Next Article in Journal
A Novel CD105 Determination System Based on an Ultrasensitive Bioelectrochemical Strategy with Pt Nanoparticles
Next Article in Special Issue
Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks
Previous Article in Journal
Efficient Text Encryption and Hiding with Double-Random Phase-Encoding
Previous Article in Special Issue
WikiSensing: An Online Collaborative Approach for Sensor Data Management
Sensors 2012, 12(10), 13458-13470; doi:10.3390/s121013458
Article

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

*  and
Received: 18 July 2012 / Revised: 10 September 2012 / Accepted: 24 September 2012 / Published: 1 October 2012
(This article belongs to the Special Issue Ubiquitous Sensing)
View Full-Text   |   Download PDF [5293 KB, uploaded 21 June 2014]   |   Browse Figures

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.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote
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.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here

Comments

Cited By

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert