Peer-to-Peer Indoor Navigation Using Smartphones

Most of existing indoor navigation systems work in a client/server manner, which needs to deploy comprehensive localization services together with precise indoor maps a prior. In this paper, we design and realize a peer-to-peer navigation system (ppNav), on smartphones, which enables the fast-to-deploy navigation services, avoiding the requirements of pre-deployed location services and detailed floorplans. ppNav navigates a user to the destination by tracking user mobility, promoting timely walking tips and alerting potential deviations, according to a previous traveller’s trace experience. Specifically, we utilize the ubiquitous WiFi fingerprints in a novel diagrammed form and extract both radio and visual features of the diagram to track relative locations and exploit fingerprint similarity trend for deviation detection. We further devise techniques to lock on a user to the nearest reference path in case he/she arrives at an uncharted place. Consolidating these techniques, we implement ppNav on commercial mobile devices and validate its performance in real environments. Our results show that ppNav achieves delightful performance, with an average relative error of 0.9 m in trace tracking and a maximum delay of nine samples (about 4.5 s) in deviation detection.

[1]  Peter A. Dinda,et al.  Indoor localization without infrastructure using the acoustic background spectrum , 2011, MobiSys '11.

[2]  Sachin Katti,et al.  WiDeo: Fine-grained Device-free Motion Tracing using RF Backscatter , 2015, NSDI.

[3]  Yunhao Liu,et al.  Enhancing wifi-based localization with visual clues , 2015, UbiComp.

[4]  Yunhao Liu,et al.  Smartphones Based Crowdsourcing for Indoor Localization , 2015, IEEE Transactions on Mobile Computing.

[5]  Jie Yang,et al.  Push the limit of WiFi based localization for smartphones , 2012, Mobicom '12.

[6]  Mo Li,et al.  Use it free: instantly knowing your phone attitude , 2014, MobiCom.

[7]  Nicholas A. Giudice,et al.  Indoor magnetic navigation for the blind , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  Moustafa Youssef,et al.  Handling samples correlation in the Horus system , 2004, IEEE INFOCOM 2004.

[9]  Gang Wang,et al.  I am the antenna: accurate outdoor AP location using smartphones , 2011, MobiCom '11.

[10]  Yunhao Liu,et al.  Mobility Increases Localizability , 2015, ACM Comput. Surv..

[11]  Chunming Qiao,et al.  Rise of the Indoor Crowd: Reconstruction of Building Interior View via Mobile Crowdsourcing , 2015, SenSys.

[12]  Jiming Chen,et al.  Last-Mile Navigation Using Smartphones , 2015, MobiCom.

[13]  Yunhao Liu,et al.  Incentives for Mobile Crowd Sensing: A Survey , 2016, IEEE Communications Surveys & Tutorials.

[14]  Ramesh Govindan,et al.  Energy-efficient positioning for smartphones using Cell-ID sequence matching , 2011, MobiSys '11.

[15]  Anshul Rai,et al.  Zee: zero-effort crowdsourcing for indoor localization , 2012, Mobicom '12.

[16]  Agata Brajdic,et al.  Walk detection and step counting on unconstrained smartphones , 2013, UbiComp.

[17]  Paul Congdon,et al.  Avoiding multipath to revive inbuilding WiFi localization , 2013, MobiSys '13.

[18]  Xi Fang,et al.  Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing , 2012, Mobicom '12.

[19]  Guobin Shen,et al.  Walkie-Markie: Indoor Pathway Mapping Made Easy , 2013, NSDI.

[20]  Robert P. Dick,et al.  Hallway based automatic indoor floorplan construction using room fingerprints , 2013, UbiComp.

[21]  Yunhao Liu,et al.  From RSSI to CSI , 2013, ACM Comput. Surv..

[22]  Xinbing Wang,et al.  Performance Analysis of RSS Fingerprinting Based Indoor Localization , 2017, IEEE Transactions on Mobile Computing.

[23]  Moustafa Youssef,et al.  No need to war-drive: unsupervised indoor localization , 2012, MobiSys '12.

[24]  Sachin Katti,et al.  SpotFi: Decimeter Level Localization Using WiFi , 2015, SIGCOMM.

[25]  Yin Chen,et al.  FM-based indoor localization , 2012, MobiSys '12.

[26]  Xinbing Wang,et al.  HiQuadLoc: A RSS Fingerprinting Based Indoor Localization System for Quadrotors , 2017, IEEE Transactions on Mobile Computing.

[27]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[28]  Eckehard Steinbach,et al.  Graph-based data fusion of pedometer and WiFi measurements for mobile indoor positioning , 2014, UbiComp.

[29]  Yunhao Liu,et al.  Decimeter level passive tracking with wifi , 2016, HotWireless@MobiCom.

[30]  Swarun Kumar,et al.  Decimeter-Level Localization with a Single WiFi Access Point , 2016, NSDI.

[31]  Kang G. Shin,et al.  EchoTag: Accurate Infrastructure-Free Indoor Location Tagging with Smartphones , 2015, MobiCom.

[32]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[33]  Mingyan Liu,et al.  Static power of mobile devices: Self-updating radio maps for wireless indoor localization , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[34]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[35]  Azeem J. Khan,et al.  Barometric phone sensors: more hype than hope! , 2014, HotMobile.

[36]  Peter Brida,et al.  Rank based fingerprinting algorithm for indoor positioning , 2011, 2011 International Conference on Indoor Positioning and Indoor Navigation.

[37]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[38]  Venkata N. Padmanabhan,et al.  Indoor localization without the pain , 2010, MobiCom.

[39]  Mo Li,et al.  Travi-Navi: Self-Deployable Indoor Navigation System , 2017, TNET.

[40]  P. Holland,et al.  Robust regression using iteratively reweighted least-squares , 1977 .

[41]  Jue Wang,et al.  Dude, where's my card?: RFID positioning that works with multipath and non-line of sight , 2013, SIGCOMM.

[42]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[43]  Jie Liu,et al.  A realistic evaluation and comparison of indoor location technologies: experiences and lessons learned , 2015, IPSN.

[44]  Feng Zhao,et al.  A reliable and accurate indoor localization method using phone inertial sensors , 2012, UbiComp.