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Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback

An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer percepti...

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Detalles Bibliográficos
Autores principales: Liu, Haoting, Zhou, Qianxiang, Yang, Jin, Jiang, Ting, Liu, Zhizhen, Li, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336081/
https://www.ncbi.nlm.nih.gov/pubmed/28208781
http://dx.doi.org/10.3390/s17020321
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author Liu, Haoting
Zhou, Qianxiang
Yang, Jin
Jiang, Ting
Liu, Zhizhen
Li, Jie
author_facet Liu, Haoting
Zhou, Qianxiang
Yang, Jin
Jiang, Ting
Liu, Zhizhen
Li, Jie
author_sort Liu, Haoting
collection PubMed
description An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs) are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes.
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spelling pubmed-53360812017-03-16 Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback Liu, Haoting Zhou, Qianxiang Yang, Jin Jiang, Ting Liu, Zhizhen Li, Jie Sensors (Basel) Article An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs) are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes. MDPI 2017-02-09 /pmc/articles/PMC5336081/ /pubmed/28208781 http://dx.doi.org/10.3390/s17020321 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Haoting
Zhou, Qianxiang
Yang, Jin
Jiang, Ting
Liu, Zhizhen
Li, Jie
Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback
title Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback
title_full Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback
title_fullStr Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback
title_full_unstemmed Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback
title_short Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback
title_sort intelligent luminance control of lighting systems based on imaging sensor feedback
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336081/
https://www.ncbi.nlm.nih.gov/pubmed/28208781
http://dx.doi.org/10.3390/s17020321
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