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المؤلفAlsalemi, Abdullah
المؤلفHimeur, Yassine
المؤلفBensaali, Faycal
المؤلفAmira, Abbes
المؤلفSardianos, Christos
المؤلفChronis, Christos
المؤلفVarlamis, Iraklis
المؤلفDimitrakopoulos, George
تاريخ الإتاحة2022-12-29T07:34:44Z
تاريخ النشر2021
اسم المنشورIEEE Systems Journal
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/JSYST.2020.2997773
معرّف المصادر الموحدhttp://hdl.handle.net/10576/37826
الملخصDomestic user behavior is a crucial factor guiding overall power consumption, necessitating the development of systems that analyze and help shape energy-efficient behavior. Therefore, the most important step in the process is the collection and understanding of highly detailed domestic consumption data. This article presents an appliance-based energy data collection and analysis system for energy efficiency applications. It leverages the concept of micro-moments, which are short-timed and energy-based events that form the overall energy behavior of the end user. The system comprises sensing modules for recording energy consumption, occupancy, temperature, humidity, and luminosity storing recordings on a database server. Sensing parameters were tested in terms of connection stability and measurement accuracy. A four-week contextual appliance-level dataset has been collected from research cubicles. Collected data were also classified into corresponding micro-moments with a variety of classifiers including ensemble decision trees and deep learning, achieving high stability and accuracy of 99%. Further, the micro-moment usage efficiency is calculated to quantify the efficiency of usage at the appliance level. 2021 IEEE.
راعي المشروعManuscript received November 4, 2019; revised March 23, 2020; accepted April 22, 2020. Date of publication June 9, 2020; date of current version March 9, 2021. This article was made possible by National Priorities Research Program (NPRP) grant No. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. (Corresponding author: Abdullah Alsalemi.) Abdullah Alsalemi, Yassine Himeur, and Faycal Bensaali are with the Department of Electrical Engineering, Qatar University, 2713 Doha, Qatar (e-mail: a.alsalemi@qu.edu.qa; yassine.himeur@qu.edu.qa; f.bensaali@qu.edu.qa).
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعArtificial intelligence
data collection
domestic energy usage
energy efficiency
micro-moment
العنوانA Micro-Moment System for Domestic Energy Efficiency Analysis
النوعArticle
الصفحات1256-1263
رقم العدد1
رقم المجلد15
dc.accessType Abstract Only


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