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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

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

Energy disaggregation or nonintrusive load monitoring (NILM), is a single-input blind source discrimination problem, aims to interpret the mains user electricity consumption into appliance level measurement. This article presents a new…

Machine Learning · Computer Science 2021-04-19 Sobhan Naderian

Energy disaggregation, known in the literature as Non-Intrusive Load Monitoring (NILM), is the task of inferring the power demand of the individual appliances given the aggregate power demand recorded by a single smart meter which monitors…

Machine Learning · Computer Science 2021-02-09 Veronica Piccialli , Antonio M. Sudoso

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…

Energy disaggregation, also known as non-intrusive load monitoring (NILM), challenges the problem of separating the whole-home electricity usage into appliance-specific individual consumptions, which is a typical application of data…

Signal Processing · Electrical Eng. & Systems 2021-08-05 Zhekai Du , Jingjing Li , Lei Zhu , Ke Lu , Heng Tao Shen

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

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

Non-intrusive load monitoring (NILM), also known as energy disaggregation, is a blind source separation problem where a household's aggregate electricity consumption is broken down into electricity usages of individual appliances. In this…

Machine Learning · Computer Science 2018-11-19 Changho Shin , Sunghwan Joo , Jaeryun Yim , Hyoseop Lee , Taesup Moon , Wonjong Rhee

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 a technique to recover source appliances from only the recorded mains in a household. NILM is unidentifiable and thus a challenge problem because the inferred power value of an appliance given only…

Machine Learning · Computer Science 2019-09-16 Michele DIncecco , Stefano Squartini , Mingjun Zhong

Non-intrusive load monitoring (NILM) is the task of disaggregating the total power consumption into its individual sub-components. Over the years, signal processing and machine learning algorithms have been combined to achieve this. A lot…

The rapid urbanization of developing countries coupled with explosion in construction of high rising buildings and the high power usage in them calls for conservation and efficient energy program. Such a program require monitoring of…

Other Computer Science · Computer Science 2017-03-13 Anthony Faustine , Nerey Henry Mvungi , Shubi Kaijage , Kisangiri Michael

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

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

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 (NILM) offers a cost-effective method to obtain fine-grained appliance-level energy consumption in smart homes and building applications. However, the increasing adoption of behind-the-meter (BTM) energy…

Machine Learning · Computer Science 2026-02-12 Xudong Wang , Guoming Tang , Junyu Xue , Srinivasan Keshav , Tongxin Li , Chris Ding

Energy disaggregation, known in the literature as Non-Intrusive Load Monitoring (NILM), is the task of inferring the energy consumption of each appliance given the aggregate signal recorded by a single smart meter. In this paper, we propose…

Optimization and Control · Mathematics 2022-04-13 Marco Balletti , Veronica Piccialli , Antonio M. Sudoso

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) 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
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