Management of Big Data in the Internet of Things in Agriculture Based on Cloud Computing

Internet of Things (IoT) is playing a more and more important role in modern agriculture development. However, problems of efficient storing and reasoning those massive heterogeneous sensor data collected from variety kinds of sensing equipment need to be resolved to implement Internet of Things in...

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Published in:Applied Mechanics and Materials Vol. 548-549; no. Achievements in Engineering Sciences; pp. 1438 - 1444
Main Authors: Wang, Hui Zhe, Wang, Jian Qin, Lin, Guo Wen, Chen, Yi Fei, Duan, Qing Ling, Gao, Wan Lin
Format: Journal Article
Language:English
Published: Zurich Trans Tech Publications Ltd 28.04.2014
Subjects:
Agriculture
Architecture (computers)
Cloud computing
Internet
Management
Programming
Sensors
Internet of Things in Agriculture
Heterogeneous Sensor Data
HBase
MapReduce
ISBN:3038350842, 9783038350842
ISSN:1660-9336, 1662-7482, 1662-7482
Online Access:Get full text
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Summary:Internet of Things (IoT) is playing a more and more important role in modern agriculture development. However, problems of efficient storing and reasoning those massive heterogeneous sensor data collected from variety kinds of sensing equipment need to be resolved to implement Internet of Things in agriculture. This paper explores the architecture of Internet of Things in agriculture with heterogeneous sensor data, and proposes a design of implementation to Internet of Things in agriculture based on cloud computing. The design is based on two-tier storage structure of HBase, which is a distributed database with high scalability. It access database using MapReduce model, a distributed programming framework. Hence, this design provides scalable storage, efficient data access, and eases other processing of sensor data.
Bibliography:Selected, peer reviewed papers from the 2014 3rd International Conference on Manufacturing Engineering and Process (ICMEP 2014), April 10-11, 2014, Seoul, Korea
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ISBN:3038350842
9783038350842
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.548-549.1438