Constructing geometric digital twins of highways at present still demands substantial human
effort. Unlike most previous work that uses deep learning models to segment point clouds of …

The lack of timely progress monitoring and quality control contributes to cost-escalation,
lowering of productivity, and broadly poor project performance. This paper addressed the …

The paper presents a novel method for automatically creating semantic digital models for
buildings in Manhattan environments from dense point cloud data. Unlike previous …

Existing buildings' geometry digitisation using Point Cloud Datasets is important. This is
evident given the lack of digital as-designed models for older buildings, which can serve as …

Digital twins have emerged as a crucial tool for the operation and maintenance of buildings
and infrastructure. A digital twin (DT) is a virtual replica of assets that provides valuable …

Digital twins for buildings can significantly reduce building operation costs. However,
existing methods for constructing geometric digital twins fail to model the complex geometry …

Purpose This study aims to introduce a new methodology for generating synthetic images for
facility management purposes. The method starts by leveraging the existing 3D open-source …

Point clouds, image data, and corresponding processing algorithms are intensively
investigated to create and enrich Building Information Models (BIM) with as-is information …

In the industrial sector, products evolve significantly over their operational life. A key
challenge has been maintaining precise, relevant engineering data. This paper explores the …

Abstract Digital Twins (DTs) have become as valuable tools for management, and operation
of assets. A main challenge, however, persists in the automated creation of high-quality …