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Processing RGB Color Sensors for Measuring the Circadian Stimulus of Artificial and Daylight Light Sources

Trinh, Vinh Quang ; Babilon, Sebastian ; Myland, Paul ; Khanh, Tran Quoc (2022)
Processing RGB Color Sensors for Measuring the Circadian Stimulus of Artificial and Daylight Light Sources.
In: Applied Sciences, 2022, 12 (3)
doi: 10.26083/tuprints-00020523
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Processing RGB Color Sensors for Measuring the Circadian Stimulus of Artificial and Daylight Light Sources
Language: English
Date: 22 April 2022
Place of Publication: Darmstadt
Year of primary publication: 2022
Publisher: MDPI
Journal or Publication Title: Applied Sciences
Volume of the journal: 12
Issue Number: 3
Collation: 27 Seiten
DOI: 10.26083/tuprints-00020523
Corresponding Links:
Origin: Secondary publication DeepGreen
Abstract:

The three main tasks of modern lighting design are to support the visual performance, satisfy color emotion (color quality), and promote positive non-visual outcomes. In view of large-scale applications, the use of simple and inexpensive RGB color sensors to monitor related visual and non-visual illumination parameters seems to be of great promise for the future development of human-centered lighting control systems. In this context, the present work proposes a new methodology to assess the circadian effectiveness of the prevalent lighting conditions for daylight and artificial light sources in terms of the physiologically relevant circadian stimulus (CS) metric using such color sensors. In the case of daylight, the raw sensor readouts were processed in such a way that the CIE daylight model can be applied as an intermediate step to estimate its spectral composition, from which CS can eventually be calculated straightforwardly. Maximal CS prediction errors of less than 0.0025 were observed when tested on real data. For artificial light sources, on the other hand, the CS approximation method of Truong et al. was applied to estimate its circadian effectiveness from the sensor readouts. In this case, a maximal CS prediction error of 0.028 must be reported, which is considerably larger compared to daylight, but still in an acceptable range for typical indoor lighting applications. The use of RGB color sensors is thus shown to be suitable for estimating the circadian effectiveness of both types of illumination with sufficient accuracy for practical applications.

Uncontrolled Keywords: circadian effectiveness, circadian stimulus, RGB color sensors, daylight and artificial light sources, non-visual effects, human-centered lighting design
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-205233
Classification DDC: 600 Technology, medicine, applied sciences > 600 Technology
Divisions: 18 Department of Electrical Engineering and Information Technology > Adaptive Lighting Systems and Visual Processing
Date Deposited: 22 Apr 2022 12:06
Last Modified: 14 Nov 2023 19:04
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/20523
PPN: 499799631
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