Simulation of virtual natural lighting solutions with a simplified view

Mangkuto, Rizki A.; Aries, Mbc Myriam; Loenen, Van; Hensen, Jlm Jan

doi:10.1177/1477153513476875

Cited by 9 publications

(2 citation statements)

References 12 publications

(16 reference statements)

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“…New light technologies have been developed in recent years that attempt to remedy this lack of windows with a view to nature. Primarily, technologies from the luminaire [25][26][27] and display industries 28,29 have been used for this purpose.…”

Section: Artificial Daylight Systemsmentioning

confidence: 99%

Room- and illumination-related effects of an artificial skylight

Canazei

Laner

Staggl

et al. 2015

Lighting Research & Technology

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An artificial skylight has been developed which aims at creating an impression of a daylight opening in the ceiling by means of an artificial sunspot and a blue sky with perceived infinite depth. It is the goal of this work to compare and quantify the perceived room atmosphere created by this artificial system with that created by a conventional lighting system. A total of 100 subjects participated in a randomized controlled study within which the short-term effects on room lighting- and room atmosphere-appearance were determined. Both the artificial skylight and the resulting room atmosphere were perceived as very natural and attractive. Thus, the first strong evidence for the expected positive effects of this artificial skylight was determined.

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Section: Artificial Daylight Systemsmentioning

confidence: 99%

Room- and illumination-related effects of an artificial skylight

Canazei

Laner

Staggl

et al. 2015

Lighting Research & Technology

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“…Recently, research has been conducted on a lighting technology that reproduced the color temperature cycle of natural light, which helped to maintain biological rhythms by delivering the benefits of natural light to the room [ 6 ]. Beyond the early technology that provided illuminance and color temperature that changed with time, another technology evolved to reproduce the characteristics of natural light more realistically [ 7 ]. A technology that can be applied to natural light simulation was introduced by developing a white LED capable of adjusting the color temperature (CCT) from 3615 K to 15,177 K through a “Phosphor Pattern” and a “Thermal-Modulating Optical Film” [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

A Method of Generating Real-Time Natural Light Color Temperature Cycle for Circadian Lighting Service

Lim

2023

Sensors

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The light intensity and color temperature of natural light periodically change and promote the circadian entrainment of the human body. In addition, the color temperature cycle of natural light that is unique to each region is formed by its location and geographic and environmental factors, affecting the health of its residents. Research on lighting and construction to provide the color temperature of real-time natural light has continued to provide the beneficial effect of natural indoor lighting. However, lighting technology that provides the real-time color temperature of natural light could not be realized since it is challenging to select a color temperature cycle zone due to abrupt color temperature changes at sunrise and sunset. Such drastic shifts cause an irregular measurement of color temperature over time due to general weather or atmospheric conditions. In a previous study, a method of generating a color temperature cycle using deep learning was introduced, but the performance at the beginning and end of the color temperature cycle was unreliable. Therefore, this study proposes generating a real-time natural light color temperature cycle for the circadian lighting service. The characteristics of the daily color temperature cycle were analyzed based on the measured natural light characteristics database, and a data set for learning was established. To improve the color temperature cycle generation performance, a deep learning (TadGAN) model was implemented by searching for the lowest point of the color temperature at the start and end points of the color temperature cycle and applying the boot and ending datasets to these points. The color temperature cycle zone was accurately detected in real-time in the experiment, and the generation performance of the color temperature cycle was maintained at the beginning and end of the color temperature cycle. The mean absolute error decreased by about 67%, confirming the generation of a more accurate real-time color temperature cycle.

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