An Overview of a New Statistical Non-Intrusive Load Monitoring (NILM) Analysis and Recognition Approach for Domestic Environments: DENARDO
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10256300" target="_blank" >RIV/61989100:27240/24:10256300 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/24:10256300
Result on the web
<a href="https://ieeexplore.ieee.org/document/10615815" target="_blank" >https://ieeexplore.ieee.org/document/10615815</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/MetroLivEnv60384.2024.10615815" target="_blank" >10.1109/MetroLivEnv60384.2024.10615815</a>
Alternative languages
Result language
angličtina
Original language name
An Overview of a New Statistical Non-Intrusive Load Monitoring (NILM) Analysis and Recognition Approach for Domestic Environments: DENARDO
Original language description
IP devices are ubiquitously spread, for both residential and industrial purposes, thanks to the low integration costs and rapid development cycle of all-IP-based 5G+ technologies. As a consequence, the engineering community now considers their automatization and energy scheduling/management as relevant research fields. These topics have a striking relevance also for the development of smart city networks. As a drawback, most ID-device applications produce a large amount of data (high-frequency complexity), requiring supervised machine learning algorithms to be properly analyzed. In this research, we focus on the performance of vehicular mobility and imaging systems, recognizing scenarios (with powered-on devices) in real-time, with the help of a simple convolutional neural network, proving the effectiveness of such an innovative low-cost approach.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20202 - Communication engineering and systems
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2024 IEEE International Workshop on Metrology for Living Environment, MetroLivEnv 2024 : proceedings
ISBN
979-8-3503-8502-1
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
465-469
Publisher name
IEEE
Place of publication
Piscataway
Event location
Chania
Event date
Jun 12, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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