Results 31 to 40 of about 2,135 (206)
IMPEC: An Integrated System for Monitoring and Processing Electricity Consumption in Buildings
Sensors, 2020 Non-intrusive Load Monitoring (NILM) systems aim at identifying and monitoring the power consumption of individual appliances using the aggregate electricity consumption. Many issues hinder their development.
Mohamed Aymane Ahajjam +3 more
doaj +1 more source
Smart Home System: A Comprehensive Review
Journal of Electrical and Computer Engineering, Volume 2023, Issue 1, 2023., 2023 Smart home is a habitation that has been outfitted with technological solutions that are intended to provide people with services that are suited to their needs. The purpose of this article is to perform a systematic assessment of the latest smart home literature and to conduct a survey of research and development conducted in this field.
Arindom Chakraborty +6 more
wiley +1 more source
NILM techniques for intelligent home energy management and ambient assisted living: a review [PDF]
, 2019 The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes, of the voltage.
Alvaro Hernandez +7 more
core +1 more source
Cloud-based Non-intrusive Load Monitoring System (NILM)
International Journal of Engineering and Advanced Technology, 2019 Design and development of a cloud-based non-intrusive load monitoring System (NILM) is presented. It serves for monitoring and disaggregating the aggregated data such as smart metering into appliance-level load information by using cloud computing and machine learning algorithms implemented in cloud.
Keh-Kim Kee +3 more
openaire +1 more source
Non Intrusive Load Monitoring (NILM): A State of the Art [PDF]
, 2018 The recent increase in smart meters installations in households and small bussiness by electric companies has led to interest in monitoring load techniques in order to provide better quality service and get useful information about appliance usage and user consumption behavior.
Revuelta Herrero, Jorge +6 more
openaire +1 more source
A comparison of generative and discriminative appliance recognition models for load monitoring [PDF]
, 2013 Appliance-level Load Monitoring (ALM) is essential, not only to optimize energy utilization, but also to promote energy awareness amongst consumers through real-time feedback mechanisms.
Gluhak, Alexander +3 more
core +1 more source
Load Hiding of Household's Power Demand [PDF]
, 2014 With the development and introduction of smart metering, the energy information for costumers will change from infrequent manual meter readings to fine-grained energy consumption data.
Egarter, Dominik +2 more
core +1 more source
Enhancing neural non-intrusive load monitoring with generative adversarial networks
Energy Informatics, 2018 The application of Deep Learning methodologies to Non-Intrusive Load Monitoring (NILM) gave rise to a new family of Neural NILM approaches which increasingly outperform traditional NILM approaches.
Kaibin Bao +3 more
doaj +1 more source
DP$^2$-NILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring
Renewable & Sustainable Energy Reviews, 2022 Non-intrusive load monitoring (NILM), which usually utilizes machine learning methods and is effective in disaggregating smart meter readings from the household-level into appliance-level consumption, can help analyze electricity consumption behaviours of users and enable practical smart energy and smart grid applications.
Dai, Shuang +3 more
openaire +3 more sources
On the Bayesian optimization and robustness of event detection methods in NILM [PDF]
, 2017 A basic but crucial step to increase efficiency and save energy in residential settings is to have an accurate view of energy consumption. To monitor residential energy consumption cost-effectively, i.e., without relying on per-device monitoring ...
De Baets, Leen +4 more
core +2 more sources