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Atmospheric pattern recognition of human activities on ubiquitous sensor network using data stream mining algorithms
Hang Yang1; Simon Fong2; Kyungeun Cho3; Junbo Wang3
2016-03
Source PublicationInternational Journal of Sensor Networks
ISSN1748-1279
Volume20Issue:3Pages:147-162
Abstract

Ubiquitous sensor networks gain tremendous popularity nowadays with practical applications such as detection of natural disasters. These applications collect real-time data about the atmospheric measurements from sensors that are installed in the field. In this paper we argue that traditional data mining methods run short of accurately analysing the activity patterns from the sensor data stream. We evaluate the successor of these algorithms which is known as data stream mining by using an example of an indoor ubiquitous sensor network. They measure various atmospheric values that are supposedly prone to the influences of different human activities. Superior result is shown in the experiment that runs on this empirical data stream. The contribution of this paper is on a comparative study between using traditional and data stream mining algorithms, in a scenario where different atmospheric patterns are to be recognised from streaming sensor data.

KeywordAtmospheric Pattern Recognition Data Stream Mining Ubiquitous Sensor Network
DOIhttps://doi.org/10.1504/IJSNET.2016.075364
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Telecommunications
WOS IDWOS:000372616300002
PublisherINDERSCIENCE ENTERPRISES LTD, WORLD TRADE CENTER BLDG, 29 ROUTE DE PRE-BOIS, CASE POSTALE 856, CH-1215 GENEVA, SWITZERLAND
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Citation statistics
Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Research Institute of Smart Grid, Nos. 6/8, Shui Jun Gang, Est Dongfeng Road, Yue Xiu District, Guangzhou, Guangdong, 510080, China
2.Department of Science and Technology, E11-4023, University of Macau, Avenida da Universidade, Taipa, Macau SAR
3.Department of Multimedia, Dongguk University 26, Pil-dong 3-ga, Jung-gu Seoul 100-715, Korea
4.University Business Innovation Center, University of Aizu, Japan
Recommended Citation
GB/T 7714
Hang Yang,Simon Fong,Kyungeun Cho,et al. Atmospheric pattern recognition of human activities on ubiquitous sensor network using data stream mining algorithms[J]. International Journal of Sensor Networks,2016,20(3):147-162.
APA Hang Yang,Simon Fong,Kyungeun Cho,&Junbo Wang.(2016).Atmospheric pattern recognition of human activities on ubiquitous sensor network using data stream mining algorithms.International Journal of Sensor Networks,20(3),147-162.
MLA Hang Yang,et al."Atmospheric pattern recognition of human activities on ubiquitous sensor network using data stream mining algorithms".International Journal of Sensor Networks 20.3(2016):147-162.
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