Indoor localization for IoT applications using fingerprinting

Fonseka, P; Sandrasegaran, K

Indoor localization for IoT applications using fingerprinting

Fonseka, P Sandrasegaran, K

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Publication Type:: Conference Proceeding
Citation:: IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings, 2018, 2018-January pp. 736 - 741
Issue Date:: 2018-05-04

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Field	Value	Language
dc.contributor.author	Fonseka, P	en_US
dc.contributor.author	Sandrasegaran, K https://orcid.org/0000-0003-1270-5756	en_US
dc.date.available	2020-05-25T19:15:09Z
dc.date.issued	2018-05-04	en_US
dc.identifier.citation	IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings, 2018, 2018-January pp. 736 - 741	en_US
dc.identifier.isbn	9781467399449	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127213
dc.description.abstract	© 2018 IEEE. Fingerprinting method is one of the preferred method used for indoor localization using Wi-Fi signals because of its low complexity and its cost effectiveness. This paper proposes an indoor localization algorithm using fingerprinting method that is suitable for an indoor IoT application. The proposed algorithm combines the location estimates from two different approaches, deterministic and probabilistic, to estimate the target location. The proposed algorithm was tested for different conditions: Stationary and moving IoT targets, line-of-sight and non-line-of-sight indoor environments. The results showed the proposed combined algorithm performed better in terms of localization accuracy, precision and robustness than deterministic and probabilistic methods individually and similar past research.	en_US
dc.relation.ispartof	IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings	en_US
dc.relation.isbasedon	10.1109/WF-IoT.2018.8355105	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Indoor localization for IoT applications using fingerprinting	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-January	en_US
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US
pubs.volume	2018-January	en_US

Abstract:

© 2018 IEEE. Fingerprinting method is one of the preferred method used for indoor localization using Wi-Fi signals because of its low complexity and its cost effectiveness. This paper proposes an indoor localization algorithm using fingerprinting method that is suitable for an indoor IoT application. The proposed algorithm combines the location estimates from two different approaches, deterministic and probabilistic, to estimate the target location. The proposed algorithm was tested for different conditions: Stationary and moving IoT targets, line-of-sight and non-line-of-sight indoor environments. The results showed the proposed combined algorithm performed better in terms of localization accuracy, precision and robustness than deterministic and probabilistic methods individually and similar past research.

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http://hdl.handle.net/10453/127213