6 papers
Fusion-ResNet: A Lightweight multi-label NILM Model Using PCA-ICA Feature Fusion
Sahar Moghimian Hoosh, Ilia Kamyshev, Henni Ouerdane
Non-intrusive load monitoring (NILM) is an advanced load monitoring technique that uses data-driven algorithms to disaggregate the total power consumption of a household into the c…
HiFAKES: Synthetic High-Frequency NILM Data for NILM Models Diagnostics and Generalization Testing
Ilia Kamyshev, Sahar Moghimian, Henni Ouerdane
Monitoring electricity consumption at the appliance level is crucial for increasing energy efficiency in residential and commercial buildings. Using a single meter, the non-intrusi…
Indoor thermal comfort management: A Bayesian machine-learning approach to data denoising and dynamics prediction of HVAC systems
Javier Penuela, Sahar Moghimian Hoosh, Ilia Kamyshev +2
The optimal management of a building's microclimate to satisfy the occupants' needs and objectives in terms of comfort, energy efficiency, and costs is particularly challenging. Th…
Toward Explainable NILM: Real-Time Event-Based NILM Framework for High-Frequency Data
Grigorii Gerasimov, Ilia Kamyshev, Sahar Moghimian Hoosh +2
Non-Intrusive Load Monitoring (NILM) is an advanced, and cost-effective technique for monitoring appliance-level energy consumption. However, its adaptability is hindered by the la…
Enhancing Non-Intrusive Load Monitoring with Features Extracted by Independent Component Analysis
Sahar Moghimian Hoosh, Ilia Kamyshev, Henni Ouerdane
In this paper, a novel neural network architecture is proposed to address the challenges in energy disaggregation algorithms. These challenges include the limited availability of d…
COLD: Concurrent Loads Disaggregator for Non-Intrusive Load Monitoring
Ilia Kamyshev, Sahar Moghimian Hoosh, Dmitrii Kriukov +2
The global effort toward renewable energy and the electrification of energy-intensive sectors have significantly increased the demand for electricity, making energy efficiency a cr…