{"id":"https://openalex.org/W4414539290","doi":"https://doi.org/10.1109/icc52391.2025.11162054","title":"Enhancing the Robustness of AI-Driven Robotic RFID Inventory Management Using Conformal Prediction","display_name":"Enhancing the Robustness of AI-Driven Robotic RFID Inventory Management Using Conformal Prediction","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414539290","doi":"https://doi.org/10.1109/icc52391.2025.11162054"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11162054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11162054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5100585231","display_name":"Yongshuai Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yongshuai Wu","raw_affiliation_strings":["Kennesaw State University,Department of Information Technology,Marietta,GA,USA,30060"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University,Department of Information Technology,Marietta,GA,USA,30060","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101473897","display_name":"Jian Zhang","orcid":"https://orcid.org/0009-0008-0097-9489"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["Kennesaw State University,Department of Information Technology,Marietta,GA,USA,30060"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University,Department of Information Technology,Marietta,GA,USA,30060","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100743605","display_name":"Shaoen Wu","orcid":"https://orcid.org/0000-0002-4768-6930"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaoen Wu","raw_affiliation_strings":["Kennesaw State University,Department of Information Technology,Marietta,GA,USA,30060"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University,Department of Information Technology,Marietta,GA,USA,30060","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080122431","display_name":"Shiwen Mao","orcid":"https://orcid.org/0000-0002-7052-0007"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiwen Mao","raw_affiliation_strings":["Auburn University,Department of Electrical and Computer Engineering,Auburn,AL,USA,36849-5201"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Auburn University,Department of Electrical and Computer Engineering,Auburn,AL,USA,36849-5201","institution_ids":["https://openalex.org/I82497590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3400","last_page":"3405"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.6726999878883362,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.6726999878883362,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10986","display_name":"RFID technology advancements","score":0.6625999808311462,"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"}},{"id":"https://openalex.org/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.6391000151634216,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/robustness","display_name":"Robustness (evolution)","score":0.829800009727478},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.5260999798774719},{"id":"https://openalex.org/keywords/inventory-management","display_name":"Inventory management","score":0.5170999765396118},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4902999997138977},{"id":"https://openalex.org/keywords/lead-time","display_name":"Lead time","score":0.37439998984336853},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.3682999908924103}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.829800009727478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407999992370605},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.5655999779701233},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.5260999798774719},{"id":"https://openalex.org/C3018434026","wikidata":"https://www.wikidata.org/wiki/Q3761396","display_name":"Inventory management","level":2,"score":0.5170999765396118},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4902999997138977},{"id":"https://openalex.org/C2781468064","wikidata":"https://www.wikidata.org/wiki/Q1267117","display_name":"Lead time","level":2,"score":0.37439998984336853},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3682999908924103},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C117938511","wikidata":"https://www.wikidata.org/wiki/Q3634830","display_name":"Inventory control","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.31949999928474426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31279999017715454},{"id":"https://openalex.org/C204222849","wikidata":"https://www.wikidata.org/wiki/Q104954","display_name":"Radio-frequency identification","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11162054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11162054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6270272746","display_name":null,"funder_award_id":"CCSS-2245607,CCSS-2245608","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2051174802","https://openalex.org/W2166693382","https://openalex.org/W2419352894","https://openalex.org/W3000191256","https://openalex.org/W4211230254","https://openalex.org/W4280501667","https://openalex.org/W4298127542","https://openalex.org/W4383112515","https://openalex.org/W4392157992","https://openalex.org/W4402674039","https://openalex.org/W4404609187","https://openalex.org/W4405908436"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3,71],"present":[4],"a":[5,73,97,107],"novel":[6],"approach":[7,141],"to":[8,48,63,78,115],"enhance":[9],"the":[10,46,52,68,91,117,137,145],"robustness":[11],"of":[12,139,149],"autonomous":[13],"robotic":[14],"Radio":[15],"Frequency":[16],"Identification":[17],"(RFID)":[18],"inventory":[19,37,84,151],"systems":[20],"using":[21,76],"Conformal":[22],"Prediction":[23],"(CP).":[24],"Recent":[25],"AI-driven":[26],"approaches,":[27],"especially":[28],"deep-learning":[29],"models,":[30],"have":[31],"made":[32],"significant":[33],"advances":[34],"in":[35,58,82,93,129,142],"performing":[36],"strategies":[38],"and":[39,61,125,147,155],"action":[40],"planning.":[41],"However,":[42],"these":[43],"models":[44],"lack":[45],"capability":[47],"measure":[49],"uncertainty":[50,92],"during":[51],"prediction":[53],"process,":[54],"which":[55],"can":[56,103],"result":[57],"accumulated":[59],"errors":[60],"lead":[62],"catastrophic":[64],"failures.":[65],"To":[66],"address":[67],"above":[69],"challenge,":[70],"propose":[72],"confidenceguaranteed":[74],"policy":[75],"CP":[77],"ensure":[79],"reliable":[80],"predictions":[81,102],"RFID":[83,150],"tasks.":[85],"Our":[86],"method":[87,119],"focuses":[88],"on":[89],"managing":[90],"sub-goal":[94],"estimation":[95],"for":[96],"trained":[98],"model,":[99],"ensuring":[100,153],"that":[101],"meet":[104],"or":[105],"exceed":[106],"user-specific":[108],"confidence":[109],"level.":[110],"We":[111],"conduct":[112],"extensive":[113],"experiments":[114],"assess":[116],"proposed":[118],"by":[120],"regulating":[121],"an":[122],"existing":[123],"model":[124],"evaluate":[126],"its":[127],"effectiveness":[128,138],"identifying":[130],"uncertain":[131],"predictions.":[132],"The":[133],"experimental":[134],"results":[135],"demonstrate":[136],"our":[140],"improving":[143],"both":[144],"reliability":[146],"efficiency":[148],"tasks,":[152],"consistent":[154],"trustworthy":[156],"operation.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
