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Predictive Energy Management for Wireless Sensor Nodes

  • Author / Creator
    Rodway, James E A
  • A wireless sensor network is a tool that can collect data, aiding in answering a number of different questions in research and industrial environments. When deployed in remote locations, it is often beneficial to use of energy harvesting technologies, allowing sensor nodes to replenish energy while in the field. This permits longer deployment times while keeping node size small. In order to make the best use of harvested energy, controllers can be used to adapt node activities to available energy. In this thesis, energy forecasts based on measurements of atmospheric pressure are created and included as inputs to fuzzy controllers. These controllers are applied to simulated sensor nodes and used to control node activity levels for effective use of available energy. They were tuned using differential evolution and simulated using measured meteorological data. The results were examined in terms of the networks overall activity level and the usage of reserve energy. With respect to the solar energy forecasts, a number of applied methods were able to achieve error levels comparable to other methods where more variables were included. The tuned fuzzy controllers represented an improvement over both the uncontrolled and human-created cases.

  • Subjects / Keywords
  • Graduation date
    2017-11:Fall 2017
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3PN8XV5F
  • 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
    Doctoral
  • Department
    • Department of Electrical and Computer Engineering
  • Specialization
    • Software Engineering and Intelligent Systemcs
  • Supervisor / co-supervisor and their department(s)
    • Musilek, Petr (Electrical and Computer Engineering)
  • Examining committee members and their departments
    • Miller, James (Electrical and Computer Engineering)
    • Reformat, Marek (Electrical and Computer Engineering)
    • Robinson, Aminah (Civil and Environmental Engineering)
    • Musilek, Petr (Electrical and Computer Engineering)
    • Pizzi, Nick (InfoMagnetics Technologies)