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

Shujaat Hussain; Jae Bang; Manhyung Han; Muhammad Ahmed; Muhammad Amin; Sungyoung Lee; CD Nugent; Sally McClean; BW Scotney; Gerard Parr

doi:10.3390/s141122001

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

Shujaat Hussain, Jae Bang, Manhyung Han, Muhammad Ahmed, Muhammad Amin, Sungyoung Lee, CD Nugent, Sally McClean, BW Scotney, Gerard Parr

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	22001
Journal	Sensors
Volume	14
Issue number	11
DOIs	https://doi.org/10.3390/s141122001
Publication status	Published (in print/issue) - 2014

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10.3390/s141122001

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title = "Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce",

abstract = "Cloud computing has revolutionized healthcare in today{\textquoteright}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{\textquoteright}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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T1 - Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce

AU - Hussain, Shujaat

AU - Bang, Jae

AU - Han, Manhyung

AU - Ahmed, Muhammad

AU - Amin, Muhammad

AU - Lee, Sungyoung

AU - Nugent, CD

AU - McClean, Sally

AU - Scotney, BW

AU - Parr, Gerard

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

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DO - 10.3390/s141122001

M3 - Article

SN - 1424-8220

VL - 14

SP - 22001

JO - Sensors

JF - Sensors

IS - 11

ER -

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

Abstract

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