Digital Twin (DT) concept has recently emerged in civil engineering; however, some
problems still need to be addressed. First, DT can be easily confused with Building …

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 …

Building energy use is expected to grow by more than 40% in the next 20 years. Electricity
remains the largest energy source consumed by buildings, and that demand is growing. To …

The occupants' presence, activities, and behaviour can significantly impact the building's
performance and energy efficiency. Currently, heating, ventilation, and air-conditioning …

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 …

Purpose The purpose of this paper is 1) to investigate the effects on the crucial Industry 4.0
technological innovations that interact between the real and virtual worlds and that are …

Occupant behavior has been widely considered as one of the key influencing factors on
building energy consumption. The complexity of its formation mechanism and the dynamic …

The energy consumption of major equipment in residential and industrial facilities can be
minimized through a variety of cost-effective energy-saving measures. Most saving …

This study carries out a literature review on studies using machine learning (ML) models to
predict occupancy and window-opening behaviour and their application in smart buildings …

Building occupants are often assumed to follow deterministic schedules in building
performance simulation programs. Therefore, to accurately capture the dynamic nature of …