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Understanding the indoor environment through mining sensory data - A case study

Wu, S. and Clements-Croome, D. (2007) Understanding the indoor environment through mining sensory data - A case study. Energy and Buildings, 39 (11). pp. 1183-1191. ISSN 0378-7788

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To link to this article DOI: 10.1016/j.enbuild.2006.07.011

Abstract/Summary

A wireless sensor network (WSN) is a group of sensors linked by wireless medium to perform distributed sensing tasks. WSNs have attracted a wide interest from academia and industry alike due to their diversity of applications, including home automation, smart environment, and emergency services, in various buildings. The primary goal of a WSN is to collect data sensed by sensors. These data are characteristic of being heavily noisy, exhibiting temporal and spatial correlation. In order to extract useful information from such data, as this paper will demonstrate, people need to utilise various techniques to analyse the data. Data mining is a process in which a wide spectrum of data analysis methods is used. It is applied in the paper to analyse data collected from WSNs monitoring an indoor environment in a building. A case study is given to demonstrate how data mining can be used to optimise the use of the office space in a building.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Construction Management and Engineering > Innovative and Sustainable Technologies
ID Code:12452
Uncontrolled Keywords:wireless sensor network, data mining, clustering, indoor environment, ENERGY-CONSUMPTION, NETWORKS

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