Indoor Localization Accuracy of Major Smartphone Location Apps

被引:0
|
作者
Moayeri, Nader [1 ]
Li, Chang [1 ]
Shi, Lu [1 ]
机构
[1] NIST, Gaithersburg, MD 20899 USA
关键词
indoor localization; smartphone apps; location apps; accuracy; Android; Fused Location Provider (FLP); iOS; Core Location; E911; PerfLoc Prize Competition; ISO/IEC; 18305;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
NIST carried out comprehensive testing in five large buildings to compare the accuracies of Fused Location Provider (FLP) Application Programming Interface (API) for Android phones and Core Location running on iPhones. The testing was done under various mobility modes using the performance metrics provided in the international standard ISO/IEC 18305. This paper presents the results of these evaluations for horizontal, vertical, and 3D errors. Even though in some cases and respects Core Location is better than FLP, it can be said that overall FLP has better accuracy than Core Location, at least in the buildings we used for testing. While Core Location consistently provides location estimates at a fast rate, FLP provides location estimates at a slower rate and sometimes it does not provide elevation information. The paper also compares the accuracy of FLP with that of the best Android app that won the PerfLoc Prize Competition organized by NIST for development of Android indoor localization apps.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Concept for building a smartphone based indoor localization system
    Willemsen, Thomas
    Keller, Friedrich
    Sternberg, Harald
    2014 17TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2014,
  • [22] Enhancing Smartphone Indoor Localization via Opportunistic Sensing
    Liu, Kaikai
    Wu, Di
    Li, Xiaolin
    2016 13TH ANNUAL IEEE INTERNATIONAL CONFERENCE ON SENSING, COMMUNICATION, AND NETWORKING (SECON), 2016, : 243 - 251
  • [23] Smartphone Indoor Localization by Photo-taking of the Environment
    Gao, Ruipeng
    Ye, Fan
    Wang, Tao
    2014 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2014, : 2599 - 2604
  • [24] Indoor localization and navigation using smartphone sensory data
    Hsu, Hui-Huang
    Chang, Jung-Kuei
    Peng, Wei-Jan
    Shih, Timothy K.
    Pai, Tun-Wen
    Man, Ka Lok
    ANNALS OF OPERATIONS RESEARCH, 2018, 265 (02) : 187 - 204
  • [25] Indoor Smartphone Localization Based on LOS and NLOS Identification
    Jo, Hyeon Jeong
    Kim, Seungku
    SENSORS, 2018, 18 (11)
  • [26] Multi-Modal Probabilistic Indoor Localization on a Smartphone
    Dumbgen, Frederike
    Oeschger, Cynthia
    Kolundzija, Mihailo
    Scholefield, Adam
    Girardin, Emmanuel
    Leuenberger, Johan
    Ayer, Serge
    2019 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 2019,
  • [27] Accuracy of Fitbit Surge and Smartphone Apps at Measuring Cycling Distance and Speed
    Gamez, Jose L.
    Figueroa, Ivan A.
    Funk, Merrill D.
    MEDICINE AND SCIENCE IN SPORTS AND EXERCISE, 2018, 50 (05): : 300 - 300
  • [28] Hybrid Indoor Location to Dominate Billion Unit Smartphone Market
    Drubin, Cliff
    MICROWAVE JOURNAL, 2013, 56 (10) : 59 - 59
  • [29] Enhancing Indoor Smartphone Location Acquisition using Floor Plans
    Rajagopal, Niranjini
    Lazik, Patrick
    Pereira, Nuno
    Chayapathy, Sindhura
    Sinopoli, Bruno
    Rowe, Anthony
    2018 17TH ACM/IEEE INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN), 2018, : 278 - 289
  • [30] Smartphone-based User Location Tracking in Indoor Environment
    Viet-Cuong Ta
    Vaufreydaz, Dominique
    Trung-Kien Dao
    Castelli, Eric
    2016 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 2016,