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Open AccessArticle

Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce

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Department of Computer Engineering, Kyung Hee University, Suwon 446-701, Korea
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School of Computing and Information Engineering, University of Ulster, Newtownabbey, Co. Antrim, BT38 0QB, UK
3
School of Computing and Information Engineering, University of Ulster, Coleraine, Co. Londonderry, BT52 1SA, UK
*
Author to whom correspondence should be addressed.
Sensors 2014, 14(11), 22001-22020; https://doi.org/10.3390/s141122001
Received: 1 January 2014 / Revised: 4 November 2014 / Accepted: 12 November 2014 / Published: 20 November 2014
(This article belongs to the Special Issue Sensors Data Fusion for Healthcare)
Cloud computing has revolutionized healthcare in today’s world as it can be seamlessly integrated into a mobile application and sensor devices. The sensory data is then transferred from these devices to the public and private clouds. In this paper, a hybrid and distributed environment is built which is capable of collecting data from the mobile phone application and store it in the cloud. We developed an activity recognition application and transfer the data to the cloud for further processing. Big data technology Hadoop MapReduce is employed to analyze the data and create user timeline of user’s activities. These activities are visualized to find useful health analytics and trends. In this paper a big data solution is proposed to analyze the sensory data and give insights into user behavior and lifestyle trends. View Full-Text
Keywords: activity recognition; mobile cloud; MapReduce; behavior analysis; big data activity recognition; mobile cloud; MapReduce; behavior analysis; big data
MDPI and ACS Style

Hussain, S.; Bang, J.H.; Han, M.; Ahmed, M.I.; Amin, M.B.; Lee, S.; Nugent, C.; McClean, S.; Scotney, B.; Parr, G. Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce. Sensors 2014, 14, 22001-22020.

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