Difference between revisions of "Publications:Virtual Testing for Smart Buildings"
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Latest revision as of 04:44, 26 June 2014
| Title | Virtual Testing for Smart Buildings |
|---|---|
| Author | Julien Bruneau and Charles Consel and Marcia O’Malley and Walid Taha and Wail Masry Hannourah |
| Year | 2012 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | Proceedings - 8th International Conference on Intelligent Environments, IE 2012 |
| DOI | http://dx.doi.org/10.1109/IE.2012.24 |
| Conference | IE'12 International Conference on Intelligent Environments 8th International Conference on Intelligent Environments, IE 2012, Guanajuato, Mexico, June 26-28 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:588230 |
| Abstract | Smart buildings promise to revolutionize the way we live. Applications ranging from climate control to fire management can have significant impact on the quality and cost of these services. However, smart buildings and any technology with direct effect on human safety and life mustundergo extensive testing. Virtual testing by means of computer simulation can significantly reduce the cost of testing and, as a result, accelerate the development of novel applications. Unfortunately, building physically-accurate simulation codes can be labor intensive.To address this problem, we propose a framework for rapid, physically-accurate virtual testing. The proposed framework supports analytical modeling of both a discrete distributed system as well as the physical environment that hosts it. The discrete models supported are accurate enough to allow the automatic generation of a dedicated programming framework that will help the developer in the implementation of these systems. The physical environment models supported are equational specifications that are accurate enough to produce running simulation codes. Combined, these two frameworks enable simulating both active systems and physical environments. These simulations can be used to monitor the behavior and gather statistics about the performance of an application in the context of precise virtual experiments. To illustrate the approach, we present models of Heating, Ventilating and Air-Conditioning (HVAC) systems. Using these models, we construct virtual experiments that illustrate how the approach can be used to optimize energy and cost of climate control for a building. © 2012 IEEE. |
