- Advising on best-fit BIM objects for 3D scanning technology;
- Guiding the integration of scanned data into BIM models;
- Offering statistical recommendations for model quality control and validation;
- Support design collaboration and decision-making within BIM environments.
- Plugins for BIM consultant (AUTODESK Revit);
- Plugins for BIM regulator (OpenBIM);
- Plugins for CIM consultant (ArcGIS Pro).
- Access to a dedicated team of experts for continuous support throughout the project lifecycle, including training and guidance on best practices for using Scan-to-BIM software and tools;
- Customized, one-stop solutions tailored to specific project needs and requirements.
BIM (building information modeling) is the key to construction digitalization. Scan-to-BIM involves the technique of surveying and reconstructing a digital representation of an existing building condition with its functional and physical attributes. The Scan-to-BIM has a huge emerging market of built assets digitalization, but has been hindered by low productivity (slow and costly manual work) and applicability (low-level object semantics, no Hong Kong context, huge file size and without texture). By solving/easing the pains, this R&D project aims to develop a Scan-to-BIM Automation System (SBASE) for built assets digitalization in Hong Kong.
As a new Scan-to-BIM paradigm, SBASE aims to (1) double the productivity: automated point segmentation and 3D BIM object fitting; solidly based on our award-winning algorithms; and deep learning models trained for Hong Kong’s projects datasets, and (2) create new values in applicability: 3 types of new functions for built assets, including verification, objects listing and checking, lightweight textured CIM output.
The critical value and urgency for SBASE can be gauged from committed strategies and recent initiatives. The proposed project is firmly built upon award-winning* algorithms and R&D strengths accumulated among the applicant and collaboration departments at the University of Hong Kong. It will help Hong Kong to strengthen its smart construction and digitalization by continuously devising innovations and technologies.
2024
ISPRS Journal of Photogrammetry and Remote Sensing2023
Automation in Construction2022
Landscape and Urban Planning2022
Research Companion to Building Information Modeling
