Understanding the indoor environment through mining sensory data--A case study
Wu, S. and Clements-croome, D.
2007
Energy and Buildings, 39(11): 1183-1191
Wireless sensor network; Data mining; Clustering; Indoor environment
Wu, S. and Clements-croome, D., (2007), "Understanding the indoor environment through mining sensory data--A case study", Energy and Buildings, 39(11): 1183-1191.
| Abstract: |
| 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. |
|
|
This publication in whole or part might be found online. Check the sources on the related article below. Or use search engines on the web.
|
Related Concepts
|
|