Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce
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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2014-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/14/11/22001 |
| _version_ | 1798040001635680256 |
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| author | Shujaat Hussain Jae Hun Bang Manhyung Han Muhammad Idris Ahmed Muhammad Bilal Amin Sungyoung Lee Chris Nugent Sally McClean Bryan Scotney Gerard Parr |
| author_facet | Shujaat Hussain Jae Hun Bang Manhyung Han Muhammad Idris Ahmed Muhammad Bilal Amin Sungyoung Lee Chris Nugent Sally McClean Bryan Scotney Gerard Parr |
| author_sort | Shujaat Hussain |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T22:01:28Z |
| format | Article |
| id | doaj.art-86ceefedbcac4f4f9d8a4abb3222a67c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T22:01:28Z |
| publishDate | 2014-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-86ceefedbcac4f4f9d8a4abb3222a67c2022-12-22T04:00:56ZengMDPI AGSensors1424-82202014-11-011411220012202010.3390/s141122001s141122001Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduceShujaat Hussain0Jae Hun Bang1Manhyung Han2Muhammad Idris Ahmed3Muhammad Bilal Amin4Sungyoung Lee5Chris Nugent6Sally McClean7Bryan Scotney8Gerard Parr9Department of Computer Engineering, Kyung Hee University, Suwon 446-701, KoreaDepartment of Computer Engineering, Kyung Hee University, Suwon 446-701, KoreaDepartment of Computer Engineering, Kyung Hee University, Suwon 446-701, KoreaDepartment of Computer Engineering, Kyung Hee University, Suwon 446-701, KoreaDepartment of Computer Engineering, Kyung Hee University, Suwon 446-701, KoreaDepartment of Computer Engineering, Kyung Hee University, Suwon 446-701, KoreaSchool of Computing and Information Engineering, University of Ulster, Newtownabbey, Co. Antrim, BT38 0QB, UKSchool of Computing and Information Engineering, University of Ulster, Coleraine, Co. Londonderry, BT52 1SA, UKSchool of Computing and Information Engineering, University of Ulster, Coleraine, Co. Londonderry, BT52 1SA, UKSchool of Computing and Information Engineering, University of Ulster, Coleraine, Co. Londonderry, BT52 1SA, UKCloud 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.http://www.mdpi.com/1424-8220/14/11/22001activity recognitionmobile cloudMapReducebehavior analysisbig data |
| spellingShingle | Shujaat Hussain Jae Hun Bang Manhyung Han Muhammad Idris Ahmed Muhammad Bilal Amin Sungyoung Lee Chris Nugent Sally McClean Bryan Scotney Gerard Parr Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce Sensors activity recognition mobile cloud MapReduce behavior analysis big data |
| title | Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce |
| title_full | Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce |
| title_fullStr | Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce |
| title_full_unstemmed | Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce |
| title_short | Behavior Life Style Analysis for Mobile Sensory Data in Cloud Computing through MapReduce |
| title_sort | behavior life style analysis for mobile sensory data in cloud computing through mapreduce |
| topic | activity recognition mobile cloud MapReduce behavior analysis big data |
| url | http://www.mdpi.com/1424-8220/14/11/22001 |
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