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Permanent link (DOI): https://doi.org/10.7939/R3RV0D839

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Deployment Planning for Location Recognition in the Smart-Condo™: Simulation, Empirical Studies and Sensor Placement Optimization Open Access

Descriptions

Other title
Subject/Keyword
Sensor Placement Optimization
Indoor Localization
Ambient Assisted Living
Wireless Sensor Networks
Smart Home
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Vlasenko, Iuliia
Supervisor and department
Stroulia, Eleni (Computing Science)
Nikolaidis, Ioanis (Computing Science)
Examining committee member and department
Ray, Nilanjan (Computing Science)
Wong, Ken (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2013-05-14T11:02:09Z
Graduation date
2013-11
Degree
Master of Science
Degree level
Master's
Abstract
The Smart-Condo™ is a comprehensive platform that aims to provide a variety of services, based on information gleaned from sensors deployed in an apartment, that can potentially improve healthcare delivery. One of our main objectives has been to develop an accurate non-invasive occupant-localization method using passive infrared sensors. In this thesis, we present a simulation framework with which we investigate tradeoffs between the number of sensors and the localization accuracy of our platform. We compare the results of simulations and real-world trials and conclude that our simulation framework is a reliable estimator of the localization accuracy of a particular sensor configuration. We then propose a methodology for planning new deployments that takes into account geometric properties of the new space and the context of occupant's activities. More specifically, we describe a model with the potential to capture typical indoor mobility patterns and formulate a sensor placement optimization problem based on this model. We propose a placement algorithm with near-optimality guarantee. Through simulation-enabled evaluation, we demonstrate that this algorithm generates sensor configurations with localization accuracy superior to that achievable with the same number of sensors placed manually or randomly in the same environment.
Language
English
DOI
doi:10.7939/R3RV0D839
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
I. Vlasenko, M. Vosoughpour Yazdchi, V. Ganev, I. Nikolaidis, and E. Stroulia,"The Smart-Condo™ Infrastructure and Experience," in Evaluating AAL Systems Through Competitive Benchmarking, ser. Communications in Computer and Information Science, S. Chessa and S. Knauth, Eds. Springer Berlin Heidelberg, 2013, vol. 362, pp. 63–82.

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