The SkyLoc Floor Localization System

Alex Varshavsky, A. LaMarca, Jeffrey Hightower, E. D. Lara
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引用次数: 108

Abstract

When a mobile user dials 911, a key to arriving to the emergency scene promptly is knowing the location of the mobile user. This paper presents SkyLoc, a GSM fingerprinting-based localization system that runs on a mobile phone and identifies the current floor of a user in tall multi-floor buildings. Knowing the floor in a tall building significantly reduces the area that emergency service personnel have to canvas to locate the individuals in need. We evaluated our system in three multi-floor buildings located in Washington DC, Seattle and Toronto. Our system identifies the floor correctly in up to 73% of the cases and is within 2 floors in 97% of the cases. The system is robust as it works for different network operators, when the training and testing sets were collected with different hardware and up to one month apart. In addition, we show that feature selection techniques that select a subset of highly relevant radio sources for fingerprint matching nearly double the localization accuracy of our system
SkyLoc楼层定位系统
当移动用户拨打911时,及时到达紧急现场的关键是知道移动用户的位置。本文介绍了一种基于GSM指纹识别的定位系统SkyLoc,该系统可以在手机上识别高层建筑中用户的当前楼层。了解高层建筑的楼层大大减少了紧急服务人员寻找有需要的人的区域。我们在位于华盛顿特区、西雅图和多伦多的三栋多层建筑中评估了我们的系统。我们的系统在高达73%的情况下正确识别楼层,在97%的情况下在两层以内。当训练集和测试集是用不同的硬件收集的,并且间隔长达一个月时,该系统可以适用于不同的网络运营商,因此具有很强的鲁棒性。此外,我们表明,选择高度相关的无线源子集进行指纹匹配的特征选择技术几乎使我们的系统的定位精度提高了一倍
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