A Survey of Indoor Positioning Systems Based on a Six-Layer Model

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aut.relation.articlenumber110042
aut.relation.endpage110042
aut.relation.journalComputer Networks
aut.relation.startpage110042
dc.contributor.authorSartayeva, Yerkezhan
dc.contributor.authorChan, Henry CB
dc.contributor.authorHo, Yik Him
dc.contributor.authorChong, Peter HJ
dc.date.accessioned2023-10-08T23:11:16Z
dc.date.available2023-10-08T23:11:16Z
dc.date.issued2023-09-22
dc.description.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.
dc.identifier.citationComputer Networks, ISSN: 1389-1286 (Print), Elsevier BV, 110042-110042. doi: 10.1016/j.comnet.2023.110042
dc.identifier.doi10.1016/j.comnet.2023.110042
dc.identifier.issn1389-1286
dc.identifier.urihttp://hdl.handle.net/10292/16756
dc.languageen
dc.publisherElsevier BV
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S1389128623004875
dc.rightsCopyright © 2023 Elsevier Ltd. All rights reserved. This is the author’s version of a work that was accepted for publication in (see Citation). Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. The definitive version was published in (see Citation). The original publication is available at (see Publisher's Version).
dc.rights.accessrightsOpenAccess
dc.subject4605 Data Management and Data Science
dc.subject46 Information and Computing Sciences
dc.subject40 Engineering
dc.subject08 Information and Computing Sciences
dc.subject09 Engineering
dc.subject10 Technology
dc.subjectNetworking & Telecommunications
dc.subject40 Engineering
dc.subject46 Information and computing sciences
dc.titleA Survey of Indoor Positioning Systems Based on a Six-Layer Model
dc.typeJournal Article
pubs.elements-id525235
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