Article

The Horus WLAN location determination system

Authors:

Moustafa Youssef,

Ashok AgrawalaAuthors Info & Claims

MobiSys '05: Proceedings of the 3rd international conference on Mobile systems, applications, and services

Pages 205 - 218

https://doi.org/10.1145/1067170.1067193

Published: 06 June 2005 Publication History

Abstract

We present the design and implementation of the Horus WLAN location determination system. The design of the Horus system aims at satisfying two goals: high accuracy and low computational requirements. The Horus system identifies different causes for the wireless channel variations and addresses them to achieve its high accuracy. It uses location-clustering techniques to reduce the computational requirements of the algorithm. The lightweight Horus algorithm helps in supporting a larger number of users by running the algorithm at the clients.We discuss the different components of the Horus system and its implementation under two different operating systems and evaluate the performance of the Horus system on two testbeds. Our results show that the Horus system achieves its goal. It has an error of less than 0.6 meter on the average and its computational requirements are more than an order of magnitude better than other WLAN location determination systems. Moreover, the techniques developed in the context of the Horus system are general and can be applied to other WLAN location determination systems to enhance their accuracy. We also report lessons learned from experimenting with the Horus system and provide directions for future work.

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The Horus WLAN location determination system

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Published In

cover image ACM Conferences

MobiSys '05: Proceedings of the 3rd international conference on Mobile systems, applications, and services

June 2005

278 pages

ISBN:1931971315

DOI:10.1145/1067170

General Chair:
Kang G. Shin
University of Michigan
,
Program Chairs:
David Kotz
Dartmouth College
,
Brian Noble
University of Michigan

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
USENIX Assoc: USENIX Assoc

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Association for Computing Machinery

New York, NY, United States

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Published: 06 June 2005

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MobiSys05: The 3rd International Conference on Mobile Systems, Applications and Services 2005

June 6 - 8, 2005

Washington, Seattle

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https://doi.org/10.3390/s24216876
Esmaeili Gorjan HGil Jiménez V(2024)Improving Indoor WiFi Localization by Using Machine Learning TechniquesSensors10.3390/s2419629324:19(6293)Online publication date: 28-Sep-2024
https://doi.org/10.3390/s24196293
Thorsager MKroeyer STaha AMelgaard MAnil LNielsen JMadsen T(2024)Automated Room-Level Localisation Using Building Plan InformationSensors10.3390/s2417575324:17(5753)Online publication date: 4-Sep-2024
https://doi.org/10.3390/s24175753
Rathnayake DRadhakrishnan MHwang IMisra A(2024)LILOC: Leveraging LiDARs for Accurate 3D Localization in Dynamic Indoor EnvironmentsACM Transactions on Internet of Things10.1145/36958815:4(1-33)Online publication date: 13-Sep-2024
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Hsiao AShen LChang CChiu CFeng K(2024)SALC: Skeleton-Assisted Learning-Based Clustering for Time-Varying Indoor LocalizationIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.330076811:1(439-452)Online publication date: Jan-2024
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