DocumentCode :
659410
Title :
Building a generic platform for big sensor data application
Author :
Chun-Hsiang Lee ; Birch, David ; Chao Wu ; Silva, Danilo ; Tsinalis, Orestis ; Yang Li ; Shulin Yan ; Ghanem, M. ; Yike Guo
Author_Institution :
Dept. of Comput., Imperial Coll. London, London, UK
fYear :
2013
fDate :
6-9 Oct. 2013
Firstpage :
94
Lastpage :
102
Abstract :
The drive toward smart cities alongside the rising adoption of personal sensors is leading to a torrent of sensor data. While systems exist for storing and managing sensor data, the real value of such data is the insight which can be generated from it. However there is currently no platform which enables sensor data to be taken from collection, through use in models to produce useful data products. The architecture of such a platform is a current research question in the field of Big Data and Smart Cities. In this paper we explore five key challenges in this field and provide a response through a sensor data platform “Concinnity” which can take sensor data from collection to final product via a data repository and workflow system. This will enable rapid development of applications built on sensor data using data fusion and the integration and composition of models to form novel workflows. We summarize the key features of our approach, exploring how it enables value to be derived from sensor data efficiently.
Keywords :
data integration; mobile computing; sensor fusion; big sensor data application; concinnity; data fusion; data integration; data products; data repository system; data workflow system; digital city; generic platform; mobile devices; personal sensors; sensing devices; smart cities; Analytical models; Biological system modeling; Cities and towns; Collaboration; Data models; Engines; Information management; Digital City; Smart City; sensor application; sensor data management; sensor platform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data, 2013 IEEE International Conference on
Conference_Location :
Silicon Valley, CA
Type :
conf
DOI :
10.1109/BigData.2013.6691559
Filename :
6691559
Link To Document :
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