{"id":"https://openalex.org/W2938051007","doi":"https://doi.org/10.1145/3312614.3312631","title":"IoT-based Urban Noise Identification Using Machine Learning","display_name":"IoT-based Urban Noise Identification Using Machine Learning","publication_year":2019,"publication_date":"2019-04-08","ids":{"openalex":"https://openalex.org/W2938051007","doi":"https://doi.org/10.1145/3312614.3312631","mag":"2938051007"},"language":"en","primary_location":{"id":"doi:10.1145/3312614.3312631","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3312614.3312631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Omni-Layer Intelligent Systems","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/A5086514130","display_name":"Yasser Alsouda","orcid":null},"institutions":[{"id":"https://openalex.org/I223464139","display_name":"Linnaeus University","ror":"https://ror.org/00j9qag85","country_code":"SE","type":"education","lineage":["https://openalex.org/I223464139"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Yasser Alsouda","raw_affiliation_strings":["Linnaeus University, V\u00e4xj\u00f6, Sweden"],"affiliations":[{"raw_affiliation_string":"Linnaeus University, V\u00e4xj\u00f6, Sweden","institution_ids":["https://openalex.org/I223464139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021961745","display_name":"Sabri Pllana","orcid":"https://orcid.org/0000-0002-4146-9062"},"institutions":[{"id":"https://openalex.org/I223464139","display_name":"Linnaeus University","ror":"https://ror.org/00j9qag85","country_code":"SE","type":"education","lineage":["https://openalex.org/I223464139"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sabri Pllana","raw_affiliation_strings":["Linnaeus University, V\u00e4xj\u00f6, Sweden"],"affiliations":[{"raw_affiliation_string":"Linnaeus University, V\u00e4xj\u00f6, Sweden","institution_ids":["https://openalex.org/I223464139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022616464","display_name":"Arianit Kurti","orcid":"https://orcid.org/0000-0003-0512-6350"},"institutions":[{"id":"https://openalex.org/I223464139","display_name":"Linnaeus University","ror":"https://ror.org/00j9qag85","country_code":"SE","type":"education","lineage":["https://openalex.org/I223464139"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Arianit Kurti","raw_affiliation_strings":["Linnaeus University, V\u00e4xj\u00f6, Sweden"],"affiliations":[{"raw_affiliation_string":"Linnaeus University, V\u00e4xj\u00f6, Sweden","institution_ids":["https://openalex.org/I223464139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086514130"],"corresponding_institution_ids":["https://openalex.org/I223464139"],"apc_list":null,"apc_paid":null,"fwci":3.6489,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.93973242,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"62","last_page":"67"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11665","display_name":"Animal Vocal Communication and Behavior","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/1309","display_name":"Developmental Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7478141784667969},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.6889412999153137},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6715858578681946},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.593376636505127},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.570931613445282},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5601349472999573},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.541473925113678},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5289595127105713},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5168991088867188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48900020122528076},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4852130711078644},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46224263310432434},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4515995383262634},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.42624998092651367},{"id":"https://openalex.org/keywords/environmental-noise","display_name":"Environmental noise","score":0.4114745855331421},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.37763434648513794},{"id":"https://openalex.org/keywords/sound","display_name":"Sound (geography)","score":0.3231082558631897},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.2827673554420471},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.22229266166687012}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7478141784667969},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.6889412999153137},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6715858578681946},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.593376636505127},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.570931613445282},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5601349472999573},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.541473925113678},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5289595127105713},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5168991088867188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48900020122528076},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4852130711078644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46224263310432434},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4515995383262634},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.42624998092651367},{"id":"https://openalex.org/C86781634","wikidata":"https://www.wikidata.org/wiki/Q2478325","display_name":"Environmental noise","level":3,"score":0.4114745855331421},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37763434648513794},{"id":"https://openalex.org/C203718221","wikidata":"https://www.wikidata.org/wiki/Q491713","display_name":"Sound (geography)","level":2,"score":0.3231082558631897},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2827673554420471},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.22229266166687012},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3312614.3312631","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3312614.3312631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Omni-Layer Intelligent Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1492815834","https://openalex.org/W1817724761","https://openalex.org/W1819491323","https://openalex.org/W1975572074","https://openalex.org/W2038484192","https://openalex.org/W2062826588","https://openalex.org/W2111331420","https://openalex.org/W2120599713","https://openalex.org/W2191779130","https://openalex.org/W2328444730","https://openalex.org/W2592417500","https://openalex.org/W2619568410","https://openalex.org/W2736789627","https://openalex.org/W2784277636","https://openalex.org/W2805337665","https://openalex.org/W2809642731"],"related_works":["https://openalex.org/W4210551185","https://openalex.org/W2336974148","https://openalex.org/W3195168932","https://openalex.org/W2783590012","https://openalex.org/W2187500075","https://openalex.org/W4377964522","https://openalex.org/W1981297204","https://openalex.org/W3195610867","https://openalex.org/W2772780115","https://openalex.org/W2385132419"],"abstract_inverted_index":{"Noise":[0],"is":[1,25],"any":[2],"undesired":[3],"environmental":[4],"sound.":[5],"A":[6],"sound":[7,104,109,137],"at":[8],"the":[9,30,36,42,121,125,130,140,151],"same":[10],"dB":[11,37],"level":[12,38],"may":[13],"be":[14],"perceived":[15],"as":[16,20,112],"annoying":[17],"noise":[18,58,91,147],"or":[19,116],"pleasant":[21],"music.":[22],"Therefore,":[23],"it":[24],"necessary":[26],"to":[27,128],"go":[28],"beyond":[29],"state-of-the-art":[31],"approaches":[32],"that":[33],"measure":[34],"only":[35],"and":[39,74,87],"also":[40],"identify":[41],"type":[43],"of":[44,101,124,136],"noise.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49],"present":[50],"a":[51,99,146],"machine":[52],"learning":[53],"based":[54],"method":[55],"for":[56,70,90,134],"urban":[57],"identification":[59],"using":[60],"an":[61],"inexpensive":[62],"IoT":[63],"unit.":[64],"We":[65,93,119,144],"use":[66],"Mel-frequency":[67],"cepstral":[68],"coefficients":[69],"audio":[71],"feature":[72],"extraction":[73],"supervised":[75],"classification":[76,135,148],"algorithms":[77,127],"(that":[78],"is,":[79],"support":[80],"vector":[81],"machine,":[82],"k-nearest":[83],"neighbors,":[84],"bootstrap":[85],"aggregation,":[86],"random":[88],"forest)":[89],"classification.":[92],"evaluate":[94],"our":[95],"approach":[96],"experimentally":[97],"with":[98],"data-set":[100,141],"about":[102],"3000":[103],"samples":[105,138],"grouped":[106],"in":[107,139,150],"eight":[108],"classes":[110],"(such":[111],"car":[113],"horn,":[114],"jackhammer,":[115],"street":[117],"music).":[118],"explore":[120],"parameter":[122,132],"space":[123],"four":[126],"estimate":[129],"optimal":[131],"values":[133],"under":[142],"study.":[143],"achieve":[145],"accuracy":[149],"range":[152],"88%":[153],"-":[154],"94%.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}