lighting based on environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fMRI system is used to determine emotional states for lighting control, then measurement precision of emotional response is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent creates a computational model that copies the emotional response detection capability of fMRI into software algorithms that analyze EEG data. Instead of using the expensive fMRI hardware directly, the system creates a digital representation of emotional states through machine learning models trained on EEG patterns, achieving similar measurement precision with much simpler equipment.
Solution Approach 2:
The patent replaces the complex mechanical and physical infrastructure of fMRI systems with computational and information-processing systems. By substituting hardware-based neural imaging with software-based EEG analysis and machine learning, the system achieves emotional detection capability without the associated complexity and cost of fMRI infrastructure.
2Device complexity
If EEG method is used to determine emotional states, then device complexity is reduced, but measurement precision and reliability of emotional determination deteriorate
Solution Approach 1:
The patent transforms the approach to EEG analysis by changing parameters from traditional single-metric evaluation to multi-dimensional spectral analysis. The system analyzes multiple frequency bands (delta, theta, alpha, beta, gamma waves) and their relationships, converting simple voltage measurements into comprehensive emotional state profiles through spectral density calculations and pattern recognition.
Solution Approach 2:
The patent combines multiple EEG signal processing techniques and analytical methods into a composite measurement approach. By integrating spectral analysis, time-frequency analysis, and machine learning classification, the system creates a composite measurement system that overcomes the limitations of individual methods and achieves high measurement precision with simple hardware.
3Adaptability or versatility
If traditional lighting systems are used without ambient light monitoring, then device complexity is reduced, but adaptability to environmental conditions and human emotional needs deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where ambient light sensors continuously monitor environmental lighting conditions and feed this information back to the lighting control system. The system adjusts lighting parameters based on this feedback, creating a closed-loop control that adapts to environmental changes and human emotional states automatically, enhancing adaptability without requiring complex manual intervention.
Solution Approach 2:
The patent designs a lighting system that performs multiple functions through integrated components. The same control system that adjusts lighting based on ambient light sensors also processes emotional state data from EEG analysis, coordinates multiple lighting zones, and manages different lighting scenarios. This multi-functionality approach enhances adaptability while avoiding the complexity of separate dedicated systems for each function.
Data Source
AI summary
A system for automatically adjusting the lighting parameters of a space is disclosed herein. The control module sets the target lighting parameters in the space and drive the smart lamp groups to illuminate by using the preset light recipe and to control the smart lamp groups to perform the illumination. The control module compares an ambient light detection value in the actual environment with the target value. When the ambient light detection value is not the same as the target value, the control module drives the ambient light sensor module performs a dimming procedure to the smart lamp groups. Wherein, the dimming procedure includes the step of adjusting an illuminance uniformity of the space according to the actual illuminance detected by the ambient light sensor module. After the calculation of the illuminance uniformity formula, the illuminance uniformity is adjusted to be the same as a target illuminance uniformity.