A cloud-based system for dynamically capturing appliance usage relations

NCUIR > School of Management at National Central University > Department of Information Management > journal & Dissertation > Item 987654321/106199

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106199

Title:	A cloud-based system for dynamically capturing appliance usage relations
Authors:	陳以錚;Chen, Yi-Cheng;Chang, Shih-Hao;Liao, Wei-Hsun;Liu, Jianquan;Watanobe, Yutaka
Contributors:	管理學院資訊管理學系
Keywords:	Correlation;Data mining;Dynamic tests;Dynamical systems;Dynamics;Internet;Smart buildings;Strategy
Date:	2016-01-01
Issue Date:	2026-04-23 13:13:03 (UTC+8)
Publisher:	Inderscience Enterprises Ltd;Inderscience Publishers (IEL)
Abstract:	摘要： Nowadays, owing to the great advent of sensor technology, data can be collected easily. Mining Internet of Things (IoT) data has attracted researchers' attention owing to its practicability. Mining smart home data is one significant application in the IoT domain. Generally, the usage data of appliances in a smart environment are generated progressively; visualising how appliances are used from huge amount of data is a challenging issue. Hence, an algorithm is needed to dynamically discover appliance usage patterns. Prior studies on usage pattern discovery are mainly focused on discovering patterns while ignoring the dynamic maintenance of mined results. In this paper, a cloud-based system, Dynamic Correlation Mining System (DCMS), is developed to incrementally capture the usage correlations among appliances in a smart home environment. Furthermore, several pruning strategies are proposed to effectively reduce the search space. Experimental results indicate that the developed system is efficient in execution time and possesses great scalability. Subsequent application of DCMS on a real data set also demonstrates the practicability of mining smart home data. 其他題名： ijwgs 出版者： Inderscience Publishers (IEL) 出版日期： 2016 出處： International Journal of Web and Grid Services, 2016, Vol.12 (3), p.257-272 版權： Copyright © 2016 Inderscience Enterprises Ltd. 識別號： ISSN: 1741-1106 識別號： EISSN: 1741-1114 識別號： DOI: 10.1504/IJWGS.2016.079161
Appears in Collections:	[Department of Information Management] journal & Dissertation

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