The cyclic properties of natural light give an effect on human health, and the intensity and wavelength of natural light are known to be important factors to maintain human circadian rhythm. However, modern people who stay longer indoors are exposed to the fixed light environment of artificial lighting, resulting in circadian rhythm imbalance and subsequent sleep disturbances. In this paper, a LED lighting system that reproduces the natural light properties with day cycle is proposed to support the human circadian rhythm. To do this, the properties of natural light that keep changing were measured and analyzed every hour, and then the color temperature and wavelength ratio of natural light over time were reproduced by controlling each channel of LED lighting. In order to confirm the effect of the proposed lighting that supports maintaining a circadian rhythm, a confirmation experiment of melatonin change in the animal body was performed. The experimental results showed that the rats irradiated with the proposed lighting had an increased melatonin level by more than around 20ng/ml compared to the rats irradiated with the general lighting, thus confirming that the proposed lighting had a positive effect on sustaining the circadian rhythm.
The characteristics of natural light are mostly collected through specialized measuring equipment, such as a spectroradiometer, and some suggested measurement methods through a small RGB sensor. However, specialized measuring equipment presents difficulty in its high cost, and the RGB-sensor-based method has the limitation of being unable to measure the wavelength characteristics of natural light that are needed to implement lighting that supports circadian rhythms. This paper presents a method for calculating the short-wavelength-ratio-based color temperature of natural light in real time. First, an analysis of the correlation between the characteristics of natural light collected through a spectroradiometer was performed to determine the factors that were needed to accurately measure the color temperature of natural light. Then, the short-wavelength ratio of natural light was calculated through chromaticity coordinates (x and y), which are output values of the RGB sensor, and an equation for calculating the color temperature of natural light was derived through the short-wavelength ratio. Furthermore, after producing an RGB-sensor-based device, the derived equation was applied to calculate the color temperature of real-time natural light that reflects the wavelength characteristics. Then, as a result of the performance evaluation of the proposed method, the color temperature of natural light was accurately calculated within 1% of the average error rate.
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