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PMC and City-Level Projects: Scan-to-BIM Services and Smart Cities

May 24, 2023

PMC and City-Level Projects: Scan-to-BIM Services and Smart Cities


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esmith |

PMC’s expertise lies in delivering city-scale projects that leverage scan-to-BIM services, thus enabling the development of smart cities. One of our latest projects, which spans fourteen city blocks in Washington, D.C., exemplifies PMC's proficiency in capturing, processing, and integrating vast amounts of data to cater to diverse analytical needs.

The Washington D.C. project involved 3D terrestrial scanning, photogrammetry, and traditional surveying in capturing the structures’ data in fourteen city blocks. The data captured included point cloud data and images that were then processed to create a highly detailed and accurate digital model of the structures.

Survey Control

One of the challenges of city-level projects is coordinating the survey teams and ensuring accuracy across a considerable distance. PMC has a team of experienced surveyors skilled in working with the latest technologies and can handle the logistics of large-scale projects. We employ various technologies and techniques such as GPS, total stations, and laser scanners to ensure accuracy across a considerable distance. This enables the surveying and capturing of data from multiple points across a large area and ensures that the data is accurate and consistent.

PMC is skilled in using survey control, which establishes a real-world coordinate system for the project and ensures that the captured data aligns with that coordinate system. This is crucial for ensuring accuracy in city-level projects where data is captured for analytical use cases. Our surveyors establish survey control points at strategic locations throughout the project site and use these points to align the data captured by the scan to BIM services.

Data Captured

  • 162 3D survey points on this project
  • 3435 panoramic images
  • 498 gigabytes of SLAM scanning (simultaneous localization and mapping)
  • Captured over 2,458,000 square feet of densely populated cityscape
  • 500,000 square feet of interior building space

Technology Used

  • NavVis VLX
  • 3 FARO Scanners,
  • Leica TS60 Total Station

Creating a Digital Model

PMC created a massing model, a simplified version of the digital model, which can be used for various analytical purposes such as energy analysis and simulations. This tool is intended to support decision-making and to optimize energy efficiency and identify opportunities and challenges for the city.

Using Scan-to-BIM technology, PMC captured a large amount of data in a short time to create a detailed digital model. The massing model was then generated from this model and used to make data-driven decisions to support smart city development.

The client also commissioned PMC to create LOD-200 level architecture and structural models for two addresses in the center of the project, in addition to capturing data from the fourteen city blocks. These models were integrated into the final master city model to provide more detail and accuracy for those specific locations. As a result, the final master city model contained a mixed level of BIM detail, with LOD-200 models providing more detail for specific locations and data from the city blocks providing a general level of detail for the rest of the project.

Conclusion

We provided the client with a detailed model of specific locations in the project while capturing and analyzing data from the entire project using a mixed level of BIM detail. This allowed us to create a model that met the client's specific needs and supported the decision-making process for the entire project. Our extensive experience in working with city-level projects across the country and internationally involves capturing and integrating large amounts of data for various analytical use cases, including pedestrian dynamics, energy analysis, sun study, and other simulations. This enables us to support city officials, architects, and engineers in making data-driven decisions and in the development of smart cities.

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