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

Integration of renewable energy and optimization of energy use are key enablers of
sustainable energy transitions and mitigating climate change. Modern technologies such the …

Applying artificial intelligence (AI), machine learning (ML), and big data to natural resource
management (NRM) is revolutionizing how natural resources are managed. To gain more …

The fusion of Internet of Things (IoTs) and computational intelligence makes it possible to
increase energetic efficiency of our homes. Connected devices can be optimally adjusted to …

The utilization of machine learning (ML) techniques is increasingly prevalent in the domain
of building performance evaluation. This trend is primarily driven by ML's capacity to capture …

Abstract The use of Artificial Intelligence (AI) technologies in buildings can assist in reducing
energy consumption through enhanced control, automation, and reliability. This review aims …

This paper reviews the state-of-the-art smart building research by a bibliometric analysis, a
content analysis, and a qualitative review. The bibliometric analysis of 364 academic papers …

Purpose The changes brought by Industry 4.0 go beyond transformations in the industrial
environment. The increasingly frequent digitization and robotization of activities is not only …

Buildings account for a significant amount of energy consumption leading to the issues of
global emissions and climate change. Thus, energy management in a building is …

Point cloud data can accurately and intuitively reflect the spatial relationship between the
coal wall and underground fully mechanized mining equipment. However, the indirect …