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High-Frequency Digital Twins: Unlocking the Power of Jobsite

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Jeevan Kalanithi, CEO of Openspace, joined our AI4AECO event in June 2021 and talked about the application of digital twins in construction sites. Jeevan elaborated on the definition of digital twins, with examples, and then discussed the Openspace technology. This report provides a high-level summary of what Jeevan shared about the applications of digital twins during the construction process.

What is a digital twin?

The construction industry borrowed the term “Digital Twin”, which refers to a virtual representation of a process or physical object, from the manufacturing industry. A digital twin model enables us to have a digital representation of something (e.g., construction process, building operation, physical object) by capturing and processing data.

When creating digital twins of your project during construction, you need to consider three main properties (see in Figure 1):

Completeness: What is the coverage of your digital twin compared to the whole project? Does it cover the entire physical object you are interested in or just a part of it? For example, if you laser scan just the first floor of a four-story building, then the completeness of your digital twin is about 25% coverage.

Frequency: How often do you update your digital twin? To create the as-built model of your project during the time of construction, you need to frequently capture and record the physical objects constructed on the site.

Density: What is the resolution of what you have captured? To have a better visualization of the whole construction process, you need to get every point mapped into your digital twin. If you have a complete and frequently captured digital twin with a very low density, your digital twin may not have everything that happened during the project.

Figure 1- Three Main Digital Twins Properties

Why does Digital Twin Matter?

By comparing the progress of as-designed and as-built during the construction of buildings, construction professionals can track the current status of projects in real-time or even look back at the previous steps of the process. By doing so, the team can mitigate risks, as well as save on time and resource costs.

What are the Technology Limitations in Creating Digital Twins?

Ideally, we need technology to create high-frequency and high-resolution digital twin solutions for the entire construction project. While many technologies (e.g., Leica, Geosystems, Topcon) provide complete and high-density digital twin models, they have a low frequency. One of the main reasons for the low frequency is that we need an expert operator to do the scan every day, which is impractical, laborious, and costly. On the contrary, some technologies, like smartphones, seem simple to operate, but their coverage is spotty, so they can only provide a low-density model. And it is almost as impractical for construction professionals to constantly take pictures of every corner of a building. Thus, most of the available digital twin technologies do not satisfy all three essential properties (axes) for creating an efficient digital twin.

How does Openspace Bridge the Technology Gap?

Openspace enables construction professionals to walk on the construction job site and collect high-frequency, complete, and high-resolution digital twins via the images taken by 360° cameras mounted on their helmet. All the captured site data is processed on Openspace’s platform, which has a BIM viewer capability (in browser) to visualize details and inspect sites at any time, without needing to travel to the job site. In addition, with the power of cloud computing, computer vision, and AI, Openspace can provide insights into how on track the project is compared to the planned schedule.

Openspace is available globally and has customers all around the world (e.g., UK, Australia, China, Singapore, Japan, and many more.) To sum up, the Openspace platform allows us to leverage the power of digital twins to unlock a ton of values that are not possible when we have infrequent, spotty information.

What are the Key Takeaways?

The top three key takeaways were:

  1. Digital twin solutions are like a bridge between as-designed models and as-built.
  2. The three essential properties of digital twin solutions are completeness, frequency, and density.
  3. Not all existing digital twin solutions can support the frequency of digital twins creation due to training, and a laborious and costly execution process.


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