{"id":"https://openalex.org/W7116729011","doi":"https://doi.org/10.1007/s43926-025-00253-y","title":"Deep learning models for asphalt material behavior analysis under smart city IoT infrastructures","display_name":"Deep learning models for asphalt material behavior analysis under smart city IoT infrastructures","publication_year":2025,"publication_date":"2025-12-22","ids":{"openalex":"https://openalex.org/W7116729011","doi":"https://doi.org/10.1007/s43926-025-00253-y"},"language":"en","primary_location":{"id":"doi:10.1007/s43926-025-00253-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s43926-025-00253-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s43926-025-00253-y.pdf","source":{"id":"https://openalex.org/S4210230675","display_name":"Discover Internet of Things","issn_l":"2730-7239","issn":["2730-7239"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Internet of Things","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s43926-025-00253-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120951585","display_name":"Wei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]},{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Li","raw_affiliation_strings":["School of Civil Engineering, Guangzhou City University of Technology, Guangzhou, 510800, China"],"affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Guangzhou City University of Technology, Guangzhou, 510800, China","institution_ids":["https://openalex.org/I37987034","https://openalex.org/I90610280","https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120997380","display_name":"Xinyu Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]},{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Xiao","raw_affiliation_strings":["School of Civil Engineering, Guangzhou City University of Technology, Guangzhou, 510800, China"],"affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Guangzhou City University of Technology, Guangzhou, 510800, China","institution_ids":["https://openalex.org/I37987034","https://openalex.org/I90610280","https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100368198","display_name":"Na Li","orcid":"https://orcid.org/0000-0003-2572-0955"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]},{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Li","raw_affiliation_strings":["School of Civil Engineering, Guangzhou City University of Technology, Guangzhou, 510800, China"],"affiliations":[{"raw_affiliation_string":"School of Civil Engineering, Guangzhou City University of Technology, Guangzhou, 510800, China","institution_ids":["https://openalex.org/I37987034","https://openalex.org/I90610280","https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5120951585"],"corresponding_institution_ids":["https://openalex.org/I139024713","https://openalex.org/I37987034","https://openalex.org/I90610280"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.63711554,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9560999870300293,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9560999870300293,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.023900000378489494,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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":0.0032999999821186066,"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/deep-learning","display_name":"Deep learning","score":0.6019999980926514},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4584999978542328},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4374000132083893},{"id":"https://openalex.org/keywords/smart-city","display_name":"Smart city","score":0.4235000014305115},{"id":"https://openalex.org/keywords/asphalt","display_name":"Asphalt","score":0.39969998598098755},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3955000042915344},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3871999979019165},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.37860000133514404},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.350600004196167}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6019999980926514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5630000233650208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.486299991607666},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4551999866962433},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C2777103469","wikidata":"https://www.wikidata.org/wiki/Q1231558","display_name":"Smart city","level":3,"score":0.4235000014305115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4043999910354614},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.40070000290870667},{"id":"https://openalex.org/C168056786","wikidata":"https://www.wikidata.org/wiki/Q202251","display_name":"Asphalt","level":2,"score":0.39969998598098755},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.3160000145435333},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.302700012922287},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.30160000920295715},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.29269999265670776},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.2791999876499176},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.2705000042915344},{"id":"https://openalex.org/C172191483","wikidata":"https://www.wikidata.org/wiki/Q1071806","display_name":"Provisioning","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C176563091","wikidata":"https://www.wikidata.org/wiki/Q669238","display_name":"Intelligent sensor","level":3,"score":0.26589998602867126},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s43926-025-00253-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s43926-025-00253-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s43926-025-00253-y.pdf","source":{"id":"https://openalex.org/S4210230675","display_name":"Discover Internet of Things","issn_l":"2730-7239","issn":["2730-7239"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Internet of Things","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ec3c9a409f6f49289392bb19ef876130","is_oa":true,"landing_page_url":"https://doaj.org/article/ec3c9a409f6f49289392bb19ef876130","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Internet of Things, Vol 5, Iss 1, Pp 1-24 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s43926-025-00253-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s43926-025-00253-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s43926-025-00253-y.pdf","source":{"id":"https://openalex.org/S4210230675","display_name":"Discover Internet of Things","issn_l":"2730-7239","issn":["2730-7239"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Internet of Things","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6325885057449341,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7116729011.pdf","grobid_xml":"https://content.openalex.org/works/W7116729011.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W4200049347","https://openalex.org/W4296571056","https://openalex.org/W4313214332","https://openalex.org/W4313571270","https://openalex.org/W4321599926","https://openalex.org/W4323041715","https://openalex.org/W4367318883","https://openalex.org/W4385555961","https://openalex.org/W4386496645","https://openalex.org/W4386851619","https://openalex.org/W4387647564","https://openalex.org/W4388996470","https://openalex.org/W4392122951","https://openalex.org/W4407597792","https://openalex.org/W4408787610","https://openalex.org/W4409559148","https://openalex.org/W4410577094","https://openalex.org/W4410695976"],"related_works":[],"abstract_inverted_index":{"Asphalt":[0,53,112],"is":[1,8,246],"used":[2],"for":[3,49,95,248],"smart":[4,83],"city":[5,84],"infrastructure,":[6],"which":[7],"subjected":[9],"to":[10,77,120,137,159,189,197,202,208],"constant":[11],"travel,":[12],"stress,":[13],"and":[14,39,89,104,132,156,163,169,204,212,223],"ultimately":[15],"decay.":[16],"Cannot":[17],"detect":[18],"real-time":[19,251],"material":[20],"activity":[21],"like":[22],"time,":[23],"destructive":[24],"testing":[25],"cannot":[26,35],"guarantee":[27],"predictive":[28,55,93],"maintenance.":[29],"The":[30,109,149,176],"algorithms":[31],"in":[32,82,172],"use":[33],"today":[34],"handle":[36],"high":[37],"spatial":[38],"temporal":[40,140,168],"data":[41,62,144,158,171],"produced":[42],"or":[43,70,236],"recorded":[44],"by":[45,146,165,220],"IoT-enabled":[46],"monitoring":[47],"systems":[48],"proactive":[50],"infrastructure":[51],"management.":[52],"analysis":[54],"maintenance":[56,94,107],"approaches":[57],"depend":[58],"on":[59,63,67,71],"either":[60],"limited":[61],"simple":[64],"rules":[65],"based":[66],"composite":[68],"models":[69],"deep":[72],"learning":[73],"(DL)":[74],"models\u2014like":[75],"LSTMs,":[76],"scale.":[78],"This":[79],"generates":[80],"inefficiency":[81],"network":[85],"maintenance,":[86],"resource":[87],"investment/reallocation,":[88],"scaling.":[90],"Multi-modal":[91],"IoT":[92,252],"asphalt":[96,161],"pavement":[97,130],"degradation":[98,162],"requires":[99],"a":[100],"more":[101],"flexible,":[102],"accurate,":[103],"interpretable":[105],"preventative":[106],"strategy.":[108],"proposed":[110],"IoT-based":[111],"Analysis":[113],"Framework":[114],"(IAAF)":[115],"incorporates":[116],"Vision":[117],"Transformers":[118],"(VITs)":[119],"collate":[121],"spatiotemporal":[122,170],"global":[123],"information":[124,214],"from":[125,142,195,200,206],"high-resolution":[126],"images":[127],"of":[128,241],"the":[129,147,173,181,244],"surface,":[131],"Temporal":[133],"Convolutional":[134],"Networks":[135],"(TCNs)":[136],"graph":[138],"long-term":[139],"patterns":[141],"sensor":[143,232],"provided":[145],"IoT.":[148],"comprehensive":[150],"hybrid":[151],"attention":[152],"module":[153],"(HAM)":[154],"connects":[155],"collates":[157],"identify":[160],"failure":[164],"utilizing":[166],"both":[167],"same":[174],"network.":[175],"experimental":[177],"assessment":[178],"shows":[179],"that":[180],"IAAF":[182],"model":[183],"significantly":[184],"reduces":[185],"prediction":[186],"errors":[187],"compared":[188],"baseline":[190],"LSTM":[191],"models.":[192],"MAE":[193],"lowers":[194],"38.23":[196],"14.04,":[198],"RMSE":[199],"40.59":[201],"20.79,":[203],"MAPE":[205],"13.03":[207],"4.21%.":[209],"Attention":[210],"mechanisms":[211],"visual":[213],"transducers":[215],"minimize":[216],"false":[217],"alarm":[218],"rates":[219],"over":[221],"25%":[222],"preserve":[224],"accuracy":[225],"with":[226],"less":[227],"than":[228],"5%":[229],"variance":[230],"when":[231],"inputs":[233],"are":[234],"noisy":[235],"insufficient.":[237],"With":[238],"inference":[239],"latency":[240],"500":[242],"ms,":[243],"framework":[245],"ideal":[247],"edge":[249],"device":[250],"deployments.":[253]},"counts_by_year":[],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-12-22T00:00:00"}