A TinyML Soft-Sensor Approach for Low-Cost Detection and Monitoring of Vehicular Emissions.

Andrade, Pedro; Silva, Ivanovitch; Silva, Marianne; Flores, Thommas; Cassiano, Jordão; Costa, Daniel G

Andrade, Pedro; Silva, Ivanovitch; Silva, Marianne; Flores, Thommas; Cassiano, Jordão; Costa, Daniel G.

Afiliação

Andrade P; Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil.
Silva I; Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil.
Silva M; Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil.
Flores T; Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil.
Cassiano J; Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil.
Costa DG; Postgraduate Program in Electrical and Computer Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Rio Grande do Norte, Brazil.

Sensors (Basel) ; 22(10)2022 May 19.

Article em En | MEDLINE | ID: mdl-35632247

Palavras-chave

Internet of Intelligent Vehicles; Internet of Things; OBD-II; TinyML; air pollution; soft sensor

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Health_economic_evaluation Idioma: En Revista: Sensors (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça

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