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 …

The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …

Future buildings will offer new convenience, comfort, and efficiency possibilities to their
residents. Changes will occur to the way people live as technology involves people's lives …

A Virtual power plant is defined as an information and communications technology system
with the following primary functionalities: enhancing renewable power generation …

The use of AI technologies in Smart Buildings is increasing as there are wide-scale benefits
that can be derived from improving the efficiency of a building's operation and management …

Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …

Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit
about one-third of greenhouse gases. In the last few years, machine learning has achieved …

With ever-rising energy demand and diminishing sources of inexpensive energy resources,
energy conservation has become an increasingly important topic. Building heating …

In a digitalized era and with the rapid growth of computational skills and advancements,
artificial intelligence and Machine Learning uses in various applications are gaining a rising …

In recent years, research on convolutional neural networks (CNN) and recurrent neural
networks (RNN) in deep learning has been actively conducted. In order to provide more …