BIMcollab Twin | Digital twin as a live real estate file
Complete digital property files with (static) information about buildings are nothing new. But an increasing number of systems can now also process dynamic sensor information of a building in property files and visualize this in models. This contributes enormously to the controllability of the indoor climate of buildings, partly thanks to signaling and control of installations. And how great would it be if a building could be ‘self-managing’? Developments in the field of Artificial Intelligence and digital twins are coming.
A digital twin is the digital version of a real building. Because more and more buildings are equipped with sensors that send data to a digital twin, property owners can get a lot of real-time information about the building from that digital twin. Information about the living environment in rooms or about objects in a building. Think of the number of hours a certain lamp has been burning or the amount of fresh air that flows through ventilation ducts in certain rooms. But how are you going to process all that information and connect it with static information from your designs, models and processes? How will you secure and store this information?
Sensors for signaling living environment
Let’s look at ventilation systems. These are getting media attention in relation to the ventilation of offices and schools. In new construction projects, a fully automatic ventilation system is built-in in the design, but in 90 percent of existing buildings, a reference value is the basis for this design, for example for controlling the ventilation systems. This is because most buildings have a heating and climate system that is designed and set according to reference values as stated in the Schedule of Requirements. The system therefore does not work from factual measured values like CO2 and temperature, but from static determined values. As a result, in undesirable circumstances, intervention is often (too) late and sometimes provides too much or too little ventilation. After all, the system is not properly tuned to the required temperature and ventilation. This also leads to unnecessary energy consumption.
Doing nothing is not an option
Purchasing a new climate system for a new construction or replacing an outdated system during renovation is expensive and, moreover, a renovation has a significant impact on an organization. Signaling systems are relatively inexpensive these days and the signaling options are increasing thanks to smart innovations. You can already provide insights into whether the CO2 content is too high or will be too high in the near future and whether action is required. In the example of ventilation, a system can automatically control whether the heating should be turned up or down.
What’s next? Predictive Digital Twin!
The innovation of digital twins is fast. In the near future you will not only be able to signal, but installation systems of buildings can also be controlled automatically from countless sensors. They thus contribute to an optimal indoor climate. Developments are even moving towards the Predictive Digital Twin in which sensors not only control, but even predict the smartest moment to start the heating (bad weather is coming), service the air treatment (there have already been x number of hours at maximum treated air and the filters x must be replaced within y days). Or; it is necessary to replace the lighting in rooms x, y and z on floors 1, 5 and 7, because the maximum number of burning hours will be reached in 10 days. The system can also automatically send a work order to a technician, who can carry out his job and report when he is finished. The system will then be updated and the property owner can count on the new parameters from that moment on.
Now you may think: yeah right, this is all in the future. To a certain extent. There are already Proofs of Concept in various buildings like The Edge in Amsterdam. Smart building solutions are ideal for property managers who place a high priority on sustainability. Don’t forget how close the future is.