This paper presents a comprehensive understanding of current digital twin (DT)
implementations in the construction industry, along with providing an overview of …

With increasing interest in automatic and intelligent systems to enhance the building and
construction industry, digital twins (DT) are gaining popularity as cost-effective solutions to …

Digital twin (DT) has been moving progressively from concept to practice for bridge
operation and maintenance (O&M), but its issues of data synchronization and fault tolerance …

The digital twin (DT) represents a powerful tool for advancing construction industry to
provide a cyber–physical integration that enables real-time monitoring of assets and …

The construction industry has traditionally been slow to adopt digital technology, resulting in
inefficient workflows, frequent cost overruns, and delays. Moreover, its fragmented structure …

The study presents the data-driven applications of continuous wavelet transforms (CWT),
orbit-shaped analysis and convolutional neural networks (CNN) using GoogLeNet for …

This paper focuses on designing a Digital Twin infrastructure that supports an agile-based
Artificial Intelligence Internet of Things (AIoT) system for intelligent fish farming in …

Using deep learning approaches to identify and locate defects in composite structures made
of Carbon Fiber Reinforced Plastics (CFRP) is becoming increasingly popular. However …

The emergence of digital twins has ushered in a new era in civil engineering with a focus on
achieving sustainable energy supply, real‐time sensing, and rapid warning systems. These …

Artificial intelligence algorithms employed for classifying excavator-related activities
predominantly rely on sensors embedded within individual machinery or computer vision …