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A WSN real-time monitoring system approach for measuring indoor air quality using the internet of things

dc.contributor.authorBrito, Thadeu
dc.contributor.authorNakano, Alberto Yoshiro
dc.contributor.authorLima, José
dc.date.accessioned2023-02-28T11:46:04Z
dc.date.available2023-02-28T11:46:04Z
dc.date.issued2023
dc.description.abstractIndoor Air Quality (IAQ) describes the air quality of a room, and it refers to the health and comfort of the occupants. Typically, people spend around 90% of their time in indoor environments where the concentration of air pollutants and, occasionally, more than 100 times higher than outdoor levels. According to the World Health Organization (WHO), indoor air pollution is responsible for the death of 3.8 million people annually. It has been indicated that IAQ in residential areas or buildings is significantly affected by three primary factors, they are outdoor air quality, human activity in buildings, and building and construction materials. In this context, this work consists of a real-time IAQ system to monitor thermal comfort and gas concentration. The system has a data acquisition stage, captured by the WSN with a set of sensors that measures the data and send it to be stored on the InfluxDB database and displayed on Grafana. A Linear Regression (LR) algorithm was used to predict the behavior of the measured parameters, scoring up to 99.7% of precision. Thereafter, prediction data is stored on InfluxDB in a new database and displayed on Grafana. In this way, it is possible to monitor the actual measurement data and prediction data in real-time.pt_PT
dc.description.sponsorshipSupported by organization FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/05757/2020, and Thadeu Brito was supported by FCT PhD grant SFRH/BD/08598/2020.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBiondo, Elias; Brito, Thadeu; Nakano, Alberto; Lima, José (2023). A WSN real-time monitoring system approach for measuring indoor air quality using the internet of things. In 1st EAI International Conference on Internet of Everything, IoECon 2022. Guimarães. p. 76 - 90pt_PT
dc.identifier.doi10.1007/978-3-031-25222-8_7pt_PT
dc.identifier.urihttp://hdl.handle.net/10198/27289
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectIndoor air qualitypt_PT
dc.subjectMonitoring systempt_PT
dc.subjectInternet of thingspt_PT
dc.subjectWireless sensor networkpt_PT
dc.titleA WSN real-time monitoring system approach for measuring indoor air quality using the internet of thingspt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.citation.conferencePlaceGuimarãespt_PT
oaire.citation.endPage90pt_PT
oaire.citation.startPage76pt_PT
oaire.citation.title1st EAI International Conference on Internet of Everything, IoECon 2022pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameBrito
person.familyNameLima
person.givenNameThadeu
person.givenNameJosé
person.identifierBjSISEAAAAAJ
person.identifierR-000-8GD
person.identifier.ciencia-idC911-A95D-712F
person.identifier.ciencia-id6016-C902-86A9
person.identifier.orcid0000-0002-5962-0517
person.identifier.orcid0000-0001-7902-1207
person.identifier.ridL-3370-2014
person.identifier.scopus-author-id57200694948
person.identifier.scopus-author-id55851941311
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublicationd88c2b2a-efc2-48ef-b1fd-1145475e0055
relation.isAuthorOfPublication.latestForDiscoveryc8641c9a-a994-4ab2-836d-c758c0e44cc9
relation.isProjectOfPublication6e01ddc8-6a82-4131-bca6-84789fa234bd
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