A review on deep learning techniques for IoT data
Continuous growth in software, hardware and internet technology has enabled the growth of
internet-based sensor tools that provide physical world observations and data …
internet-based sensor tools that provide physical world observations and data …
NILM applications: Literature review of learning approaches, recent developments and challenges
This paper presents a critical approach to the non-intrusive load monitoring (NILM) problem,
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
[HTML][HTML] Next-generation energy systems for sustainable smart cities: Roles of transfer learning
Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while
improving grid stability and meeting service demand. This is possible by adopting next …
improving grid stability and meeting service demand. This is possible by adopting next …
Non-intrusive residential electricity load decomposition via low-resource model transferring
L Lin, J Shi, C Ma, S Zuo, J Zhang, C Chen… - Journal of Building …, 2023 - Elsevier
Non-intrusive load decomposition (NILD) technology has a broad application prospect
because it can deeply excavate the internal electricity consumption data of customers and …
because it can deeply excavate the internal electricity consumption data of customers and …
Non-intrusive load monitoring: A review
PA Schirmer, I Mporas - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
The rapid development of technology in the electrical energy sector within the last 20 years
has led to growing electric power needs through the increased number of electrical …
has led to growing electric power needs through the increased number of electrical …
Energy management using non-intrusive load monitoring techniques–State-of-the-art and future research directions
R Gopinath, M Kumar, CPC Joshua… - Sustainable Cities and …, 2020 - Elsevier
In recent years, the development of smart sustainable cities has become the primary focus
among urban planners and policy makers to make responsible use of resources, conserve …
among urban planners and policy makers to make responsible use of resources, conserve …
Sequence-to-point learning with neural networks for non-intrusive load monitoring
Energy disaggregation (aka nonintrusive load monitoring, NILM), a single-channel blind
source separation problem, aims to decompose the mains which records the whole house …
source separation problem, aims to decompose the mains which records the whole house …
Occupant behavior modeling for building performance simulation: Current state and future challenges
Occupant behavior is now widely recognized as a major contributing factor to uncertainty of
building performance. While a surge of research on the topic has occurred over the past four …
building performance. While a surge of research on the topic has occurred over the past four …
Transfer learning for non-intrusive load monitoring
M D'Incecco, S Squartini… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) is a technique to recover source appliances from only
the recorded mains in a household. NILM is unidentifiable and thus a challenge problem …
the recorded mains in a household. NILM is unidentifiable and thus a challenge problem …
An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study
Smart meter roll-outs provide easy access to granular meter measurements, enabling
advanced energy services, ranging from demand response measures, tailored energy …
advanced energy services, ranging from demand response measures, tailored energy …