基于IEEE 802.15.4设备的室内指纹定位系统参数优化方法

Yuan-Zhi Huo, P. Puspitaningayu, N. Funabiki, K. Hamazaki, M. Kuribayashi, K. Kojima
{"title":"基于IEEE 802.15.4设备的室内指纹定位系统参数优化方法","authors":"Yuan-Zhi Huo, P. Puspitaningayu, N. Funabiki, K. Hamazaki, M. Kuribayashi, K. Kojima","doi":"10.1109/ICCCI51764.2021.9486801","DOIUrl":null,"url":null,"abstract":"To achieve the high accuracy while wearing an inexpensive, tiny, and long-life transmitter, we have developed a fingerprint-based indoor localization system. It adopts IEEE802.15.4 devices and restricts the detection granularity to one room in an indoor environment. Unfortunately, wireless signals of the devices often fluctuate due to human movements and other uncontrollable factors. It has been observed that it can be solved by assigning plural fingerprints to one room. However, their values need to be properly selected. In this paper, we study the parameter optimization method for this indoor localization system. An existing parameter optimization tool is employed where the score function is newly defined to estimate the optimality of the current parameters. For evaluations, we apply the method to the measured data using the system in #2 Engineering Building of Okayama University. The results show that the detection accuracy becomes higher than 95% for any room by increasing the number of fingerprints and optimizing the parameter values by the proposal.","PeriodicalId":180004,"journal":{"name":"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Parameter Optimization Method for Fingerprint-Based Indoor Localization System Using IEEE 802.15.4 Devices\",\"authors\":\"Yuan-Zhi Huo, P. Puspitaningayu, N. Funabiki, K. Hamazaki, M. Kuribayashi, K. Kojima\",\"doi\":\"10.1109/ICCCI51764.2021.9486801\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To achieve the high accuracy while wearing an inexpensive, tiny, and long-life transmitter, we have developed a fingerprint-based indoor localization system. It adopts IEEE802.15.4 devices and restricts the detection granularity to one room in an indoor environment. Unfortunately, wireless signals of the devices often fluctuate due to human movements and other uncontrollable factors. It has been observed that it can be solved by assigning plural fingerprints to one room. However, their values need to be properly selected. In this paper, we study the parameter optimization method for this indoor localization system. An existing parameter optimization tool is employed where the score function is newly defined to estimate the optimality of the current parameters. For evaluations, we apply the method to the measured data using the system in #2 Engineering Building of Okayama University. The results show that the detection accuracy becomes higher than 95% for any room by increasing the number of fingerprints and optimizing the parameter values by the proposal.\",\"PeriodicalId\":180004,\"journal\":{\"name\":\"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCI51764.2021.9486801\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Computer Communication and the Internet (ICCCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCI51764.2021.9486801","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

为了在佩戴廉价、小巧、长寿命的发射器的同时实现高精度,我们开发了一种基于指纹的室内定位系统。它采用IEEE802.15.4设备,将检测粒度限制在室内环境中的一个房间。不幸的是,由于人的运动和其他不可控因素,设备的无线信号经常波动。据观察,它可以通过分配多个指纹到一个房间来解决。但是,需要正确选择它们的值。本文研究了该室内定位系统的参数优化方法。利用现有的参数优化工具,其中新定义分数函数来估计当前参数的最优性。为了进行评估,我们将该方法应用于冈山大学2号工程大楼的测量数据。结果表明,通过增加指纹数量和优化参数值,该方法对任意房间的指纹检测准确率均在95%以上。
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
A Parameter Optimization Method for Fingerprint-Based Indoor Localization System Using IEEE 802.15.4 Devices
To achieve the high accuracy while wearing an inexpensive, tiny, and long-life transmitter, we have developed a fingerprint-based indoor localization system. It adopts IEEE802.15.4 devices and restricts the detection granularity to one room in an indoor environment. Unfortunately, wireless signals of the devices often fluctuate due to human movements and other uncontrollable factors. It has been observed that it can be solved by assigning plural fingerprints to one room. However, their values need to be properly selected. In this paper, we study the parameter optimization method for this indoor localization system. An existing parameter optimization tool is employed where the score function is newly defined to estimate the optimality of the current parameters. For evaluations, we apply the method to the measured data using the system in #2 Engineering Building of Okayama University. The results show that the detection accuracy becomes higher than 95% for any room by increasing the number of fingerprints and optimizing the parameter values by the proposal.
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
期刊最新文献
Intrusion Detection Method Based on Sparse Autoencoder The Architecture Design for Publicizing Digital Competence to Online Job Market Improved AOMDV Routing Protocol in Manet UAV Based on Virtual Hop Improving Face Recognition Using Pre-trained Models for Mask Wearer Images Data Offloading in Heterogeneous Dynamic Fog Computing Network: A Contextual Bandit Approach
×
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