Zareipour, HamidrezaMotta Cabrera, David Francisco2017-12-182017-12-182012Motta Cabrera, D. F. (2012). Reducing energy waste in post-secondary educational institutions using artificial intelligence (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/4937http://hdl.handle.net/1880/105938Bibliography: p. 136-153Some pages are in colour.This thesis focuses on computer-related and lighting energy consumption in post-secondary educational institutions. In this respect, artificial intelligence and data association mining are proposed as tools to identify and reduce energy waste. First, an artificial intelligence­based method for forecasting computer usage is proposed. Based on the models' forecast, workstations can be turned on and off, in order to strike a balance between energy sav­ings and user comfort. The models are evaluated on different datasets and their results compared to commercially available alternatives. Second, a data association mining-based approach is proposed to uncover possible re­lationships between occupancy patterns and lighting-related energy waste in classrooms. A wireless data collection system is used to log data from both lighting consumption and occupancy states during a year. Next, energy savings results of using the proposed approach are compared to those of an occupancy-activated lighting control system for classrooms.xv, 153 leaves : ill. ; 30 cm.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.master thesis10.11575/PRISM/4937