A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data
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Otros documentos de la autoría: Trilles, Sergio; Belmonte-Fernández, Óscar; Schade, Sven; Huerta, Joaquin
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Título
A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental dataFecha de publicación
2016-07Editor
Taylor & FrancisCita bibliográfica
TRILLES, 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.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.tandfonline.com/doi/abs/10.1080/17538947.2016.1209583Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Pushed 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 ... [+]
Pushed 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. [-]
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International Journal of Digital Earth, 2016Derechos de acceso
© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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