Cargando…
A Smart Home Energy Management System Using Two-Stage Non-Intrusive Appliance Load Monitoring over Fog-Cloud Analytics Based on Tridium’s Niagara Framework for Residential Demand-Side Management
Electricity is a vital resource for various human activities, supporting customers’ lifestyles in today’s modern technologically driven society. Effective demand-side management (DSM) can alleviate ever-increasing electricity demands that arise from customers in downstream sectors of a smart grid. C...
Autores principales: | Chen, Yung-Yao, Chen, Ming-Hung, Chang, Che-Ming, Chang, Fu-Sheng, Lin, Yu-Hsiu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074283/ https://www.ncbi.nlm.nih.gov/pubmed/33924090 http://dx.doi.org/10.3390/s21082883 |
Ejemplares similares
-
A Smart Autonomous Time- and Frequency-Domain Analysis Current Sensor-Based Power Meter Prototype Developed over Fog-Cloud Analytics for Demand-Side Management
por: Chen, Yung-Yao, et al.
Publicado: (2019) -
Smart Distribution Boards (Smart DB), Non-Intrusive Load Monitoring (NILM) for Load Device Appliance Signature Identification and Smart Sockets for Grid Demand Management
por: Kerk, See Gim, et al.
Publicado: (2020) -
Design and Implementation of Cloud Analytics-Assisted Smart Power Meters Considering Advanced Artificial Intelligence as Edge Analytics in Demand-Side Management for Smart Homes
por: Chen, Yung-Yao, et al.
Publicado: (2019) -
A Mobility Management Using Follow-Me Cloud-Cloudlet in Fog-Computing-Based RANs for Smart Cities
por: Chen, Yuh-Shyan, et al.
Publicado: (2018) -
A Parallel Evolutionary Computing-Embodied Artificial Neural Network Applied to Non-Intrusive Load Monitoring for Demand-Side Management in a Smart Home: Towards Deep Learning
por: Lin, Yu-Hsiu
Publicado: (2020)