{"id":"https://openalex.org/W4391768709","doi":"https://doi.org/10.1109/itsc57777.2023.10422327","title":"Road Surface Monitoring System Through Machine Learning Ensemble Models","display_name":"Road Surface Monitoring System Through Machine Learning Ensemble Models","publication_year":2023,"publication_date":"2023-09-24","ids":{"openalex":"https://openalex.org/W4391768709","doi":"https://doi.org/10.1109/itsc57777.2023.10422327"},"language":"en","primary_location":{"id":"doi:10.1109/itsc57777.2023.10422327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc57777.2023.10422327","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)","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/A5087525156","display_name":"Luis A. Arce-S\u00e1enz","orcid":"https://orcid.org/0000-0003-0732-8693"},"institutions":[{"id":"https://openalex.org/I98461037","display_name":"Tecnol\u00f3gico de Monterrey","ror":"https://ror.org/03ayjn504","country_code":"MX","type":"education","lineage":["https://openalex.org/I98461037"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Luis A. Arce-Saenz","raw_affiliation_strings":["School of Engineering and Science, Tecnologico de Monterrey,Mexico City,Mexico,14380"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Science, Tecnologico de Monterrey,Mexico City,Mexico,14380","institution_ids":["https://openalex.org/I98461037"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077688534","display_name":"Javier Izquierdo-Reyes","orcid":"https://orcid.org/0000-0001-9698-4355"},"institutions":[{"id":"https://openalex.org/I98461037","display_name":"Tecnol\u00f3gico de Monterrey","ror":"https://ror.org/03ayjn504","country_code":"MX","type":"education","lineage":["https://openalex.org/I98461037"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Javier Izquierdo-Reyes","raw_affiliation_strings":["School of Engineering and Science, Tecnologico de Monterrey,Mexico City,Mexico,14380"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Science, Tecnologico de Monterrey,Mexico City,Mexico,14380","institution_ids":["https://openalex.org/I98461037"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071817870","display_name":"Rogelio Bustamante-Bello","orcid":"https://orcid.org/0000-0001-9270-0052"},"institutions":[{"id":"https://openalex.org/I98461037","display_name":"Tecnol\u00f3gico de Monterrey","ror":"https://ror.org/03ayjn504","country_code":"MX","type":"education","lineage":["https://openalex.org/I98461037"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Rogelio Bustamante-Bello","raw_affiliation_strings":["School of Engineering and Science, Tecnologico de Monterrey,Mexico City,Mexico,14380"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Science, Tecnologico de Monterrey,Mexico City,Mexico,14380","institution_ids":["https://openalex.org/I98461037"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087525156"],"corresponding_institution_ids":["https://openalex.org/I98461037"],"apc_list":null,"apc_paid":null,"fwci":0.4631,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61685104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"175","last_page":"181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9807000160217285,"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":0.9807000160217285,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9707000255584717,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5826295018196106},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4681931436061859},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3643704056739807}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5826295018196106},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4681931436061859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3643704056739807}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc57777.2023.10422327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc57777.2023.10422327","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G464401800","display_name":null,"funder_award_id":"A01271635","funder_id":"https://openalex.org/F4320323037","funder_display_name":"Instituto Tecnol\u00f3gico y de Estudios Superiores de Monterrey"}],"funders":[{"id":"https://openalex.org/F4320323037","display_name":"Instituto Tecnol\u00f3gico y de Estudios Superiores de Monterrey","ror":"https://ror.org/03ayjn504"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1658600643","https://openalex.org/W1969600416","https://openalex.org/W1977324115","https://openalex.org/W2071758169","https://openalex.org/W2101234009","https://openalex.org/W2135778154","https://openalex.org/W2148143831","https://openalex.org/W2168463792","https://openalex.org/W2185029355","https://openalex.org/W2511482214","https://openalex.org/W2603250181","https://openalex.org/W2789238015","https://openalex.org/W2791787077","https://openalex.org/W2896942768","https://openalex.org/W2897765576","https://openalex.org/W2908669831","https://openalex.org/W3086827472","https://openalex.org/W4206774559","https://openalex.org/W4232963393","https://openalex.org/W4235243453","https://openalex.org/W4280516246","https://openalex.org/W4293319418","https://openalex.org/W4312269039","https://openalex.org/W6610557702","https://openalex.org/W6686385793","https://openalex.org/W6753429110","https://openalex.org/W6845017753"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W2350741829","https://openalex.org/W2530322880","https://openalex.org/W1596801655"],"abstract_inverted_index":{"The":[0],"proliferation":[1],"of":[2,82,154],"large":[3],"urban":[4],"centers":[5],"presents":[6],"numerous":[7],"challenges,":[8],"including":[9,85],"effective":[10],"road":[11,83,89],"pavement":[12],"maintenance,":[13],"which":[14],"is":[15],"a":[16,25,56,98,151,164,177,184],"critical":[17],"issue.":[18],"To":[19],"address":[20],"this":[21],"concern,":[22],"we":[23,123,157],"developed":[24],"low-resource":[26],"framework":[27],"that":[28,179],"utilizes":[29],"Inertial":[30],"Measurement":[31],"Units":[32],"(IMUs)":[33],"and":[34,52,60,76,79,87,94,102,113,134,161],"elementary":[35,125],"Machine":[36],"Learning":[37],"(ML)":[38],"classification":[39,126],"models":[40,138,162],"to":[41,74,105,128,167],"monitor":[42],"surface":[43],"defects":[44],"in":[45,109,176],"the":[46,107,111,130,136,147,159],"pavement.":[47],"Our":[48],"platform":[49],"recorded":[50],"accelerometer":[51],"gyroscope":[53],"measurements":[54,73],"on":[55,65,142,183],"test":[57],"vehicle's":[58],"damped":[59],"undamped":[61],"mass":[62],"while":[63],"driving":[64],"Mexico":[66],"City's":[67],"street.":[68],"We":[69,96],"then":[70],"labeled":[71],"these":[72],"identify":[75],"classify":[77],"general":[78],"specific":[80],"elements":[81],"irregularities,":[84],"smooth":[86],"uneven":[88],"segments,":[90],"manholes-potholes,":[91],"speed":[92],"bumps,":[93],"patches.":[95],"employed":[97],"time":[99,112],"series":[100],"analysis":[101],"feature":[103],"extraction":[104],"preprocess":[106],"data":[108],"both":[110],"frequency":[114],"domains.":[115],"Next,":[116],"utilizing":[117],"an":[118],"exhaustive":[119],"grid":[120],"search":[121],"methodology,":[122],"trained":[124],"algorithms":[127,160],"find":[129],"best":[131],"possible":[132],"predictors":[133],"train":[135],"ensemble":[137],"with":[139,172],"them.":[140],"Based":[141],"several":[143],"validation":[144],"routes":[145],"traveled,":[146],"overall":[148],"system":[149],"demonstrated":[150],"macro":[152],"F1-score":[153],"0.827.":[155],"Finally,":[156],"deployed":[158],"onto":[163],"cloud":[165],"instance":[166],"process":[168],"incoming":[169],"raw":[170],"data,":[171],"resultant":[173],"predictions":[174],"stored":[175],"database":[178],"can":[180],"be":[181],"visualized":[182],"web":[185],"platform.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}