Timely and accurate fault diagnosis (FD) in building energy systems (BESs) can promote
energy efficiency and sustainable development. Especially the heating, ventilating, and air …

Although deep learning models have been rapidly developed, their practical applications
still lag behind for building energy systems (BESs) fault diagnosis. Owing to the “black-box” …

As with economic growth and urbanization, there is a significant impact on energy
consumption in residential and commercial buildings. Analyzing the energy consumption of …

Abstract Smart Island Energy Management (SIEM) heralds a new era in sustainable island
energy utilization, orchestrating an innovative system that optimizes efficiency and …

In this paper, we discuss the usage of smart and machine learning based model to aid
children with autism. Children with autism require constant care because you never know …

Rural buildings have high optimization potential as a major source of carbon emissions.
However, the current research on carbon reduction in rural buildings is rough and lacks …

Technology makes cleaning more intelligent and accessible. Future energy sources will
become saturated and run out. Instead of using nonrenewable energies, consider solar …

Machine learning techniques are widely applied in the field of building energy analysis to
provide accurate energy models. The majority of previous studies, however, apply single …

Earthquake is one of the most devastating natural catastrophes, mainly because there is
rarely any advance notice and hence little opportunity to react. This makes the issue of …

Timely and accurate fault diagnosis in building energy systems is crucial for improving the
energy efficiency of equipment and realizing energy savings. With the widespread use of …