Deep learning for anomaly detection in multivariate time series: Approaches, applications, and challenges
Anomaly detection has recently been applied to various areas, and several techniques
based on deep learning have been proposed for the analysis of multivariate time series. In …
based on deep learning have been proposed for the analysis of multivariate time series. In …
[HTML][HTML] Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
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 …
installed in residential buildings. If leveraged properly, that data could assist end-users …
Anomaly detection for IoT time-series data: A survey
Anomaly detection is a problem with applications for a wide variety of domains; it involves
the identification of novel or unexpected observations or sequences within the data being …
the identification of novel or unexpected observations or sequences within the data being …
Deep learning for anomaly detection: A survey
R Chalapathy, S Chawla - arXiv preprint arXiv:1901.03407, 2019 - arxiv.org
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …
research areas and application domains. The aim of this survey is two-fold, firstly we present …
A novel approach for detecting anomalous energy consumption based on micro-moments and deep neural networks
Nowadays, analyzing, detecting, and visualizing abnormal power consumption behavior of
householders are among the principal challenges in identifying ways to reduce power …
householders are among the principal challenges in identifying ways to reduce power …
[HTML][HTML] An ensemble learning framework for anomaly detection in building energy consumption
During building operation, a significant amount of energy is wasted due to equipment and
human-related faults. To reduce waste, today's smart buildings monitor energy usage with …
human-related faults. To reduce waste, today's smart buildings monitor energy usage with …
Smart power consumption abnormality detection in buildings using micromoments and improved K‐nearest neighbors
Y Himeur, A Alsalemi, F Bensaali… - International Journal of …, 2021 - Wiley Online Library
Anomaly detection in energy consumption is a crucial step towards developing efficient
energy saving systems, diminishing overall energy expenditure and reducing carbon …
energy saving systems, diminishing overall energy expenditure and reducing carbon …
[HTML][HTML] Anomaly detection based on machine learning in IoT-based vertical plant wall for indoor climate control
Indoor climate is closely related to human health, comfort and productivity. Vertical plant wall
systems, embedded with sensors and actuators, have become a promising application for …
systems, embedded with sensors and actuators, have become a promising application for …
Development and implementation of automated fault detection and diagnostics for building systems: A review
This article reviews the current research on the development and implementation of
automated fault detection and diagnostics (AFDD) technology for building systems. This …
automated fault detection and diagnostics (AFDD) technology for building systems. This …
Machine learning for smart building applications: Review and taxonomy
The use of machine learning (ML) in smart building applications is reviewed in this article.
We split existing solutions into two main classes: occupant-centric versus energy/devices …
We split existing solutions into two main classes: occupant-centric versus energy/devices …