Summary: Integrates LiDAR data, 3D models, and GIS asset layers to create a digital representation of real-world infrastructure for visualization, monitoring, and spatial analysis.
Detailed Description: The project focuses on developing a 3D digital twin of infrastructure by integrating terrestrial LiDAR point clouds, 3D mesh models, and GIS datasets. The workflow includes point cloud cleaning and registration, 3D model generation and refinement, infrastructure feature extraction, and spatial alignment of assets such as buildings, roads, streetlights, vehicles, and other campus facilities. The resulting digital environment supports infrastructure visualization, asset identification, spatial data integration, and digital campus management.
Status: Ongoing — LiDAR data processing, 3D mesh refinement, GIS asset extraction, and integration for digital twin visualization.
Research Area: Digital Twin Technology, 3D GIS, LiDAR-Based Infrastructure Modeling, Smart Campus, Geospatial Data Integration.
Technology: Terrestrial LiDAR, Point Cloud Processing, MicroStation, TerraScan, CloudCompare, Blender, ArcGIS Pro, Shapefiles, 3D Modeling.
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