A completed innovation project has developed a new AI-based chatbot that analyzes energy label data to optimize energy improvements in Danish buildings. The potential is less energy waste and lower costs.
Energy consumption in buildings accounts for almost 40% of Denmark's total energy consumption, and there is a great potential for energy efficiency improvement, especially in existing properties.
This potential can be identified, among other things, via the statutory energy label. The enormous amounts of data in the energy label database therefore have great potential for identifying and qualifying opportunities for energy improvements.
A recently completed innovation project, “Better utilization of data from energy labels with new AI analysis techniques,” has developed a prototype of an AI-based chatbot that can analyze energy label data and provide precise recommendations on how the energy label of a given building can be optimized.
The project was carried out by the Alexandra Institute, 4B Consulting and CB Group. The project is supported by the Danish Business Development Agency with funds from the European Union.
Artificial intelligence and large datasets
By using generative AI to analyze the available data, the chatbot can answer how the energy label can be optimized for a given building based on a comprehensive understanding of the large dataset. This makes the process more efficient and the answers more qualified, as they are based on the information in the entire database. This creates better conditions for predicting the best path to an improved energy label.
The potential of the prototype is that Danish buildings can now reduce energy waste, which is beneficial for both the climate and the economy. At the same time, the improvements made to the buildings are optimized so that they are carried out in the most efficient and cost-effective way. This will make the work easier for several parties, including carpenters, bank advisors and real estate agents.
Jakob Nørby is a data-driven energy advisor and founder of 4B Consulting, which is part of the innovation project. He says:
"Energy Cluster Denmark has been a great supporter of the project and has quickly seen its value. It has been exciting to challenge the current approach to energy labeling and utilize the existing data. As a society, we must accelerate the green transition of our building stock, and therefore we should utilize all available data. The next step is to secure funding to further develop our prototype for the benefit of everyone who works with buildings.”
Webinar: AI and “big data” in energy labelling
In an upcoming webinar, participants will gain insight into the EMO database and the many possibilities that lie in energy labelling data. In addition, the project results and the prototype of the AI tool will be presented, and there will be a dialogue about municipal and commercial perspectives as well as potential project ideas.
Register here: Better use of energy label data via “big data” access and chatbot » Energy Cluster Denmark
