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Digital twinning for smart real estate management

Reference number
Coordinator RESPACE AB
Funding from Vinnova SEK 300 000
Project duration September 2020 - December 2020
Status Completed
Venture Innovative Startups
Call Innovative Startups step 1 spring 2020

Important results from the project

Digital twins are digital models of physical objects such as real estate. The digital twin enables completely new ways to plan, monitor and manage a property. The digital twin is central to digital real estate management, to great advantage for real estate managers and tenants. In this project, we have further developed our digital twin ReSpace Twin which in a simple and intuitive way integrates 3D data (BIM) and sensor data (IoT) in both AR and VR. Using ReSpace Twin, we have created a digital twin for the building A Working Lab (AWL) in Gothenburg.

Expected long term effects

Through this project, we have developed an easy-to-use and integrated system that makes it possible to easily create powerful and easy-to-use digital twins of real estate. By making all data available to many users in AR and VR, completely new possibilities for digital real estate management are created. We are now launching our solution ReSpace Twin for digital twins to a broad market with the main focus on digital real estate management. For inquiries and more information about our digital twin, visit our website https://respace.ai/

Approach and implementation

The project has been carried out in close collaboration with our partners Akademiska Hus and Johanneberg Science Park. Following an initial survey of customer needs, we have developed a prototype of the digital twin. The prototype has then been tested and evaluated together with end-users. Based on feedback from users, our solution has since been further developed and refined into an integrated and complete solution for digital twins of real estate.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 24 January 2022

Reference number 2020-01171