The mass data mining research based on the information platform of Internet of Things

Juan Li, Xuan Luo, Fengqi Hao
{"title":"The mass data mining research based on the information platform of Internet of Things","authors":"Juan Li, Xuan Luo, Fengqi Hao","doi":"10.1109/ICAIT.2017.8388923","DOIUrl":null,"url":null,"abstract":"This paper analyzes the key technologies of the distributed data, and proposes the solution of the mass data processing based on the Information platform of Internet of Things. The solution uses Hadoop as the open source framework to realize the distributed computing system, and uses Mahout as the data mining algorithm library to realize the parallelization of k-means clustering algorithm. This will achieve the high efficiency and the large expansibility through the mass data processing. The mass data source used in this project is from the intelligent agricultural Information service platform. The system takes the deployment test on the mass sensing information, and it optimizes and parallelizes the K-means algorithm to realize the mass data processing based on the Information platform of Internet of Things. It can make the statistical analysis, and provide fine management and other services. the algorithm is used to improve the efficiency and the accuracy of the platform with the supercomputing and the reliable storage ability.","PeriodicalId":376884,"journal":{"name":"2017 9th International Conference on Advanced Infocomm Technology (ICAIT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 9th International Conference on Advanced Infocomm Technology (ICAIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIT.2017.8388923","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper analyzes the key technologies of the distributed data, and proposes the solution of the mass data processing based on the Information platform of Internet of Things. The solution uses Hadoop as the open source framework to realize the distributed computing system, and uses Mahout as the data mining algorithm library to realize the parallelization of k-means clustering algorithm. This will achieve the high efficiency and the large expansibility through the mass data processing. The mass data source used in this project is from the intelligent agricultural Information service platform. The system takes the deployment test on the mass sensing information, and it optimizes and parallelizes the K-means algorithm to realize the mass data processing based on the Information platform of Internet of Things. It can make the statistical analysis, and provide fine management and other services. the algorithm is used to improve the efficiency and the accuracy of the platform with the supercomputing and the reliable storage ability.
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
基于物联网信息平台的海量数据挖掘研究
分析了分布式数据的关键技术,提出了基于物联网信息平台的海量数据处理解决方案。该方案采用Hadoop作为开源框架实现分布式计算系统,采用Mahout作为数据挖掘算法库实现k-means聚类算法的并行化。通过对海量数据的处理,实现了高效率和大可扩展性。本项目使用的海量数据源来自智能农业信息服务平台。系统对海量传感信息进行了部署测试,并对K-means算法进行了优化并行化,实现了基于物联网信息平台的海量数据处理。可以进行统计分析,并提供精细化管理等服务。该算法具有超强的计算能力和可靠的存储能力,可以提高平台的效率和精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Data fusion of heterogeneous network based on BP neural network and improved SEP Generation of PAM4 signal over 10-km multi core fiber using DMLs and photodiode Backstepping adaptive sliding mode control for the USV course tracking system Color demosaicking with the spatial alignment property of spectral Laplacians The principle and application of hyperspectral imaging technology in detection of handwriting
×
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