A domain-independent methodology to analyze IoT data streams in real-time.A proof of concept implementation for anomaly detection from environmental data

作     者：Sergio Trilles Òscar Belmonte Sven Schade Joaquìn Huerta 

作者机构：Institute of New Imaging TechnologiesUniversitat Jaume ICastellóde la PlanaSpain European Commission–Joint Research CentreInstitute for Environment and SustainabilityIspraItaly 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2017年第10卷第1期

页      面：103-120页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：European Commission and Generalitat Valenciana government[ACIF/2012/112]and[BEFPI/2014/067] 

主　　题：Big data real-time analysis data streams sensor networks interoperability brokering approach 

摘      要：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 *** 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 ***,the rapid processing of these sensor data streams still continues to challenge traditional data-handling solutions and new approaches are being *** propose a generic answer to this challenge,which has the potential to support any form of distributed real-time *** neutral methodology follows a brokering approach to work with different kinds of data sources and uses web-based standards to achieve *** a proof of concept,we implemented the methodology to detect anomalies in real-time and applied it to the area of environmental *** developed system is capable of detecting anomalies,generating notifications,and displaying the recent situation to the user.