{"id":"https://openalex.org/W2597087204","doi":"https://doi.org/10.1109/wisee.2016.7877329","title":"Compressed radio transmission of spatial field measurements by virtual sensors","display_name":"Compressed radio transmission of spatial field measurements by virtual sensors","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2597087204","doi":"https://doi.org/10.1109/wisee.2016.7877329","mag":"2597087204"},"language":"en","primary_location":{"id":"doi:10.1109/wisee.2016.7877329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wisee.2016.7877329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)","raw_type":"proceedings-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/A5087956380","display_name":"Reiner Jedermann","orcid":"https://orcid.org/0000-0002-0390-9143"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Reiner Jedermann","raw_affiliation_strings":["Institute for Microsensors - actuators and - systems, University of Bremen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Microsensors - actuators and - systems, University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107809337","display_name":"Henning Paul","orcid":null},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Henning Paul","raw_affiliation_strings":["Department of Communications Engineering, University of Bremen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Communications Engineering, University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077352854","display_name":"Walter Lang","orcid":"https://orcid.org/0000-0002-9813-5231"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Walter Lang","raw_affiliation_strings":["Microsystems Center Bremen, University of Bremen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsystems Center Bremen, University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8833,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.85752873,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"23","issue":null,"first_page":"184","last_page":"189"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.7070401906967163},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.602818489074707},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5695218443870544},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5252230167388916},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5019488334655762},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.4291396737098694},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.4216781258583069},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3925899267196655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20605984330177307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17826223373413086},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14853212237358093},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09727677702903748}],"concepts":[{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.7070401906967163},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.602818489074707},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5695218443870544},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5252230167388916},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5019488334655762},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4291396737098694},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4216781258583069},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3925899267196655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20605984330177307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17826223373413086},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14853212237358093},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09727677702903748},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"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/wisee.2016.7877329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wisee.2016.7877329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)","raw_type":"proceedings-article"},{"id":"mag:2746576968","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/201702235431571898","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1539472441","https://openalex.org/W1970679066","https://openalex.org/W1980448497","https://openalex.org/W1988488280","https://openalex.org/W2024596917","https://openalex.org/W2064314582","https://openalex.org/W2064649305","https://openalex.org/W2069074182","https://openalex.org/W2106742582","https://openalex.org/W2110410293","https://openalex.org/W2171033594","https://openalex.org/W2598706517","https://openalex.org/W2642675874","https://openalex.org/W4229875153","https://openalex.org/W6632376587","https://openalex.org/W6739726603"],"related_works":["https://openalex.org/W1968523686","https://openalex.org/W298893735","https://openalex.org/W2199291344","https://openalex.org/W4210770325","https://openalex.org/W2211316729","https://openalex.org/W2167342507","https://openalex.org/W4221140712","https://openalex.org/W1970319972","https://openalex.org/W2953254336","https://openalex.org/W2112030392"],"abstract_inverted_index":{"The":[0,100,149],"remote":[1],"exploration":[2],"or":[3,58,79],"monitoring":[4],"of":[5,18,22,49,60,111,128,176,183,186,189,192],"an":[6],"environment":[7],"often":[8],"includes":[9],"sensor":[10,96,115],"measurements":[11,89],"at":[12],"multiple":[13],"probe":[14],"points":[15],"and":[16,38,142,165,188],"reconstruction":[17,75],"the":[19,23,36,39,50,88,119,125,132,146,184,190,195,203],"spatial":[20,51,133],"distribution":[21,52],"observed":[24],"physical":[25,56],"quantity":[26],"by":[27,163,173],"a":[28,46,108,155,159,170,174],"regression":[29],"model.":[30],"Especially":[31],"for":[32,44,73,158],"long":[33],"distances":[34],"between":[35],"observer":[37],"environment,":[40],"required":[41],"data":[42,97,141,171],"volume":[43],"transmitting":[45,123],"parametric":[47,61,204],"description":[48],"becomes":[53],"critical.":[54],"Simple":[55],"models":[57],"assumption":[59],"base":[62,205],"functions":[63],"do":[64],"not":[65],"provide":[66,83],"sufficient":[67],"prediction":[68,147,196],"accuracy.":[69],"Statistically":[70],"based":[71],"methods":[72],"field":[74,134,161],"such":[76],"as":[77],"Kriging":[78],"Gaussian":[80],"Process":[81],"Regression":[82],"good":[84],"accuracy,":[85],"even":[86],"if":[87],"are":[90],"overlaid":[91],"with":[92,138,202],"noise,":[93,194],"provided":[94],"all":[95],"is":[98],"transmitted.":[99],"new":[101,150],"method":[102],"presented":[103],"in":[104,154],"this":[105],"paper":[106],"calculates":[107],"small":[109],"set":[110],"quasi":[112],"optimal":[113],"virtual":[114,130],"positions":[116],"located":[117],"in-between":[118],"real":[120],"sensors.":[121],"By":[122],"only":[124],"predicted":[126],"values":[127],"these":[129],"sensors,":[131],"can":[135],"be":[136],"reconstructed":[137],"less":[139],"transmitted":[140],"without":[143],"significantly":[144],"increasing":[145],"error.":[148],"approach":[151],"was":[152,198],"verified":[153],"simulation":[156],"scenario":[157],"temperature":[160],"caused":[162],"diffusion":[164],"advection":[166],"phenomena,":[167],"which":[168],"yielded":[169],"compression":[172],"factor":[175],"up":[177],"to":[178],"four.":[179],"For":[180],"large":[181],"variations":[182],"number":[185],"sensors":[187],"magnitude":[191],"measurement":[193],"error":[197],"always":[199],"lower":[200],"compared":[201],"function":[206],"models.":[207]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}