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

Sensors

Shujaat Hussain²  Jae Hun Bang²  Manhyung Han²  Muhammad Idris Ahmed²  Muhammad Bilal Amin²  Sungyoung Lee²  Chris Nugent¹  Sally McClean³  Bryan Scotney³ 

[1] School of Computing and Information Engineering, University of Ulster, Newtownabbey, Co. Antrim, BT38 0QB, UK; E-Mail:;Department of Computer Engineering, Kyung Hee University, Suwon 446-701, Korea; E-Mails:;School of Computing and Information Engineering, University of Ulster, Coleraine, Co. Londonderry, BT52 1SA, UK; E-Mails:

关键词: activity recognition;    mobile cloud;    MapReduce;    behavior analysis;    big data;   

DOI  :  10.3390/s141122001

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.