An effect of numerical data through monitoring device on perception of indoor air quality

Despite a growing interest in indoor air quality (IAQ), a scientific basis for human self-awareness and understanding of IAQ has yet to be provided. To fill this research gap, this study examined the effect of numerical data through monitoring devices on the occupants’ perception of IAQ. Therefore, an experiment was planned to evaluate the perceived IAQ based on a self-report questionnaire among ten subjects in an office environment. The experiment was divided into three sessions, with a classification model built for each session using automated machine learning and then derived variable importance for predictor variables. Results showed that when occupants did not check the numerical data of IAQ factors, they tended to perceive IAQ based on the perceived thermal comfort. In addition, occupants made a biased judgment of the current IAQ condition based on the past perceived IAQ checked 30 min ago. When occupants checked the numerical data of IAQ factors, they responded more sensitively to IAQ factors than to thermal environment factors when perceiving IAQ conditions. The results of this study confirmed that real-time numerical data of IAQ factors measured using monitoring devices are essential for occupants to perceive and judge the current IAQ clearly.