• Sensors (Basel) · Nov 2014

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

    • Shujaat Hussain, Jae Hun Bang, Manhyung Han, Muhammad Idris Ahmed, Muhammad Bilal Amin, Sungyoung Lee, Chris Nugent, Sally McClean, Bryan Scotney, and Gerard Parr.
    • Department of Computer Engineering, Kyung Hee University, Suwon 446-701, Korea. shujaat.hussain@oslab.khu.ac.kr.
    • Sensors (Basel). 2014 Nov 20; 14 (11): 22001-20.

    AbstractCloud 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.

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