PLYTEQ
Fighting climate change through innovation
36% of the energy consumption in Germany is caused by the operation of existing buildings. Optimising building operation therefore seems like a good idea. But where exactly does this optimisation potential lie?
The current status of the building must first be recorded and this is not so easy, especially in existing buildings. Although various technical systems provide data points on, for example, the running times of the systems and current temperatures, they are described so heterogeneously that a high level of manual engineering effort is required for data preparation/mapping for applications.
We solve this problem with our AI algorithm and create a fully automated digital twin of existing buildings. A monitoring system then shows where the optimisation potential lies and how we can implement it. Simply operate buildings more sustainably!
Significant energy savings potential with the digital AI twin
Our solution is based on seven years of research work at the TH Köln. We collect the operating data of buildings with our edge-device, process it automatically using our developed AI and thus automatically generate digital twins of the buildings.
These form the basis for applications in the area of facility management, such as our technical monitoring. Energy and performance-related weak points in the building can be detected and optimised - and all of this is very simple and requires no configuration effort.
How did you get together as a team?
We have known each other for many years through our joint work in the research team at the Laboratory for Building Automation and Control Technology at the TH Köln.
This is where research work, scientific exchange, dialogue with users and one or two Kölsch together have resulted in ideas and visions for improving building operation. And we now want to realise these visions together!
What are you studying/working or what have you studied?
All three of us studied energy and building technology engineering and specialised in building automation and control technology. In our research, we then specialised in different areas.
Max researched the interoperability of heterogeneous systems in his PhD and developed the AI algorithm.
Björn is a specialist in the field of embedded systems and data communication and Alina focused on the AI areas of language processing and optimisation through reinforcement learning.
What has Gateway ESC helped you with?
Whichever the topic, the exchange and support from Gateway help us enormously. Financing and making contacts are particularly important at the beginning, and through pitch events and individual consultations with Gateway we have been able to reach our first milestones !