Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …

Deep learning has been acknowledged as being robust in managing and controlling the
performance of construction safety. However, there is an absence of state-of-the-art review …

Purpose The purpose of this paper is to investigate the potential integration of deep learning
(DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an …

Spatial locations of personnel, equipment, and materials are constantly changing as
construction projects progress. The dynamic nature of the construction industry affects …

High-rise building fires can pose a significant threat to occupants and firefighters. The state-
of-the-art technologies such as sensor-based Internet of Things (IoT), Building Information …

The growing environmental concerns have emerged the necessity of sustainable waste
management of construction and demolition (C&D) wastes. This review explores the …

Visual data captured at construction sites is a rich source of information for the day-to-day
operation of construction projects. The development of deep-learning-based methods has …

Environmental effects may lead to cracking, stiffness loss, brace damage, and other
damages in bridges, frame structures, buildings, etc. Structural Health Monitoring (SHM) …

Low situational awareness contributes to safety incidents in construction. Existing Deep
Learning (DL)-based applications lack the capability to provide context-specific and …

Natural disasters can cause severe damages to civil infrastructure and lead to extensive
economic losses and casualties. To improve the emergency response capability of civil …