Department of Applied and Pure Sciences (DiSPeA), University of Urbino Carlo Bo, 61029 Urbino, Italy.
Sensors (Basel). 2022 Mar 27;22(7):2558. doi: 10.3390/s22072558.
Indoor environmental quality (IEQ) has a high-level of impact on one's health and productivity. It is widely accepted that IEQ is composed of four categories: thermal comfort, indoor air quality (IAQ), visual comfort, and acoustic comfort. The main physical parameters that primarily represent these comfort categories can be monitored using sensors. To this purpose, the article proposes a wireless indoor environmental quality logger. In the literature, global comfort indices are often assessed objectively (using sensors) or subjectively (through surveys). This study adopts an integrated approach that calculates a predicted indoor global comfort index (P-IGCI) using sensor data and estimates a real perceived indoor global comfort index (RP-IGCI) based on questionnaires. Among the 19 different tested algorithms, the stepwise multiple linear regression model minimized the distance between the two comfort indices. In the case study involving a university classroom setting-thermal comfort and indoor air quality were identified as the most relevant IEQ elements from a subjective point of view. The model also confirms this findings from an objective perspective since temperature and CO merge as the measured physical parameters with the most impacts on overall comfort.
室内环境质量（IEQ）对人们的健康和生产力有很大的影响。人们普遍认为，IEQ 由四个类别组成：热舒适、室内空气质量（IAQ）、视觉舒适和声学舒适。主要的物理参数可以使用传感器来监测这些舒适类别。为此，本文提出了一种无线室内环境质量记录器。在文献中，全球舒适指数通常是通过传感器客观地（使用传感器）或主观地（通过调查）进行评估。本研究采用了一种综合方法，使用传感器数据计算预测的室内全球舒适指数（P-IGCI），并根据问卷估计实际感知的室内全球舒适指数（RP-IGCI）。在测试的 19 种不同算法中，逐步多元线性回归模型最小化了两个舒适指数之间的距离。在涉及大学教室环境的案例研究中，从主观角度来看，热舒适和室内空气质量被确定为最相关的 IEQ 因素。该模型也从客观角度证实了这一发现，因为温度和 CO 作为对整体舒适度影响最大的测量物理参数合并在一起。
