In this study, the author estimates the hourly spatial brightness index in an office under daylighting control by Venetian blinds and examines new evaluation methods on the basis of annual variation in the values. A spatial brightness index (SB), which has been previously proposed by the author, is applied for the evaluations in this study. The 90% range of annual variation in SB values, which is the difference between the 95th percentile value and the 5th percentile value, is useful for comparing the influence of daylighting control on the spatial brightness variation. Also, evaluating the 50th percentile value of them results in a suitable target illuminance level for electric light control in each daylighting condition. These results indicate that the evaluation methods in this study are useful for designing daylighting or lighting control so that it will lead to a comfortable condition, which means not too bright and not too dark.

The authors have proposed a visibility estimation method using Contrast-Average (C-A) graphs based on the contrast profile method. C-A graphs can express three factors (luminance contrast, adaptation luminance, and object size) necessary for visibility estimations from luminance images. The objective of this study is to propose a visibility estimation method considering disability glare (impaired visibility caused by high luminance light sources in the visual field) using C-A graphs. Visibility evaluation experiments were conducted under various conditions with high luminance light sources presented in the visual field. In experiments, the changes of visibility threshold C values were examined. Estimations of visibility threshold C values were attempted by using the ‘equivalent veiling luminance’ of past studies. However, it was confirmed that the estimation method has limitations in its applicable range. Therefore, by focusing on increments of C values, a visibility estimation equation was established from the multiple regression analyses of increments of C values and the illuminance received from each of the segmented visual fields. In this study, the estimation equation was established from experimental results that used circular objects with a 20-minute diameter.

The authors have developed an intelligent lighting system, which improves the comfort of office workers and which reduces the energy consumption of the lights in an office. We propose a new algorithm for improving ease of introduction and performance of the system. The system classifies the lights into three groups: one group that is very close to a sensor, one that is close to it, and one that is far away. With these classifications, the system can efficiently achieve a well-lit state. The designers of the system empirically classify the conventions of the groups. However, a method for determining the optimum classification has not been studied. Therefore, this study determined how effective the classifications are for the time required to converge illuminance and power consumption. Finally, a method logically determining classifications is presented.