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Indoor Localization with Passive Sensors.

机译:使用无源传感器进行室内定位。

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摘要

In this thesis, a framework is described that is designed to perform indoor localization in the SmartCondo(TM). A significant aspect of the framework is that it mainly operates on the basis of binary sensors -- including motion sensors and occupancy sensors -- and it primarily involves geometric computations. In addition, switch-type sensors have been incorporated. We have specifically designed and implemented a geometry library to facilitate the necessary computations, as well as a simulation tool to simulate the environment and its sensors. Compared to previous related research work, we adopt a more realistic environment model, as well as models for a person's body, and models for the sensors. In the experiments conducted, when the sensors are assumed to behave in an ideal fashion, we have achieved 67cm and 49cm as mean localization error for minimum coverage and dense coverage sensor configurations respectively. Under a more realistic sensor behavior model the corresponding numbers are 69cm and 62cm respectively.
机译:在本文中,描述了一个框架,该框架旨在在SmartCondo™中执行室内定位。该框架的一个重要方面是,它主要基于二进制传感器(包括运动传感器和占用传感器)进行操作,并且主要涉及几何计算。此外,还集成了开关型传感器。我们专门设计并实现了一个几何库,以方便进行必要的计算,以及一个用于模拟环境及其传感器的仿真工具。与以前的相关研究工作相比,我们采用了更现实的环境模型,人体模型和传感器模型。在进行的实验中,当假设传感器以理想的方式工作时,对于最小覆盖率和密集覆盖率传感器配置,我们分别获得了67cm和49cm的平均定位误差。在更实际的传感器行为模型下,相应的数字分别为69cm和62cm。

著录项

  • 作者单位

    University of Alberta (Canada).;

  • 授予单位 University of Alberta (Canada).;
  • 学科 Computer Science.
  • 学位 M.Sc.
  • 年度 2013
  • 页码 63 p.
  • 总页数 63
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 老年病学;
  • 关键词

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