The Haar Wavelet Transform in IoT Digital Audio Signal Processing

Detalhes bibliográficos
Autor(a) principal: Escola, João Paulo Lemos
Data de Publicação: 2022
Outros Autores: de Souza, Uender Barbosa, Guido, Rodrigo Capobianco [UNESP], Silva, Ivan Nunes da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s00034-022-01979-8
http://hdl.handle.net/11449/234150
Resumo: Digital signal processing allows a wide range of digital applications, including audio processing. Discrete wavelet transform (DWT) is one of the most efficient ways of time–frequency analysis of an audio signal. The Internet of Things (IoT) is a technology that has been growing in commercial automation applications with the availability of low-cost modules and microcontrollers. IoT projects that use DWT for digital audio processing can solve many problems involving audio signals. In this paper, a performance comparison of an algorithm implementing DWT on three commercially available IoT devices is presented. The results show that it is possible to process signals in the 256 Hz to 6.5 KHz range, opening possibilities for future work integrating the technologies described.
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spelling The Haar Wavelet Transform in IoT Digital Audio Signal ProcessingDigital Signal ProcessingInternet of ThingsPerformance analysisWaveletsDigital signal processing allows a wide range of digital applications, including audio processing. Discrete wavelet transform (DWT) is one of the most efficient ways of time–frequency analysis of an audio signal. The Internet of Things (IoT) is a technology that has been growing in commercial automation applications with the availability of low-cost modules and microcontrollers. IoT projects that use DWT for digital audio processing can solve many problems involving audio signals. In this paper, a performance comparison of an algorithm implementing DWT on three commercially available IoT devices is presented. The results show that it is possible to process signals in the 256 Hz to 6.5 KHz range, opening possibilities for future work integrating the technologies described.Instituto Federal de São Paulo, Av. C1 n250, SPInstituto Federal de Goiás, Rua 75 n46, GOInstituto de Biociências Letras e Ciências Exatas Unesp - Universidade Estadual Paulista (São Paulo State University), Rua Cristóvão Colombo n2265, SPEscola de Engenharia de São Carlos Universidade de São Paulo, Av. Trabalhador São-carlense n400, SPEMC Universidade Federal de Goiás, Av. Universitária n1488, GOInstituto de Biociências Letras e Ciências Exatas Unesp - Universidade Estadual Paulista (São Paulo State University), Rua Cristóvão Colombo n2265, SPInstituto Federal de São PauloInstituto Federal de GoiásUniversidade Estadual Paulista (UNESP)Universidade de São Paulo (USP)Universidade Federal de Goiás (UFG)Escola, João Paulo Lemosde Souza, Uender BarbosaGuido, Rodrigo Capobianco [UNESP]Silva, Ivan Nunes da2022-05-01T13:41:38Z2022-05-01T13:41:38Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1007/s00034-022-01979-8Circuits, Systems, and Signal Processing.1531-58780278-081Xhttp://hdl.handle.net/11449/23415010.1007/s00034-022-01979-82-s2.0-85124730665Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCircuits, Systems, and Signal Processinginfo:eu-repo/semantics/openAccess2022-05-01T13:41:38Zoai:repositorio.unesp.br:11449/234150Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:15:00.465726Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv The Haar Wavelet Transform in IoT Digital Audio Signal Processing
title The Haar Wavelet Transform in IoT Digital Audio Signal Processing
spellingShingle The Haar Wavelet Transform in IoT Digital Audio Signal Processing
Escola, João Paulo Lemos
Digital Signal Processing
Internet of Things
Performance analysis
Wavelets
title_short The Haar Wavelet Transform in IoT Digital Audio Signal Processing
title_full The Haar Wavelet Transform in IoT Digital Audio Signal Processing
title_fullStr The Haar Wavelet Transform in IoT Digital Audio Signal Processing
title_full_unstemmed The Haar Wavelet Transform in IoT Digital Audio Signal Processing
title_sort The Haar Wavelet Transform in IoT Digital Audio Signal Processing
author Escola, João Paulo Lemos
author_facet Escola, João Paulo Lemos
de Souza, Uender Barbosa
Guido, Rodrigo Capobianco [UNESP]
Silva, Ivan Nunes da
author_role author
author2 de Souza, Uender Barbosa
Guido, Rodrigo Capobianco [UNESP]
Silva, Ivan Nunes da
author2_role author
author
author
dc.contributor.none.fl_str_mv Instituto Federal de São Paulo
Instituto Federal de Goiás
Universidade Estadual Paulista (UNESP)
Universidade de São Paulo (USP)
Universidade Federal de Goiás (UFG)
dc.contributor.author.fl_str_mv Escola, João Paulo Lemos
de Souza, Uender Barbosa
Guido, Rodrigo Capobianco [UNESP]
Silva, Ivan Nunes da
dc.subject.por.fl_str_mv Digital Signal Processing
Internet of Things
Performance analysis
Wavelets
topic Digital Signal Processing
Internet of Things
Performance analysis
Wavelets
description Digital signal processing allows a wide range of digital applications, including audio processing. Discrete wavelet transform (DWT) is one of the most efficient ways of time–frequency analysis of an audio signal. The Internet of Things (IoT) is a technology that has been growing in commercial automation applications with the availability of low-cost modules and microcontrollers. IoT projects that use DWT for digital audio processing can solve many problems involving audio signals. In this paper, a performance comparison of an algorithm implementing DWT on three commercially available IoT devices is presented. The results show that it is possible to process signals in the 256 Hz to 6.5 KHz range, opening possibilities for future work integrating the technologies described.
publishDate 2022
dc.date.none.fl_str_mv 2022-05-01T13:41:38Z
2022-05-01T13:41:38Z
2022-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/s00034-022-01979-8
Circuits, Systems, and Signal Processing.
1531-5878
0278-081X
http://hdl.handle.net/11449/234150
10.1007/s00034-022-01979-8
2-s2.0-85124730665
url http://dx.doi.org/10.1007/s00034-022-01979-8
http://hdl.handle.net/11449/234150
identifier_str_mv Circuits, Systems, and Signal Processing.
1531-5878
0278-081X
10.1007/s00034-022-01979-8
2-s2.0-85124730665
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Circuits, Systems, and Signal Processing
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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