Integrated Predicted Mean Vote Sensing System Using MEMS Multi-Sensors for Smart HVAC Systems

Izhar, Xiaoyi Wang, Wei Xu, Hadi Tavakkoli, Zhikun Yuen, Xiaofang Shan, Yi Kuen Lee*

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

14 引用 (Scopus)

摘要

In this article, we report a predicted mean vote (PMV) index based micro Human Thermal Comfort Sensing (HTCS) system with multiple MEMS sensors. The system consists of a wireless multi-sensor (CMOS MEMS air velocity, MEMS relative humidity (RH) and MEMS air temperature) module to measure three environmental parameters and a smartphone App with a novel motion analytics algorithm (for estimation of metabolic rate) and personal factors (clothing insulation) input. While the majority of the reported HTCS systems are bulky and takes only environmental parameters into consideration, the developed system utilizes MEMS technology for sensors' fabrication and measures the essential environmental and human factors involved to compute human thermal comfort. Furthermore, the developed HTCS system shows much better accuracy (±0.13) than its commercial and reported counterparts (±0.17 to ±0.4). Moreover, the packaged HTCS system is placed in a testing room to monitor the PMV. The experimental results indicated that our micro PMV-based HTCS system is promising for smart HVAC system integration in the era of the Internet of Things.

源语言英语
文章编号9311141
页(从-至)8400-8410
页数11
期刊IEEE Sensors Journal
21
6
DOI
出版状态已出版 - 15 3月 2021
已对外发布

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