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Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
(
Elsevier
, 2021 , Article Review)
Enormous amounts of data are being produced everyday by sub-meters and smart sensors installed in residential buildings. If leveraged properly, that data could assist end-users, energy producers and utility companies in ...
A survey of recommender systems for energy efficiency in buildings: Principles, challenges and prospects
(
Elsevier
, 2021 , Short Survey)
Recommender systems have significantly developed in recent years in parallel with the witnessed advancements in both internet of things (IoT) and artificial intelligence (AI) technologies. Accordingly, as a consequence of ...
Blockchain-based recommender systems: Applications, challenges and future opportunities
(
Elsevier
, 2022 , Article Review)
Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of ...
Techno-economic assessment of building energy efficiency systems using behavioral change: A case study of an edge-based micro-moments solution
(
Elsevier
, 2022 , Article)
Energy efficiency based on behavioral change has attracted increasing interest in recent years, although, solutions in this area lack much needed techno-economic analysis. That is due to the absence of both prospective ...
Building power consumption datasets: Survey, taxonomy and future directions
(
Elsevier
, 2020 , Article Review)
In the last decade, extended efforts have been poured into energy efficiency. Several energy consumption datasets were henceforth published, with each dataset varying in properties, uses and limitations. For instance, ...
Robust event-based non-intrusive appliance recognition using multi-scale wavelet packet tree and ensemble bagging tree
(
Elsevier
, 2020 , Article)
Providing the user with appliance-level consumption data is the core of each energy efficiency system. To that end, non-intrusive load monitoring is employed for extracting appliance specific consumption data at a low cost ...
Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier
(
Elsevier
, 2021 , Article)
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 ...
A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks
(
Springer
, 2020 , Article)
Nowadays, analyzing, detecting, and visualizing abnormal power consumption behavior of householders are among the principal challenges in identifying ways to reduce power consumption. This paper introduces a new solution ...
Interactive visual study for residential energy consumption data
(
Elsevier
, 2022 , Article)
Interactive data visualization tools for residential energy data are instrumental indicators for analyzing end user behavior. These visualizations can be used as continuous home feedback systems and can be accessed from ...
Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction
(
Elsevier
, 2020 , Article)
Recently, a growing interest has been dedicated towards developing and implementing low-cost energy efficiency solutions in buildings. Accordingly, non-intrusive load monitoring has been investigated in various academic ...