M. Rossi, J. Seiter, O. Amft, Seraina Buchmeier, G. Tröster
{"title":"RoomSense: an indoor positioning system for smartphones using active sound probing","authors":"M. Rossi, J. Seiter, O. Amft, Seraina Buchmeier, G. Tröster","doi":"10.1145/2459236.2459252","DOIUrl":null,"url":null,"abstract":"We present RoomSense, a new method for indoor positioning using smartphones on two resolution levels: rooms and within-rooms positions. Our technique is based on active sound fingerprinting and needs no infrastructure. Rooms and within-rooms positions are characterized by impulse response measurements. Using acoustic features of the impulse response and pattern classification, an estimation of the position is performed. An evaluation study was conducted to analyse the localization performance of RoomSense. Impulse responses of 67 within-rooms positions from 20 rooms were recorded with the hardware of a smartphone. In total 5360 impulse response measurements were collected. Our evaluation study showed that RoomSense achieves a room-level accuracy of > 98% and a within-rooms positions accuracy of > 96%. Additionally, the implementation of RoomSense as an Android App is presented in detail. The RoomSense App enables to identify an indoor location within one second.","PeriodicalId":407457,"journal":{"name":"International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"66","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2459236.2459252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 66
Abstract
We present RoomSense, a new method for indoor positioning using smartphones on two resolution levels: rooms and within-rooms positions. Our technique is based on active sound fingerprinting and needs no infrastructure. Rooms and within-rooms positions are characterized by impulse response measurements. Using acoustic features of the impulse response and pattern classification, an estimation of the position is performed. An evaluation study was conducted to analyse the localization performance of RoomSense. Impulse responses of 67 within-rooms positions from 20 rooms were recorded with the hardware of a smartphone. In total 5360 impulse response measurements were collected. Our evaluation study showed that RoomSense achieves a room-level accuracy of > 98% and a within-rooms positions accuracy of > 96%. Additionally, the implementation of RoomSense as an Android App is presented in detail. The RoomSense App enables to identify an indoor location within one second.