[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 …
Recent trends of smart nonintrusive load monitoring in buildings: A review, open challenges, and future directions
Y Himeur, A Alsalemi, F Bensaali… - … Journal of Intelligent …, 2022 - Wiley Online Library
Smart nonintrusive load monitoring (NILM) represents a cost‐efficient technology for
observing power usage in buildings. It tackles several challenges in transitioning into a more …
observing power usage in buildings. It tackles several challenges in transitioning into a more …
The UCR time series archive
The UCR time series archive–introduced in 2002, has become an important resource in the
time series data mining community, with at least one thousand published papers making use …
time series data mining community, with at least one thousand published papers making use …
Matrix profile I: all pairs similarity joins for time series: a unifying view that includes motifs, discords and shapelets
The all-pairs-similarity-search (or similarity join) problem has been extensively studied for
text and a handful of other datatypes. However, surprisingly little progress has been made …
text and a handful of other datatypes. However, surprisingly little progress has been made …
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 …
Non-intrusive load disaggregation using graph signal processing
K He, L Stankovic, J Liao… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
With the large-scale roll-out of smart metering worldwide, there is a growing need to account
for the individual contribution of appliances to the load demand. In this paper, we design a …
for the individual contribution of appliances to the load demand. In this paper, we design a …
A novel approach for detecting anomalous energy consumption based on micro-moments and deep neural networks
Nowadays, analyzing, detecting, and visualizing abnormal power consumption behavior of
householders are among the principal challenges in identifying ways to reduce power …
householders are among the principal challenges in identifying ways to reduce power …
[HTML][HTML] From time-series to 2d images for building occupancy prediction using deep transfer learning
Building occupancy information could aid energy preservation while simultaneously
maintaining the end-user comfort level. Energy conservation becomes essential since …
maintaining the end-user comfort level. Energy conservation becomes essential since …
On a training-less solution for non-intrusive appliance load monitoring using graph signal processing
With ongoing large-scale smart energy metering deployments worldwide, disaggregation of
a household's total energy consumption down to individual appliances using analytical …
a household's total energy consumption down to individual appliances using analytical …
Performance evaluation in non‐intrusive load monitoring: datasets, metrics, and tools—A review
Non‐intrusive load monitoring (also known as NILM or energy disaggregation) is the
process of estimating the energy consumption of individual appliances from electric power …
process of estimating the energy consumption of individual appliances from electric power …