Development and optimization of wireless indoor localization error modelling

Yu, Z; Chaczko, Z; Jiang, J

Development and optimization of wireless indoor localization error modelling

Yu, Z Chaczko, Z

Jiang, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 25th International Conference on Systems Engineering, ICSEng 2017, 2017, 2017-January pp. 475 - 479
Issue Date:: 2017-11-27

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Field	Value	Language
dc.contributor.author	Yu, Z	en_US
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Jiang, J	en_US
dc.date.issued	2017-11-27	en_US
dc.identifier.citation	Proceedings - 25th International Conference on Systems Engineering, ICSEng 2017, 2017, 2017-January pp. 475 - 479	en_US
dc.identifier.isbn	9781538606100	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126431
dc.description.abstract	© 2017 IEEE. This paper introduces a new generation an error modelling of wireless indoor localization. A newly designed algorithm modelling by using Kalman Filter is developed to optimize the wireless indoor localization system based on iBeacon sensors. It is designed to detect and minimize the errors. Matlab simulations, implementation, and validation are presented in the paper.	en_US
dc.relation.ispartof	Proceedings - 25th International Conference on Systems Engineering, ICSEng 2017	en_US
dc.relation.isbasedon	10.1109/ICSEng.2017.41	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Development and optimization of wireless indoor localization error modelling	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2017-January	en_US
utslib.for	0806 Information Systems	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 - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	2017-January	en_US

Abstract:

© 2017 IEEE. This paper introduces a new generation an error modelling of wireless indoor localization. A newly designed algorithm modelling by using Kalman Filter is developed to optimize the wireless indoor localization system based on iBeacon sensors. It is designed to detect and minimize the errors. Matlab simulations, implementation, and validation are presented in the paper.

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http://hdl.handle.net/10453/126431