@article{TrillesOliver16,
title = {A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data},
author = { Sergio Trilles-Oliver and Óscar Belmonte-Fernández and Sven Schade and Joaquín Huerta-Guijarro},
issn = {1753-8947},
year = {2017},
date = {2017-01-01},
journal = {International Journal of Digital Earth},
volume = {10},
number = {1},
pages = {103-120},
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.},
keywords = {environmental monitoring, Internet of things, Real time analysis, real-time sensor streams},
pubstate = {published},
tppubtype = {article}
}