{"id":"https://openalex.org/W4415745994","doi":"https://doi.org/10.1109/hpcc67675.2025.00150","title":"Long-Time Sensor Accuracy Management: A Combined Approach of Manual and Automatic Calibration","display_name":"Long-Time Sensor Accuracy Management: A Combined Approach of Manual and Automatic Calibration","publication_year":2025,"publication_date":"2025-08-13","ids":{"openalex":"https://openalex.org/W4415745994","doi":"https://doi.org/10.1109/hpcc67675.2025.00150"},"language":null,"primary_location":{"id":"doi:10.1109/hpcc67675.2025.00150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcc67675.2025.00150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on High Performance Computing and Communications (HPCC)","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/A5008751771","display_name":"Taiki Yamada","orcid":"https://orcid.org/0000-0002-9004-8731"},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taiki Yamada","raw_affiliation_strings":["Graduate School of Systems Engineering, Wakayama University,Wakayama,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Systems Engineering, Wakayama University,Wakayama,Japan","institution_ids":["https://openalex.org/I75198481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050061781","display_name":"Takuya Yoshihiro","orcid":"https://orcid.org/0000-0002-7420-4132"},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuya Yoshihiro","raw_affiliation_strings":["Wakayama University,Faculty of Systems Engineering,Wakayama,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wakayama University,Faculty of Systems Engineering,Wakayama,Japan","institution_ids":["https://openalex.org/I75198481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I75198481"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49138325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1029","last_page":"1036"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.1551000028848648,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.1551000028848648,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.09730000048875809,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.06930000334978104,"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/calibration","display_name":"Calibration","score":0.7915999889373779},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5702999830245972},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5333999991416931},{"id":"https://openalex.org/keywords/observational-error","display_name":"Observational error","score":0.5324000120162964},{"id":"https://openalex.org/keywords/accuracy-and-precision","display_name":"Accuracy and precision","score":0.5004000067710876},{"id":"https://openalex.org/keywords/systematic-error","display_name":"Systematic error","score":0.4765999913215637}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7915999889373779},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6521999835968018},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5702999830245972},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5333999991416931},{"id":"https://openalex.org/C19619285","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Observational error","level":2,"score":0.5324000120162964},{"id":"https://openalex.org/C202799725","wikidata":"https://www.wikidata.org/wiki/Q272035","display_name":"Accuracy and precision","level":2,"score":0.5004000067710876},{"id":"https://openalex.org/C100253034","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Systematic error","level":2,"score":0.4765999913215637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39010000228881836},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29260000586509705},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpcc67675.2025.00150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcc67675.2025.00150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on High Performance Computing and Communications (HPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310903","display_name":"Takahashi Industrial and Economic Research Foundation","ror":"https://ror.org/02nnhm363"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1991498481","https://openalex.org/W2046125942","https://openalex.org/W2074719413","https://openalex.org/W2112453888","https://openalex.org/W2152139894","https://openalex.org/W2560308067","https://openalex.org/W2597698998","https://openalex.org/W2911884683","https://openalex.org/W2965175293","https://openalex.org/W2982693506","https://openalex.org/W3138616181","https://openalex.org/W3149494651","https://openalex.org/W4384302446"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,16,40,61,64,77,95,103,106,116,129,135,153,160,167,192,196,206],"spread":[2],"of":[3,19,26,79,98,105,109,131,137,163,182,191,208],"IoT":[4],"technology,":[5],"many":[6],"applications":[7],"using":[8],"sensor":[9,52,100,210],"data":[10],"have":[11,90],"emerged.":[12],"In":[13],"these":[14],"applications,":[15],"accuracy":[17,25,130,169],"management":[18],"sensors":[20,27,80,110,157,165,193],"is":[21,48,68,140],"crucial.":[22],"The":[23,175],"measurement":[24],"decreases":[28],"over":[29,45],"time":[30,218],"due":[31],"to":[32,50,58,151],"a":[33,144,172,179,189,212,216],"systematic":[34],"error":[35,138],"known":[36],"as":[37,56,76],"bias.":[38],"Because":[39],"bias":[41,62,132,154,161,185,207],"can":[42,204],"grow":[43],"significantly":[44],"time,":[46],"it":[47,82],"essential":[49],"perform":[51],"calibration":[53,88,119,147],"periodically,":[54],"such":[55],"annually,":[57],"correct":[59],"for":[60,72,171,215],"and":[63,128,158,186],"maintain":[65,159,205],"accuracy.":[66],"Calibration":[67],"typically":[69],"performed":[70],"manually":[71],"each":[73,99,183,209],"sensor,":[74],"but":[75],"number":[78],"increases,":[81],"becomes":[83],"challenging.":[84],"Therefore,":[85],"several":[86],"automatic":[87,118,146],"methods":[89,120],"been":[91],"proposed":[92,176],"that":[93,149,201],"estimate":[94],"correction":[96,126],"values":[97,108],"based":[101,194],"on":[102,123,195],"correlation":[104],"measured":[107],"located":[111],"in":[112,155],"close":[113],"proximity.":[114],"However,":[115],"existing":[117],"focus":[121],"solely":[122],"estimating":[124],"optimal":[125],"values,":[127],"estimation,":[133],"i.e.,":[134],"amount":[136],"included,":[139],"unclear.":[141],"We":[142,199],"propose":[143],"novel":[145],"method":[148,177,203],"aims":[150],"minimize":[152],"all":[156,164],"errors":[162],"within":[166,211],"required":[168,213],"threshold":[170],"long":[173,217],"time.":[174],"estimates":[178],"probability":[180],"distribution":[181],"sensor's":[184],"periodically":[187],"calibrates":[188],"part":[190],"estimated":[197],"distributions.":[198],"show":[200],"our":[202],"range":[214],"through":[219],"simulations.":[220]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-31T00:00:00"}
