{"id":"https://openalex.org/W2782768990","doi":"https://doi.org/10.1109/ispacs.2017.8266474","title":"A novel excavation device recognition based underground network surveilliance system","display_name":"A novel excavation device recognition based underground network surveilliance system","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2782768990","doi":"https://doi.org/10.1109/ispacs.2017.8266474","mag":"2782768990"},"language":"en","primary_location":{"id":"doi:10.1109/ispacs.2017.8266474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2017.8266474","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","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/A5103145983","display_name":"Xu Ru","orcid":"https://orcid.org/0000-0001-9161-3651"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ru Xu","raw_affiliation_strings":["Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Zhejiang, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036807368","display_name":"Jianzhong Wang","orcid":"https://orcid.org/0000-0001-7353-5995"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzhong Wang","raw_affiliation_strings":["Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Zhejiang, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075474564","display_name":"Tianlei Wang","orcid":"https://orcid.org/0000-0002-4498-4326"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianlei Wang","raw_affiliation_strings":["Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Zhejiang, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074063024","display_name":"Jiuwen Cao","orcid":"https://orcid.org/0000-0002-6480-5794"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiuwen Cao","raw_affiliation_strings":["Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Lab for IOT and Information Fusion Technology of Zhejiang, Hangzhou Dianzi University, Zhejiang, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035422552","display_name":"Huanqiang Zeng","orcid":"https://orcid.org/0000-0002-2802-7745"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanqiang Zeng","raw_affiliation_strings":["School of Information Science and Engineering, Huaqiao University, Xiamen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Huaqiao University, Xiamen, China","institution_ids":["https://openalex.org/I119045251"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20589509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"206","last_page":"211"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9994000196456909,"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/T12676","display_name":"Machine Learning and ELM","score":0.9994000196456909,"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/T11220","display_name":"Water Systems and Optimization","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11609","display_name":"Geophysical Methods and Applications","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/excavation","display_name":"Excavation","score":0.808091938495636},{"id":"https://openalex.org/keywords/microphone","display_name":"Microphone","score":0.5971468091011047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5837278366088867},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5829246640205383},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5530824065208435},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.5035292506217957},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.48129573464393616},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46989676356315613},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.44617608189582825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42064958810806274},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.36930662393569946},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10840368270874023},{"id":"https://openalex.org/keywords/sound-pressure","display_name":"Sound pressure","score":0.09581205248832703}],"concepts":[{"id":"https://openalex.org/C31858485","wikidata":"https://www.wikidata.org/wiki/Q959782","display_name":"Excavation","level":2,"score":0.808091938495636},{"id":"https://openalex.org/C2778263558","wikidata":"https://www.wikidata.org/wiki/Q46384","display_name":"Microphone","level":3,"score":0.5971468091011047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5837278366088867},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5829246640205383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5530824065208435},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.5035292506217957},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.48129573464393616},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46989676356315613},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.44617608189582825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42064958810806274},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36930662393569946},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10840368270874023},{"id":"https://openalex.org/C68115822","wikidata":"https://www.wikidata.org/wiki/Q1068172","display_name":"Sound pressure","level":2,"score":0.09581205248832703},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispacs.2017.8266474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2017.8266474","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1551640747","https://openalex.org/W2007146523","https://openalex.org/W2026131661","https://openalex.org/W2031878488","https://openalex.org/W2032510388","https://openalex.org/W2044961446","https://openalex.org/W2048629585","https://openalex.org/W2098290011","https://openalex.org/W2111072639","https://openalex.org/W2131284441","https://openalex.org/W2138260443","https://openalex.org/W2175070000","https://openalex.org/W2214628823","https://openalex.org/W2292698124","https://openalex.org/W2343801481","https://openalex.org/W2463468632","https://openalex.org/W2524029051","https://openalex.org/W2526793952","https://openalex.org/W6688690571","https://openalex.org/W6728182163"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2968645206","https://openalex.org/W2556335056","https://openalex.org/W2002678693","https://openalex.org/W1584764049","https://openalex.org/W2765298776"],"abstract_inverted_index":{"In":[0],"this":[1,126],"paper,":[2],"we":[3],"propose":[4],"an":[5,37,84],"intelligent":[6,38],"network":[7,87],"surveillance":[8,46],"system":[9],"to":[10,71,103],"protect":[11],"the":[12,50,73,79,90,97,105,116,119],"urban":[13],"underground":[14],"pipelines":[15],"from":[16],"external":[17],"damages":[18],"caused":[19],"by":[20,89],"excavation":[21,39,108],"devices.":[22],"At":[23],"each":[24,111],"monitoring":[25,54,112],"site,":[26],"a":[27,59],"microphone":[28],"array":[29],"is":[30,43,56,68,101,135],"implemented":[31],"for":[32,58,78],"real-time":[33],"acoustic":[34,81],"collection":[35],"and":[36,75,96],"device":[40],"recognition":[41,106],"algorithm":[42],"embedded.":[44],"A":[45,62],"platform":[47],"built":[48],"on":[49,130],"fusion":[51],"of":[52,107,118],"multi":[53],"sites":[55],"designed":[57],"whole":[60],"city.":[61],"novel":[63],"statistical":[64],"feature":[65],"extraction":[66],"method":[67],"first":[69],"developed":[70],"mining":[72],"useful":[74],"representative":[76],"information":[77],"collected":[80],"signals.":[82],"Then,":[83],"artificial":[85],"neural":[86],"trained":[88],"popular":[91],"extreme":[92],"learning":[93],"machine":[94],"(ELM)":[95],"regularized":[98],"ELM":[99],"(RELM)":[100],"used":[102],"perform":[104],"devices":[109,134],"in":[110,125],"site.":[113],"To":[114],"show":[115],"efficiency":[117],"proposed":[120],"system,":[121],"experiments":[122],"are":[123],"conducted":[124],"paper.":[127],"Recognition":[128],"performance":[129],"four":[131],"most":[132],"destructive":[133],"studied.":[136]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}