Accuracy analysis of BLE beacon-based localization in smart buildings

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Ambient Intelligence and Smart Environments Pub Date : 2021-01-01 DOI:10.3233/AIS-210607
R. Ivanov
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引用次数: 1

Abstract

The majority of services that deliver personalized content in smart buildings require accurate localization of their clients. This article presents an analysis of the localization accuracy using Bluetooth Low Energy (BLE) beacons. The aim is to present an approach to create accurate Indoor Positioning Systems (IPS) using algorithms that can be implemented in real time on platforms with low computing power. Parameters on which the localization accuracy mostly depends are analyzed: localization algorithm, beacons’ density, deployment strategy, and noise in the BLE channels. An adaptive algorithm for pre-processing the signals from the beacons is proposed, which aims to reduce noise in beacon’s data and to capture visitor’s dynamics. The accuracy of five range-based localization algorithms in different use case scenarios is analyzed. Three of these algorithms are specially designed to be less sensitive to noise in radio channels and require little computing power. Experiments conducted in a simulated and real environment show that using proposed algorithms the localization accuracy less than 1 m can be obtained.
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智能建筑中基于BLE信标的定位精度分析
在智能建筑中提供个性化内容的大多数服务都需要对其客户进行准确的定位。本文对低功耗蓝牙信标的定位精度进行了分析。目的是提出一种使用算法创建精确的室内定位系统(IPS)的方法,该算法可以在低计算能力的平台上实时实现。分析了定位精度主要依赖的参数:定位算法、信标密度、部署策略、BLE信道噪声。提出了一种自适应的信标信号预处理算法,旨在降低信标数据中的噪声,捕捉游客的动态特征。分析了5种基于距离的定位算法在不同用例场景下的精度。其中三种算法是专门设计的,对无线电信道中的噪声不太敏感,并且需要很少的计算能力。在模拟和真实环境下进行的实验表明,采用该算法可以获得小于1 m的定位精度。
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来源期刊
Journal of Ambient Intelligence and Smart Environments
Journal of Ambient Intelligence and Smart Environments COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
4.30
自引率
17.60%
发文量
23
审稿时长
>12 weeks
期刊介绍: The Journal of Ambient Intelligence and Smart Environments (JAISE) serves as a forum to discuss the latest developments on Ambient Intelligence (AmI) and Smart Environments (SmE). Given the multi-disciplinary nature of the areas involved, the journal aims to promote participation from several different communities covering topics ranging from enabling technologies such as multi-modal sensing and vision processing, to algorithmic aspects in interpretive and reasoning domains, to application-oriented efforts in human-centered services, as well as contributions from the fields of robotics, networking, HCI, mobile, collaborative and pervasive computing. This diversity stems from the fact that smart environments can be defined with a variety of different characteristics based on the applications they serve, their interaction models with humans, the practical system design aspects, as well as the multi-faceted conceptual and algorithmic considerations that would enable them to operate seamlessly and unobtrusively. The Journal of Ambient Intelligence and Smart Environments will focus on both the technical and application aspects of these.
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