{"title":"A scalable Wi-Fi based localization approach","authors":"T. Le, N. Nguyen","doi":"10.1109/ATC.2011.6027451","DOIUrl":null,"url":null,"abstract":"This paper proposes a scalable method which allows deploying the fingerprint Wi-Fi localization algorithm for different devices. The original fingerprint localization algorithm performs accurately only if the device used in the testing phase is the same as the device used in the training phase. When a different device is used in the testing phase, a time-consuming re-training step (in the order of hours or days) is required to achieve the equivalent degree of accuracy. Our proposed approach replaces the re-training step with a short period of calibration (in the order of a few minutes), which can be done transparently to the user. To validate our approach, we collected data from a large scale experiment (14 laptops and 2 smartphones with 224-hour of collected data) to evaluate the performance.","PeriodicalId":221905,"journal":{"name":"The 2011 International Conference on Advanced Technologies for Communications (ATC 2011)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2011 International Conference on Advanced Technologies for Communications (ATC 2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATC.2011.6027451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper proposes a scalable method which allows deploying the fingerprint Wi-Fi localization algorithm for different devices. The original fingerprint localization algorithm performs accurately only if the device used in the testing phase is the same as the device used in the training phase. When a different device is used in the testing phase, a time-consuming re-training step (in the order of hours or days) is required to achieve the equivalent degree of accuracy. Our proposed approach replaces the re-training step with a short period of calibration (in the order of a few minutes), which can be done transparently to the user. To validate our approach, we collected data from a large scale experiment (14 laptops and 2 smartphones with 224-hour of collected data) to evaluate the performance.