Human Thermal Comfort Estimation in Indoor Space by Crowd Sensing
Human Thermal Comfort Estimation in Indoor Space by Crowd Sensing
复制标题
通过人群感知评估室内空间人体热舒适度
DOI：
10.1109/smartgridcomm.2016.7778736
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Teruo Higashino and Yoshiyuki Shimoda
中科院分区：
文献类型：
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作者：
Masao Chiguchi;Hirozumi Yamaguchi;Teruo Higashino and Yoshiyuki Shimoda
在最近的BEMS中，空调现在是高度自动化的，但为建筑物的居住者和参观者提供真正的热舒适仍然是具有挑战性的，因为用有限的传感器来感知整个3D空间是困难的。特别是，到目前为止，在这种自动化空调中还没有考虑人群的热效应。本文提出了一种考虑人群热效应的准确估计建筑人员热舒适性的方法。我们修改了PMV指数，这是一个著名的热舒适指数，以反映这种影响。对该模型进行了进一步的修正，减少了模型参数，重点考虑了其行为和环境特征。利用计算流体力学(CFD)模拟建立了新的PMV模型。该模型在实际的田间试验中得到了检验。
Air conditioning in recent BEMS is now being highly automated, but providing true thermal comfort to building occupants and visitors is still challenging due to difficulty of sensing whole 3D space with limited number of sensors. In particular, thermal effect by crowd of people has not been considered so far in such automated air conditioning. This paper presents a method to accurately estimate the thermal comfort of building occupants considering the thermal effect by human crowd. We modify the PMV index, an well-known thermal comfort index, to reflect such effect. This model is further modified to reduce the model parameters, focusing on the behavior and environmental characteristics. Computational fluid dynamics (CFD) simulations have been employed to build the new PMV model. The model was examined in a real field experiment.