{"id":"https://openalex.org/W4408401774","doi":"https://doi.org/10.1109/ictbig64922.2024.10911746","title":"Traffic Flow in Smart Cities using Dense Clisteer Humboldt Squid Steerable Nested Convolutional Attention Network","display_name":"Traffic Flow in Smart Cities using Dense Clisteer Humboldt Squid Steerable Nested Convolutional Attention Network","publication_year":2024,"publication_date":"2024-12-13","ids":{"openalex":"https://openalex.org/W4408401774","doi":"https://doi.org/10.1109/ictbig64922.2024.10911746"},"language":"en","primary_location":{"id":"doi:10.1109/ictbig64922.2024.10911746","doi":"https://doi.org/10.1109/ictbig64922.2024.10911746","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictbig64922.2024.10911746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 4th International Conference on ICT in Business Industry &amp;amp; Government (ICTBIG)","raw_type":"proceedings-article"},"volume":null,"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/A5121810666","display_name":"P. Vishnu Kumar","orcid":"https://orcid.org/0009-0006-1342-906X","observed_orcids":["https://orcid.org/0009-0006-1342-906X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P Vishnu Kumar","raw_affiliation_strings":["G. Pullaiah College of Engineering and Technology,Department of ECE,Kurnool,518002"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"G. Pullaiah College of Engineering and Technology,Department of ECE,Kurnool,518002","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108539560","display_name":"Bandaru Satya Lakshmi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405262389","display_name":"Aditya University","ror":"https://ror.org/03127q162","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405262389"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bandaru Satya Lakshmi","raw_affiliation_strings":["Aditya University,Department of Computer Science and Engineering,Surampalem,Andhra Pradesh,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aditya University,Department of Computer Science and Engineering,Surampalem,Andhra Pradesh,India","institution_ids":["https://openalex.org/I4405262389"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mohanapriya R","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405258486","display_name":"Paavai Engineering College","ror":"https://ror.org/00r7c6e04","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405258486"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mohanapriya R","raw_affiliation_strings":["Paavai Engineering College,Department of ECE,Namakkal,Tamil Nadu,637018"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Paavai Engineering College,Department of ECE,Namakkal,Tamil Nadu,637018","institution_ids":["https://openalex.org/I4405258486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104325645","display_name":"R. Archana Reddy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405263155","display_name":"SR University","ror":"https://ror.org/039t32v17","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405263155"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Archana Reddy","raw_affiliation_strings":["SR University,School of Computer Science and Artificial Intelligence,Warangal,Telangana,506371"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SR University,School of Computer Science and Artificial Intelligence,Warangal,Telangana,506371","institution_ids":["https://openalex.org/I4405263155"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092647371","display_name":"Ramya Maranan","orcid":"https://orcid.org/0009-0007-8772-961X","observed_orcids":["https://orcid.org/0009-0007-8772-961X"]},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R Maranan","raw_affiliation_strings":["Saveetha School of Engineering, SIMATS,Department of Research and Innovation,Chennai,Tamil Nadu,India,602105"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saveetha School of Engineering, SIMATS,Department of Research and Innovation,Chennai,Tamil Nadu,India,602105","institution_ids":["https://openalex.org/I85461943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053416047","display_name":"M. Ramya","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I110360157","display_name":"Lovely Professional University","ror":"https://ror.org/00et6q107","country_code":"IN","type":"education","lineage":["https://openalex.org/I110360157"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M. Ramya","raw_affiliation_strings":["Lovely Professional University,Division of Research and Development,Phagwara,Punjab,India,144411"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lovely Professional University,Division of Research and Development,Phagwara,Punjab,India,144411","institution_ids":["https://openalex.org/I110360157"]}]}],"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":0.46151288,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10524","display_name":"Traffic control and management","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/traffic-flow-prediction","display_name":"traffic flow prediction","score":0.9229999780654907},{"id":"https://openalex.org/keywords/smart-cities","display_name":"smart cities","score":0.796999990940094},{"id":"https://openalex.org/keywords/urban-traffic-management","display_name":"urban traffic management","score":0.8289999961853027},{"id":"https://openalex.org/keywords/traffic-congestion-prediction","display_name":"traffic congestion prediction","score":0.8510000109672546},{"id":"https://openalex.org/keywords/dosidicus-gigas","display_name":"Dosidicus gigas","score":0.6650000214576721},{"id":"https://openalex.org/keywords/traffic-data-preprocessing","display_name":"traffic data preprocessing","score":0.5889999866485596},{"id":"https://openalex.org/keywords/spatiotemporal-traffic-patterns","display_name":"spatiotemporal traffic patterns","score":0.8479999899864197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5627704858779907},{"id":"https://openalex.org/C2777743550","wikidata":"https://www.wikidata.org/wiki/Q81900","display_name":"Squid","level":2,"score":0.4821888506412506},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4752483367919922},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4430181682109833},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.39255648851394653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2699510455131531},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14589297771453857},{"id":"https://openalex.org/C505870484","wikidata":"https://www.wikidata.org/wiki/Q180538","display_name":"Fishery","level":1,"score":0.11945146322250366},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictbig64922.2024.10911746","doi":"https://doi.org/10.1109/ictbig64922.2024.10911746","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictbig64922.2024.10911746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 4th International Conference on ICT in Business Industry &amp;amp; Government (ICTBIG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":1.0,"display_name":"Industry, innovation and infrastructure"},{"id":"https://metadata.un.org/sdg/11","score":1.0,"display_name":"Sustainable cities and communities"}],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/11","score":0.6499999761581421,"display_name":"Sustainable cities and communities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W3016083025","https://openalex.org/W3134953499","https://openalex.org/W4293104632","https://openalex.org/W4297018398","https://openalex.org/W4298109690","https://openalex.org/W4322506664","https://openalex.org/W4323781837","https://openalex.org/W4327772947","https://openalex.org/W4328025122","https://openalex.org/W4362544663","https://openalex.org/W4362612809","https://openalex.org/W4362613122","https://openalex.org/W4387422716","https://openalex.org/W4387446363","https://openalex.org/W4387677188","https://openalex.org/W4387677285","https://openalex.org/W4387677421","https://openalex.org/W4387677423","https://openalex.org/W4389236973","https://openalex.org/W4391075550","https://openalex.org/W4391643840","https://openalex.org/W4391698389","https://openalex.org/W4392944985","https://openalex.org/W4392945087","https://openalex.org/W4393028533","https://openalex.org/W4394744629","https://openalex.org/W4395070057","https://openalex.org/W4401567508","https://openalex.org/W4402982000","https://openalex.org/W4403023083","https://openalex.org/W4409360857"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2327985590","https://openalex.org/W2330592365","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W2021707253","https://openalex.org/W2313240169"],"abstract_inverted_index":{"As":[0],"urban":[1,28,146],"populations":[2],"continue":[3],"to":[4,47,101,131,135],"swell;":[5],"managing":[6],"traffic":[7,16,33,49,66,123,143,147,163],"flow":[8,67,144],"in":[9,150,168],"smart":[10,169],"cities":[11],"becomes":[12],"increasingly":[13],"complex.":[14],"Efficient":[15],"management":[17,50,166],"is":[18,59,87,130],"essential":[19],"for":[20,99,116],"reducing":[21],"congestion,":[22],"improving":[23,142,162],"safety,":[24],"and":[25,42,110,121,138,165],"enhancing":[26],"overall":[27],"quality":[29],"of":[30,44,145,159],"life.":[31],"Traditional":[32],"monitoring":[34],"systems":[35],"often":[36],"struggle":[37],"with":[38],"the":[39,71,84,133,152],"sheer":[40],"volume":[41],"variety":[43],"data,":[45],"leading":[46],"suboptimal":[48],"strategies.":[51],"This":[52],"research":[53],"addresses":[54],"these":[55],"challenges,":[56],"this":[57,62,128],"work":[58],"proposed.":[60],"In":[61,82],"manuscript,":[63],"an":[64,113,156],"advanced":[65],"analysis":[68],"framework":[69,129],"utilizing":[70],"Dense":[72],"Clisteer":[73],"Humboldt":[74],"Squid":[75],"Steerable":[76],"Nested":[77],"Convolutional":[78],"Attention":[79],"Network":[80],"(DCli-H2S-NConv-AtNet).":[81],"this,":[83],"input":[85],"dataset":[86],"taken":[88],"from":[89],"INRIX":[90],"database.":[91],"Then":[92],"using":[93,112],"Shape-Aware":[94],"Mesh":[95],"Normal":[96],"Filtering":[97],"(SAMNF)":[98],"preprocessing":[100],"ensure":[102],"high-quality,":[103],"noise-free":[104],"data.":[105],"Features":[106],"are":[107],"then":[108],"extracted":[109],"classified":[111],"appropriate":[114],"DCli-H2S-NConv-AtNet":[115,153],"accurately":[117],"modelling":[118],"complex":[119],"spatial":[120],"temporal":[122],"patterns.":[124],"The":[125],"rationale":[126],"behind":[127],"improve":[132],"ability":[134],"forecast":[136],"congestion":[137],"non-congestion":[139],"conditions":[140],"thus":[141],"management.":[148],"Implemented":[149],"Python,":[151],"model":[154],"achieves":[155],"impressive":[157],"accuracy":[158],"99%,":[160],"significantly":[161],"prediction":[164],"capabilities":[167],"cities.":[170]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}
