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Article: A learning model of intelligent home

TitleA learning model of intelligent home
Authors
KeywordsAutomation
Buildings
Learning
Issue Date2006
PublisherEmerald Group Publishing Limited. The Journal's web site is located at http://www.emeraldinsight.com/f.htm
Citation
Facilities, 2006, v. 24 n. 9-10, p. 365-375 How to Cite?
AbstractPurpose - This paper aims to review the extant intelligent home specifications and put forward a new dimension for the specifications of intelligent home (IHS). Design/methodology/approach - This study adopts a learning (bottom-up) algorithm which emphasizes the importance of learning and adaptability to the dynamic environmental changes in the IHS. Findings - The study finds that the intelligent home has been characterized by automation, integration of facilities and communication. However, it is contended here that an intelligent home specification in such a hard-wired (top-down) approach cannot be sustained in the light of the continuous changes of user requirements. Hence, adaptation to users' needs must be encompassed in a system of home intelligence. Research limitations/implications - This study provides a framework for all stakeholders to work for a common goal and a platform for benchmarking the performance of intelligent home in the long run. Originality/value - This is the first to adopt the learning (bottom-up) algorithm in defining home intelligence. © Emerald Group Publishing Limited.
Persistent Identifierhttp://hdl.handle.net/10722/168746
ISSN
2015 SCImago Journal Rankings: 0.371
References

 

DC FieldValueLanguage
dc.contributor.authorYiu, CYen_HK
dc.contributor.authorYau, Yen_HK
dc.date.accessioned2012-10-08T03:32:03Z-
dc.date.available2012-10-08T03:32:03Z-
dc.date.issued2006en_HK
dc.identifier.citationFacilities, 2006, v. 24 n. 9-10, p. 365-375en_HK
dc.identifier.issn0263-2772en_HK
dc.identifier.urihttp://hdl.handle.net/10722/168746-
dc.description.abstractPurpose - This paper aims to review the extant intelligent home specifications and put forward a new dimension for the specifications of intelligent home (IHS). Design/methodology/approach - This study adopts a learning (bottom-up) algorithm which emphasizes the importance of learning and adaptability to the dynamic environmental changes in the IHS. Findings - The study finds that the intelligent home has been characterized by automation, integration of facilities and communication. However, it is contended here that an intelligent home specification in such a hard-wired (top-down) approach cannot be sustained in the light of the continuous changes of user requirements. Hence, adaptation to users' needs must be encompassed in a system of home intelligence. Research limitations/implications - This study provides a framework for all stakeholders to work for a common goal and a platform for benchmarking the performance of intelligent home in the long run. Originality/value - This is the first to adopt the learning (bottom-up) algorithm in defining home intelligence. © Emerald Group Publishing Limited.en_HK
dc.languageengen_US
dc.publisherEmerald Group Publishing Limited. The Journal's web site is located at http://www.emeraldinsight.com/f.htmen_HK
dc.relation.ispartofFacilitiesen_HK
dc.subjectAutomationen_HK
dc.subjectBuildingsen_HK
dc.subjectLearningen_HK
dc.titleA learning model of intelligent homeen_HK
dc.typeArticleen_HK
dc.identifier.emailYiu, CY: ecyyiu@hkucc.hku.hken_HK
dc.identifier.authorityYiu, CY=rp01035en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1108/02632770610677646en_HK
dc.identifier.scopuseid_2-s2.0-33745615810en_HK
dc.identifier.hkuros121455-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33745615810&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume24en_HK
dc.identifier.issue9-10en_HK
dc.identifier.spage365en_HK
dc.identifier.epage375en_HK
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridYiu, CY=9248825800en_HK
dc.identifier.scopusauthoridYau, Y=12806101900en_HK
dc.identifier.citeulike760886-

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