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实时空气质量和流感样疾病数据存储与处理平台的一种实现方式。

An implementation of real-time air quality and influenza-like illness data storage and processing platform.

作者信息

Yang Chao-Tung, Chen Cai-Jin, Tsan Yu-Tse, Liu Po-Yu, Chan Yu-Wei, Chan Wei-Chen

机构信息

Department of Computer Science, Tunghai University, No.1727, Sec.4, Taiwan Boulevard, Xitun District, Taichung 40704, Taiwan.

Department of Emergency Medicine, Taichung Veterans General Hospital, No. 1650, Section 4, Taiwan Boulevard, Taichung, Taiwan.

出版信息

Comput Human Behav. 2019 Nov;100:266-274. doi: 10.1016/j.chb.2018.10.009. Epub 2018 Oct 8.

DOI:10.1016/j.chb.2018.10.009
PMID:32288172
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7126110/
Abstract

Recently, air pollution has become the primary concern in Taiwan as it significantly affected people's health. Some air pollution monitoring, analysis, and prediction systems were proposed to solve the problem. However, there is very little research to see whether the air quality is associated with the Influenza-Like Illness (ILI) disease or not. In this study, a system is needed, in which the air quality data and the influenza-like illness data can be analyzed together to determine their associations accurately and effectively. In this work, a novel integrated platform was implemented by building a cluster environment based on Hadoop, Spark and a visualization environment with ELK Stack as well as a backup storage system based on Ceph object storage architecture. Also, Sqoop and Alluxio were used to solve the inefficiency problem in processing vast amounts of data. The experimental results showed the visualization of air quality and influenza-like illness data collected from 2016 to 2017 in Taichung, Taiwan. Besides, the association analyses and discussion between air quality and influenza-like illness were also presented.

摘要

近年来，空气污染已成为台湾地区的首要关注问题，因为它对人们的健康产生了重大影响。为了解决这一问题，人们提出了一些空气污染监测、分析和预测系统。然而，关于空气质量与流感样疾病（ILI）之间是否存在关联的研究却非常少。在本研究中，需要一个系统，能够将空气质量数据和流感样疾病数据一起进行分析，以准确有效地确定它们之间的关联。在这项工作中，通过构建基于Hadoop、Spark的集群环境以及使用ELK Stack的可视化环境和基于Ceph对象存储架构的备份存储系统，实现了一个新颖的集成平台。此外，还使用了Sqoop和Alluxio来解决处理大量数据时的效率低下问题。实验结果展示了2016年至2017年在台湾台中收集的空气质量和流感样疾病数据的可视化情况。此外，还给出了空气质量与流感样疾病之间的关联分析和讨论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/2ccb7a351cef/gr14_lrg.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/98f1113634ae/gr9_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/d6e697e1751a/gr10_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/17d857dc4109/gr11_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/826e38f5579d/gr12_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/6a35cb7edb24/gr13_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/2ccb7a351cef/gr14_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/de21b46f1887/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/c5bff3eddfeb/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/52c01b17d746/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/7d6974d9f6dc/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/9b623a4adffd/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/f9477fe8aa26/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/c8b0dd51f4d2/gr7_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/4cf43971fecf/gr8_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/98f1113634ae/gr9_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/d6e697e1751a/gr10_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/17d857dc4109/gr11_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/826e38f5579d/gr12_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/6a35cb7edb24/gr13_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c51/7126110/2ccb7a351cef/gr14_lrg.jpg

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