{"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.