Journal article 838 views
Self-mapping radio maps for location fingerprinting
Wireless Networks
Swansea University Authors: Gareth Ayres , Jason Jones
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DOI (Published version): 10.1007/s11276-014-0864-1
Abstract
Localisation of a mobile device in Wi-Fi based indoor environments has received much attention and is an important area of research, considering the uptake of devices with built-in Wi-Fi and often blanket coverage in enterprise. Most localisation techniques in this area require an off-line calibrati...
Published in: | Wireless Networks |
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ISSN: | 1022-0038 1572-8196 |
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2014
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Online Access: |
Check full text
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URI: | https://cronfa.swan.ac.uk/Record/cronfa20616 |
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2018-06-19T18:50:37Z |
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2018-06-19T15:27:41.7349214 v2 20616 2015-04-10 Self-mapping radio maps for location fingerprinting fe862943cbab3ed08a0b886c6e9e194a 0000-0002-7472-6272 Gareth Ayres Gareth Ayres true false aa4865d48c53a0df1c1547171826eab9 0000-0002-7715-1857 Jason Jones Jason Jones true false 2015-04-10 INFR Localisation of a mobile device in Wi-Fi based indoor environments has received much attention and is an important area of research, considering the uptake of devices with built-in Wi-Fi and often blanket coverage in enterprise. Most localisation techniques in this area require an off-line calibration phase where a radio map is manually built using the laborious efforts of administrators. This radio map is then subject to becoming inaccurate with time and requires refreshing as the equipment is upgraded and replaced. We propose a system that can automatically build and calibrate a radio map for use with location fingerprinting techniques to provide indoor and outdoor localisation with Wi-Fi. This system first uses a self-mapping technique that makes use of user roaming patterns to build a weighted undirected graph of Access Point locations. We then combine this initial map with a map built by users of smartphones with built-in Wi-Fi and GPS to generate anchor nodes. We show that the unique combination of these two techniques provides a zero-configuration calibration map for use with location fingerprinting techniques, which not only saves time and effort in the calibration phase, but provides a constantly fine-tuning and self-healing map. Journal Article Wireless Networks 1022-0038 1572-8196 Wireless Localization Visualization Graph theory Force-directed layout 31 12 2014 2014-12-31 10.1007/s11276-014-0864-1 COLLEGE NANME Digital Infrastructure COLLEGE CODE INFR Swansea University 2018-06-19T15:27:41.7349214 2015-04-10T11:36:01.9105642 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Gareth Ayres 0000-0002-7472-6272 1 Jason Jones 0000-0002-7715-1857 2 |
title |
Self-mapping radio maps for location fingerprinting |
spellingShingle |
Self-mapping radio maps for location fingerprinting Gareth Ayres Jason Jones |
title_short |
Self-mapping radio maps for location fingerprinting |
title_full |
Self-mapping radio maps for location fingerprinting |
title_fullStr |
Self-mapping radio maps for location fingerprinting |
title_full_unstemmed |
Self-mapping radio maps for location fingerprinting |
title_sort |
Self-mapping radio maps for location fingerprinting |
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fe862943cbab3ed08a0b886c6e9e194a aa4865d48c53a0df1c1547171826eab9 |
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fe862943cbab3ed08a0b886c6e9e194a_***_Gareth Ayres aa4865d48c53a0df1c1547171826eab9_***_Jason Jones |
author |
Gareth Ayres Jason Jones |
author2 |
Gareth Ayres Jason Jones |
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Journal article |
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Wireless Networks |
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2014 |
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Swansea University |
issn |
1022-0038 1572-8196 |
doi_str_mv |
10.1007/s11276-014-0864-1 |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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Faculty of Science and Engineering |
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School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering |
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description |
Localisation of a mobile device in Wi-Fi based indoor environments has received much attention and is an important area of research, considering the uptake of devices with built-in Wi-Fi and often blanket coverage in enterprise. Most localisation techniques in this area require an off-line calibration phase where a radio map is manually built using the laborious efforts of administrators. This radio map is then subject to becoming inaccurate with time and requires refreshing as the equipment is upgraded and replaced. We propose a system that can automatically build and calibrate a radio map for use with location fingerprinting techniques to provide indoor and outdoor localisation with Wi-Fi. This system first uses a self-mapping technique that makes use of user roaming patterns to build a weighted undirected graph of Access Point locations. We then combine this initial map with a map built by users of smartphones with built-in Wi-Fi and GPS to generate anchor nodes. We show that the unique combination of these two techniques provides a zero-configuration calibration map for use with location fingerprinting techniques, which not only saves time and effort in the calibration phase, but provides a constantly fine-tuning and self-healing map. |
published_date |
2014-12-31T00:50:38Z |
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1821455195241971712 |
score |
11.064692 |