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 …

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 …

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 …

Nowadays, analyzing, detecting, and visualizing abnormal power consumption behavior of
householders are among the principal challenges in identifying ways to reduce power …

This article reviews the current research on the development and implementation of
automated fault detection and diagnostics (AFDD) technology for building systems. This …

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 …

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 …