{"id":"https://openalex.org/W7128700453","doi":"https://doi.org/10.1109/jiot.2026.3664042","title":"Monocular Camera-Based Substation Safety Distance Monitoring and Early Warning Method","display_name":"Monocular Camera-Based Substation Safety Distance Monitoring and Early Warning Method","publication_year":2026,"publication_date":"2026-02-12","ids":{"openalex":"https://openalex.org/W7128700453","doi":"https://doi.org/10.1109/jiot.2026.3664042"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3664042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3664042","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-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/A5125691614","display_name":"Hanbo Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanbo Zheng","raw_affiliation_strings":["Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China"],"raw_orcid":"https://orcid.org/0000-0002-7660-7293","affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125699685","display_name":"Yu Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Huang","raw_affiliation_strings":["Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China"],"raw_orcid":"https://orcid.org/0009-0004-8614-9291","affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015718732","display_name":"Jinheng Li","orcid":"https://orcid.org/0000-0002-0748-1666"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinheng Li","raw_affiliation_strings":["Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China"],"raw_orcid":"https://orcid.org/0000-0002-0748-1666","affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079739228","display_name":"Shiqi Xu","orcid":"https://orcid.org/0009-0008-1578-6268"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqi Xu","raw_affiliation_strings":["Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125712205","display_name":"Fang Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Gao","raw_affiliation_strings":["Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China"],"raw_orcid":"https://orcid.org/0000-0003-1816-5420","affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150807315"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13126298,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"10","first_page":"20660","last_page":"20674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13715","display_name":"Power Line Inspection Robots","score":0.6922000050544739,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T13715","display_name":"Power Line Inspection Robots","score":0.6922000050544739,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.04910000041127205,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.022099999710917473,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5404999852180481},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5246000289916992},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.45559999346733093},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.42010000348091125},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.3840000033378601},{"id":"https://openalex.org/keywords/warning-system","display_name":"Warning system","score":0.3813999891281128},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.38040000200271606},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.361299991607666}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8148000240325928},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5404999852180481},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5246000289916992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5116999745368958},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4693000018596649},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.45559999346733093},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4487000107765198},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.3840000033378601},{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.3813999891281128},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.38040000200271606},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.361299991607666},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.31679999828338623},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.31630000472068787},{"id":"https://openalex.org/C158829959","wikidata":"https://www.wikidata.org/wiki/Q1640606","display_name":"Monocular vision","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.2989000082015991},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.25940001010894775}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3664042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3664042","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4422888855","display_name":null,"funder_award_id":"2024GXNSFFA999017","funder_id":"https://openalex.org/F4320336125","funder_display_name":"National Science Fund for Distinguished Young Scholars"},{"id":"https://openalex.org/G645866467","display_name":null,"funder_award_id":"52277139","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6727114826","display_name":null,"funder_award_id":"52367014","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336125","display_name":"National Science Fund for Distinguished Young Scholars","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"To":[0,36,122],"ensure":[1],"the":[2,19,72,90,110,116,124,157,168,187,209],"stable":[3],"operation":[4],"of":[5,21,74,119,176,212],"substations,":[6],"staff":[7],"members":[8],"are":[9],"frequently":[10],"required":[11],"to":[12,18,32,70,88,93,108],"enter":[13],"operational":[14],"areas.":[15],"However,":[16],"due":[17],"lack":[20],"proactive":[22],"monitoring":[23,206],"mechanisms,":[24],"accidental":[25],"intrusions":[26],"into":[27,54],"live":[28],"zones":[29],"often":[30],"lead":[31],"electric":[33],"shock":[34],"incidents.":[35],"address":[37],"this":[38,40],"issue,":[39],"study":[41],"proposes":[42],"an":[43,141,152,203],"intelligent":[44,213],"method":[45],"that":[46,126,135,167],"integrates":[47],"keypoint":[48],"detection,":[49],"ranging,":[50],"and":[51,134,180],"early":[52],"warning":[53],"a":[55,59,79,101],"unified":[56],"framework.":[57],"First,":[58],"Channel-aware":[60],"Inception":[61],"Depthwise":[62],"Convolution":[63],"(CIDW)":[64],"feature":[65,76,83,111],"extraction":[66],"module":[67,85,105],"is":[68,86,106,148],"proposed":[69,169],"enhance":[71],"capability":[73],"small-object":[75],"extraction.":[77],"Second,":[78],"Context-Dynamic":[80],"Attention":[81],"(CDA)":[82],"enhancement":[84],"developed":[87],"improve":[89,109],"model\u2019s":[91,117],"ability":[92],"capture":[94],"fine-grained":[95],"details":[96],"in":[97,174],"critical":[98],"regions.":[99],"Third,":[100],"Context-Enhanced":[102],"Mechanism":[103],"(CEM)":[104],"designed":[107],"pyramid":[112],"network,":[113],"thereby":[114],"strengthening":[115],"perception":[118,210],"high-resolution":[120],"features.":[121],"overcome":[123],"challenges":[125],"monocular":[127],"cameras":[128],"cannot":[129],"directly":[130],"obtain":[131],"threedimensional":[132],"information":[133],"long-distance":[136,194],"pixels":[137],"exhibit":[138],"nonlinear":[139],"errors,":[140],"innovative":[142],"Long-distance":[143],"Error":[144],"Correction":[145],"(LEC)":[146],"model":[147,159],"proposed.":[149],"By":[150],"combining":[151],"inverse":[153],"coordinate":[154],"transformation":[155],"formula,":[156],"LEC":[158],"enables":[160],"high-precision":[161],"3D":[162],"ranging.":[163],"Experimental":[164],"results":[165],"demonstrate":[166],"detector":[170],"outperforms":[171],"existing":[172],"algorithms":[173],"terms":[175],"detection":[177],"accuracy,":[178],"speed,":[179],"lightweight":[181],"design.":[182],"The":[183],"ranging":[184],"accuracy":[185],"reaches":[186],"millimeter":[188],"level":[189],"at":[190],"short":[191],"distances,":[192],"with":[193],"errors":[195],"controlled":[196],"within":[197],"approximately":[198],"5":[199],"cm,":[200],"making":[201],"it":[202],"effective":[204],"safety":[205],"approach":[207],"for":[208],"layer":[211],"substation":[214],"IoT":[215],"systems.":[216]},"counts_by_year":[],"updated_date":"2026-05-09T06:09:20.037420","created_date":"2026-02-13T00:00:00"}
