{"id":"https://openalex.org/W4378697511","doi":"https://doi.org/10.1109/tim.2023.3280516","title":"Access Point Selection for Indoor Positioning Using Fingerprint Distance Maximization","display_name":"Access Point Selection for Indoor Positioning Using Fingerprint Distance Maximization","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4378697511","doi":"https://doi.org/10.1109/tim.2023.3280516"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3280516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3280516","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012663495","display_name":"Ai Hui Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Ai Hui Tan","raw_affiliation_strings":["Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia"],"raw_orcid":"https://orcid.org/0000-0002-6926-3867","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5012663495"],"corresponding_institution_ids":["https://openalex.org/I173029219"],"apc_list":null,"apc_paid":null,"fwci":0.4681,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.61255613,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10986","display_name":"RFID technology advancements","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.7339752316474915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.710191547870636},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.7029844522476196},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6868947744369507},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.5372474193572998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4930977523326874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4874013066291809},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4832916557788849},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.41611552238464355},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3741060495376587},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19829905033111572},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.09755095839500427}],"concepts":[{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.7339752316474915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.710191547870636},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7029844522476196},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6868947744369507},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.5372474193572998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4930977523326874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4874013066291809},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4832916557788849},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.41611552238464355},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3741060495376587},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19829905033111572},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.09755095839500427},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tim.2023.3280516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3280516","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:shdl.mmu.edu.my:11590","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196753","display_name":"Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173029219","host_organization_name":"Multimedia University","host_organization_lineage":["https://openalex.org/I173029219"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1562327244","https://openalex.org/W1844858819","https://openalex.org/W1979172919","https://openalex.org/W2049577911","https://openalex.org/W2067710374","https://openalex.org/W2108126247","https://openalex.org/W2143243918","https://openalex.org/W2147348082","https://openalex.org/W2276986197","https://openalex.org/W2295124130","https://openalex.org/W2342827161","https://openalex.org/W2408343751","https://openalex.org/W2603071509","https://openalex.org/W2607595839","https://openalex.org/W2762342365","https://openalex.org/W2787516708","https://openalex.org/W2804547194","https://openalex.org/W2917132850","https://openalex.org/W2924468481","https://openalex.org/W3004340854","https://openalex.org/W3035419842","https://openalex.org/W3128181023","https://openalex.org/W3135387830","https://openalex.org/W3164883109","https://openalex.org/W3210294081","https://openalex.org/W3214241276","https://openalex.org/W4205185952","https://openalex.org/W4214869693","https://openalex.org/W6633786245","https://openalex.org/W6792020946"],"related_works":["https://openalex.org/W2380927352","https://openalex.org/W3178621026","https://openalex.org/W2137598809","https://openalex.org/W2085553065","https://openalex.org/W4211209597","https://openalex.org/W2138391900","https://openalex.org/W2997969508","https://openalex.org/W4293863368","https://openalex.org/W2389470892","https://openalex.org/W2548999290"],"abstract_inverted_index":{"This":[0,70],"paper":[1],"addresses":[2],"the":[3,27,30,33,38,49,61,77,83,108,126,131,138,152,155,164,168,175],"issue":[4],"of":[5,26,32,60,79,100,154],"access":[6],"point":[7],"(AP)":[8],"selection":[9],"for":[10,160,192],"indoor":[11],"positioning":[12],"using":[13,115],"wireless":[14],"networks.":[15],"A":[16],"fingerprint":[17],"distance":[18,34,63],"maximization":[19],"(FDM)":[20],"method":[21,28,110,128,140],"is":[22,29,67,72,104,123,189],"proposed.":[23],"The":[24,186],"novelty":[25],"treatment":[31],"between":[35,53,64],"fingerprints,":[36],"where":[37,194],"APs":[39],"are":[40,93,202],"evaluated":[41],"based":[42],"on":[43],"how":[44],"frequently":[45],"they":[46],"contribute":[47],"to":[48,130,149,182],"largest":[50],"difference":[51],"term":[52],"fingerprints":[54,65,81],"measured":[55],"at":[56],"different":[57],"locations,":[58],"instead":[59],"overall":[62],"which":[66],"conventionally":[68],"applied.":[69],"strategy":[71],"effective":[73],"because":[74],"it":[75],"increases":[76],"number":[78,99],"distinctive":[80],"in":[82,95],"database":[84],"by":[85,172,179],"preserving":[86],"distinguishing":[87],"features,":[88],"even":[89],"if":[90],"these":[91],"features":[92],"dominant":[94],"only":[96],"a":[97,119,161],"small":[98],"fingerprints.":[101],"Performance":[102],"analysis":[103,147],"carried":[105],"out":[106],"comparing":[107],"FDM":[109,127,139],"with":[111,144,197],"several":[112],"competing":[113],"techniques":[114],"experimental":[116],"data":[117,169],"from":[118],"well-known":[120],"dataset.":[121],"It":[122],"shown":[124],"that":[125,159],"leads":[129],"highest":[132],"accuracy":[133],"and":[134,174,200],"lowest":[135],"uncertainty.":[136],"Additionally,":[137],"can":[141],"be":[142],"combined":[143],"principal":[145],"component":[146],"(PCA)":[148],"further":[150],"reduce":[151],"dimensionality":[153],"problem.":[156],"Results":[157],"show":[158],"fixed":[162],"accuracy,":[163],"FDM-PCA":[165,187],"technique":[166,188],"reduces":[167],"storage":[170,199],"requirement":[171],"30%":[173],"online":[176],"execution":[177],"time":[178],"5.5%":[180],"compared":[181],"its":[183],"closest":[184],"competitor.":[185],"thus":[190],"suitable":[191],"applications":[193],"mobile":[195],"devices":[196],"limited":[198],"capacity":[201],"used":[203],"as":[204],"measuring":[205],"instruments.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}