Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104550
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorWong, Ben_US
dc.creatorHo, GTSen_US
dc.creatorTsui, Een_US
dc.date.accessioned2024-02-05T08:51:01Z-
dc.date.available2024-02-05T08:51:01Z-
dc.identifier.issn0263-5577en_US
dc.identifier.urihttp://hdl.handle.net/10397/104550-
dc.language.isoenen_US
dc.publisherEmerald Publishing Limiteden_US
dc.rights© Emerald Publishing Limited. This AAM is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher.en_US
dc.rightsThe following publication Wong, B., Ho, G. T. S., & Tsui, E. (2017). Development of an intelligent e-healthcare system for the domestic care industry. Industrial Management and Data Systems, 117(7), 1426–1445 is published by Emerald and is available at https://doi.org/10.1108/IMDS-08-2016-0342.en_US
dc.subjectE-healthcare systemen_US
dc.subjectElderly care serviceen_US
dc.subjectFuzzy association rule miningen_US
dc.subjectInternet of thingsen_US
dc.titleDevelopment of an intelligent e-healthcare system for the domestic care industryen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1426en_US
dc.identifier.epage1445en_US
dc.identifier.volume117en_US
dc.identifier.issue7en_US
dc.identifier.doi10.1108/IMDS-08-2016-0342en_US
dcterms.abstractPurpose: In view of the elderly caregiving service being in high demand nowadays, the purpose of this paper is to develop an intelligent e-healthcare system for the domestic care industry by using the Internet of Things (IoTs) and Fuzzy Association Rule Mining (FARM) approach.en_US
dcterms.abstractDesign/methodology/approach: The IoTs connected with the e-healthcare system collect real-time vital sign monitoring data for the e-healthcare system. The FARM approach helps to identify the hidden relationships between the data records in the e-healthcare system to support the elderly care management tasks.en_US
dcterms.abstractFindings: To evaluate the proposed system and approach, a case study was carried out to identify the association between the specific collected demographic data, behavior data and the health measurements data in the e-healthcare system. It is found that the discovered rules are useful for the care management tasks in the elderly healthcare service.en_US
dcterms.abstractOriginality/value: Knowledge discovery in databases uses various data mining techniques and rule-based artificial intelligence algorithms. This paper demonstrates complete processes on how an e-healthcare system connected with IoTs can support the elderly care services via a data collection phase, data analysis phase and data reporting phase by using the FARM to evaluate the fuzzy sets of the data attributes. The caregivers can use the discovered rules for proactive decision support of healthcare services and to improve the overall service quality by enhancing the elderly healthcare service responsiveness.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIndustrial management and data systems, 2017, v. 117, no. 7, p. 1426-1445en_US
dcterms.isPartOfIndustrial management and data systemsen_US
dcterms.issued2017-
dc.identifier.scopus2-s2.0-85027322952-
dc.identifier.eissn1758-5783en_US
dc.description.validate202402 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberISE-0854-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6769674-
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Tsui_Development_Intelligent_E-healthcare.pdfPre-Published version1.15 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

107
Last Week
1
Last month
Citations as of Nov 30, 2025

Downloads

110
Citations as of Nov 30, 2025

SCOPUSTM   
Citations

28
Citations as of Dec 19, 2025

WEB OF SCIENCETM
Citations

26
Citations as of Dec 18, 2025

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.