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Non-intrusive load monitoring (NILM) is a key cost-effective technology for monitoring power consumption and contributing to several challenges encountered when transiting to an efficient, sustainable, and competitive energy efficiency…

Computers and Society · Computer Science 2021-02-10 Yassine Himeur , Abdullah Alsalemi , Faycal Bensaali , Abbes Amira

Non-intrusive load monitoring (NILM) or energy disaggregation aims to extract the load profiles of individual consumer electronic appliances, given an aggregate load profile of the mains of a smart home. This work proposes a novel…

Individual device loads and energy consumption feedback is one of the important approaches for pursuing users to save energy in residences. This can help in identifying faulty devices and wasted energy by devices when left On unused. The…

Signal Processing · Electrical Eng. & Systems 2021-11-10 Ronak Aghera , Sahil Chilana , Vishal Garg , Raghunath Reddy

With the increased demand on economy and efficiency of measurement technology, Non-Intrusive Load Monitoring (NILM) has received more and more attention as a cost-effective way to monitor electricity and provide feedback to users. Deep…

Machine Learning · Computer Science 2020-09-28 Gan Zhou , Zhi Li , Meng Fu , Yanjun Feng , Xingyao Wang , Chengwei Huang

Non-intrusive load monitoring (NILM) has been extensively researched over the last decade. The objective of NILM is to identify the power consumption of individual appliances and to detect when particular devices are on or off from…

Machine Learning · Computer Science 2021-09-16 Jordan Holweger , Marina Dorokhova , Lionel Bloch , Christophe Ballif , Nicolas Wyrsch

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

The global effort toward renewable energy and the electrification of energy-intensive sectors have significantly increased the demand for electricity, making energy efficiency a critical focus. Non-intrusive load monitoring (NILM) enables…

Signal Processing · Electrical Eng. & Systems 2025-10-17 Ilia Kamyshev , Sahar Moghimian Hoosh , Dmitrii Kriukov , Elena Gryazina , Henni Ouerdane

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…

Machine Learning · Computer Science 2024-11-26 Dhruv Patel , Ankita Kumari Jain , Haikoo Khandor , Xhitij Choudhary , Nipun Batra

Improving energy efficiency is a necessity in the fight against climate change. Non Intrusive Load Monitoring (NILM) systems give important information about the household consumption that can be used by the electric utility or the end…

Signal Processing · Electrical Eng. & Systems 2020-04-30 Franco Marchesoni-Acland , Camilo Mariño , Elías Masquil , Pablo Masaferro , Alicia Fernández

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 lack of transparency and explainability. To address this…

Systems and Control · Electrical Eng. & Systems 2025-10-17 Grigorii Gerasimov , Ilia Kamyshev , Sahar Moghimian Hoosh , Elena Gryazina , Henni Ouerdane

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

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

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…

Machine Learning · Computer Science 2023-08-01 Jing Xiong , Tianqi Hong , Dongbo Zhao , Yu Zhang

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

In the recent years, there has been an increasing academic and industrial interest for analyzing the electrical consumption of commercial buildings. Whilst having similarities with the Non Intrusive Load Monitoring (NILM) tasks for…

Other Computer Science · Computer Science 2018-03-02 Simon Henriet , Umut Simsekli , Benoit Fuentes , Gaël Richard

With the help of smart metering valuable information of the appliance usage can be retrieved. In detail, non-intrusive load monitoring (NILM), also called load disaggregation, tries to identify appliances in the power draw of an household.…

Other Computer Science · Computer Science 2018-07-03 Dominik Egarter , Wilfried Elmenreich

Non-intrusive load monitoring (NILM) is an advanced load monitoring technique that uses data-driven algorithms to disaggregate the total power consumption of a household into the consumption of individual appliances. However, real-world…

Machine Learning · Computer Science 2025-11-18 Sahar Moghimian Hoosh , Ilia Kamyshev , Henni Ouerdane

Millions of smart meters have been deployed worldwide, collecting the total power consumed by individual households. Based on these data, electricity suppliers offer their clients energy monitoring solutions to provide feedback on the…

Machine Learning · Computer Science 2025-06-09 Adrien Petralia , Philippe Charpentier , Youssef Kadhi , Themis Palpanas

Non-Intrusive Load Monitoring (NILM) enables the disaggregation of the global power consumption of multiple loads, taken from a single smart electrical meter, into appliance-level details. State-of-the-Art approaches are based on Machine…

Machine Learning · Computer Science 2021-05-24 Enrico Tabanelli , Davide Brunelli , Andrea Acquaviva , Luca Benini

Increasing population indicates that energy demands need to be managed in the residential sector. Prior studies have reflected that the customers tend to reduce a significant amount of energy consumption if they are provided with…

Machine Learning · Computer Science 2019-10-21 Sagar Verma , Shikha Singh , Angshul Majumdar