{"id":"https://openalex.org/W7128616239","doi":"https://doi.org/10.1109/jiot.2026.3663597","title":"A Geospatial Grid Constrained Deep Learning Prediction Framework Based on AIS Data for Improving Vessel Traffic Services in Maritime Internet of Things","display_name":"A Geospatial Grid Constrained Deep Learning Prediction Framework Based on AIS Data for Improving Vessel Traffic Services in Maritime Internet of Things","publication_year":2026,"publication_date":"2026-02-11","ids":{"openalex":"https://openalex.org/W7128616239","doi":"https://doi.org/10.1109/jiot.2026.3663597"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3663597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3663597","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Internet of Things Journal","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/A5125679457","display_name":"Wenjing Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjing Yan","raw_affiliation_strings":["School of Management, China University of Mining and Technology (Beijing), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5746-2474","affiliations":[{"raw_affiliation_string":"School of Management, China University of Mining and Technology (Beijing), Beijing, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123762808","display_name":"Jiabao Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiabao Wen","raw_affiliation_strings":["School of Public Policy and Administration, Nanchang University, Nanchang, Jiangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Public Policy and Administration, Nanchang University, Nanchang, Jiangxi, China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121496786","display_name":"Keping Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keping Yu","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-0500-2851","affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024939674","display_name":"Denghui Zhang","orcid":"https://orcid.org/0009-0004-2606-3234"},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Denghui Zhang","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400155","display_name":"Shuo Wang","orcid":"https://orcid.org/0000-0002-4098-7319"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210117825","display_name":"Beijing Research Institute of Mechanical and Electrical Technology","ror":"https://ror.org/02bjnsn63","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210117825"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Wang","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, Japan"],"raw_orcid":"https://orcid.org/0000-0002-4098-7319","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, Japan","institution_ids":["https://openalex.org/I4210117825","https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069368009","display_name":"Yiyuan Li","orcid":"https://orcid.org/0009-0008-3118-6211"},"institutions":[{"id":"https://openalex.org/I114218197","display_name":"Chinese Academy of Social Sciences","ror":"https://ror.org/05bxbmy32","country_code":"CN","type":"facility","lineage":["https://openalex.org/I114218197"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiyuan Li","raw_affiliation_strings":["Administrative Bureau, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Administrative Bureau, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I114218197"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125647841","display_name":"Yuanyuan Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Cai","raw_affiliation_strings":["School of Management, China University of Mining and Technology (Beijing), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1310-033X","affiliations":[{"raw_affiliation_string":"School of Management, China University of Mining and Technology (Beijing), Beijing, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":16.7219,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.98577236,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"13","issue":"8","first_page":"17731","last_page":"17746"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.9556999802589417,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T11622","display_name":"Maritime Navigation and Safety","score":0.9556999802589417,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T12126","display_name":"Maritime Transport Emissions and Efficiency","score":0.017100000753998756,"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"}},{"id":"https://openalex.org/T11223","display_name":"Maritime Ports and Logistics","score":0.003599999938160181,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/deep-learning","display_name":"Deep learning","score":0.5486999750137329},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.4968999922275543},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.47540000081062317},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.41370001435279846},{"id":"https://openalex.org/keywords/automatic-identification-system","display_name":"Automatic Identification System","score":0.4036000072956085},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.3849000036716461},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.37040001153945923},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.3418000042438507},{"id":"https://openalex.org/keywords/geographic-coordinate-system","display_name":"Geographic coordinate system","score":0.3296999931335449},{"id":"https://openalex.org/keywords/smart-city","display_name":"Smart city","score":0.31839999556541443}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7972000241279602},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5486999750137329},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5058000087738037},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.4968999922275543},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.49559998512268066},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.47540000081062317},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4133000075817108},{"id":"https://openalex.org/C146997752","wikidata":"https://www.wikidata.org/wiki/Q787197","display_name":"Automatic Identification System","level":2,"score":0.4036000072956085},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.336899995803833},{"id":"https://openalex.org/C123046963","wikidata":"https://www.wikidata.org/wiki/Q22664","display_name":"Geographic coordinate system","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C2777103469","wikidata":"https://www.wikidata.org/wiki/Q1231558","display_name":"Smart city","level":3,"score":0.31839999556541443},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.2913999855518341},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.29120001196861267},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2703999876976013},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2680000066757202},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C32802771","wikidata":"https://www.wikidata.org/wiki/Q2443617","display_name":"Port (circuit theory)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C156172958","wikidata":"https://www.wikidata.org/wiki/Q3438407","display_name":"Grid reference","level":4,"score":0.2538999915122986},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C144745244","wikidata":"https://www.wikidata.org/wiki/Q4927286","display_name":"Blocking (statistics)","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3663597","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3663597","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7961052804","display_name":null,"funder_award_id":"72301010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"a":[1,23,74,107,113,138,159],"core":[2],"component":[3],"of":[4,8,62,162,171,175,184,188,206,210,231,244],"the":[5,11,95,99,135,148,166,229,241],"maritime":[6,29,247],"Internet":[7],"Things":[9],"(IoT),":[10],"Automatic":[12],"Identification":[13],"System":[14],"(AIS)":[15],"continuously":[16],"collects":[17],"dynamic":[18,108],"vessel":[19,42,46,91,96],"navigation":[20],"data,":[21],"providing":[22],"solid":[24],"foundation":[25],"for":[26,177,190,212],"addressing":[27],"complex":[28],"traffic":[30],"prediction":[31,44,58,89,202],"tasks":[32],"that":[33],"support":[34],"intelligent":[35],"Vessel":[36],"Traffic":[37],"Services":[38],"(VTS),":[39],"such":[40],"as":[41],"trajectory":[43,92],"and":[45,102,112,147,155,173,181,203,222],"arrival":[47,200],"time":[48],"(VAT)":[49],"estimation.":[50],"However,":[51],"existing":[52],"methods":[53],"typically":[54],"focus":[55],"on":[56,81],"single":[57],"objectives,":[59],"falling":[60],"short":[61],"meeting":[63],"practical":[64],"multi-task":[65],"requirements.":[66],"To":[67],"address":[68],"this":[69,71],"gap,":[70],"study":[72,161],"proposes":[73],"geospatial":[75],"grid-constrained":[76],"deep":[77],"learning":[78],"framework":[79,105,216],"based":[80],"AIS":[82],"data":[83],"to":[84,119,142,239],"simultaneously":[85],"handle":[86],"three":[87],"key":[88],"tasks:":[90],"prediction,":[93,180],"whether":[94],"arrives":[97],"within":[98,246],"specified":[100],"time,":[101],"VAT.":[103],"The":[104,215],"incorporates":[106],"patch":[109],"construction":[110],"method":[111],"Graph":[114],"Soft":[115],"Evolution":[116],"(GSE)":[117],"module":[118],"capture":[120],"temporal":[121,156],"correlations":[122],"among":[123],"observations":[124],"under":[125],"spatial":[126],"grid":[127],"constraints.":[128],"An":[129],"encoder-decoder":[130],"architecture":[131],"is":[132],"introduced,":[133],"where":[134],"encoder":[136],"employs":[137],"Squeeze-and-Excitation":[139],"(SE)":[140],"block":[141],"adaptively":[143],"select":[144],"feature":[145],"channels,":[146],"decoder":[149],"models":[150],"dependencies":[151],"across":[152],"both":[153],"variable":[154],"dimensions.":[157],"In":[158],"case":[160],"New":[163],"York":[164],"Harbor,":[165],"model":[167],"achieved":[168],"an":[169,182,204],"R\u00b2":[170,183,205],"0.8386":[172],"RMSE":[174,187,209],"0.0329":[176],"latitude":[178],"increment":[179,192],"0.8432":[185],"with":[186,208],"0.0322":[189],"longitude":[191],"prediction.":[193,214],"It":[194],"also":[195],"attained":[196],"99.83%":[197],"accuracy":[198],"in":[199,219,225],"status":[201],"0.9350":[207],"0.0701":[211],"VAT":[213],"demonstrated":[217],"effectiveness":[218],"port":[220],"scheduling":[221],"robust":[223],"generalizability":[224],"cross-validation":[226],"experiments":[227],"at":[228],"Port":[230],"Los":[232],"Angeles,":[233],"thereby":[234],"demonstrating":[235],"its":[236],"substantial":[237],"potential":[238],"enhance":[240],"operational":[242],"efficiency":[243],"VTS":[245],"IoT":[248],"systems.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-06-20T22:02:38.213706","created_date":"2026-02-12T00:00:00"}
