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Non-Intrusive Load Monitoring (NILM) is an energy efficiency technique to track electricity consumption of an individual appliance in a household by one aggregated single, such as building level meter readings. The goal of NILM is to…

机器学习 · 计算机科学 2023-03-08 Jinsong Wang , Kenneth A. Loparo

Non intrusive load monitoring (NILM), or energy disaggregation, is the process of separating the total electricity consumption of a building as measured at single point into the building's constituent loads. Previous research in the field…

系统与控制 · 计算机科学 2014-08-29 Nipun Batra , Oliver Parson , Mario Berges , Amarjeet Singh , Alex Rogers

Non-intrusive load monitoring, or energy disaggregation, aims to separate household energy consumption data collected from a single point of measurement into appliance-level consumption data. In recent years, the field has rapidly expanded…

Non-Intrusive Load Monitoring (NILM) comprises of a set of techniques that provide insights into the energy consumption of households and industrial facilities. Latest contributions show significant improvements in terms of accuracy and…

信号处理 · 电气工程与系统科学 2020-01-23 Christoph Klemenjak , Stephen Makonin , Wilfried Elmenreich

Non-Intrusive Load Monitoring (NILM) is the method of detecting an individual device's energy signal from an aggregated energy consumption signature [1]. As existing energy meters provide very little to no information regarding the energy…

机器学习 · 计算机科学 2020-12-23 Mohammad Mahmudur Rahman Khan , Md. Abu Bakr Siddique , Shadman Sakib

Non-intrusive load monitoring (NILM) focuses on disaggregating total household power consumption into appliance-specific usage. Many advanced NILM methods are based on neural networks that typically require substantial amounts of labeled…

机器学习 · 计算机科学 2024-11-26 Dhruv Patel , Ankita Kumari Jain , Haikoo Khandor , Xhitij Choudhary , Nipun Batra

We propose a novel approach to enable Automated Machine Learning (AutoML) for Non-Intrusive Appliance Load Monitoring (NIALM), also known as Energy Disaggregation, through Bayesian Optimization. NIALM offers a cost-effective alternative to…

软件工程 · 计算机科学 2025-05-13 Armin Moin , Ukrit Wattanavaekin , Alexandra Lungu , Stephan Rössler , Stephan Günnemann

Non-intrusive load monitoring (NILM) or energy disaggregation, aims to disaggregate a household's electricity consumption into constituent appliances. More than three decades of work in NILM has resulted in the development of several novel…

其他计算机科学 · 计算机科学 2014-10-09 Nipun Batra , Manoj Gulati , Puneet Jain , Kamin Whitehouse , Amarjeet Singh

Demand-side management now encompasses more residential loads. To efficiently apply demand response strategies, it's essential to periodically observe the contribution of various domestic appliances to total energy consumption.…

信号处理 · 电气工程与系统科学 2023-06-09 Mohammad Irani Azad , Roozbeh Rajabi , Abouzar Estebsari

The importance of Non-Intrusive Load Monitoring (NILM) has been increasingly recognized, given that NILM can enhance energy awareness and provide valuable insights for energy program design. Many existing NILM methods often rely on…

信号处理 · 电气工程与系统科学 2024-09-04 Xiangrui Li

Non-intrusive load monitoring (NILM), aims to infer the power profiles of appliances from the aggregated power signal via purely analytical methods. Existing NILM methods are susceptible to various issues such as the noise and transient…

系统与控制 · 电气工程与系统科学 2020-09-08 Elnaz Azizi , Mohammad TH Beheshti , Sadegh Bolouki

Non-intrusive load monitoring (NILM) identifies the status and power consumption of various household appliances by disaggregating the total power usage signal of an entire house. Efficient and accurate load monitoring facilitates user…

机器学习 · 计算机科学 2023-08-01 Jing Xiong , Tianqi Hong , Dongbo Zhao , Yu Zhang

Non-intrusive load monitoring (NILM) as the process of extracting the usage pattern of appliances from the aggregated power signal is among successful approaches aiding residential energy management. In recent years, high volume datasets on…

系统与控制 · 电气工程与系统科学 2021-01-19 Mohammad-Mehdi Keramati , Elnaz Azizi , Hamidreza Momeni , Sadegh Bolouki

The growing global energy demand and the urgent need for sustainability call for innovative ways to boost energy efficiency. While advanced energy-saving systems exist, they often fall short without user engagement. Providing feedback on…

机器学习 · 计算机科学 2025-05-13 Sotirios Athanasoulias

Non-intrusive load monitoring (NILM) is the process of obtaining appliance-level data from a single metering point, measuring total electricity consumption of a household or a business. Appliance-level data can be directly used for demand…

机器学习 · 计算机科学 2024-04-01 Anže Pirnat , Blaž Bertalanič , Gregor Cerar , Mihael Mohorčič , Carolina Fortuna

In this paper, we investigate whether "big-data" is more valuable than "precise" data for the problem of energy disaggregation: the process of breaking down aggregate energy usage on a per-appliance basis. Existing techniques for…

机器学习 · 计算机科学 2015-11-11 Nipun Batra , Amarjeet Singh , Kamin Whitehouse

With the roll-out of smart meters the importance of effective non-intrusive load monitoring (NILM) techniques has risen rapidly. NILM estimates the power consumption of individual devices given their aggregate consumption. In this way, the…

其他计算机科学 · 计算机科学 2016-10-06 Christoph Klemenjak , Peter Goldsborough

Energy disaggregation estimates appliance-by-appliance electricity consumption from a single meter that measures the whole home's electricity demand. Compared with intrusive load monitoring, NILM (Non-intrusive load monitoring) is low cost,…

机器学习 · 计算机科学 2022-07-27 Jonah Edmonds , Zahraa S. Abdallah

Energy disaggregation (a.k.a nonintrusive load monitoring, NILM), a single-channel blind source separation problem, aims to decompose the mains which records the whole house electricity consumption into appliance-wise readings. This problem…

应用统计 · 统计学 2018-01-19 Chaoyun Zhang , Mingjun Zhong , Zongzuo Wang , Nigel Goddard , Charles Sutton

Industrial Non-Intrusive Load Monitoring (NILM) is limited by the scarcity of high-quality datasets and the complex variability of industrial energy consumption patterns. To address data scarcity and privacy issues, we introduce the…

机器学习 · 计算机科学 2025-09-16 Christian Internò , Andrea Castellani , Sebastian Schmitt , Fabio Stella , Barbara Hammer