Yiqing Hu, Yan Xiong, Wenchao Huang, Xiangyang Li, Yanan Zhang, Xufei Mao, Panlong Yang, Caimei Wang
{"title":"Lightitude: Indoor Positioning Using Ubiquitous Visible Lights and COTS Devices","authors":"Yiqing Hu, Yan Xiong, Wenchao Huang, Xiangyang Li, Yanan Zhang, Xufei Mao, Panlong Yang, Caimei Wang","doi":"10.1109/ICDCS.2015.82","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel indoor localization scheme, Lightitude, by exploiting ubiquitous visible lights, which are necessarily and densely deployed in almost all indoor environments. Different from existing positioning systems that exploit special LEDs, ubiquitous visible lights lack fingerprints that can uniquely identify the light source, which results in an ambiguity problem that an RLS may correspond to multiple candidate positions. Moreover, received light strength (RLS) is not only determined by device's position, but also seriously affected by its orientation, which causes great complexity in site-survey. To address these challenges, we first propose and validate a realistic light strength model to avoid the expensive site-survey, then harness user's mobility to generate spatial-related RLS to tackle single RLS's position-ambiguity problem. Experiment results show that Lightitude achieves mean accuracy 1.93m and 2.24m in office (720m2) and library scenario (960m2) respectively.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 35th International Conference on Distributed Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2015.82","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
In this paper, we propose a novel indoor localization scheme, Lightitude, by exploiting ubiquitous visible lights, which are necessarily and densely deployed in almost all indoor environments. Different from existing positioning systems that exploit special LEDs, ubiquitous visible lights lack fingerprints that can uniquely identify the light source, which results in an ambiguity problem that an RLS may correspond to multiple candidate positions. Moreover, received light strength (RLS) is not only determined by device's position, but also seriously affected by its orientation, which causes great complexity in site-survey. To address these challenges, we first propose and validate a realistic light strength model to avoid the expensive site-survey, then harness user's mobility to generate spatial-related RLS to tackle single RLS's position-ambiguity problem. Experiment results show that Lightitude achieves mean accuracy 1.93m and 2.24m in office (720m2) and library scenario (960m2) respectively.