{"title":"Design and implementation of indoor positioning system based on iBeacon","authors":"Xiangjie Li, Dan Xu, Xuzhi Wang, Rizwan Muhammad","doi":"10.1109/ICALIP.2016.7846648","DOIUrl":null,"url":null,"abstract":"With the rapid increase in data and multimedia services, demand for positioning has increased especially in complex indoor environment which often needs to determine the location information of the mobile terminal. There is a lack of accuracy and robustness in current indoor positioning system. This paper designs and implements an indoor positioning system based on iBeacon. We adopt Gaussian filter and Unscented Kalman filter method to robustly extract strong signals from iBeacon device. With the extracted signals, we compared them with-in database. The goal of this paper is to design and implement a mobile-based indoor location system which has the mobile applications with the Bluetooth Low Energy technology based on the iBeacon. Using a mobile terminal our system can show position results. Moreover, our system can run on both Android systems and IOS ones. Our method has better performance compared with WiFi method. The experimental results demonstrates that the error is only within 4 meters and our system can achieve accurate and robust positioning.","PeriodicalId":184170,"journal":{"name":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Audio, Language and Image Processing (ICALIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALIP.2016.7846648","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
With the rapid increase in data and multimedia services, demand for positioning has increased especially in complex indoor environment which often needs to determine the location information of the mobile terminal. There is a lack of accuracy and robustness in current indoor positioning system. This paper designs and implements an indoor positioning system based on iBeacon. We adopt Gaussian filter and Unscented Kalman filter method to robustly extract strong signals from iBeacon device. With the extracted signals, we compared them with-in database. The goal of this paper is to design and implement a mobile-based indoor location system which has the mobile applications with the Bluetooth Low Energy technology based on the iBeacon. Using a mobile terminal our system can show position results. Moreover, our system can run on both Android systems and IOS ones. Our method has better performance compared with WiFi method. The experimental results demonstrates that the error is only within 4 meters and our system can achieve accurate and robust positioning.