{"id":"https://openalex.org/W4205148976","doi":"https://doi.org/10.1109/comsnets53615.2022.9668404","title":"Covid-19 Impact and Implications on Traffic: Smart Predictive Analytics for Mobility Navigation","display_name":"Covid-19 Impact and Implications on Traffic: Smart Predictive Analytics for Mobility Navigation","publication_year":2022,"publication_date":"2022-01-04","ids":{"openalex":"https://openalex.org/W4205148976","doi":"https://doi.org/10.1109/comsnets53615.2022.9668404"},"language":"en","primary_location":{"id":"doi:10.1109/comsnets53615.2022.9668404","is_oa":false,"landing_page_url":"https://doi.org/10.1109/comsnets53615.2022.9668404","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on COMmunication Systems &amp; NETworkS (COMSNETS)","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/A5063510135","display_name":"Jaswanth Nidamanuri","orcid":"https://orcid.org/0000-0003-1614-7341"},"institutions":[{"id":"https://openalex.org/I4387155292","display_name":"Indian Institute of Information Technology Sri City","ror":"https://ror.org/026873d40","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155292"]},{"id":"https://openalex.org/I26072440","display_name":"Indian Institute of Information Technology Allahabad","ror":"https://ror.org/03rgjt374","country_code":"IN","type":"education","lineage":["https://openalex.org/I26072440"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jaswanth Nidamanuri","raw_affiliation_strings":["Smart Transportation Research Group, Indian Institute of Information Technology, Sri City, India"],"affiliations":[{"raw_affiliation_string":"Smart Transportation Research Group, Indian Institute of Information Technology, Sri City, India","institution_ids":["https://openalex.org/I26072440","https://openalex.org/I4387155292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050803243","display_name":"A Rohith","orcid":null},"institutions":[{"id":"https://openalex.org/I26072440","display_name":"Indian Institute of Information Technology Allahabad","ror":"https://ror.org/03rgjt374","country_code":"IN","type":"education","lineage":["https://openalex.org/I26072440"]},{"id":"https://openalex.org/I4387155292","display_name":"Indian Institute of Information Technology Sri City","ror":"https://ror.org/026873d40","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A. Rohith","raw_affiliation_strings":["Smart Transportation Research Group, Indian Institute of Information Technology, Sri City, India"],"affiliations":[{"raw_affiliation_string":"Smart Transportation Research Group, Indian Institute of Information Technology, Sri City, India","institution_ids":["https://openalex.org/I26072440","https://openalex.org/I4387155292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083121355","display_name":"SRIVASTAVA PRANJAL","orcid":null},"institutions":[{"id":"https://openalex.org/I26072440","display_name":"Indian Institute of Information Technology Allahabad","ror":"https://ror.org/03rgjt374","country_code":"IN","type":"education","lineage":["https://openalex.org/I26072440"]},{"id":"https://openalex.org/I4387155292","display_name":"Indian Institute of Information Technology Sri City","ror":"https://ror.org/026873d40","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. Pranjal","raw_affiliation_strings":["Smart Transportation Research Group, Indian Institute of Information Technology, Sri City, India"],"affiliations":[{"raw_affiliation_string":"Smart Transportation Research Group, Indian Institute of Information Technology, Sri City, India","institution_ids":["https://openalex.org/I26072440","https://openalex.org/I4387155292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039283122","display_name":"Hrishikesh Venkataraman","orcid":"https://orcid.org/0000-0002-9635-9872"},"institutions":[{"id":"https://openalex.org/I26072440","display_name":"Indian Institute of Information Technology Allahabad","ror":"https://ror.org/03rgjt374","country_code":"IN","type":"education","lineage":["https://openalex.org/I26072440"]},{"id":"https://openalex.org/I4387155292","display_name":"Indian Institute of Information Technology Sri City","ror":"https://ror.org/026873d40","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hrishikesh Venkataraman","raw_affiliation_strings":["Smart Transportation Research Group, Indian Institute of Information Technology, Sri City, India"],"affiliations":[{"raw_affiliation_string":"Smart Transportation Research Group, Indian Institute of Information Technology, Sri City, India","institution_ids":["https://openalex.org/I26072440","https://openalex.org/I4387155292"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5063510135"],"corresponding_institution_ids":["https://openalex.org/I26072440","https://openalex.org/I4387155292"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00282417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"141","issue":null,"first_page":"812","last_page":"817"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7351773381233215},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5905869007110596},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5553109049797058},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5405650734901428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5201804637908936},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5178318619728088},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48129382729530334},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45442771911621094},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.450204998254776},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4270632266998291},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4138652980327606},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36841878294944763},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.34671974182128906},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.32971012592315674},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.30149900913238525},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1700599491596222}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7351773381233215},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5905869007110596},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5553109049797058},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5405650734901428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5201804637908936},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5178318619728088},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48129382729530334},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45442771911621094},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.450204998254776},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4270632266998291},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4138652980327606},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36841878294944763},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34671974182128906},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.32971012592315674},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30149900913238525},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1700599491596222},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/comsnets53615.2022.9668404","is_oa":false,"landing_page_url":"https://doi.org/10.1109/comsnets53615.2022.9668404","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on COMmunication Systems &amp; NETworkS (COMSNETS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2601802123","https://openalex.org/W2907228515","https://openalex.org/W3017208336","https://openalex.org/W3112210044","https://openalex.org/W3116454788","https://openalex.org/W3119265355","https://openalex.org/W3131927228","https://openalex.org/W3131983688","https://openalex.org/W3199176291","https://openalex.org/W3209752914"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W4386690025","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W2073883415","https://openalex.org/W4310224730"],"abstract_inverted_index":{"Traffic":[0],"prediction":[1],"and":[2,15,32,63,75,84,114,157,164,177,207,210],"analysis":[3,127,153,182],"is":[4,26,89,121,139,179,202],"an":[5],"essential":[6],"task":[7],"towards":[8],"intelligent":[9],"mobility,":[10],"particularly":[11,43],"for":[12,124,141,181,204],"path":[13],"planning":[14],"navigation.":[16],"When":[17],"the":[18,23,28,54,64,96,107,111,119,129,135,155,189,205,213],"traffic":[19,77,104,160,186],"flow":[20],"starts":[21],"after":[22],"COVID-19":[24],"pandemic":[25],"subsided,":[27],"mobility":[29],"patterns":[30],"changes":[31],"may":[33,40],"become":[34],"unpredictable":[35],"or":[36],"challenging.":[37],"This":[38],"problem":[39],"be":[41],"crucial,":[42],"if":[44],"many":[45],"people":[46],"hurry":[47],"to":[48,73,94],"single":[49],"occupancy":[50],"transport":[51],"mode.":[52],"Notably,":[53,148],"rapid":[55],"development":[56],"in":[57,79,91,101,145,183],"machine":[58],"learning":[59,163,167],"with":[60,193,212],"new":[61,67],"methods":[62],"emergence":[65],"of":[66,98,110,132,154,175,200],"data":[68],"sources":[69],"make":[70],"it":[71],"possible":[72],"evaluate":[74],"predict":[76],"conditions":[78],"smart":[80],"cities":[81],"more":[82],"quickly":[83],"precisely.":[85],"The":[86],"proposed":[87,185],"work":[88],"modeled":[90],"two-fold":[92],"manner":[93],"investigate":[95],"impact":[97],"COVID":[99],"shift":[100],"regular":[102],"urban":[103],"movements":[105],"given":[106],"particular":[108],"period":[109],"pre,":[112],"during,":[113],"post":[115],"lockdown":[116],"phases.":[117],"Firstly,":[118],"investigation":[120],"carried":[122],"out":[123],"time":[125,143],"series":[126],"considering":[128],"three":[130],"phases":[131],"lockdown.":[133],"Secondly,":[134],"real-time":[136],"spatial":[137],"information":[138],"analyzed":[140],"different":[142],"zones":[144],"a":[146,151],"day.":[147],"this":[149,184],"requires":[150],"detailed":[152],"heterogeneous":[156],"complex":[158],"input":[159],"data.":[161],"Machine":[162],"advanced":[165],"deep":[166],"methodologies":[168],"such":[169],"as":[170],"regression":[171,216],"models,":[172,209],"RNN,":[173],"variants":[174],"LSTM,":[176],"GRU":[178,208],"used":[180],"modeling.":[187],"Significantly,":[188],"least":[190],"error":[191],"scores":[192],"Root":[194],"Mean":[195],"Square":[196],"Error":[197],"(RMSE)":[198],"loss":[199],"1.82":[201],"observed":[203],"RNN":[206],"0.058":[211],"Gradient":[214],"Boosting":[215],"analysis,":[217],"respectively.":[218]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
