{"id":"https://openalex.org/W3216259322","doi":"https://doi.org/10.1155/2021/4799921","title":"Collaborative Big Data Management and Analytics in Complex Systems with Edge 2021 eaCamera: A Case Study on AI\u2010Based Complex Attention Analysis with Edge System","display_name":"Collaborative Big Data Management and Analytics in Complex Systems with Edge 2021 eaCamera: A Case Study on AI\u2010Based Complex Attention Analysis with Edge System","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3216259322","doi":"https://doi.org/10.1155/2021/4799921","mag":"3216259322"},"language":"en","primary_location":{"id":"doi:10.1155/2021/4799921","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/4799921","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/4799921.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/complexity/2021/4799921.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053468308","display_name":"Chaopeng Guo","orcid":"https://orcid.org/0000-0001-5022-5919"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaopeng Guo","raw_affiliation_strings":["Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning, China neu.edu.cn","Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning"],"raw_orcid":"https://orcid.org/0000-0001-5022-5919","affiliations":[{"raw_affiliation_string":"Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning, China neu.edu.cn","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075201826","display_name":"Peimeng Zhu","orcid":"https://orcid.org/0000-0001-9034-0380"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peimeng Zhu","raw_affiliation_strings":["Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning, China neu.edu.cn","Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning"],"raw_orcid":"https://orcid.org/0000-0001-9034-0380","affiliations":[{"raw_affiliation_string":"Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning, China neu.edu.cn","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448839","display_name":"Feng Li","orcid":"https://orcid.org/0000-0001-9236-1927"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Li","raw_affiliation_strings":["Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning, China neu.edu.cn","Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning"],"raw_orcid":"https://orcid.org/0000-0001-9236-1927","affiliations":[{"raw_affiliation_string":"Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning, China neu.edu.cn","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004612882","display_name":"Jie Song","orcid":"https://orcid.org/0000-0003-0704-3217"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Song","raw_affiliation_strings":["Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning, China neu.edu.cn","Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning"],"raw_orcid":"https://orcid.org/0000-0003-0704-3217","affiliations":[{"raw_affiliation_string":"Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning, China neu.edu.cn","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, Liaoning","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004612882"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":{"value":2760,"currency":"USD","value_usd":2760},"apc_paid":{"value":2760,"currency":"USD","value_usd":2760},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23062025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2021","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.989799976348877,"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"}},{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.9675999879837036,"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/perspective","display_name":"Perspective (graphical)","score":0.7186368107795715},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6727740168571472},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6570973992347717},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6210862994194031},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.6200072765350342},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.6157710552215576},{"id":"https://openalex.org/keywords/learning-analytics","display_name":"Learning analytics","score":0.540479302406311},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.528801441192627},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.47162652015686035},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4663267433643341},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.46423664689064026},{"id":"https://openalex.org/keywords/data-analysis","display_name":"Data analysis","score":0.4358088970184326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3900299370288849},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3572709560394287},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.19903600215911865},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1034790575504303}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7186368107795715},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6727740168571472},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6570973992347717},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6210862994194031},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.6200072765350342},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.6157710552215576},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.540479302406311},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.528801441192627},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.47162652015686035},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4663267433643341},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.46423664689064026},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.4358088970184326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3900299370288849},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3572709560394287},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.19903600215911865},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1034790575504303},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2021/4799921","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/4799921","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/4799921.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:4799921","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/complexity/2021/4799921.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:fd365f5f90c4484ba7370a4a09760a1d","is_oa":true,"landing_page_url":"https://doaj.org/article/fd365f5f90c4484ba7370a4a09760a1d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/4799921","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/4799921","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/4799921.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3216259322.pdf","grobid_xml":"https://content.openalex.org/works/W3216259322.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1996326832","https://openalex.org/W2046771020","https://openalex.org/W2113170322","https://openalex.org/W2141047785","https://openalex.org/W2161469100","https://openalex.org/W2197252109","https://openalex.org/W2212216676","https://openalex.org/W2468296993","https://openalex.org/W2511374729","https://openalex.org/W2585592883","https://openalex.org/W2612135493","https://openalex.org/W2626473805","https://openalex.org/W2735953094","https://openalex.org/W2739604974","https://openalex.org/W2755159844","https://openalex.org/W2760647406","https://openalex.org/W2808423829","https://openalex.org/W2886335102","https://openalex.org/W2901931186","https://openalex.org/W2909184935","https://openalex.org/W2912516042","https://openalex.org/W2938260698","https://openalex.org/W2955060956","https://openalex.org/W2962819150","https://openalex.org/W2963173190","https://openalex.org/W2969985801","https://openalex.org/W2972023276","https://openalex.org/W2988098865","https://openalex.org/W2988916019","https://openalex.org/W3006999887","https://openalex.org/W3014989972","https://openalex.org/W3018824114","https://openalex.org/W3034357629","https://openalex.org/W3092487288","https://openalex.org/W3110818405","https://openalex.org/W3114441380","https://openalex.org/W3118212025","https://openalex.org/W3121014547","https://openalex.org/W3122238731","https://openalex.org/W3126486982","https://openalex.org/W3133568254","https://openalex.org/W3154796165","https://openalex.org/W3157367050","https://openalex.org/W3162156224","https://openalex.org/W3167554351","https://openalex.org/W3171821356","https://openalex.org/W3196435190","https://openalex.org/W4293584584"],"related_works":["https://openalex.org/W1987827786","https://openalex.org/W2799586942","https://openalex.org/W2504091800","https://openalex.org/W2331775400","https://openalex.org/W2768832457","https://openalex.org/W2804624249","https://openalex.org/W605203981","https://openalex.org/W2560130217","https://openalex.org/W2911048623","https://openalex.org/W3025951784"],"abstract_inverted_index":{"As":[0],"an":[1,112],"extension":[2],"of":[3,13,36,57,76,80,102,126,179],"cloud":[4,14],"computing,":[5],"edge":[6,114],"computing":[7,15,21],"makes":[8,27],"up":[9],"for":[10,116,212],"the":[11,32,37,47,55,72,95,100,129,137,146,177,180,189,206],"deficiency":[12],"to":[16,31,40,46,93,99,121,144,201],"a":[17,28,67,151,183,192,198],"certain":[18],"extent.":[19],"Edge":[20],"reduces":[22],"unnecessary":[23],"data":[24],"transmission":[25],"and":[26,34,74,104,135,161,208],"significant":[29],"contribution":[30],"real\u2010time":[33],"security":[35],"system":[38,115],"due":[39],"its":[41],"characteristics":[42],"that":[43],"are":[44],"closer":[45],"terminal":[48],"equipment.":[49],"In":[50],"this":[51,108],"paper,":[52],"we":[53,110],"study":[54,194],"problem":[56],"attention":[58,117],"detection.":[59],"Attentional":[60],"concentration":[61,82,118,124,147],"during":[62],"some":[63],"specific":[64],"tasks":[65,103],"plays":[66],"vital":[68],"role,":[69],"which":[70],"indicates":[71,166,176],"effectiveness":[73],"performance":[75,204],"human":[77],"beings.":[78],"Evaluation":[79],"attentional":[81,123],"status":[83],"is":[84,91,195],"essential":[85],"in":[86,170,205],"many":[87],"fields.":[88],"However,":[89],"it":[90],"hard":[92],"define":[94],"behavior":[96,152,168,181,185],"features":[97],"related":[98],"variety":[101],"behaviors.":[105],"To":[106,131,187],"solve":[107],"problem,":[109],"propose":[111],"intelligent":[113],"analysis,":[119],"eaCamera,":[120],"recognize":[122],"behaviors":[125,148],"students":[127],"at":[128],"edge.":[130],"make":[132],"objective":[133],"measurements":[134],"save":[136],"label":[138],"cost,":[139],"eaCamera":[140],"utilizes":[141],"AI":[142],"approaches":[143],"find":[145],"based":[149],"on":[150],"analysis":[153],"model":[154],"with":[155],"two":[156],"perspectives,":[157],"namely,":[158],"individual":[159],"perspective":[160,165,175],"group":[162,174,184],"perspective.":[163],"Individual":[164],"personal":[167],"changes":[169,178],"time":[171],"dimension":[172],"while":[173],"within":[182,197],"manner.":[186],"evaluate":[188,202],"proposed":[190],"system,":[191],"case":[193],"done":[196],"primary":[199],"school":[200],"student\u2019s":[203],"classroom":[207],"offer":[209],"teaching":[210],"advice":[211],"teachers.":[213]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
