Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103005
DC FieldValueLanguage
dc.contributorDepartment of Computingen_US
dc.creatorSartayeva, Yen_US
dc.creatorChan, CBHen_US
dc.creatorHo, YHen_US
dc.creatorChong, PHJen_US
dc.date.accessioned2023-11-21T06:05:10Z-
dc.date.available2023-11-21T06:05:10Z-
dc.identifier.citationv. 237, 110042-
dc.identifier.issn1389-1286en_US
dc.identifier.urihttp://hdl.handle.net/10397/103005-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.subjectCOVID-19en_US
dc.subjectIndoor positioningen_US
dc.subjectLayered modelen_US
dc.subjectProximity-based servicesen_US
dc.titleA survey of indoor positioning systems based on a six-layer modelen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume237en_US
dc.identifier.doi10.1016/j.comnet.2023.110042en_US
dcterms.abstractIndoor positioning has attracted considerable interest in both the industry and academic communities because of its wide range of applications, such as asset tracking, healthcare and context-aware services like targeted advertisements. While there are many indoor localisation methods, each has its advantages and disadvantages, taking into consideration various factors such as the effect of the indoor environment, ease of implementation, computational cost, positioning accuracy, etc. In other words, no single solution can cater for all different situations. Although many survey papers have been published on indoor positioning, new techniques and methods are proposed every year, so it is important to stay abreast of its latest developments. In addition, each survey has its own classification for indoor positioning systems without a common scheme. Inspired by the well-known OSI model and TCP/IP model, it would be desirable to develop a systematic framework for studying indoor positioning systems. In this paper, we make this new contribution by introducing a systemic survey framework based on a six-layer model to give a comprehensive survey of indoor positioning systems, namely: device layer, communication layer, network layer, data layer, method layer and application layer. Complementing the previous survey papers, this paper provides a survey of the latest research works on indoor positioning based on the six-layer model. Our emphasis is on systematic categorisation, machine learning-based enhancements, collaborative localisation and COVID-19-related applications. The six-layer model should provide a useful framework and new insights for the research community.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationComputer networks, Dec. 2023, v. 237, 110042en_US
dcterms.isPartOfComputer networksen_US
dcterms.issued2023-12-
dc.identifier.eissn1872-7069en_US
dc.identifier.artn110042en_US
dc.description.validate202311 bcchen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera2515-
dc.identifier.SubFormID47805-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2025-12-31en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
Open Access Information
Status embargoed access
Embargo End Date 2025-12-31
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

134
Last Week
14
Last month
Citations as of Nov 9, 2025

WEB OF SCIENCETM
Citations

11
Citations as of Dec 18, 2025

Google ScholarTM

Check

Altmetric


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