MeshMap: A Magnetic Field-Based Indoor Navigation System with Crowdsourcing Support

Lina Chen, Jinbin Wu, Chen Yang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

In this paper, a new indoor navigation system-MeshMap is put forward based on the magnetic fields and crowdsourcing. It only needs the users to have a smart phone for easy indoor navigation. Compared with the RFID, Bluetooth and WiFi-based approaches, it does not require pre-deployed infrastructure, has wide applications and low cost, and is not prone to be influenced by the occlusions of human bodies and other barriers. Thus MeshMap can be highly stable and cost-effective. The proposed approach includes two important techniques: 1) crowdsourcing is adopted to construct a global magnetic fingerprints database, which used to require huge efforts, by merging sensor data from multiple users' different paths; 2) a dynamic time warping based matching algorithm is proposed to realize the magnetic field time serial matching and position correction, considering different users' walking behaviors, magnetic abnormal positions, corners, etc. Implementation and testing have proved that MeshMap can realize real-time positioning and navigation. Testing results show that the space error of the navigation can be controlled within 2 meters in the 70 percentage of the time and within 4 meters in the 95 percentage of the time.

Original languageEnglish
Article number9001013
Pages (from-to)39959-39970
Number of pages12
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020

Keywords

  • Indoor navigation
  • crowdsourcing
  • magnetic field
  • map construction
  • mobile applications
  • multi-sensors

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