Weighted Visibility Graph Based WiFi Indoor Positioning Method Using Heuristic Optimization

Turan Goktug Altundogan, Mehmet Karaköse
{"title":"Weighted Visibility Graph Based WiFi Indoor Positioning Method Using Heuristic Optimization","authors":"Turan Goktug Altundogan, Mehmet Karaköse","doi":"10.55525/tjst.1254099","DOIUrl":null,"url":null,"abstract":"With the widespread use of wireless communication technologies and IoT applications, researchers are \ndeveloping approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process \nbased on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength (RSSI) values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.","PeriodicalId":516893,"journal":{"name":"Turkish Journal of Science and Technology","volume":"20 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Turkish Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55525/tjst.1254099","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

With the widespread use of wireless communication technologies and IoT applications, researchers are developing approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process based on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength (RSSI) values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.
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
使用启发式优化的基于加权可见性图的 WiFi 室内定位方法
随着无线通信技术和物联网应用的广泛使用,研究人员正在开发利用 WiFi 信号确定室内位置的方法。在本研究中,通过根据 WiFi 信号强度(RSSI)值创建接入点的加权可见度矩阵,执行了基于启发式优化方法的室内定位过程。在所提出的方法中,PSO 和 GA 方法使用基于可见度加权矩阵的通用拟合函数确定移动用户的位置。所提出的方法已在一个虚拟场景中进行了测试,该场景中的位置范围是根据 RSSI 范围确定的。根据不同的标准对两种启发式优化方法进行了比较,定位过程中,基于 GA 的方法的最大误差为 3 米,基于 PSO 的方法的最大误差为 1.5 米。
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
The Design of Machine Learning-Based Computer-Aided System with LabVIEW For Abnormalities in Mammogram Images Comparative Analysis of Wavelet Families in Image Compression, Featuring the Proposed New Wavelet Improved Spatial Modulation with Mapping Diversity Molecular Dynamics Simulation of Bauschinger Effect in Cu Nanowire with Different Crystallographic Orientation Vitamins, Phytosterols and Oil Acids in Sulphurized Apricots
×
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