[HTML][HTML] Technologies for digital twin applications in construction
The construction industry is facing enormous pressure to adopt digital solutions to solve the
industry's inherent problems. The digital twin has emerged as a solution that can update a …
industry's inherent problems. The digital twin has emerged as a solution that can update a …
Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
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 …
about one-third of greenhouse gases. In the last few years, machine learning has achieved …
[HTML][HTML] A review on occupancy prediction through machine learning for enhancing energy efficiency, air quality and thermal comfort in the built environment
The occupants' presence, activities, and behaviour can significantly impact the building's
performance and energy efficiency. Currently, heating, ventilation, and air-conditioning …
performance and energy efficiency. Currently, heating, ventilation, and air-conditioning …
Reinforcement learning for building controls: The opportunities and challenges
Building controls are becoming more important and complicated due to the dynamic and
stochastic energy demand, on-site intermittent energy supply, as well as energy storage …
stochastic energy demand, on-site intermittent energy supply, as well as energy storage …
[HTML][HTML] Review of urban building energy modeling (UBEM) approaches, methods and tools using qualitative and quantitative analysis
The world has witnessed a significant population shift to urban areas over the past few
decades. Urban areas account for about two-thirds of the world's total primary energy …
decades. Urban areas account for about two-thirds of the world's total primary energy …
[HTML][HTML] Application of deep learning in facility management and maintenance for heating, ventilation, and air conditioning
Despite the promising results of deep learning research, construction industry applications
are still limited. Facility Management (FM) in construction has yet to take full advantage of …
are still limited. Facility Management (FM) in construction has yet to take full advantage of …
Applications of machine learning to BIM: A systematic literature review
Abstract As Building Information Modeling (BIM) workflows are becoming very relevant for
the different stages of the project's lifecycle, more data is produced and managed across it …
the different stages of the project's lifecycle, more data is produced and managed across it …
[HTML][HTML] Virtual sensing in intelligent buildings and digitalization
S Yoon - Automation in Construction, 2022 - Elsevier
Virtual sensing technologies have a huge potential in an informative and reliable sensing
environment, which is essential to provide and maintain intelligent services in building life …
environment, which is essential to provide and maintain intelligent services in building life …
Data-driven building energy modelling–An analysis of the potential for generalisation through interpretable machine learning
Data-driven building energy modelling techniques have proven to be effective in multiple
applications. However, the debate around the possibility of generalisation is open …
applications. However, the debate around the possibility of generalisation is open …
Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles
Implementing machine-learning models in real applications is crucial to achieving intelligent
building control and high energy efficiency. Over the past few decades, numerous studies …
building control and high energy efficiency. Over the past few decades, numerous studies …