Correlation between Indoor Environmental Data and Biometric Parameters for the Impact Assessment of a Living Wall in a ZEB Lab

Rapidly Quantifying Interior Greenery Using 360° Panoramic Images

Many people spend the majority of their time indoors and there is emerging evidence that interior greenery contributes to human wellbeing. Accurately capturing the amount of interior greenery is an important first step in studying its contribution to human well-being. In this study, we evaluated the accuracy of interior greenery captured using 360° panoramic images taken within a range of different interior spaces. We developed an Interior Green View Index (iGVI) based on a K-means clustering algorithm to estimate interior greenery from 360° panoramic images taken within 66 interior spaces and compared these estimates with interior greenery measured manually from the same panoramic images. Interior greenery estimated using the automated method ranged from 0% to 34.19% of image pixels within the sampled interior spaces. Interior greenery estimated using the automated method was highly correlated (r = 0.99) with interior greenery measured manually, although we found the accuracy of the automated method compared with the manual method declined with the volume and illuminance of interior spaces. The results suggested that our automated method for extracting interior greenery from 360° panoramic images is a useful tool for rapidly estimating interior greenery in all but very large and highly illuminated interior spaces.

Psychophysiological Response According to the Greenness Index of Subway Station Space

This study proposed a plan for implementing a pleasant and healthy indoor landscape in subway station space. To this end, it established a 3D landscape model of the subway interior by reviewing previous studies on indoor landscape and the greenness index of indoor spaces. Moreover, it investigated and analyzed psychophysiological responses of users to environmental indoor landscape design in subway station space. Subway stations were classified as underground subway stations and ground subway stations according to the presence of natural light inflow. The greenness index of indoor spaces was also divided into four types of 0%, 10%, 15%, and 20%. Through this process, eight 3D landscape models of the subway interior were implemented. In addition, this study investigated psychophysiological responses of 60 male and female adults in their 20 s and 30 s using the models implemented. The investigation result was analyzed based on a frequency analysis, the χ2 test, T-test, one-way analysis of variance, and multidimensional scaling, which were performed in SPSS Statistics 25. The results of this study can be summarized as follows. First, physiological responses of research subjects were analyzed based on their prefrontal α wave asymmetric values. The analytic result showed that the environment where interior landscape was adopted produced more positive effects than the environment where interior landscape was not adopted. Second, psychological responses of research subjects were examined based on their greenness index preference, awareness of interior landscape area, attention restoration effect, and space images. The analytic result indicated that, among eight 3D landscape models of the subway interior, they preferred the model with the greenness index of 15% for underground subway stations. In addition, they preferred the model with the greenness index of 10% the most for ground subway stations.