{"id":"https://openalex.org/W3039723251","doi":"https://doi.org/10.1109/percom45495.2020.9127366","title":"OmniCells: Cross-Device Cellular-based Indoor Location Tracking Using Deep Neural Networks","display_name":"OmniCells: Cross-Device Cellular-based Indoor Location Tracking Using Deep Neural Networks","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3039723251","doi":"https://doi.org/10.1109/percom45495.2020.9127366","mag":"3039723251"},"language":"en","primary_location":{"id":"doi:10.1109/percom45495.2020.9127366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percom45495.2020.9127366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Pervasive Computing and Communications (PerCom)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5013317917","display_name":"Hamada Rizk","orcid":"https://orcid.org/0000-0002-8278-8801"},"institutions":[{"id":"https://openalex.org/I21376657","display_name":"Tanta University","ror":"https://ror.org/016jp5b92","country_code":"EG","type":"education","lineage":["https://openalex.org/I21376657"]},{"id":"https://openalex.org/I32619867","display_name":"Egypt-Japan University of Science and Technology","ror":"https://ror.org/02x66tk73","country_code":"EG","type":"education","lineage":["https://openalex.org/I32619867"]},{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["EG","JP"],"is_corresponding":false,"raw_author_name":"Hamada Rizk","raw_affiliation_strings":["Dept. of Comp. Sci. and Eng., E-JUST, Alexandria, Egypt Tanta University, Tanta, Egypt Osaka University, Osaka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Comp. Sci. and Eng., E-JUST, Alexandria, Egypt Tanta University, Tanta, Egypt Osaka University, Osaka, Japan","institution_ids":["https://openalex.org/I21376657","https://openalex.org/I32619867","https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040381211","display_name":"Moustafa Abbas","orcid":null},"institutions":[{"id":"https://openalex.org/I84524832","display_name":"Alexandria University","ror":"https://ror.org/00mzz1w90","country_code":"EG","type":"education","lineage":["https://openalex.org/I84524832"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Moustafa Abbas","raw_affiliation_strings":["Dept. of Comp. and Sys. Eng., Alexandria University, Alexandria, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Comp. and Sys. Eng., Alexandria University, Alexandria, Egypt","institution_ids":["https://openalex.org/I84524832"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008352007","display_name":"Moustafa Youssef","orcid":"https://orcid.org/0000-0002-2063-4364"},"institutions":[{"id":"https://openalex.org/I84524832","display_name":"Alexandria University","ror":"https://ror.org/00mzz1w90","country_code":"EG","type":"education","lineage":["https://openalex.org/I84524832"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Moustafa Youssef","raw_affiliation_strings":["Dept. of Comp. and Sys. Eng., Alexandria University, Alexandria, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Comp. and Sys. Eng., Alexandria University, Alexandria, Egypt","institution_ids":["https://openalex.org/I84524832"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9975000023841858,"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/T10860","display_name":"Speech and Audio Processing","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.8757956027984619},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.830910325050354},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7372714281082153},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.6176018118858337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5218119621276855},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5153062343597412},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.502964198589325},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.49914050102233887},{"id":"https://openalex.org/keywords/signal-strength","display_name":"Signal strength","score":0.48195573687553406},{"id":"https://openalex.org/keywords/android","display_name":"Android (operating system)","score":0.417671799659729},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3395681381225586},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.20767369866371155},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1743794083595276}],"concepts":[{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.8757956027984619},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.830910325050354},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7372714281082153},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.6176018118858337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5218119621276855},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5153062343597412},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.502964198589325},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.49914050102233887},{"id":"https://openalex.org/C176808163","wikidata":"https://www.wikidata.org/wiki/Q17105794","display_name":"Signal strength","level":3,"score":0.48195573687553406},{"id":"https://openalex.org/C557433098","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android (operating system)","level":2,"score":0.417671799659729},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3395681381225586},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.20767369866371155},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1743794083595276},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/percom45495.2020.9127366","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percom45495.2020.9127366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Pervasive Computing and Communications (PerCom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W995630646","https://openalex.org/W1513671680","https://openalex.org/W1522301498","https://openalex.org/W1806891645","https://openalex.org/W1862952379","https://openalex.org/W1974419917","https://openalex.org/W1990603581","https://openalex.org/W2038327679","https://openalex.org/W2069284707","https://openalex.org/W2095705004","https://openalex.org/W2101891684","https://openalex.org/W2118936352","https://openalex.org/W2133671968","https://openalex.org/W2142908542","https://openalex.org/W2143095760","https://openalex.org/W2240192984","https://openalex.org/W2274198861","https://openalex.org/W2290207474","https://openalex.org/W2291315001","https://openalex.org/W2291859485","https://openalex.org/W2309512289","https://openalex.org/W2507151029","https://openalex.org/W2599936006","https://openalex.org/W2739582838","https://openalex.org/W2774684174","https://openalex.org/W2782840052","https://openalex.org/W2785787327","https://openalex.org/W2901328414","https://openalex.org/W2903835995","https://openalex.org/W2914278951","https://openalex.org/W2914484425","https://openalex.org/W2953121424","https://openalex.org/W2963539531","https://openalex.org/W2964121744","https://openalex.org/W2982408623","https://openalex.org/W2982519817","https://openalex.org/W2983679773","https://openalex.org/W2988138047","https://openalex.org/W2995128391","https://openalex.org/W3002652589","https://openalex.org/W3040199298","https://openalex.org/W3175413200","https://openalex.org/W4212863985","https://openalex.org/W4255949318","https://openalex.org/W6631190155","https://openalex.org/W6674330103","https://openalex.org/W6675517766","https://openalex.org/W6771553805"],"related_works":["https://openalex.org/W2162859609","https://openalex.org/W4200318234","https://openalex.org/W150547863","https://openalex.org/W2022445516","https://openalex.org/W2982532306","https://openalex.org/W1891938465","https://openalex.org/W1639914594","https://openalex.org/W4237766728","https://openalex.org/W4253688861","https://openalex.org/W1550605711"],"abstract_inverted_index":{"The":[0],"demand":[1],"for":[2,35],"a":[3,16,70,86,96,110,173],"ubiquitous":[4,22],"and":[5,62,112,140,147,164],"accurate":[6],"indoor":[7,189],"localization":[8,176],"service":[9,23],"is":[10,37,184],"continuously":[11],"growing.":[12],"Cellular-based":[13],"systems":[14,191],"are":[15],"good":[17],"candidate":[18],"to":[19,25,84,99,108,130,141],"provide":[20,85],"such":[21],"due":[24],"their":[26],"wide":[27],"availability":[28],"worldwide.":[29],"One":[30],"of":[31,41,43,50,150],"the":[32,38,51,59,120,132,143,187],"main":[33],"barriers":[34],"accuracy":[36,134,177],"large":[39],"number":[40],"models":[42],"cell":[44],"phones,":[45],"which":[46],"results":[47],"in":[48,152],"variations":[49],"measured":[52],"received":[53],"signal":[54],"strength":[55],"(RSS),":[56],"even":[57],"at":[58,193],"same":[60],"location":[61],"time.":[63],"In":[64],"this":[65],"paper,":[66],"we":[67],"propose":[68],"OmniCells,":[69],"deep":[71,144],"learning-based":[72],"system":[73],"that":[74,105,169],"leverages":[75],"cellular":[76,165],"measurements":[77],"from":[78],"one":[79],"or":[80,122],"more":[81],"training":[82],"devices":[83],"consistent":[87,174],"performance":[88],"across":[89],"unseen":[90],"tracking":[91],"phones.":[92,182],"Specifically,":[93],"OmniCells":[94,125,151,170],"uses":[95],"novel":[97],"approach":[98],"multi-task":[100],"learning":[101],"based":[102],"on":[103,180],"autoencoders":[104],"allows":[106],"it":[107],"learn":[109],"rich":[111],"device-invariant":[113],"RSS":[114,136],"representation":[115],"without":[116],"any":[117],"assumptions":[118],"about":[119],"source":[121],"target":[123],"devices.":[124],"also":[126],"incorporates":[127],"different":[128,157,161,181],"modules":[129],"boost":[131],"system\u2019s":[133],"with":[135,160],"relative":[137],"difference-based":[138],"features":[139],"improve":[142],"model\u2019s":[145],"generalization":[146],"robustness.":[148],"Evaluation":[149],"two":[153],"realistic":[154],"testbeds":[155],"using":[156],"Android":[158],"phones":[159],"form":[162],"factors":[163],"radio":[166],"hardware":[167],"shows":[168],"can":[171],"achieve":[172],"median":[175],"when":[178],"tested":[179],"This":[183],"better":[185],"than":[186],"state-of-the-art":[188],"cellular-based":[190],"by":[192],"least":[194],"101%.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
