Title :
Concinnity: A Generic Platform for Big Sensor Data Applications
Author :
Chao Wu ; Birch, David ; Silva, Danilo ; Chun-Hsiang Lee ; Tsinalis, Orestis ; Guo, Youguang
Author_Institution :
Dept. of Comput., Imperial Coll. London, London, UK
Abstract :
The drive toward smart cities alongside the increasing adoption of personal sensors is leading to big sensor data, which is so large and complex that traditional methods for utilizing it are inadequate. Although systems exist for storing and managing large-scale sensor data, the real value of such data are the insights it could enable. However, no current platforms enable sensor data to be taken from collection through use in models to produce useful data products. This article explores key challenges and introduces the Concinnity sensor data platform. Concinnity takes sensor data from collection to final product via a cloud-based data repository and easy-to-use workflow system. It supports rapid development of applications built on sensor data using data fusion and the integration and composition of models to form novel workflows. These key features enable value to be efficiently derived from sensor data.
Keywords :
cloud computing; sensor fusion; Concinnity platform; big sensor data applications; cloud-based data repository; data management; data products; data storage; personal sensor adoption; smart city; Analytical models; Big data; Biological system modeling; Cloud computing; Computational modeling; Data models; Smart buildings; cloud; cloud computing; digital city; sensor data management; sensor platform; virtualization;
Journal_Title :
Cloud Computing, IEEE
DOI :
10.1109/MCC.2014.33