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JAISE
2010

Predicting air quality in smart environments

12 years 9 months ago
Predicting air quality in smart environments
The pervasive sensing technologies found in smart environments offer unprecedented opportunities for monitoring and assisting the individuals who live and work in these spaces. As aspect of daily life that is often overlooked in maintaining a healthy lifestyle is the air quality of the environment. In this paper we investigate the use of machine learning technologies to predict CO2 levels as an indicator of air quality in smart environments. We introduce techniques for collecting and analyzing sensor information in smart environments and analyze the correlation between resident activities and air quality levels. The effectiveness of our techniques is evaluated using three physical smart environment testbeds.
Seun Deleawe, Jim Kusznir, Brian Lamb, Diane J. Co
Added 19 May 2011
Updated 19 May 2011
Type Journal
Year 2010
Where JAISE
Authors Seun Deleawe, Jim Kusznir, Brian Lamb, Diane J. Cook
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