Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2016

Abstract

In this work, we propose RAD, a RApid Deployment localization framework without human sampling. The basic idea of RAD is to automatically generate a fingerprint database through space partition, of which each cell is fingerprinted by its maximum influence APs. Based on this robust location indicator, fine-grained localization can be achieved by a discretized particle filter utilizing sensor data fusion. We devise techniques for CIVD-based field division, graph-based particle filter, EM-based individual character learning, and build a prototype that runs on commodity devices. Extensive experiments show that RAD provides a comparable performance to the state-of-the-art RSSbased methods while relieving it of prior human participation.

Keywords

Localization, Field Division, Smart Phone

Discipline

Digital Communications and Networking | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 41st IEEE Conference on Local Computer Networks, Dubai, United Arab Emirates, 2016 November 7-10

First Page

547

Last Page

550

Identifier

10.1109/LCN.2016.89

Publisher

IEEE

City or Country

Dubai, UAE

Additional URL

https://doi.org/10.1109/LCN.2016.89

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