{"id":"https://openalex.org/W3080875990","doi":"https://doi.org/10.1145/3394486.3403378","title":"CrowdQuake","display_name":"CrowdQuake","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3080875990","doi":"https://doi.org/10.1145/3394486.3403378","mag":"3080875990"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403378","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403378","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","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/A5050693826","display_name":"Xin Huang","orcid":"https://orcid.org/0000-0002-5470-1203"},"institutions":[{"id":"https://openalex.org/I106959904","display_name":"Florida Institute of Technology","ror":"https://ror.org/04atsbb87","country_code":"US","type":"education","lineage":["https://openalex.org/I106959904"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Huang","raw_affiliation_strings":["Florida Institute of Technology, Melbourne, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Institute of Technology, Melbourne, FL, USA","institution_ids":["https://openalex.org/I106959904"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079507878","display_name":"Jang\u2010Soo Lee","orcid":"https://orcid.org/0000-0002-0255-1629"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jangsoo Lee","raw_affiliation_strings":["Kyungpook National University, Daegu, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyungpook National University, Daegu, South Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037246393","display_name":"Youngwoo Kwon","orcid":"https://orcid.org/0000-0003-0625-8232"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Young-Woo Kwon","raw_affiliation_strings":["Kyungpook National University, Daegu, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyungpook National University, Daegu, South Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100622990","display_name":"Chul\u2010Ho Lee","orcid":"https://orcid.org/0000-0001-6918-976X"},"institutions":[{"id":"https://openalex.org/I106959904","display_name":"Florida Institute of Technology","ror":"https://ror.org/04atsbb87","country_code":"US","type":"education","lineage":["https://openalex.org/I106959904"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chul-Ho Lee","raw_affiliation_strings":["Florida Institute of Technology, Melbourne, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Florida Institute of Technology, Melbourne, FL, USA","institution_ids":["https://openalex.org/I106959904"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.84,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.88552971,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3261","last_page":"3271"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13018","display_name":"Seismology and Earthquake Studies","score":0.9997000098228455,"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9976999759674072,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.736333966255188},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.6369260549545288},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.6009871959686279},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5924116969108582},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5234596133232117},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5106034874916077},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.4444178342819214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1986970603466034},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08801549673080444}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.736333966255188},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.6369260549545288},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.6009871959686279},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5924116969108582},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5234596133232117},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5106034874916077},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.4444178342819214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1986970603466034},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08801549673080444},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3403378","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403378","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2035160176","https://openalex.org/W2074607162","https://openalex.org/W2095705004","https://openalex.org/W2118216551","https://openalex.org/W2128889245","https://openalex.org/W2135566483","https://openalex.org/W2148580977","https://openalex.org/W2158698691","https://openalex.org/W2158979899","https://openalex.org/W2334757426","https://openalex.org/W2557283755","https://openalex.org/W2596487044","https://openalex.org/W2794417179","https://openalex.org/W2903104367","https://openalex.org/W3123554940","https://openalex.org/W4297727097","https://openalex.org/W6776634092"],"related_works":["https://openalex.org/W1974895211","https://openalex.org/W2176409448","https://openalex.org/W2129841057","https://openalex.org/W3040712279","https://openalex.org/W2364769705","https://openalex.org/W4367555392","https://openalex.org/W2374664672","https://openalex.org/W2056136368","https://openalex.org/W2538520412","https://openalex.org/W2883092465"],"abstract_inverted_index":{"Recently,":[0],"low-cost":[1,30,104],"acceleration":[2,105],"sensors":[3],"have":[4,149],"been":[5,150],"widely":[6],"used":[7],"to":[8,12,26,49,52,62,76],"detect":[9],"earthquakes":[10,147],"due":[11],"the":[13,29,65,87],"significant":[14],"development":[15],"of":[16,39,57,64,83,143],"MEMS":[17],"technologies.":[18],"It,":[19],"however,":[20],"still":[21],"requires":[22],"a":[23,40,54,99,116,132,144],"high-density":[24],"network":[25,119],"fully":[27],"harness":[28],"sensors,":[31,106],"especially":[32],"for":[33],"real-time":[34],"earthquake":[35,78],"detection.":[36],"The":[37],"design":[38],"high-performance":[41],"and":[42,69,111],"scalable":[43],"networked":[44,100],"system":[45,101],"thus":[46],"becomes":[47],"essential":[48],"be":[50],"able":[51],"process":[53],"large":[55],"amount":[56],"sensor":[58],"data":[59,89],"from":[60,80],"hundreds":[61],"thousands":[63],"sensors.":[66],"An":[67],"efficient":[68],"accurate":[70],"earthquake-detection":[71],"algorithm":[72],"is":[73],"also":[74,136],"necessary":[75],"distinguish":[77],"waveforms":[79],"various":[81],"kinds":[82],"non-earthquake":[84],"ones":[85],"within":[86],"huge":[88],"in":[90],"real":[91],"time.":[92],"In":[93],"this":[94],"paper,":[95],"we":[96],"present":[97],"CrowdQuake,":[98],"based":[102],"on":[103,141],"which":[107],"monitors":[108],"ground":[109],"motions":[110],"detects":[112],"earthquakes,":[113],"by":[114,152],"developing":[115],"convolutional-recurrent":[117],"neural":[118],"model.":[120],"This":[121],"model":[122],"ensures":[123],"high":[124],"detection":[125],"performance":[126],"while":[127],"maintaining":[128],"false":[129],"alarms":[130],"at":[131],"negligible":[133],"level.":[134],"We":[135],"provide":[137],"detailed":[138],"case":[139],"studies":[140],"two":[142],"few":[145],"small":[146],"that":[148],"detected":[151],"CrowdQuake":[153],"during":[154],"its":[155],"last":[156],"one-year":[157],"operation.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2020-09-01T00:00:00"}
