Simplified Indoor Localization Using Bluetooth Beacons and Received Signal Strength Fingerprinting with Smartwatch

被引:6
|
作者
Bouse, Leana [1 ,2 ]
King, Scott A. [1 ,2 ]
Chu, Tianxing [1 ,3 ]
机构
[1] Texas A&M Univ, Dept Comp Sci, 6300 Ocean Dr, Corpus Christi, TX 78412 USA
[2] Texas A&M Univ, Innovat Comp Res, 6300 Ocean Dr, Corpus Christi, TX 78412 USA
[3] Texas A&M Univ, Conrad Blucher Inst Surveying & Sci, 6300 Ocean Dr, Corpus Christi, TX 78412 USA
关键词
indoor tracking; Bluetooth Low Energy; smartwatch; mobile tracking; indoor positioning systems; TRACKING SYSTEM; RECOGNITION;
D O I
10.3390/s24072088
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Variations in Global Positioning Systems (GPSs) have been used for tracking users' locations. However, when location tracking is needed for an indoor space, such as a house or building, then an alternative means of precise position tracking may be required because GPS signals can be severely attenuated or completely blocked. In our approach to indoor positioning, we developed an indoor localization system that minimizes the amount of effort and cost needed by the end user to put the system to use. This indoor localization system detects the user's room-level location within a house or indoor space in which the system has been installed. We combine the use of Bluetooth Low Energy beacons and a smartwatch Bluetooth scanner to determine which room the user is located in. Our system has been developed specifically to create a low-complexity localization system using the Nearest Neighbor algorithm and a moving average filter to improve results. We evaluated our system across a household under two different operating conditions: first, using three rooms in the house, and then using five rooms. The system was able to achieve an overall accuracy of 85.9% when testing in three rooms and 92.106% across five rooms. Accuracy also varied by region, with most of the regions performing above 96% accuracy, and most false-positive incidents occurring within transitory areas between regions. By reducing the amount of processing used by our approach, the end-user is able to use other applications and services on the smartwatch concurrently.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] Measurement Fusion of Connectivity and Received Signal Strength for Indoor Localization and Tracking
    Kim, Hyowon
    Kim, Sunwoo
    2016 IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS WIRELESS BROADBAND (ICUWB2016), 2016,
  • [32] Improved Fingerprinting Localization with Connected Component Labeling Based on Received Signal Strength
    Abdelghani, Belaabed
    Gao, Qiang
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON PROGRESS IN INFORMATICS AND COMPUTING (PIC), VOL 1, 2016, : 198 - 204
  • [33] Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting
    Husen, Mohd Nizam
    Lee, Sukhan
    SENSORS, 2016, 16 (11):
  • [34] Multi-Band Received Signal Strength Fingerprinting Based Indoor Location System
    Sertthin, Chinnapat
    Fujii, Takeo
    Ohtsuki, Tomoaki
    Nakagawa, Masao
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2010, E93B (08) : 1993 - 2003
  • [35] A NOVEL INDOOR LOCALIZATION METHOD BASED ON RECEIVED SIGNAL STRENGTH USING DISCRETE FOURIER TRANSFORM
    Zhang, Minghua
    Zhang, Shensheng
    Cao, Jian
    Mei, Haibin
    2006 FIRST INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND NETWORKING IN CHINA, 2006,
  • [36] Hybrid Kernel Based Machine Learning Using Received Signal Strength Measurements for Indoor Localization
    Yan, Jun
    Zhao, Lin
    Tang, Jian
    Chen, Yuwei
    Chen, Ruizhi
    Chen, Liang
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (03) : 2824 - 2829
  • [37] IMLours: Indoor Mapping and Localization Using Time-stamped WLAN Received Signal Strength
    Zhou, Mu
    Zhang, Qiao
    Tian, Zengshan
    Xu, Kunjie
    Qiu, Feng
    Wu, Haibo
    2015 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2015, : 1817 - 1822
  • [38] A method of fingerprint indoor localization based on received signal strength difference by using compressive sensing
    Xiao-min Yu
    Hui-qiang Wang
    Jin-qiu Wu
    EURASIP Journal on Wireless Communications and Networking, 2020
  • [39] IMLours: Indoor Mapping and Localization Using Time-stamped WLAN Received Signal Strength
    Zhou, Mu
    Zhang, Qiao
    Tian, Zengshan
    Xu, Kunjie
    Qiu, Feng
    Wu, Haibo
    2015 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2015, : 1924 - 1929
  • [40] A method of fingerprint indoor localization based on received signal strength difference by using compressive sensing
    Yu, Xiao-min
    Wang, Hui-qiang
    Wu, Jin-qiu
    EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2020, 2020 (01)