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|Title:||A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data|
|Authors:||TRILLES Sergi; BELMONTE Oscar; SCHADE SVEN; HUERTA Joaquin|
|Citation:||INTERNATIONAL JOURNAL OF DIGITAL EARTH vol. 10 no. 1 p. 103-120|
|Publisher:||TAYLOR & FRANCIS LTD|
|Type:||Articles in periodicals and books|
|Abstract:||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.|
|JRC Directorate:||Growth and Innovation|
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