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An Indoor Positioning System Based on Wearables for Ambient-Assisted Living

机译:基于可穿戴设备的室内辅助环境定位系统

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摘要

The urban population is growing at such a rate that by 2050 it is estimated that 84% of the world’s population will live in cities, with flats being the most common living place. Moreover, WiFi technology is present in most developed country urban areas, with a quick growth in developing countries. New Ambient-Assisted Living applications will be developed in the near future having user positioning as ground technology: elderly tele-care, energy consumption, security and the like are strongly based on indoor positioning information. We present an indoor positioning system for wearable devices based on WiFi fingerprinting. Smart-watch wearable devices are used to acquire the WiFi strength signals of the surrounding Wireless Access Points used to build an ensemble of Machine Learning classification algorithms. Once built, the ensemble algorithm is used to locate a user based on the WiFi strength signals provided by the wearable device. Experimental results for five different urban flats are reported, showing that the system is robust and reliable enough for locating a user at room level into his/her home. Another interesting characteristic of the presented system is that it does not require deployment of any infrastructure, and it is unobtrusive, the only device required for it to work is a smart-watch.
机译:城市人口的增长速度到了2050年,据估计,全世界84%的人口将居住在城市中,而公寓是最常见的居住地。此外,WiFi技术存在于大多数发达国家的城市地区,并在发展中国家迅速增长。在不久的将来,将开发新的环境辅助生活应用程序,将用户定位作为地面技术:老年人远程护理,能耗,安全性等将强烈基于室内定位信息。我们提出了一种基于WiFi指纹的可穿戴设备室内定位系统。智能手表可穿戴设备用于获取周围无线接入点的WiFi强度信号,这些信号用于构建机器学习分类算法的集合。建立后,集成算法将根据可穿戴设备提供的WiFi强度信号来定位用户。报告了五个不同城市单位的实验结果,表明该系统足够强大且可靠,足以将房间水平的用户安置在他/她的家中。所提出的系统的另一个有趣的特征是它不需要部署任何基础结构,并且不引人注目,其工作所需的唯一设备是智能手表。

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