New AI chatbot aims to improve energy labeling of Danish buildings

Result

The project that developed the prototype of the chatbot will ensure that Danish buildings waste less energy, benefiting both the climate and financial savings. At the same time, it will optimize improvements made to buildings, ensuring that they are carried out in the most efficient and cost-effective way. It will also make the work easier for several stakeholders, such as the carpenter providing a quote for additional insulation, the bank advisor discussing potential energy improvements with a client, or the real estate agent presenting energy labels before a property can be put up for sale.

Challenge

The Danish Energy Agency's EMOWeb contains large amounts of publicly available data on energy labeling. However, the challenge is that much of the data is stored in file formats that are difficult to understand. At the same time, the vast amount of energy labeling data is not being utilized to improve the quality of energy labels for the Danish building stock. Energy consultants today rely on the knowledge they have gained through experience and competency development, but each individual consultant may have different areas of focus, meaning that there may be optimization opportunities that are overlooked.

Solution

By using Generative AI to analyze the available data, a chatbot will respond to how to optimize the energy labeling for a given building based on a comprehensive understanding of the entire dataset. This makes the process more efficient and the answers more qualified, as they are based on the information from the entire database, providing better conditions to predict the best path for improving a building's energy label.