Pedestrian Simulation – Improve services for digital building twin

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Siemens Knowledge Hub

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348,000

Published on June 29, 2020 10:49:52 PM ● Video Link: https://www.youtube.com/watch?v=LPTQKIWvAyE

Game:

The Pedestrian (2020)

Duration: 2:25

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When planning and constructing a building, we see the greatest challenge in the large number of actors which are involved in the process. On the one hand, they produce data, and on the other hand they also need data. Nowadays, the data is distributed across different silos but with a digital twin, the data can be brought together, linked and made accessible to everyone.
With a digital twin of a building, we can already simulate certain aspects of the building and recognize errors before the completion of a building: finding errors before constructing a building can avoid re-planning later in the operation phase, when it is expensive and time consuming to fix. An important topic in the design phase is the planning of optimal evacuation routes. We can look at the 3D building in virtual reality, plan the escape routes for this virtual building and can thus find the best evacuation route.
This approach reaches its limits in the case of complex buildings, because authorities do not have confidence, that an evacuation route calculated “by hand” will work e.g.. To support architects in the planning of evacuation routes, we took our pedestrian flow analysis, the “Crowd Control” System, developed here in Munich, Germany, at Corporate Technology. It offers the opportunity to insert building data of the planner as well as to simulate different use cases. The entire building is digitized from the ground up and then we optimized the building's evacuation by simulation. Such a simulation has the huge advantage that this evacuation plan works to get the people to their evacuation site safely.
The effort to create a digital twin for a building should not be underestimated. If used only in a single application, the effort required can be too daunting to gain benefits. Today, information about a building and its use is distributed across numerous systems. They are usually difficult to use together and have to be manually and repeatedly merged. A building twin automatically summarizes this data and adds further information based on its knowledge of the structure and use of the building. In operation, data from different disciplines can be easily connected to one another and data is available over long time periods, even for a large number of buildings. This enables the creation and use of new applications, e.g. for predictive maintenance, for operational optimization, but also for simulations with real-time data, for example to find the best evacuation route for the current location or distribution of people in the building or per floor.

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