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In this demonstration, we present an open source toolkit for evaluating non-intrusive load monitoring research; a field which aims to disaggregate a household's total electricity consumption into individual appliances. The toolkit contains:…

Other Computer Science · Computer Science 2014-11-11 Jack Kelly , Nipun Batra , Oliver Parson , Haimonti Dutta , William Knottenbelt , Alex Rogers , Amarjeet Singh , Mani Srivastava

Non-Intrusive Load Monitoring (NILM) is a practical method to provide appliance-level electricity consumption information. Event detection, as an important part of event-based NILM methods, has a direct impact on the accuracy of the…

Signal Processing · Electrical Eng. & Systems 2019-03-25 Mengqi Lu , Zuyi Li

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 or energy disaggregation involves estimating the power consumption of individual appliances from measurements of the total power consumption of a home. Deep neural networks have been shown to be effective for…

Machine Learning · Computer Science 2018-12-11 Cillian Brewitt , Nigel Goddard

Non-Intrusive Load Monitoring (NILM) is pivotal in today's energy landscape, offering vital solutions for energy conservation and efficient management. Its growing importance in enhancing energy savings and understanding consumer behavior…

Signal Processing · Electrical Eng. & Systems 2024-03-12 Yinyan Liu , Yi Wang , Jin Ma

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

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

Non-intrusive load monitoring (NILM) aims at separating a whole-home energy signal into its appliance components. Such method can be harnessed to provide various services to better manage and control energy consumption (optimal planning and…

Machine Learning · Statistics 2019-10-28 Saad Mohamad , Abdelhamid Bouchachia

Being able to track appliances energy usage without the need of sensors can help occupants reduce their energy consumption to help save the environment all while saving money. Non-intrusive load monitoring (NILM) tries to do just that. One…

Signal Processing · Electrical Eng. & Systems 2019-07-26 Alejandro Rodriguez-Silva , Stephen Makonin

Energy disaggregation, a.k.a. Non-Intrusive Load Monitoring, aims to separate the energy consumption of individual appliances from the readings of a mains power meter measuring the total energy consumption of, e.g. a whole house. Energy…

Machine Learning · Computer Science 2019-08-06 Jie Jiang , Qiuqiang Kong , Mark Plumbley , Nigel Gilbert

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

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

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) aims to estimate appliance-level consumption from aggregate electrical signals recorded at a single measurement point. In recent years, the field has increasingly adopted deep learning approaches;…

Machine Learning · Computer Science 2026-03-06 L. E. Garcia-Marrero , G. Petrone , E. Monmasson

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) is an important application to monitor household appliance activities and provide related information to house owner or/and utility company via a single sensor installed at the electrical entry of the…

Signal Processing · Electrical Eng. & Systems 2018-09-25 Mengqi Lu , Jinfeng Gao , Zuyi Li

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

Prudent and meaningful performance evaluation of algorithms is essential for the progression of any research field. In the field of Non-Intrusive Load Monitoring (NILM), performance evaluation can be conducted on real-world aggregate…

Other Computer Science · Computer Science 2020-10-06 Christoph Klemenjak , Stephen Makonin , Wilfried Elmenreich

Improving smart grid system management is crucial in the fight against climate change, and enabling consumers to play an active role in this effort is a significant challenge for electricity suppliers. In this regard, millions of smart…

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

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