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Energy management using non-intrusive load monitoring techniques–State-of-the-art and future research directions
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 …
Review on deep neural networks applied to low-frequency nilm
This paper reviews non-intrusive load monitoring (NILM) approaches that employ deep
neural networks to disaggregate appliances from low frequency data, ie, data with sampling …
neural networks to disaggregate appliances from low frequency data, ie, data with sampling …
Fednilm: Applying federated learning to nilm applications at the edge
Non-intrusive load monitoring (NILM) helps disaggregate a household's main electricity
consumption to energy usages of individual appliances, greatly cutting down the cost of fine …
consumption to energy usages of individual appliances, greatly cutting down the cost of fine …
EdgeNILM: Towards NILM on edge devices
Non-intrusive load monitoring (NILM) or energy disaggregation refers to the task of
estimating the appliance power consumption given the aggregate power consumption …
estimating the appliance power consumption given the aggregate power consumption …
Time–frequency mask estimation based on deep neural network for flexible load disaggregation in buildings
In this paper, a novel mask-based load disaggregation scheme is presented to extract
flexible load profiles in buildings. Flexible loads are those that can be adjusted as needed …
flexible load profiles in buildings. Flexible loads are those that can be adjusted as needed …
An energy efficient smart metering system using edge computing in LoRa network
An important research issue in smart metering is to correctly transfer the smart meter
readings from consumers to the operator within the given time period by consuming …
readings from consumers to the operator within the given time period by consuming …
Improving the precision of solids velocity measurement in gas-solid fluidized beds with a hybrid machine learning model
Accurate measurement of solids velocity is crucial for fluidized bed reactor design,
optimization, and scaling in chemical engineering. However, the cross-correlation …
optimization, and scaling in chemical engineering. However, the cross-correlation …
Trending machine learning models in cyber‐physical building environment: A survey
Electricity usage of buildings (including offices, malls, and residential apartments)
represents a significant portion of a nation's energy expenditure and carbon footprint. In the …
represents a significant portion of a nation's energy expenditure and carbon footprint. In the …
An implementation framework overview of non-intrusive load monitoring
Sažetak The implementation of non-intrusive load monitoring has gained significant
attention as a promising solution for disaggregating and identifying individual appliances' …
attention as a promising solution for disaggregating and identifying individual appliances' …
An alternative Low-Cost embedded NILM system for household energy conservation with a low sampling rate
The measurement of the energy consumption of electrical appliances, where the meter is
installed at a single point on the main input circuit of the building, is called non-intrusive load …
installed at a single point on the main input circuit of the building, is called non-intrusive load …