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dc.contributor.authorTrilles Oliver, Sergi
dc.contributor.authorBelmonte Fernández, Óscar
dc.contributor.authorSchade, Sven
dc.contributor.authorHuerta, Joaquín
dc.date.accessioned2016-10-13T11:17:27Z
dc.date.available2016-10-13T11:17:27Z
dc.date.issued2016-07
dc.identifier.citationTRILLES, Sergio, et al. A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data. International Journal of Digital Earth, 2016, p. 1-18.ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/163581
dc.description.abstractPushed by the Internet of Things (IoT) paradigm modern sensor networks monitor a wide range of phenomena, in areas such as environmental monitoring, health care, industrial processes, and smart cities. These networks provide a continuous pulse of the almost infinite activities that are happening in the physical space and are thus, key enablers for a Digital Earth Nervous System. Nevertheless, the rapid processing of these sensor data streams still continues to challenge traditional data-handling solutions and new approaches are being requested. We propose a generic answer to this challenge, which has the potential to support any form of distributed real-time analysis. This neutral methodology follows a brokering approach to work with different kinds of data sources and uses web-based standards to achieve interoperability. As a proof of concept, we implemented the methodology to detect anomalies in real-time and applied it to the area of environmental monitoring. The developed system is capable of detecting anomalies, generating notifications, and displaying the recent situation to the user.ca_CA
dc.format.extent17 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherTaylor & Francisca_CA
dc.relation.isPartOfInternational Journal of Digital Earth, 2016ca_CA
dc.rights© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Groupca_CA
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectBig dataca_CA
dc.subjectreal-time analysisca_CA
dc.subjectdata streamsca_CA
dc.subjectsensor networksca_CA
dc.subjectinteroperabilityca_CA
dc.subjectbrokering approachca_CA
dc.titleA domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental dataca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1080/17538947.2016.1209583
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttp://www.tandfonline.com/doi/abs/10.1080/17538947.2016.1209583ca_CA


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