Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

1-2020

Abstract

In spite of many advances in indoor localization techniques, practical implementation of robust device independent, server-side Wi-Fi localization (i.e., without any active participation of client devices) remains a challenge. This work utilizes an operationally-deployed Wi-Fi based indoor location infrastructure, based on the classical RADAR algorithm, to tackle two such practical challenges: (a) low cardinality, whereby only the associated AP generates sufficient RSSI reports and (b) outlier identification, which requires explicit identification of mobile clients that are attached to the Wi-Fi network but outside the fingerprinted region. To tackle the low-cardinality problem, we present a technique that uses cardinality changes to demarcate periods of stationary behaviour, and then augment the RSSI reports with useful but apparently “stale” RSSI readings from neighbouring APs. To tackle the filtering of clients with outlier locations, we propose a model that combines a weighted path-loss propagation model with a Voronoi tessellation of the fingerprint map to define suitable boundary values for RSSI readings. We experimentally show how these two approaches improve the stability and robustness of location tracking, and consequently, the accuracy of overall occupancy estimation.

Keywords

location based services, WLAN network measurements

Discipline

Computer Sciences | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

2020 International Conference on COMmunication Systems & NETworkS COMSNET: January 7-11, Bengaluru, India: Proceedings

First Page

192

Last Page

199

ISBN

9781728131870

Identifier

10.1109/COMSNETS48256.2020.9027304

Publisher

IEEE

City or Country

Piscataway, NJ

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/COMSNETS48256.2020.9027304

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