{"id":"https://openalex.org/W4410810302","doi":"https://doi.org/10.1109/rivf64335.2024.11009058","title":"Development of an Integrated Safety Management Model in Traditional Markets Based on Deep Learning","display_name":"Development of an Integrated Safety Management Model in Traditional Markets Based on Deep Learning","publication_year":2024,"publication_date":"2024-12-21","ids":{"openalex":"https://openalex.org/W4410810302","doi":"https://doi.org/10.1109/rivf64335.2024.11009058"},"language":"en","primary_location":{"id":"doi:10.1109/rivf64335.2024.11009058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rivf64335.2024.11009058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 RIVF International Conference on Computing and Communication Technologies (RIVF)","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/A5089961726","display_name":"Sook-Haeng Joe","orcid":"https://orcid.org/0000-0003-2316-0691"},"institutions":[{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"SeongJu Joe","raw_affiliation_strings":["Chungbuk National University,Dept. of Bigdata,Cheongju,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Chungbuk National University,Dept. of Bigdata,Cheongju,Republic of Korea","institution_ids":["https://openalex.org/I163753206"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072864792","display_name":"Deokgyu Yun","orcid":"https://orcid.org/0000-0002-5463-1479"},"institutions":[{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongkyu Yun","raw_affiliation_strings":["Chungbuk National University,Dept. of Bigdata,Cheongju,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Chungbuk National University,Dept. of Bigdata,Cheongju,Republic of Korea","institution_ids":["https://openalex.org/I163753206"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032405346","display_name":"Sang Hyun Choi","orcid":"https://orcid.org/0000-0002-6898-6617"},"institutions":[{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanghyun Choi","raw_affiliation_strings":["Chungbuk National University,Dept. of Bigdata,Cheongju,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Chungbuk National University,Dept. of Bigdata,Cheongju,Republic of Korea","institution_ids":["https://openalex.org/I163753206"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5089961726"],"corresponding_institution_ids":["https://openalex.org/I163753206"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49663408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14484","display_name":"Technology and Data Analysis","score":0.6610000133514404,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T14484","display_name":"Technology and Data Analysis","score":0.6610000133514404,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/deep-learning","display_name":"Deep learning","score":0.5576634407043457},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5340608358383179},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.43572449684143066},{"id":"https://openalex.org/keywords/engineering-management","display_name":"Engineering management","score":0.37323758006095886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37212076783180237},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3525789678096771},{"id":"https://openalex.org/keywords/process-management","display_name":"Process management","score":0.33936652541160583},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.3383418321609497},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2400064468383789}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5576634407043457},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5340608358383179},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.43572449684143066},{"id":"https://openalex.org/C110354214","wikidata":"https://www.wikidata.org/wiki/Q6314146","display_name":"Engineering management","level":1,"score":0.37323758006095886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37212076783180237},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3525789678096771},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.33936652541160583},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3383418321609497},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2400064468383789}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rivf64335.2024.11009058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rivf64335.2024.11009058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 RIVF International Conference on Computing and Communication Technologies (RIVF)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2790670888","https://openalex.org/W2793703265","https://openalex.org/W3095292005","https://openalex.org/W3107727158","https://openalex.org/W4385812309","https://openalex.org/W4388450957","https://openalex.org/W6801002424"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2804383999"],"abstract_inverted_index":{"The":[0,24,53],"roofs":[1],"installed":[2],"in":[3,7,90],"most":[4],"traditional":[5],"markets":[6],"Korea":[8],"are":[9],"made":[10],"of":[11,49],"flammable":[12],"materials,":[13],"making":[14],"them":[15],"highly":[16],"susceptible":[17],"to":[18,31,64,99],"large":[19],"fires":[20,50],"from":[21],"small":[22],"sparks.":[23],"enclosed":[25],"structure":[26],"further":[27],"exacerbates":[28],"the":[29],"vulnerability":[30],"safety":[32],"accidents.":[33],"Therefore,":[34],"this":[35,79],"study":[36],"proposes":[37],"a":[38,43,75,83],"unified":[39],"model":[40,84],"that":[41,85],"employs":[42],"modular":[44,54],"approach":[45],"for":[46,59],"accurate":[47],"detection":[48],"and":[51,69],"smoke.":[52],"method":[55],"enables":[56],"optimized":[57],"learning":[58,65],"each":[60],"event,":[61],"as":[62],"opposed":[63],"all":[66],"events":[67],"simultaneously,":[68],"maintains":[70],"superior":[71],"performance":[72],"even":[73],"with":[74],"smaller":[76],"dataset.":[77],"Through":[78],"study,":[80],"we":[81],"propose":[82],"can":[86],"be":[87],"easily":[88],"implemented":[89],"aging":[91],"facilities,":[92],"mitigating":[93],"indiscriminate":[94],"fire":[95],"department":[96],"dispatches":[97],"due":[98],"IoT":[100],"sensor":[101],"malfunctions":[102]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
