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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…

Machine Learning · Computer Science 2025-05-13 Sotirios Athanasoulias

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…

Machine Learning · Computer Science 2023-03-08 Jinsong Wang , Kenneth A. Loparo

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…

Machine Learning · Computer Science 2024-04-01 Anže Pirnat , Blaž Bertalanič , Gregor Cerar , Mihael Mohorčič , Carolina Fortuna

We consider the problem of learning the energy disaggregation signals for residential load data. Such task is referred as non-intrusive load monitoring (NILM), and in order to find individual devices' power consumption profiles based on…

Machine Learning · Computer Science 2022-11-29 Ruohong Liu , Yize Chen

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…

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…

Other Computer Science · Computer Science 2016-10-06 Christoph Klemenjak , Peter Goldsborough

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…

Machine Learning · Computer Science 2020-12-23 Mohammad Mahmudur Rahman Khan , Md. Abu Bakr Siddique , Shadman Sakib

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…

Systems and Control · Electrical Eng. & Systems 2021-01-19 Mohammad-Mehdi Keramati , Elnaz Azizi , Hamidreza Momeni , Sadegh Bolouki

Non-intrusive load monitoring (NILM) is a well-known single-channel blind source separation problem that aims to decompose the household energy consumption into itemised energy usage of individual appliances. In this way, considerable…

Machine Learning · Computer Science 2021-06-02 Yu Zhang , Guoming Tang , Qianyi Huang , Yi Wang , Hong Xu

Energy disaggregation or Non-Intrusive Load Monitoring (NILM) addresses the issue of extracting device-level energy consumption information by monitoring the aggregated signal at one single measurement point without installing meters on…

Computational Engineering, Finance, and Science · Computer Science 2018-05-16 Alireza Rahimpour , Hairong Qi , David Fugate , Teja Kuruganti

Non-intrusive load monitoring (NILM) is an important topic in smart-grid and smart-home. Many energy disaggregation algorithms have been proposed to detect various individual appliances from one aggregated signal observation. However, few…

Other Computer Science · Computer Science 2016-11-17 Zhilin Zhang , Jae Hyun Son , Ying Li , Mark Trayer , Zhouyue Pi , Dong Yoon Hwang , Joong Ki Moon

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…

Machine Learning · Computer Science 2015-11-11 Nipun Batra , Amarjeet Singh , Kamin Whitehouse

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…

Signal Processing · Electrical Eng. & Systems 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…

Systems and Control · Electrical Eng. & Systems 2020-09-08 Elnaz Azizi , Mohammad TH Beheshti , Sadegh Bolouki

Non-intrusive Load Monitoring (NILM) is an established technique for effective and cost-efficient electricity consumption management. The method is used to estimate appliance-level power consumption from aggregated power measurements. This…

Systems and Control · Electrical Eng. & Systems 2023-11-16 Amanie Azzam , Saba Sanami , Amir G. Aghdam

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,…

Machine Learning · Computer Science 2022-07-27 Jonah Edmonds , Zahraa S. Abdallah

Modern smart sensor-based energy management systems leverage non-intrusive load monitoring (NILM) to predict and optimize appliance load distribution in real-time. NILM, or energy disaggregation, refers to the decomposition of electricity…

Machine Learning · Computer Science 2022-04-01 Zhenrui Yue , Huimin Zeng , Ziyi Kou , Lanyu Shang , Dong Wang

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…

Applications · Statistics 2018-01-19 Chaoyun Zhang , Mingjun Zhong , Zongzuo Wang , Nigel Goddard , Charles Sutton

Energy disaggregation in a non-intrusive way estimates appliance level electricity consumption from a single meter that measures the whole house electricity demand. Recently, with the ongoing increment of energy data, there are many…

Machine Learning · Computer Science 2019-03-20 Peng Xiao , Samuel Cheng

To assess the performance of load disaggregation algorithms it is common practise to train a candidate algorithm on data from one or multiple households and subsequently apply cross-validation by evaluating the classification and energy…

Machine Learning · Computer Science 2019-12-16 Christoph Klemenjak , Anthony Faustine , Stephen Makonin , Wilfried Elmenreich