ppNav: Peer-to-Peer Indoor Navigation for 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, named ppNav, on smartphones, which enables the fast-t...

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Bibliographic Details
Main Authors: Zuwei Yin, Chenshu Wu, Zheng Yang, Lane, Nicholas, Yunhao Liu
Format: Conference Proceeding
Language:English
Subjects:
Feature extraction
IEEE 802.11 Standard
indoor navigation
Legged locomotion
Navigation
peer-to-peer
sequential fingerprints
Synchronization
Visualization
Online Access:Request full text
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Summary: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, named 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. 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 0.9m in trace tracking and a maximum delay of 9 samples (about 4.5s) in deviation detection.
ISSN:1521-9097
2690-5965
DOI:10.1109/ICPADS.2016.0023