| Project Reference: | ITP/004/23LP |
| Project Title: | Scan-to-BIM Automation System for Built Assets Digitalization in Hong Kong |
| Hosting Institution: | The University of Hong Kong (HKU) |
| Abstract: | BIM 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 awardwinning 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. |
| Project Coordinator: | Dr Fan Xue |
| Approved Funding Amount: | HK$ 5.21 M |
| Project Period: | 31 Mar 2023 - 31 Mar 2025 |
