Digital Twin Use Case At El Paso International Airport

This thesis explores the potential of implementing Digital Twin technology in airports, with a concrete use case at the Innovation Factory at El Paso International Airport. The Digital Twin model was developed using project documentation and LiDAR scanning, resulting in point cloud datasets that served as the foundation for further analysis. A comparison was conducted between reality-captured data and the model created from project documentation, highlighting the presence of noise in the field data. This analysis revealed key challenges and identified opportunities to enhance efficiency through automation. Instead of relying on a resource-intensive manual process to clean point cloud datasets from noise, a future approach utilizing machine learning is proposed to streamline the point cloud processing workflow. The resulting Digital Twin model of the Innovation Factory demonstrates several valuable applications for the airport, including optimized electricity consumption and enhanced real estate management, and presents a solid framework for how this technology can be expanded and applied across the entire airport.