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Sensors 2012, 12(10), 13458-13470; doi:10.3390/s121013458
Article

Building Environment Analysis Based on Temperature and Humidity for Smart Energy Systems

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Received: 18 July 2012; in revised form: 10 September 2012 / Accepted: 24 September 2012 / Published: 1 October 2012
(This article belongs to the Special Issue Ubiquitous Sensing)
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Abstract: In this paper, we propose a new HVAC (heating, ventilation, and air conditioning) control strategy as part of the smart energy system that can balance occupant comfort against building energy consumption using ubiquitous sensing and machine learning technology. We have developed ZigBee-based wireless sensor nodes and collected realistic temperature and humidity data during one month from a laboratory environment. With the collected data, we have established a building environment model using machine learning algorithms, which can be used to assess occupant comfort level. We expect the proposed HVAC control strategy will be able to provide occupants with a consistently comfortable working or home environment.
Keywords: building environment analysis; building energy efficiency; machine learning; smart energy system; occupant comfort building environment analysis; building energy efficiency; machine learning; smart energy system; occupant comfort
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Yun, J.; Won, K.-H. Building Environment Analysis Based on Temperature and Humidity for Smart Energy Systems. Sensors 2012, 12, 13458-13470.

AMA Style

Yun J, Won K-H. Building Environment Analysis Based on Temperature and Humidity for Smart Energy Systems. Sensors. 2012; 12(10):13458-13470.

Chicago/Turabian Style

Yun, Jaeseok; Won, Kwang-Ho. 2012. "Building Environment Analysis Based on Temperature and Humidity for Smart Energy Systems." Sensors 12, no. 10: 13458-13470.


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