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Journal of Sensors
Volume 2015 (2015), Article ID 834217, 11 pages
http://dx.doi.org/10.1155/2015/834217
Research Article

Architecture and Implementation of a Scalable Sensor Data Storage and Analysis System Using Cloud Computing and Big Data Technologies

Computer Engineering Department, Firat University, 23100 Elazig, Turkey

Received 6 February 2015; Accepted 20 February 2015

Academic Editor: Sergiu Dan Stan

Copyright © 2015 Galip Aydin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Sensors are becoming ubiquitous. From almost any type of industrial applications to intelligent vehicles, smart city applications, and healthcare applications, we see a steady growth of the usage of various types of sensors. The rate of increase in the amount of data produced by these sensors is much more dramatic since sensors usually continuously produce data. It becomes crucial for these data to be stored for future reference and to be analyzed for finding valuable information, such as fault diagnosis information. In this paper we describe a scalable and distributed architecture for sensor data collection, storage, and analysis. The system uses several open source technologies and runs on a cluster of virtual servers. We use GPS sensors as data source and run machine-learning algorithms for data analysis.