基于物联网大数据分析的分类扩展,用于智能环境监测与实时系统分析

Riyadh Arridha, S. Sukaridhoto, D. Pramadihanto, N. Funabiki
{"title":"基于物联网大数据分析的分类扩展,用于智能环境监测与实时系统分析","authors":"Riyadh Arridha, S. Sukaridhoto, D. Pramadihanto, N. Funabiki","doi":"10.1504/IJSSC.2017.10008038","DOIUrl":null,"url":null,"abstract":"Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of water resources. To integrate the water monitoring system into the big data technology for real-time analysis, we have engaged in the ongoing project named smart environment monitoring and analytic in real-time system (SEMAR), which provides the IoT-big data platform for water monitoring. However, SEMAR does not have an analytical system yet. This paper proposes the analytical system for water quality classification using Pollution Index method, which is an extension of SEMAR. Besides, the communication protocol is updated from REST to MQTT. Furthermore, the real-time user interface is implemented for visualisation. The evaluations confirmed that the data analytic function adopting the linear SVM and decision tree algorithms achieves more than 90% for the estimation accuracy with 0.019075 for the MSE.","PeriodicalId":43931,"journal":{"name":"International Journal of Space-Based and Situated Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"70","resultStr":"{\"title\":\"Classification extension based on IoT-big data analytic for smart environment monitoring and analytic in real-time system\",\"authors\":\"Riyadh Arridha, S. Sukaridhoto, D. Pramadihanto, N. Funabiki\",\"doi\":\"10.1504/IJSSC.2017.10008038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of water resources. To integrate the water monitoring system into the big data technology for real-time analysis, we have engaged in the ongoing project named smart environment monitoring and analytic in real-time system (SEMAR), which provides the IoT-big data platform for water monitoring. However, SEMAR does not have an analytical system yet. This paper proposes the analytical system for water quality classification using Pollution Index method, which is an extension of SEMAR. Besides, the communication protocol is updated from REST to MQTT. Furthermore, the real-time user interface is implemented for visualisation. The evaluations confirmed that the data analytic function adopting the linear SVM and decision tree algorithms achieves more than 90% for the estimation accuracy with 0.019075 for the MSE.\",\"PeriodicalId\":43931,\"journal\":{\"name\":\"International Journal of Space-Based and Situated Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"70\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Space-Based and Situated Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJSSC.2017.10008038\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Space-Based and Situated Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSSC.2017.10008038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 70

摘要

实时监测水情是保护海洋和群岛国家(如依赖丰富水资源的印度尼西亚)水生态系统的一项关键任务。为了将水监测系统整合到大数据技术中进行实时分析,我们正在开展智能环境实时监测与分析系统(SEMAR)项目,为水监测提供物联网大数据平台。然而,SEMAR还没有一个分析系统。本文提出了一种基于污染指数法的水质分类分析系统,该系统是SEMAR的扩展。此外,通信协议也从REST更新为MQTT。此外,还实现了实时用户界面的可视化。评价结果表明,采用线性支持向量机和决策树算法的数据分析函数的估计精度达到90%以上,MSE的估计精度为0.019075。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Classification extension based on IoT-big data analytic for smart environment monitoring and analytic in real-time system
Monitoring water conditions in real-time is a critical mission to preserve the water ecosystem in maritime and archipelagic countries, such as Indonesia that is relying on the wealth of water resources. To integrate the water monitoring system into the big data technology for real-time analysis, we have engaged in the ongoing project named smart environment monitoring and analytic in real-time system (SEMAR), which provides the IoT-big data platform for water monitoring. However, SEMAR does not have an analytical system yet. This paper proposes the analytical system for water quality classification using Pollution Index method, which is an extension of SEMAR. Besides, the communication protocol is updated from REST to MQTT. Furthermore, the real-time user interface is implemented for visualisation. The evaluations confirmed that the data analytic function adopting the linear SVM and decision tree algorithms achieves more than 90% for the estimation accuracy with 0.019075 for the MSE.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Journal of Space-Based and Situated Computing
International Journal of Space-Based and Situated Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
0.00%
发文量
0
期刊最新文献
A hierarchical outlier detection method for spare parts transaction A multi-tiered spare parts inventory forecasting system GPS availability prediction based on air-ground collaboration Inventory Optimization based on NSGA-III Algorithm Data privacy and anonymisation of simulated health-care dataset using the ARX open source tool
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1