{"id":"https://openalex.org/W4398150818","doi":"https://doi.org/10.1109/tbdata.2024.3403392","title":"Deep Learning Based Anomaly Detection Approach for Air Pollution Assessment","display_name":"Deep Learning Based Anomaly Detection Approach for Air Pollution Assessment","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4398150818","doi":"https://doi.org/10.1109/tbdata.2024.3403392"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2024.3403392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2024.3403392","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Big Data","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/A5008410457","display_name":"Anindita Borah","orcid":"https://orcid.org/0000-0001-6023-849X"},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Anindita Borah","raw_affiliation_strings":["Technology Innovation and Development Foundation, Indian Institute of Technology Guwahati, Guwahati, Assam, India","Technology Innovation and Development Foundation, Indian Institute of Technology, Guwahati, India"],"raw_orcid":"https://orcid.org/0000-0001-6023-849X","affiliations":[{"raw_affiliation_string":"Technology Innovation and Development Foundation, Indian Institute of Technology Guwahati, Guwahati, Assam, India","institution_ids":["https://openalex.org/I1317621060"]},{"raw_affiliation_string":"Technology Innovation and Development Foundation, Indian Institute of Technology, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5008410457"],"corresponding_institution_ids":["https://openalex.org/I1317621060"],"apc_list":null,"apc_paid":null,"fwci":0.7861,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.6711548,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"11","issue":"2","first_page":"414","last_page":"425"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.740246057510376},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.715305507183075},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4490467309951782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44062909483909607},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44023096561431885},{"id":"https://openalex.org/keywords/air-pollution","display_name":"Air pollution","score":0.4204222857952118},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3655524253845215},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3520730137825012},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3427305221557617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.740246057510376},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.715305507183075},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4490467309951782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44062909483909607},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44023096561431885},{"id":"https://openalex.org/C559116025","wikidata":"https://www.wikidata.org/wiki/Q131123","display_name":"Air pollution","level":2,"score":0.4204222857952118},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3655524253845215},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3520730137825012},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3427305221557617},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2024.3403392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2024.3403392","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5}],"awards":[],"funders":[{"id":"https://openalex.org/F4320327457","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079"},{"id":"https://openalex.org/F4320336765","display_name":"Indian Institute of Tropical Meteorology","ror":"https://ror.org/03jf2m686"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1850325679","https://openalex.org/W1969865391","https://openalex.org/W1971402834","https://openalex.org/W2032576386","https://openalex.org/W2039082808","https://openalex.org/W2048752066","https://openalex.org/W2186910770","https://openalex.org/W2608847424","https://openalex.org/W2767894694","https://openalex.org/W2803892188","https://openalex.org/W2889285628","https://openalex.org/W2906498146","https://openalex.org/W2909877301","https://openalex.org/W2987793235","https://openalex.org/W2989592345","https://openalex.org/W3086419524","https://openalex.org/W3113701344","https://openalex.org/W3175807109","https://openalex.org/W4233713109","https://openalex.org/W4293507940","https://openalex.org/W4313644197","https://openalex.org/W6744798462","https://openalex.org/W6756753118"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"Environmental":[0],"air":[1,19,29,49,106,220],"pollution":[2,221],"has":[3],"become":[4],"a":[5,35,89,112,121,159],"cause":[6],"of":[7,18,46,115,162,183,198,213],"global":[8],"concern":[9],"due":[10],"to":[11,42,133,158,173,194],"its":[12],"adverse":[13],"effects.":[14],"Unusually":[15],"high":[16],"concentration":[17,206],"pollutants":[20,107],"can":[21],"be":[22],"regarded":[23],"as":[24],"an":[25],"anomaly":[26,39,169],"indicating":[27],"certain":[28],"quality":[30],"problems.":[31],"This":[32],"paper":[33],"presents":[34],"deep":[36],"learning":[37],"based":[38,128,179],"detection":[40],"approach":[41,215],"identify":[43,174],"anomalous":[44,176,205],"concentrations":[45],"five":[47],"different":[48],"pollutants:":[50],"Carbon":[51],"Monoxide":[52],"(":[53,60,68,77],"<inline-formula":[54,61,69,78,83],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[55,62,70,79,84],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[56,63,71,80,85],"notation=\"LaTeX\">$CO$</tex-math></inline-formula>":[57],"),":[58,65],"Ozone":[59],"notation=\"LaTeX\">$O_{3}$</tex-math></inline-formula>":[64],"Nitogen":[66],"Oxide":[67],"notation=\"LaTeX\">$NO_{X}$</tex-math></inline-formula>":[72],")":[73,87],"and":[74,108,200],"Particulate":[75],"Matters":[76],"notation=\"LaTeX\">$PM_{2.5}$</tex-math></inline-formula>":[81],",":[82],"notation=\"LaTeX\">$PM_{10}$</tex-math></inline-formula>":[86],"in":[88,98,139],"real-life":[90],"environmental":[91],"dataset.":[92,143],"The":[93,117,144],"collected":[94],"data":[95],"is":[96,147,171],"multivariate":[97],"nature":[99],"containing":[100],"hourly":[101],"generated":[102],"information":[103],"about":[104],"several":[105],"atmospheric":[109,201],"parameters":[110,202],"from":[111],"non-polluted":[113],"city":[114],"India.":[116],"proposed":[118,190,214],"framework":[119,191],"contains":[120],"Bidirectional":[122],"Long":[123],"Short":[124],"Term":[125],"Memory":[126],"(Bi-LSTM)":[127],"predictor":[129,145,184],"model":[130,146],"with":[131,203],"self-attention":[132],"capture":[134],"the":[135,140,151,154,163,175,181,189,196,204,211],"normal":[136],"pollutant":[137,177],"levels":[138,178],"time":[141,164],"series":[142,165],"responsible":[148],"for":[149],"predicting":[150],"value":[152],"at":[153],"next":[155],"timestamp,":[156],"corresponding":[157],"given":[160],"window":[161],"data.":[166],"A":[167],"subsequent":[168],"detector":[170],"utilized":[172,193],"on":[180],"predictions":[182],"model.":[185],"Anomalies":[186],"detected":[187],"by":[188],"are":[192],"analyze":[195],"correlation":[197],"temporal":[199],"levels.":[207],"Experimental":[208],"results":[209],"illustrate":[210],"predominance":[212],"over":[216],"existing":[217],"approaches":[218],"towards":[219],"assessment.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
