6 citations · 16 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Physics-informed appliance signatures generator for energy disaggregation
Ilia Kamyshev, Sahar Moghimian Hoosh, Henni Ouerdane
Energy disaggregation is a promising solution to access detailed information on energy consumption in a household, by itemizing its total energy consumption. However, in real-world…