Use of Arduino for Monitoring the Air Quality of Indoor Environments
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista de Engenharia Química e Química |
Texto Completo: | https://periodicos.ufv.br/jcec/article/view/15050 |
Resumo: | In this work, a prototype was developed to assess indoor air quality using an Arduino system. The system is based on the measurement of the light level, smoke concentration, temperature and air humidity. A thermal comfort index (TCI) was proposed, where a scale from 0 to 1 based on the weighted average of the individual indices was developed. Another approach, based on artificial neural networks, was formulated in which the parameters were used as input arguments of the network and the TCI was used as a target parameter. The response of the two models was compared, where it was possible to observe that the TCI values calculated by the network were considerably close to the values obtained by the deterministic model, with MSE of 1.73?10-5. |
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Use of Arduino for Monitoring the Air Quality of Indoor Environments Uso do Arduino para Monitoramento da Qualidade do Ar em Ambientes FechadosArduinoMachine LearningProcess ControlArduino. Aprendizado de Máquina. Controle de Processos.In this work, a prototype was developed to assess indoor air quality using an Arduino system. The system is based on the measurement of the light level, smoke concentration, temperature and air humidity. A thermal comfort index (TCI) was proposed, where a scale from 0 to 1 based on the weighted average of the individual indices was developed. Another approach, based on artificial neural networks, was formulated in which the parameters were used as input arguments of the network and the TCI was used as a target parameter. The response of the two models was compared, where it was possible to observe that the TCI values calculated by the network were considerably close to the values obtained by the deterministic model, with MSE of 1.73?10-5.Neste trabalho, um protótipo foi desenvolvido para avaliar a qualidade do ar em ambientes internos usando um sistema Arduino. O sistema é baseado na medição do nível de luz, concentração de fumaça, temperatura e umidade do ar. Foi proposto um índice de conforto térmico (ICT), onde foi desenvolvida uma escala de 0 a 1 com base na média ponderada dos índices individuais. Outra abordagem, baseada em redes neurais artificiais, foi formulada na qual os parâmetros foram utilizados como argumentos de entrada da rede e o ICT foi usado como variável de saída. A resposta dos dois modelos foi comparada, onde foi possível observar que os valores de ICT calculados pela rede neural foram consideravelmente próximos dos valores obtidos pelo modelo determinístico, com erro médio quadrático de 1,73 ?10-5.Universidade Federal de Viçosa - UFV2022-12-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/1505010.18540/jcecvl8iss11pp15050-01eThe Journal of Engineering and Exact Sciences; Vol. 8 No. 11 (2022); 15050-01eThe Journal of Engineering and Exact Sciences; Vol. 8 Núm. 11 (2022); 15050-01eThe Journal of Engineering and Exact Sciences; v. 8 n. 11 (2022); 15050-01e2527-1075reponame:Revista de Engenharia Química e Químicainstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/15050/7704Copyright (c) 2022 The Journal of Engineering and Exact Scienceshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSiqueira, Felipe Macedo FreitasSantos, Lizandro de Sousa2023-02-23T13:29:33Zoai:ojs.periodicos.ufv.br:article/15050Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/indexONGhttps://periodicos.ufv.br/jcec/oaijcec.journal@ufv.br||req2@ufv.br2446-94162446-9416opendoar:2023-02-23T13:29:33Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV)false |
dc.title.none.fl_str_mv |
Use of Arduino for Monitoring the Air Quality of Indoor Environments Uso do Arduino para Monitoramento da Qualidade do Ar em Ambientes Fechados |
title |
Use of Arduino for Monitoring the Air Quality of Indoor Environments |
spellingShingle |
Use of Arduino for Monitoring the Air Quality of Indoor Environments Siqueira, Felipe Macedo Freitas Arduino Machine Learning Process Control Arduino. Aprendizado de Máquina. Controle de Processos. |
title_short |
Use of Arduino for Monitoring the Air Quality of Indoor Environments |
title_full |
Use of Arduino for Monitoring the Air Quality of Indoor Environments |
title_fullStr |
Use of Arduino for Monitoring the Air Quality of Indoor Environments |
title_full_unstemmed |
Use of Arduino for Monitoring the Air Quality of Indoor Environments |
title_sort |
Use of Arduino for Monitoring the Air Quality of Indoor Environments |
author |
Siqueira, Felipe Macedo Freitas |
author_facet |
Siqueira, Felipe Macedo Freitas Santos, Lizandro de Sousa |
author_role |
author |
author2 |
Santos, Lizandro de Sousa |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Siqueira, Felipe Macedo Freitas Santos, Lizandro de Sousa |
dc.subject.por.fl_str_mv |
Arduino Machine Learning Process Control Arduino. Aprendizado de Máquina. Controle de Processos. |
topic |
Arduino Machine Learning Process Control Arduino. Aprendizado de Máquina. Controle de Processos. |
description |
In this work, a prototype was developed to assess indoor air quality using an Arduino system. The system is based on the measurement of the light level, smoke concentration, temperature and air humidity. A thermal comfort index (TCI) was proposed, where a scale from 0 to 1 based on the weighted average of the individual indices was developed. Another approach, based on artificial neural networks, was formulated in which the parameters were used as input arguments of the network and the TCI was used as a target parameter. The response of the two models was compared, where it was possible to observe that the TCI values calculated by the network were considerably close to the values obtained by the deterministic model, with MSE of 1.73?10-5. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-12-22 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.ufv.br/jcec/article/view/15050 10.18540/jcecvl8iss11pp15050-01e |
url |
https://periodicos.ufv.br/jcec/article/view/15050 |
identifier_str_mv |
10.18540/jcecvl8iss11pp15050-01e |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.ufv.br/jcec/article/view/15050/7704 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 The Journal of Engineering and Exact Sciences https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 The Journal of Engineering and Exact Sciences https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Viçosa - UFV |
publisher.none.fl_str_mv |
Universidade Federal de Viçosa - UFV |
dc.source.none.fl_str_mv |
The Journal of Engineering and Exact Sciences; Vol. 8 No. 11 (2022); 15050-01e The Journal of Engineering and Exact Sciences; Vol. 8 Núm. 11 (2022); 15050-01e The Journal of Engineering and Exact Sciences; v. 8 n. 11 (2022); 15050-01e 2527-1075 reponame:Revista de Engenharia Química e Química instname:Universidade Federal de Viçosa (UFV) instacron:UFV |
instname_str |
Universidade Federal de Viçosa (UFV) |
instacron_str |
UFV |
institution |
UFV |
reponame_str |
Revista de Engenharia Química e Química |
collection |
Revista de Engenharia Química e Química |
repository.name.fl_str_mv |
Revista de Engenharia Química e Química - Universidade Federal de Viçosa (UFV) |
repository.mail.fl_str_mv |
jcec.journal@ufv.br||req2@ufv.br |
_version_ |
1800211190802022400 |