A recent review of NILM framework: Development and challenges

MD Silva, Q Liu, OF Darteh - … and Computing, Intl Conf on Cloud …, 2022 - ieeexplore.ieee.org
Development of sustainable energy management solution is a promising research area with
the energy crisis in the world. Many studies have been conducted to implement an electricity …

Non-intrusive load monitoring using identity library based on structured feature graph and group decision classifier

X Wu, Y Guo, M Yan, X Li, L Yao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) is performed to realize intelligent power consumption.
A load identification algorithm which is flexible for various households is required to realize …

Non-intrusive load monitoring: Comparative analysis of transient state clustering methods

M Etezadifar, H Karimi, J Mahseredjian - Electric Power Systems Research, 2023 - Elsevier
Non-intrusive load monitoring is one of the key tools in demand-side management (DSM).
Recent advancements in the computational power of processors have accentuated the role …

Pre-trained non-intrusive load monitoring model for recognizing activity of daily living

G Kim, S Park - Applied Intelligence, 2023 - Springer
Non-intrusive load monitoring (NILM) is a technology that analyzes total electricity
consumption data to determine whether a specific type of residential appliance is operated …

Non-intrusive load monitoring and forecasting for home appliances using artificial intelligence–a review

ALP De Ocampo, AMM Baes… - … Conference on Smart …, 2022 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) provides insights into how much energy consumers
are consuming, encouraging them to make energy-saving changes. Load forecasting, on the …

Machine Learning-Based Human Posture Identification from Point Cloud Data Acquisitioned by FMCW Millimetre-Wave Radar

G Zhang, S Li, K Zhang, YJ Lin - Sensors, 2023 - mdpi.com
Human posture recognition technology is widely used in the fields of healthcare, human-
computer interaction, and sports. The use of a Frequency-Modulated Continuous Wave …

A federated learning model with short sequence to point mechanism for smart home energy disaggregation

S Kaspour, A Yassine - 2022 IEEE Symposium on Computers …, 2022 - ieeexplore.ieee.org
Residential households contribute significantly to the overall energy consumption in
developed countries. To reduce their energy consumption, they need solutions that help …

Exploration of Artificial-intelligence Oriented Power System Dynamic Simulators

T Xiao, Y Chen, J Wang, S Huang… - Journal of Modern …, 2022 - ieeexplore.ieee.org
With the rapid development of artificial intelligence (AI), it is foreseeable that the accuracy
and efficiency of dynamic analysis for future power system will be greatly improved by the …

Simultaneous load identification method based on hybrid features and genetic algorithm for nonintrusive load monitoring

SH Yi, J Wang, JJ Liu - Mathematical Problems in Engineering, 2022 - Wiley Online Library
Nonintrusive load monitoring (NILM) is a widely accepted technology to conduct load
monitoring. Many effective methods have been established to make NILM more practical …

Event Detection Based on Robust Random Cut Forest Algorithm for Non-Intrusive Load Monitoring

L Lu, JS Kang, M Yu - Journal of Modern Power Systems and …, 2024 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) can provide appliance-level power consumption
information without deploying submeters for each load, in which load event detection is one …