Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

8-2016

Abstract

Many emerging applications drive the needs of device-free localization (DfL), in which the target can be localized without any device attached. Because of the ubiquitousness of WiFi infrastructures nowadays, the widely available Received Signal Strength (RSS) information at the WiFi Access points are commonly employed for localization purposes. However, current RSS based DfL systems have one main drawback hindering their real-life applications. That is, the RSS measurements (fingerprints) vary slowly in time even without any change in the environment and frequent updates of RSS at each location lead to a high human labor cost. In this paper, we propose an RSS based low cost DfL system named TafLoc which is able to accurately localize the target over a long time scale. To reduce the amount of human labor cost in updating the RSS fingerprints, TafLoc represents the RSS fingerprints as a matrix which has several unique properties. Based on these properties, we propose a novel fingerprint matrix reconstruction scheme to update the whole fingerprint database with just a few RSS measurements, thus the labor cost is greatly reduced. Extensive experiments illustrate the effectiveness of TafLoc, outperforming the state-of-the-art RSS based DfL systems.

Keywords

Time Adaptive, Fine-grained, Device Free Localization, Received Signal Strength

Discipline

Computer Sciences | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

SIGCOMM '16: Proceedings of the 2016 ACM Conference on Special Interest Group on Data Communication: Florianopolis, Brazil, August 22-26, 2016

First Page

563

Last Page

564

ISBN

9781450341936

Identifier

10.1145/2934872.2959051

Publisher

ACM

City or Country

New York

Additional URL

http://doi.org/10.1145/2934872.2959051

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