Multisource data acquisition based on single-chip microcomputer and sensor technology

IF 1.1 Q3 COMPUTER SCIENCE, THEORY & METHODS Open Computer Science Pub Date : 2022-01-01 DOI:10.1515/comp-2022-0261
Yahui Huang, Daozhong Lei
{"title":"Multisource data acquisition based on single-chip microcomputer and sensor technology","authors":"Yahui Huang, Daozhong Lei","doi":"10.1515/comp-2022-0261","DOIUrl":null,"url":null,"abstract":"Abstract Today, data and information are flooded every day. Data are a reliable basis for scientific research. Their function is not only to clearly show real problems in various fields, but also to guide people to find the key factors that cause problems. The emergence of big data responds to this era of information explosion, and it is precisely by virtue of the accumulation of quantity that it presents the rules more clearly. No matter political, economic, cultural, and other fields are closely related to data. The application of microcontroller and sensor technology can help explore new branches of multisource data. However, the collection and analysis of multisource data only stays in the aspects of computer and communication technology. In view of the earlier problems, this article carried out scientific data collection and analysis of multisource data based on single-chip microcomputer and sensor technology. The research results showed that based on two algorithms, random early detection and weighted fair queuing, the analysis algorithm according to the Genetic Algorithm had a higher successful conversion rate. The power consumption of a node with better antenna performance was 9–10% lower than that of a node with poor antenna performance, which provided a basis for multisource data collection and analysis.","PeriodicalId":43014,"journal":{"name":"Open Computer Science","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/comp-2022-0261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 1

Abstract

Abstract Today, data and information are flooded every day. Data are a reliable basis for scientific research. Their function is not only to clearly show real problems in various fields, but also to guide people to find the key factors that cause problems. The emergence of big data responds to this era of information explosion, and it is precisely by virtue of the accumulation of quantity that it presents the rules more clearly. No matter political, economic, cultural, and other fields are closely related to data. The application of microcontroller and sensor technology can help explore new branches of multisource data. However, the collection and analysis of multisource data only stays in the aspects of computer and communication technology. In view of the earlier problems, this article carried out scientific data collection and analysis of multisource data based on single-chip microcomputer and sensor technology. The research results showed that based on two algorithms, random early detection and weighted fair queuing, the analysis algorithm according to the Genetic Algorithm had a higher successful conversion rate. The power consumption of a node with better antenna performance was 9–10% lower than that of a node with poor antenna performance, which provided a basis for multisource data collection and analysis.
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
基于单片机和传感器技术的多源数据采集
摘要今天,数据和信息每天都在泛滥。数据是科学研究的可靠基础。它们的作用不仅是清楚地展示各个领域的真实问题,而且引导人们找到导致问题的关键因素。大数据的出现回应了这个信息爆炸的时代,而正是凭借数量的积累,它将规则呈现得更加清晰。无论是政治、经济、文化等领域都与数据密切相关。微控制器和传感器技术的应用可以帮助探索多源数据的新分支。然而,多源数据的收集和分析只停留在计算机和通信技术方面。针对前期存在的问题,本文采用单片机和传感器技术对多源数据进行了科学的数据采集和分析。研究结果表明,基于随机早期检测和加权公平排队两种算法,基于遗传算法的分析算法具有较高的成功转换率。天线性能较好的节点的功耗比天线性能较差的节点低9-10%,这为多源数据收集和分析提供了基础。
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
Open Computer Science
Open Computer Science COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
4.00
自引率
0.00%
发文量
24
审稿时长
25 weeks
期刊最新文献
Task offloading in mobile edge computing using cost-based discounted optimal stopping A Bi-GRU-DSA-based social network rumor detection approach Artificial intelligence-based public safety data resource management in smart cities Application of fingerprint image fuzzy edge recognition algorithm in criminal technology Application of SSD network algorithm in panoramic video image vehicle detection system
×
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