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Behavior life style analysis for mobile sensory data in cloud computing through MapReduce


Hussain, S and Bang, JH and Han, M and Ahmed, MI and Amin, MB and Lee, S and Nugent, C and McClean, S and Scotney, B and Gerard, P, Behavior life style analysis for mobile sensory data in cloud computing through MapReduce, Sensors, 14, (11) pp. 22001-22020. ISSN 1424-8220 (2014) [Refereed Article]


Copyright Statement

Copyright 2014 The Authors Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.3390/s141122001


Cloud computing has revolutionized healthcare in todayís 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 userís 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.

Item Details

Item Type:Refereed Article
Keywords:activity recognition, mobile cloud, MapReduce, behavior analysis, big data
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Distributed systems and algorithms
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Amin, MB (Dr Muhammad Bilal Amin)
UTAS Author:Lee, S (Professor Sungyoung Lee)
ID Code:122918
Year Published:2014
Web of Science® Times Cited:17
Deposited By:Information and Communication Technology
Deposited On:2017-12-06
Last Modified:2021-03-25
Downloads:150 View Download Statistics

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