{"title":"A map framework using crowd-sourced data for indoor positioning and navigation","authors":"Thomas Graichen, Erik Gruschka, U. Heinkel","doi":"10.1109/IWMN.2017.8078395","DOIUrl":null,"url":null,"abstract":"In this paper, we present a framework for indoor positioning and navigation purposes. This framework uses crowd-sourced OpenStreetMap (OSM) data for rendering combined outdoor and indoor maps, for the calculation of navigation routes as well as for the correction of indoor positioning algorithms. Based on six general requirements, which we formulate and explain in this paper, the architecture and realization of this framework was designed. Finally, we show that, with the help of this framework, future indoor positioning applications can be developed in a time-efficient and reliable way.","PeriodicalId":201479,"journal":{"name":"2017 IEEE International Workshop on Measurement and Networking (M&N)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Workshop on Measurement and Networking (M&N)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWMN.2017.8078395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, we present a framework for indoor positioning and navigation purposes. This framework uses crowd-sourced OpenStreetMap (OSM) data for rendering combined outdoor and indoor maps, for the calculation of navigation routes as well as for the correction of indoor positioning algorithms. Based on six general requirements, which we formulate and explain in this paper, the architecture and realization of this framework was designed. Finally, we show that, with the help of this framework, future indoor positioning applications can be developed in a time-efficient and reliable way.
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