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dc.contributor.authorBach, Kerstin
dc.contributor.authorAkselsen, Sigmund
dc.contributor.authorVeiga, Tiago Santos
dc.contributor.authorKalamaras, Ilias
dc.date.accessioned2021-10-15T07:22:33Z
dc.date.available2021-10-15T07:22:33Z
dc.date.created2020-11-20T14:04:27Z
dc.date.issued2020
dc.identifier.isbn978-1-4503-8820-7
dc.identifier.urihttps://hdl.handle.net/11250/2823184
dc.description.abstractIn this poster we present how a network of Internet-of-things (IoT) devices facilitated through machine learning can improve decision making. Our application domain is air quality in the municipality of Trondheim. Ambient air pollution poses a major threat to both health and climate with millions of premature deaths occurring every year. To enable solutions to this problem, accurate measurements of the phenomenon are required and tools for decision makers need to be in place to quickly understand situations as well as suggest actions that lead to the best possible outcome.en_US
dc.language.isoengen_US
dc.publisherACMen_US
dc.relation.ispartofIoT '20 Companion: 10th International Conference on the Internet of Things Companion
dc.relation.urihttps://dl.acm.org/doi/pdf/10.1145/3423423.3423463
dc.titleOn the Use of Air Quality Microsensors for Supporting Decision Makersen_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published here, http://dx.doi.org/https://doi.org/10.1145/3423423.3423463en_US
dc.identifier.doi10.1145/3423423.3423463
dc.identifier.cristin1850442
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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