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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering , Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 8 , ISSUE 2 (June 2015) > List of articles


Yi Zhao * / Valentin Gies / Jean-Marc Ginoux

Keywords : Wireless Sensors Network, Back-propagation Neural Network, Thermal Modeling, Linear Approximations, Effective Indoor Thermal Time Constant

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 2, Pages 869-895, DOI:

License : (CC BY-NC-ND 4.0)

Received Date : 15-January-2015 / Accepted: 27-March-2015 / Published Online: 01-June-2015



In this paper, we proposed to use the Efficient Indoor Thermal Time Constant (EITTC) to characterize the indoor thermal response in old buildings. Accordingly, a low cost, energy-efficient, wide-applicable indoor thermal modeling solution is developed by combining Wireless Sensor Network (WSN) and Artificial Neural Network (ANN). Experiments on both prototype and building room showed consistent results that the combination of WSN and ANN can provide accurate indoor thermal models. A linear approximation of these models makes it possible to estimate the EITTC of building room. Statistical computations confirmed these estimations by showing a strong correlation between the
model's predicted EITTC and measured data. Thus the indoor thermal response under different indoor/outdoor conditions can be characterized. Finally, a model based adaptive heating Start/Shut control method is proposed and tested, with which, direct energy saving is achieved.

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