article

Disease Surveillance System for Big Climate Data Processing and Dengue Transmission

Authors:

Gunasekaran Manogaran,

Daphne LopezAuthors Info & Claims

International Journal of Ambient Computing and Intelligence, Volume 8, Issue 2

Pages 88 - 105

https://doi.org/10.4018/IJACI.2017040106

Published: 01 April 2017 Publication History

Abstract

Ambient intelligence is an emerging platform that provides advances in sensors and sensor networks, pervasive computing, and artificial intelligence to capture the real time climate data. This result continuously generates several exabytes of unstructured sensor data and so it is often called big climate data. Nowadays, researchers are trying to use big climate data to monitor and predict the climate change and possible diseases. Traditional data processing techniques and tools are not capable of handling such huge amount of climate data. Hence, there is a need to develop advanced big data architecture for processing the real time climate data. The purpose of this paper is to propose a big data based surveillance system that analyzes spatial climate big data and performs continuous monitoring of correlation between climate change and Dengue. Proposed disease surveillance system has been implemented with the help of Apache Hadoop MapReduce and its supporting tools.

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cover image International Journal of Ambient Computing and Intelligence

International Journal of Ambient Computing and Intelligence Volume 8, Issue 2

April 2017

105 pages

ISSN:1941-6237

EISSN:1941-6245

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Publisher

IGI Global

United States

Publication History

Published: 01 April 2017

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