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基于模糊逻辑 Type-2 的无线室内定位系统,用于建筑物中视障人士的导航。

Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings.

机构信息

Computer Engineering Department, College of Computer Science and Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.

Faculty of Informatics, Kaunas University of Technology, Kaunas 51386, Lithuania.

出版信息

Sensors (Basel). 2019 May 7;19(9):2114. doi: 10.3390/s19092114.

Abstract

The ability to precisely locate and navigate a partially impaired or a blind person within a building is increasingly important for a wide variety of public safety and localization services. In this paper, we explore indoor localization algorithms using Bluetooth Low Energy (BLE) beacons. We propose using the BLE beacon's received signal strength indication (RSSI) and the geometric distance from the current beacon to the fingerprint point in the framework of fuzzy logic for calculating the Euclidean distance for the subsequent determination of location. According to our results, the fingerprinting algorithm with fuzzy logic type-2 (hesitant fuzzy sets) is fit for use as an indoor localization method with BLE beacons. The average error of localization is only 0.43 m, and the algorithm obtains a navigation precision of 98.2 ± 1%. This precision confirms that the algorithms provide great aid to a visually impaired person in unknown spaces, especially those designed without physical tactile guides, as confirmed by low Fréchet and Hausdorff distance values and high navigation efficiency index (NEI) scores.

摘要

精确定位和导航建筑物内部分受损或失明人员的能力对于各种公共安全和定位服务越来越重要。在本文中,我们探索了使用蓝牙低能(BLE)信标的室内定位算法。我们提出在模糊逻辑框架中使用 BLE 信标的接收信号强度指示(RSSI)和当前信标与指纹点之间的几何距离来计算欧几里得距离,以便随后确定位置。根据我们的结果,具有模糊逻辑类型-2(犹豫模糊集)的指纹算法适合用作具有 BLE 信标的室内定位方法。定位的平均误差仅为 0.43 米,算法的导航精度为 98.2 ± 1%。该精度证实,这些算法为视障人士在未知空间中提供了极大的帮助,特别是那些没有物理触觉引导设计的空间,这一点得到了较低的 Fréchet 和 Hausdorff 距离值以及较高的导航效率指数(NEI)分数的证实。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab9e/6539245/14a51a07b066/sensors-19-02114-g001.jpg

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