Demonstration abstract: Crowdsourced indoor localization and navigation with Anyplace

L. Petrou, Georgios Larkou, C. Laoudias, D. Zeinalipour-Yazti, C. Panayiotou
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引用次数: 24

Abstract

In this demonstration paper, we present the Anyplace system that relies on the abundance of sensory data on smartphones (e.g., WiFi signal strength and inertial measurements) to deliver reliable indoor geolocation information. Our system features two highly desirable properties, namely crowdsourcing and scalability. Anyplace implements a set of crowdsourcing-supportive mechanisms to handle the enormous amount of crowdsensed data, filter incorrect user contributions and exploit WiFi data from heterogeneous mobile devices. Moreover, Anyplace follows a big-data architecture for efficient and scalable storage and retrieval of localization and mapping data.
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演示摘要:基于Anyplace的众包室内定位与导航
在这篇演示论文中,我们展示了Anyplace系统,该系统依赖于智能手机上丰富的感官数据(例如WiFi信号强度和惯性测量)来提供可靠的室内地理位置信息。我们的系统具有两个非常理想的特性,即众包和可扩展性。Anyplace实现了一套支持众包的机制来处理海量的众包数据,过滤不正确的用户贡献,并利用来自异构移动设备的WiFi数据。此外,Anyplace遵循大数据架构,用于高效、可扩展的存储和检索本地化和地图数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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