Automated Scan to BIM of Existing Buildings (Building and MEP Components)

Building Information Models (BIM), particularly that of the Mechanical, Electrical and Plumbing (MEP) components, has many use cases. However, BIM of completed buildings, also known as the as-built BIM, are often not available or inaccurate.

While it is possible to build BIM retroactively, it is very challenging and labourious. The staff need to measure and determine the properties of everything in the building/infrastructure, then manually build the BIM and update the information.

Challenges

Archival drawings of existing buildings can provide important information, but they could be missing or damaged or outdated. LiDar scans can provide as-built point cloud data, but the conversion to distinct BIM elements remains difficult.

The challenge is to deliver a solution/product/platform that can make use of data from reality captures to automatically produce as-built BIM of existing assets’ selected objects (See Annex A) that satisfy JTC Model Content Requirement’s (MCR) as-built stage geometrical requirement.

1. For this challenge, the awarded vendor shall acquire all reality capture data (e.g. LiDAR point cloud) by themselves.
2. The awarded vendor's acquired reality capture data shall be accurately georeferenced.
3. The proposal shall clearly state the detailed methodology of processing reality capture data into compliant BIM models.
4. Applicant should indicate estimated commercial price of solution, cost of operation/maintenance and cost-benefit analysis of the solution in the proposal to achieve cost-effectiveness.
5. The solution shall be able to produce a coordinated and representative as-built BIM for a given set of scan data.
6. The produced BIM shall be in Revit and IFC format.
7. The produced BIM shall contain at least all selected objects (See Annex A) present in the set of scan data.
8. The produced BIM shall be made of clearly distinguished reconstruction of scanned objects.
9. The produced BIM shall be made of accurately categorized reconstruction of scanned objects.
10. The produced BIM shall meet or exceed JTC MCR's as-built stage geometrical requirement.
11. The produced BIM shall be accurately georeferenced.
12. The produced BIM's elements should be correctly connected where applicable.
13. The solution shall prompt warnings and suggestions whenever the scanned data is insufficient or inadequate to produce satisfactory BIM.
14. The ownership of the relevant data, such as the produced BIM, shall be given to the Corporation.
15. The solution shall contain reasonably clear and comprehensive user guide(s).
16. The solution's platform shall be reasonably accessible, and user-friendly.
17. The solution shall produce the required BIM reliably.
18. The solution shall be fully automated and available for use any time.
19. The solution's rate of BIM production shall be reasonably fast (e.g. 20 min per 100m² GFA)

A cloud based platform powered by machine learning and linked to BIM authoring software.

Applicants are encouraged to propose phases of development and delivery. Total project period shall not exceed 12 months.

A reference timeline is as follows:

1. 1 months: To acquire and process reality capture data.
2. 3 months: To develop identification and classification algorithm.
3. 4 months: To work on backend platform for point cloud to BIM object conversion.
4. 2 months: To work on frontend platform and user interface.
5. 2 months: To wrap up any outstanding matters.

Concurrent work may be necessary.

Evaluation Criteria

• Time to implementation; Impact factor.
• Price (40%): Value-for-money; level of co-funding.
• Quality(60%): Proposal’s scope of work; Operational feasibility for deployment at the targeted Estate or Facility; Minimal/no nuisance and disruption to operations and/or tenants; Cost benefit analysis; Relevant experiences required to develop and deploy; Commercialisation and/or Implementation plans.

Testbed/ Trial Site

The necessary reality capture and testbed will be at a JTC property. Details will be given to the awarded company.

Video of Briefing

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