Smartphone-based indoor pedestrian tracking using geo-magnetic observations

被引:15
|
作者
Lee, Sungnam [1 ]
Chon, Yohan [1 ]
Cha, Hojung [1 ]
机构
[1] Yonsei Univ, Dept Comp Sci, Seoul 120749, South Korea
基金
新加坡国家研究基金会;
关键词
Indoor localization system; unconstrained device placements; infrastructure-free; SYSTEM;
D O I
10.1155/2013/295838
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the widespread use of smartphones, the use of location-based services (LBS) with smartphones has become an active research issue. The accurate measurement of user location is necessary to provide LBS. While outdoor locations are easily obtained with GPS, indoor location information is difficult to acquire. Previous work on indoor location tracking systems often relied on infrastructures that are influenced by environmental changes and temporal differences. Several studies have proposed infrastructure-less systems that are independent of the surroundings, but these works generally required non-trivial computation time or energy costs. In this paper, we propose an infrastructure-less pedestrian tracking system in indoor environments. The system uses accelerometers and magnetic sensors in smartphones without pre-installed infrastructure. We reduced the cumulative error of location tracking by geo-magnetic observations at corners and spots with magnetic fluctuations. In addition, we developed a robust estimation model that is tolerant to false positives, as well as a mobility model that reflects the characteristics of multiple sensors. Extensive evaluation in a real environment indicates that our system is accurate and cost-effective.
引用
收藏
页码:123 / 137
页数:15
相关论文
共 50 条
  • [41] Smartphone-based Distracted Pedestrian Localization using Bluetooth Low Energy Beacons
    Hasan, Raiful
    Hoque, Mohammad Aminul
    Karim, Yasser
    Griffin, Russell
    Schwebel, David
    Hasan, Ragib
    [J]. IEEE SOUTHEASTCON 2020, 2020,
  • [42] Pedestrian Indoor Positioning and Tracking using Smartphone Sensors, Step Detection and Map Matching Algorithm
    Ilkovicova, Lubica
    Kajanek, Pavol
    Kopacik, Alojz
    [J]. GEODETSKI LIST, 2016, 70 (01) : 1 - 24
  • [43] Smartphone-Based Real-Time Indoor Location Tracking With 1-m Precision
    Liang, Po-Chou
    Krause, Paul
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2016, 20 (03) : 756 - 762
  • [44] Self-Contained Indoor Pedestrian Navigation Using Smartphone Sensors and Magnetic Features
    Li, You
    Zhuang, Yuan
    Lan, Haiyu
    Zhang, Peng
    Niu, Xiaoji
    El-Sheimy, Naser
    [J]. IEEE SENSORS JOURNAL, 2016, 16 (19) : 7173 - 7182
  • [45] Validating a Smartphone-Based Pedestrian Navigation System Prototype An Informal Eye-Tracking Pilot Test
    Kluge, Mario
    Asche, Hartmut
    [J]. COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2012, PT II, 2012, 7334 : 386 - 396
  • [46] Smartphone-Based Cooperative Indoor Localization with RFID Technology
    Seco, Fernando
    Jimenez, Antonio R.
    [J]. SENSORS, 2018, 18 (01)
  • [47] A New Smartphone-based Indoor GPS Positioning System
    Xu, Rui
    Chen, Wu
    Yang, Yang
    Liu, Jianye
    Li, Rongbin
    [J]. PROCEEDINGS OF THE 29TH INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS+ 2016), 2016, : 1838 - 1842
  • [48] Smartphone-based Wi-Fi Pedestrian-Tracking System Tolerating the RSS Variance Problem
    Kim, Yungeun
    Shin, Hyojeong
    Cha, Hojung
    [J]. 2012 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS (PERCOM), 2012, : 11 - 19
  • [49] Eye Tracking Using Built-in Camera for Smartphone-based HMD
    Hakoda, Hiroyuki
    Yamada, Wataru
    Manabe, Hiroyuki
    [J]. UIST'17 ADJUNCT: ADJUNCT PUBLICATION OF THE 30TH ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY, 2017, : 15 - 16
  • [50] Smartphone-Based 3D Indoor Pedestrian Positioning through Multi-Modal Data Fusion
    Zhao, Hongyu
    Cheng, Wanli
    Yang, Ning
    Qiu, Sen
    Wang, Zhelong
    Wang, Jianjun
    [J]. SENSORS, 2019, 19 (20)