DecarbonAIte

Urban Digital Twins

The building sector has a huge potential to save greenhouse gas emissions. Large scale renovations are urgently needed to meet Sweden’s climate goal for 2045. One barrier is the manual, time consuming planning of renovation measures. Digital twins of cities can provide a good basis for efficient renovation planning and decision-making support.

However, data needed for energy simulation such as windows or u-values of the building envelope are currently missing. The aim of this project is to adapt and apply machine learning to extract features from publicly available databases to enrich urban digital twin models and provide optimized renovation measures for decision-support.

Real estate managers and municipalities will directly benefit from the decision-support tool and a better digital platform to manage the buildings. In the long term, the project contributes to increasing the renovation rate and achieving the climate goals. The enriched digital twins also provide numerous benefits beyond renovation planning.

Watch our project video

Do you want to know more?

Dag Wästberg

Data scientist, Geodata specialist, MSc

Jens Olsson

Scientific programmer, PhD, MSc Engineering, MSc Architecture

Siddhartha Kasaraneni

Data Scientist, Software Developer, MSc

Bernd Ketzler

Group manager Applied AI

More projects
Project

PLA bio-based plastics from secondary raw materials

The purpose of this project is to develop a techno-economically viable production route for PLA, Polylactic acid, from second generation raw materials such as side streams from the…

Project

SpårKons

In this project we place the users of the product pass and their needs in the centre. The aim is to increase the insight regarding what product information that is relevant, for th…

Project

AutoWEEEdakt II – Automatic AI based WEEE recognition system

In 2020, the EU recycled 4.7 million tons of electronic waste with a low collection rate. In the AutoWEEEdakt II project, we employ artificial intelligence to enhance sorting and i…