| 3 | A domain-independent methodology to analyze IoT data streams in real-time.A proof of concept implementation for anomaly detection from environmental data显示文摘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. | Sergio Trilles Òscar Belmonte Sven Schade Joaquìn Huerta | 2017 | International Journal of Digital Earth2017，10，1： | 0 |
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