T. Chowdhury, M. M. Rahman, Sadre-Ala Parvez, A. Alam, A. Basher, A. Alam, S. Rizwan
{"title":"A multi-step approach for RSSi-based distance estimation using smartphones","authors":"T. Chowdhury, M. M. Rahman, Sadre-Ala Parvez, A. Alam, A. Basher, A. Alam, S. Rizwan","doi":"10.1109/NSysS.2015.7042942","DOIUrl":null,"url":null,"abstract":"Measuring distance from Received Signal Strength Indication (RSSI) of wireless devices has become one of the rudimentary but challenging requirements for Indoor Positioning and Indoor Navigation (IPIN). To address this subject, we propose a novel multi-step approach combining Flat Earth Model, Free Space Friis Model and Linear Approximation Model for measuring distance from RSSI for smart devices with Bluetooth Low Energy (BLE) connectivity. To get better result we proposed an improved averaging and smoothing algorithm of RSSI. We have significantly achieved 13.4% reduced error of measured distance.","PeriodicalId":408601,"journal":{"name":"2015 International Conference on Networking Systems and Security (NSysS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"46","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Networking Systems and Security (NSysS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSysS.2015.7042942","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 46
Abstract
Measuring distance from Received Signal Strength Indication (RSSI) of wireless devices has become one of the rudimentary but challenging requirements for Indoor Positioning and Indoor Navigation (IPIN). To address this subject, we propose a novel multi-step approach combining Flat Earth Model, Free Space Friis Model and Linear Approximation Model for measuring distance from RSSI for smart devices with Bluetooth Low Energy (BLE) connectivity. To get better result we proposed an improved averaging and smoothing algorithm of RSSI. We have significantly achieved 13.4% reduced error of measured distance.