{"id":"https://openalex.org/W4312557520","doi":"https://doi.org/10.1109/access.2022.3218785","title":"Long Gaps Missing IoT Sensors Time Series Data Imputation: A Bayesian Gaussian Approach","display_name":"Long Gaps Missing IoT Sensors Time Series Data Imputation: A Bayesian Gaussian Approach","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312557520","doi":"https://doi.org/10.1109/access.2022.3218785"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3218785","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3218785","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09934837.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09934837.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009067513","display_name":"H.M. Ahmed","orcid":"https://orcid.org/0000-0003-3474-9645"},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Hassan M. Ahmed","raw_affiliation_strings":["D&#x00E9;partement d&#x2019;informatique, Facult&#x00E9; des sciences, Ambient Intelligence Laboratory (AMI-Lab), Universit&#x00E9; de Sherbrooke, Sherbrooke, Canada"],"raw_orcid":"https://orcid.org/0000-0003-3474-9645","affiliations":[{"raw_affiliation_string":"D&#x00E9;partement d&#x2019;informatique, Facult&#x00E9; des sciences, Ambient Intelligence Laboratory (AMI-Lab), Universit&#x00E9; de Sherbrooke, Sherbrooke, Canada","institution_ids":["https://openalex.org/I135117807"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008260426","display_name":"Bessam Abdulrazak","orcid":"https://orcid.org/0000-0002-5468-0190"},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bessam Abdulrazak","raw_affiliation_strings":["D&#x00E9;partement d&#x2019;informatique, Facult&#x00E9; des sciences, Ambient Intelligence Laboratory (AMI-Lab), Universit&#x00E9; de Sherbrooke, Sherbrooke, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5468-0190","affiliations":[{"raw_affiliation_string":"D&#x00E9;partement d&#x2019;informatique, Facult&#x00E9; des sciences, Ambient Intelligence Laboratory (AMI-Lab), Universit&#x00E9; de Sherbrooke, Sherbrooke, Canada","institution_ids":["https://openalex.org/I135117807"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021345205","display_name":"F. Guillaume Blanchet","orcid":"https://orcid.org/0000-0001-5149-2488"},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"F. Guillaume Blanchet","raw_affiliation_strings":["D&#x00E9;partement de Biologie, Facult&#x00E9; des sciences, Universit&#x00E9; de Sherbrooke, Sherbrooke, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"D&#x00E9;partement de Biologie, Facult&#x00E9; des sciences, Universit&#x00E9; de Sherbrooke, Sherbrooke, Canada","institution_ids":["https://openalex.org/I135117807"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029604789","display_name":"Hamdi Aloulou","orcid":null},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Hamdi Aloulou","raw_affiliation_strings":["ReDCAD, ENIS, University of Sfax, Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ReDCAD, ENIS, University of Sfax, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107391061","display_name":"Mounir Mokhtari","orcid":"https://orcid.org/0000-0001-9347-0121"},"institutions":[{"id":"https://openalex.org/I205703379","display_name":"Institut Mines-T\u00e9l\u00e9com","ror":"https://ror.org/025vp2923","country_code":"FR","type":"facility","lineage":["https://openalex.org/I205703379"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mounir Mokhtari","raw_affiliation_strings":["Institut Mines T&#x00E9;l&#x00E9;com, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Mines T&#x00E9;l&#x00E9;com, Paris, France","institution_ids":["https://openalex.org/I205703379"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5009067513"],"corresponding_institution_ids":["https://openalex.org/I135117807"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.117,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.79206042,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"116107","last_page":"116119"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9767000079154968,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.9299100637435913},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.82829749584198},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6994985938072205},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6265544891357422},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5707122087478638},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5577660202980042},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5035988688468933},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.41814157366752625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29315462708473206},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2841690480709076}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.9299100637435913},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.82829749584198},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6994985938072205},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6265544891357422},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5707122087478638},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5577660202980042},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5035988688468933},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.41814157366752625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29315462708473206},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2841690480709076},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3218785","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3218785","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09934837.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ec8cc88869e34524905109c6482500c6","is_oa":true,"landing_page_url":"https://doaj.org/article/ec8cc88869e34524905109c6482500c6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 116107-116119 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3218785","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3218785","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09934837.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312557520.pdf","grobid_xml":"https://content.openalex.org/works/W4312557520.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W84374273","https://openalex.org/W186039566","https://openalex.org/W1484864026","https://openalex.org/W1578474427","https://openalex.org/W1610612296","https://openalex.org/W1982012380","https://openalex.org/W2070807660","https://openalex.org/W2074184525","https://openalex.org/W2100358124","https://openalex.org/W2104275550","https://openalex.org/W2127841934","https://openalex.org/W2134295053","https://openalex.org/W2134843796","https://openalex.org/W2137434741","https://openalex.org/W2139075905","https://openalex.org/W2151182129","https://openalex.org/W2159586267","https://openalex.org/W2170674956","https://openalex.org/W2217207621","https://openalex.org/W2786769798","https://openalex.org/W2808891699","https://openalex.org/W2891381594","https://openalex.org/W2893901527","https://openalex.org/W2901273662","https://openalex.org/W2920529430","https://openalex.org/W2944122571","https://openalex.org/W3004178587","https://openalex.org/W3012479489","https://openalex.org/W3049453136","https://openalex.org/W3130968222","https://openalex.org/W4285110495","https://openalex.org/W4298870207"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"Missing":[0],"sensor":[1,50,114],"data":[2,58,72,125,151,179],"is":[3,36,43,74],"a":[4,97,164],"common":[5],"problem":[6,35],"associated":[7,21],"with":[8],"the":[9,17,20,112,157,177],"Internet":[10],"of":[11,19,45,81,83,159],"Things":[12],"(IoT)":[13],"ecosystems,":[14],"which":[15,180],"affect":[16],"accuracy":[18],"services":[22],"such":[23],"as":[24],"adequate":[25],"medical":[26],"intervention":[27],"for":[28,106,132],"older":[29,161],"adults":[30,162],"living":[31],"at":[32,127],"home.":[33],"This":[34],"caused":[37],"by":[38],"many":[39],"factors,":[40],"power":[41],"down":[42],"one":[44],"them,":[46],"communication":[47],"failure":[48,51],"and":[49,87,131],"are":[52],"another":[53],"two":[54],"reasons.":[55],"Multiple":[56],"missing":[57,71,113,124,129,178],"imputation":[59,102],"methods":[60],"have":[61,192],"been":[62,193],"developed":[63],"to":[64,76,79,109,174,183,195],"solve":[65],"this":[66,93],"issue.":[67],"However,":[68],"irregular":[69],"temporal":[70,90,107,134],"locations":[73],"challenging":[75],"handle,":[77],"due":[78],"lack":[80],"knowledge":[82,138],"their":[84,88],"occurrence":[85],"probability":[86],"random":[89],"location.":[91],"In":[92],"paper,":[94],"we":[95,171,189],"propose":[96],"Bayesian":[98,118],"Gaussian":[99,119],"Process":[100,120],"based":[101],"technique":[103],"that":[104,188],"accounts":[105],"forcing":[108],"fill":[110],"in":[111,156],"data.":[115],"Our":[116],"approach;":[117],"(BGaP);":[121],"can":[122],"impute":[123,175],"efficiently":[126],"any":[128,133],"rate":[130],"location":[135],"using":[136,149],"prior":[137],"gathered":[139],"on":[140],"past":[141],"observations.":[142],"We":[143],"illustrated":[144],"how":[145],"our":[146,168],"approach":[147],"performs":[148],"real":[150],"collected":[152],"from":[153],"sensors":[154],"deployed":[155],"residence":[158],"10":[160],"over":[163],"two-year":[165],"period.":[166],"Using":[167],"novel":[169],"approach,":[170],"were":[172],"able":[173,194],"all":[176],"allowed":[181],"us":[182],"observe":[184,196],"long-term":[185],"behavior":[186],"changes":[187],"would":[190],"not":[191],"otherwise.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-10T08:33:47.465468","created_date":"2025-10-10T00:00:00"}
