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

  • Author / Creator
    Vlasenko, Iuliia
  • 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.

  • Subjects / Keywords
  • Graduation date
    2013-11
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3RV0D839
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Stroulia, Eleni (Computing Science)
    • Nikolaidis, Ioanis (Computing Science)
  • Examining committee members and their departments
    • Wong, Ken (Computing Science)
    • Ray, Nilanjan (Computing Science)