Constructing a Precise Radio Map and Application of Indoor Positioning With Dual-Frequency Wi-Fi Fingerprinting Method

dc.contributor.author Özdemir, Behlül Numan
dc.contributor.author Ceylan, Ayhan
dc.date.accessioned 2021-12-13T10:34:41Z
dc.date.available 2021-12-13T10:34:41Z
dc.date.issued 2020
dc.description.abstract Location-based services provide information about objects and people primarily including their location. While their location can be easily estimated outdoors using GNSS, satellite signals are unable to reach indoor spaces such as buildings. Thus, to provide the position information indoors, several technologies have been proposed. Wi-Fi, which is a wireless communication technology offers a wide range of applications for indoor positioning. One of them is the fingerprinting method that uses the diversity of RSS measurements from different wireless access points for each location in indoor space. Here, we constructed a precise radio map with a measuring tool and compared the 2.4 GHz and 5 GHz frequencies with the dual-band fingerprint dataset. Experimental results show that, even if they do not represent a different location, the incorporation of these two frequencies with different characteristics into a single fingerprint dataset improves the overall positioning accuracy. (C) 2020 Elsevier Ltd. All rights reserved. en_US
dc.identifier.doi 10.1016/j.measurement.2020.107997
dc.identifier.issn 0263-2241
dc.identifier.issn 1873-412X
dc.identifier.scopus 2-s2.0-85086142727
dc.identifier.uri https://doi.org/10.1016/j.measurement.2020.107997
dc.identifier.uri https://hdl.handle.net/20.500.13091/1098
dc.language.iso en en_US
dc.publisher ELSEVIER SCI LTD en_US
dc.relation.ispartof MEASUREMENT en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Wi-Fi fingerprinting en_US
dc.subject Radio map construction en_US
dc.subject Dual frequency indoor positioning en_US
dc.subject Indoor navigation en_US
dc.title Constructing a Precise Radio Map and Application of Indoor Positioning With Dual-Frequency Wi-Fi Fingerprinting Method en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Ozdemir, Behlul Numan/0000-0001-7351-1870
gdc.author.scopusid 57217089141
gdc.author.scopusid 57217089450
gdc.author.wosid Ozdemir, Behlul Numan/AAY-7872-2021
gdc.author.wosid Ceylan, Ayhan/ABE-2689-2020
gdc.bip.impulseclass C4
gdc.bip.influenceclass C5
gdc.bip.popularityclass C4
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.description.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Harita Mühendisliği Bölümü en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 107997
gdc.description.volume 163 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W3033655616
gdc.identifier.wos WOS:000575772000013
gdc.index.type WoS
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gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration National
gdc.openalex.fwci 0.68743061
gdc.openalex.normalizedpercentile 0.71
gdc.opencitations.count 9
gdc.plumx.crossrefcites 10
gdc.plumx.mendeley 16
gdc.plumx.scopuscites 11
gdc.scopus.citedcount 11
gdc.virtual.author Özdemir, Behlül Numan
gdc.virtual.author Ceylan, Ayhan
gdc.wos.citedcount 9
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