[HTML][HTML] Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications

SK Baduge, S Thilakarathna, JS Perera… - Automation in …, 2022 - Elsevier
This article presents a state-of-the-art review of the applications of Artificial Intelligence (AI),
Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in …

[HTML][HTML] AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

Y Himeur, M Elnour, F Fadli, N Meskin, I Petri… - Artificial Intelligence …, 2023 - Springer
In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …

A review of machine learning in building load prediction

L Zhang, J Wen, Y Li, J Chen, Y Ye, Y Fu, W Livingood - Applied Energy, 2021 - Elsevier
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …

Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption—A systematic review

M Khalil, AS McGough, Z Pourmirza… - … Applications of Artificial …, 2022 - Elsevier
The building sector accounts for 36% of the total global energy usage and 40% of
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …

[HTML][HTML] A global model of hourly space heating and cooling demand at multiple spatial scales

I Staffell, S Pfenninger, N Johnson - Nature Energy, 2023 - nature.com
Accurate modelling of the weather's temporal and spatial impacts on building energy
demand is critical to decarbonizing energy systems. Here we introduce a customizable …

Advanced controls on energy reliability, flexibility, resilience, and occupant-centric control for smart and energy-efficient buildings—a state-of-the-art review

Z Liu, X Zhang, Y Sun, Y Zhou - Energy and Buildings, 2023 - Elsevier
Advanced controls have attracted increasing interests due to the high requirement on smart
and energy-efficient (SEE) buildings and decarbonization in the building industry with …

Data-driven estimation of building energy consumption and GHG emissions using explainable artificial intelligence

Y Zhang, BK Teoh, M Wu, J Chen, L Zhang - Energy, 2023 - Elsevier
Energy consumption prediction is an integral part of planning and controlling energy used in
the building sector which accounts for 40% of the global energy consumption and a …

Application of machine learning in thermal comfort studies: A review of methods, performance and challenges

ZQ Fard, ZS Zomorodian, SS Korsavi - Energy and Buildings, 2022 - Elsevier
This paper provides a systematic review on the application of Machine Learning (ML) in
thermal comfort studies to highlight the latest methods and findings and provide an agenda …

A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems

TM Alabi, EI Aghimien, FD Agbajor, Z Yang, L Lu… - Renewable Energy, 2022 - Elsevier
The optimal co-planning of the integrated energy system (IES) and machine learning (ML)
application on the multivariable prediction of IES parameters have mostly been carried out …

On-demand monitoring of construction projects through a game-like hybrid application of BIM and machine learning

FP Rahimian, S Seyedzadeh, S Oliver… - Automation in …, 2020 - Elsevier
While unavoidable, inspections, progress monitoring, and comparing as-planned with as-
built conditions in construction projects do not readily add tangible intrinsic value to the end …