  Digital Twin is an emerging technology at the forefront of Industry 4.0, with
the ultimate goal of combining the physical space and the virtual space. To
date, the Digital Twin concept has been applied in many engineering fields,
providing useful insights in the areas of engineering design, manufacturing,
automation, and construction industry. While the nexus of various technologies
opens up new opportunities with Digital Twin, the technology requires a
framework to integrate the different technologies, such as the Building
Information Model used in the Building and Construction industry. In this work,
an Information Fusion framework is proposed to seamlessly fuse heterogeneous
components in a Digital Twin framework from the variety of technologies
involved. This study aims to augment Digital Twin in buildings with the use of
AI and 3D reconstruction empowered by unmanned aviation vehicles. We proposed a
drone-based Digital Twin augmentation framework with reusable and customisable
components. A proof of concept is also developed, and extensive evaluation is
conducted for 3D reconstruction and applications of AI for defect detection.

Computer Vision and Pattern Recognition;Artificial Intelligence;Human-Computer Interaction