Smart-Building Applications: Deep Learning-Based, Real-Time Load Monitoring
| dc.contributor.author | Çimen, Halil | |
| dc.contributor.author | Palacios-Garcia, Emilio J. | |
| dc.contributor.author | Kolbaek, Morten | |
| dc.contributor.author | Çetinkaya, Nurettin | |
| dc.contributor.author | Vasquez, Juan C. | |
| dc.contributor.author | Guerrero, Josep M. | |
| dc.date.accessioned | 2021-12-13T10:24:07Z | |
| dc.date.available | 2021-12-13T10:24:07Z | |
| dc.date.issued | 2021 | |
| dc.description.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. | en_US |
| dc.description.sponsorship | Scientific and Technological Research Council of Turkey BIDEB-2214 International Doctoral Research Fellowship Program; VILLUM FONDEN under the VILLUM Investigator Grant [25920]; Aalborg University [771116] | en_US |
| dc.description.sponsorship | This work was supported by the Scientific and Technological Research Council of Turkey BIDEB-2214 International Doctoral Research Fellowship Program, VILLUM FONDEN under the VILLUM Investigator Grant 25920: Center for Research on Microgrids (www.crom.et.aau.dk), and the Aalborg University Talent Program 2016 with the research project The Energy Internet-Integrating the Internet of Things Into the Smart Grid (771116). | en_US |
| dc.identifier.doi | 10.1109/MIE.2020.3023075 | |
| dc.identifier.issn | 1932-4529 | |
| dc.identifier.issn | 1941-0115 | |
| dc.identifier.scopus | 2-s2.0-85099079431 | |
| dc.identifier.uri | https://doi.org/10.1109/MIE.2020.3023075 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.13091/379 | |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | en_US |
| dc.relation.ispartof | IEEE INDUSTRIAL ELECTRONICS MAGAZINE | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Home appliances | en_US |
| dc.subject | Data models | en_US |
| dc.subject | Monitoring | en_US |
| dc.subject | Feature extraction | en_US |
| dc.subject | Smart meters | en_US |
| dc.subject | Internet of Things | en_US |
| dc.subject | Hidden Markov models | en_US |
| dc.subject | Algorithm design and theory | en_US |
| dc.subject | SYSTEM | en_US |
| dc.title | Smart-Building Applications: Deep Learning-Based, Real-Time Load Monitoring | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.id | Palacios-Garcia, Emilio Jose/0000-0003-2703-6532 | |
| gdc.author.scopusid | 57205614115 | |
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| gdc.author.wosid | Palacios-Garcia, Emilio Jose/K-9567-2015 | |
| gdc.author.wosid | Guerrero, Josep/D-5519-2014 | |
| gdc.author.wosid | Vasquez, Juan C./J-2247-2014 | |
| gdc.bip.impulseclass | C4 | |
| gdc.bip.influenceclass | C5 | |
| gdc.bip.popularityclass | C4 | |
| gdc.coar.access | metadata only access | |
| gdc.coar.type | text::journal::journal article | |
| gdc.description.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
| gdc.description.endpage | 15 | en_US |
| gdc.description.issue | 2 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q1 | |
| gdc.description.startpage | 4 | en_US |
| gdc.description.volume | 15 | en_US |
| gdc.description.wosquality | Q1 | |
| gdc.identifier.openalex | W3116485394 | |
| gdc.identifier.wos | WOS:000679819200003 | |
| gdc.index.type | WoS | |
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| gdc.oaire.influence | 3.101136E-9 | |
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| gdc.oaire.keywords | Meters | |
| gdc.oaire.keywords | Monitoring | |
| gdc.oaire.keywords | Smart meters | |
| gdc.oaire.keywords | Data models | |
| gdc.oaire.keywords | Feature extraction | |
| gdc.oaire.keywords | Home appliances | |
| gdc.oaire.keywords | Hidden Markov models | |
| gdc.oaire.popularity | 1.0563775E-8 | |
| gdc.oaire.publicfunded | false | |
| gdc.oaire.sciencefields | 0202 electrical engineering, electronic engineering, information engineering | |
| gdc.oaire.sciencefields | 02 engineering and technology | |
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| gdc.scopus.citedcount | 12 | |
| gdc.virtual.author | Çetinkaya, Nurettin | |
| gdc.virtual.author | Çimen, Halil | |
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