NILM applications: Literature review of learning approaches, recent developments and challenges
This paper presents a critical approach to the non-intrusive load monitoring (NILM) problem,
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
Review on deep neural networks applied to low-frequency nilm
This paper reviews non-intrusive load monitoring (NILM) approaches that employ deep
neural networks to disaggregate appliances from low frequency data, ie, data with sampling …
neural networks to disaggregate appliances from low frequency data, ie, data with sampling …
Requirements engineering for artificial intelligence systems: A systematic map** study
Context: In traditional software systems, Requirements Engineering (RE) activities are well-
established and researched. However, building Artificial Intelligence (AI) based software …
established and researched. However, building Artificial Intelligence (AI) based software …
Towards trustworthy energy disaggregation: A review of challenges, methods, and perspectives for non-intrusive load monitoring
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 …
consumption into its individual sub-components. Over the years, signal processing and …
A synthetic energy dataset for non-intrusive load monitoring in households
Research on smart grid technologies is expected to result in effective climate change
mitigation. Non-Intrusive Load Monitoring (NILM) is seen as a key technique for enabling …
mitigation. Non-Intrusive Load Monitoring (NILM) is seen as a key technique for enabling …
Intelligent home energy management using Internet of Things platform based on NILM technique
Due to the continuous increase in the global energy demand, it is essential to find solutions
to improve energy efficiency. Non-intrusive load monitoring (NILM) is one of the most …
to improve energy efficiency. Non-intrusive load monitoring (NILM) is one of the most …
[HTML][HTML] Requirements practices and gaps when engineering human-centered Artificial Intelligence systems
Abstract Context: Engineering Artificial Intelligence (AI) software is a relatively new area with
many challenges, unknowns, and limited proven best practices. Big companies such as …
many challenges, unknowns, and limited proven best practices. Big companies such as …
A critical review of state-of-the-art non-intrusive load monitoring datasets
HK Iqbal, FH Malik, A Muhammad, MA Qureshi… - Electric Power Systems …, 2021 - Elsevier
Abstract Nowadays Non-Intrusive Load Monitoring (NILM) is considered a hot topic among
researchers. The energy disaggregation datasets are used as the benchmark to validate the …
researchers. The energy disaggregation datasets are used as the benchmark to validate the …
What's up with requirements engineering for artificial intelligence systems?
In traditional approaches to building software systems (that do not include an Artificial
Intelligent (AI) or Machine Learning (ML) component), Requirements Engineering (RE) …
Intelligent (AI) or Machine Learning (ML) component), Requirements Engineering (RE) …
The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea
AMI has been gradually replacing conventional meters because newer models can acquire
more informative energy consumption data. The additional information has enabled …
more informative energy consumption data. The additional information has enabled …