Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/379
Title: Smart-Building Applications: Deep Learning-Based, Real-Time Load Monitoring
Authors: Çimen, Halil
Palacios-Garcia, Emilio J.
Kolbaek, Morten
Çetinkaya, Nurettin
Vasquez, Juan C.
Guerrero, Josep M.
Keywords: Home appliances
Data models
Monitoring
Feature extraction
Smart meters
Internet of Things
Hidden Markov models
Algorithm design and theory
SYSTEM
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Abstract: Google's Director of Research Peter Norvig said, We don't have better algorithms than anyone else; we just have more data. This inspiring statement shows that having more data is directly related to better decision making and foresight about the future. With the development of Internet of Things (IoT) technology, it is now much easier to gather data. Technological tools, such as social media websites, smartphones, and security cameras, can be considered as data generators. When the focus is shifted to the energy field, these generators are smart meters.
URI: https://doi.org/10.1109/MIE.2020.3023075
https://hdl.handle.net/20.500.13091/379
ISSN: 1932-4529
1941-0115
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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