一种新的环境参数节能测量自适应采样方法

Obiora Sam Ezeora, J. Heckenbergerova, P. Musílek
{"title":"一种新的环境参数节能测量自适应采样方法","authors":"Obiora Sam Ezeora, J. Heckenbergerova, P. Musílek","doi":"10.1109/EEEIC.2016.7555688","DOIUrl":null,"url":null,"abstract":"A new method involving adaptive sampling of environmental parameters at sensor nodes has been proposed and developed. The method involves determination of stochastic models of the environmental parameters so that forward and backward predictions could be performed accurately with minimal energy. When difference between measured values and corresponding model-predicted values falls outside predefined threshold interval, measured values are upheld and used to update the model by computing for new model parameters while keeping stochastic order of the model constant. The proposed method has been applied and validated using environmental field data. Favorable results were obtained. The method was also used to determine, with sufficient accuracy, numerical values of missed measurements during a low frequency sampling.","PeriodicalId":246856,"journal":{"name":"2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A new adaptive sampling method for energy-efficient measurement of environmental parameters\",\"authors\":\"Obiora Sam Ezeora, J. Heckenbergerova, P. Musílek\",\"doi\":\"10.1109/EEEIC.2016.7555688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method involving adaptive sampling of environmental parameters at sensor nodes has been proposed and developed. The method involves determination of stochastic models of the environmental parameters so that forward and backward predictions could be performed accurately with minimal energy. When difference between measured values and corresponding model-predicted values falls outside predefined threshold interval, measured values are upheld and used to update the model by computing for new model parameters while keeping stochastic order of the model constant. The proposed method has been applied and validated using environmental field data. Favorable results were obtained. The method was also used to determine, with sufficient accuracy, numerical values of missed measurements during a low frequency sampling.\",\"PeriodicalId\":246856,\"journal\":{\"name\":\"2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EEEIC.2016.7555688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEEIC.2016.7555688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

提出并发展了一种对传感器节点环境参数进行自适应采样的新方法。该方法包括确定环境参数的随机模型,以便以最小的能量准确地进行前向和后向预测。当实测值与相应的模型预测值之间的差值超出预定义的阈值区间时,维持实测值,并在保持模型随机阶不变的情况下,通过计算新的模型参数来更新模型。该方法已通过环境现场数据进行了应用和验证。取得了良好的效果。该方法还用于确定在低频采样期间错过的测量值的数值,具有足够的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new adaptive sampling method for energy-efficient measurement of environmental parameters
A new method involving adaptive sampling of environmental parameters at sensor nodes has been proposed and developed. The method involves determination of stochastic models of the environmental parameters so that forward and backward predictions could be performed accurately with minimal energy. When difference between measured values and corresponding model-predicted values falls outside predefined threshold interval, measured values are upheld and used to update the model by computing for new model parameters while keeping stochastic order of the model constant. The proposed method has been applied and validated using environmental field data. Favorable results were obtained. The method was also used to determine, with sufficient accuracy, numerical values of missed measurements during a low frequency sampling.
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信