Imagine having a high-tech SimCity for a real neighborhood that doesn't just show buildings, but also tracks energy and traffic in real-time. It lets city planners test out new green energy ideas in a virtual world before spending money to build them in real life. By adding human and social data to the map, it ensures that new energy projects actually work for the people living there.
City planners often make suboptimal decisions for green energy districts because they rely on narrow data (only energy or traffic) and ignore social or economic factors. This leads to expensive mistakes when deploying sustainable infrastructure in the real world.
A multi-dimensional Local Digital Twin (LDT) featuring a 3D city model, an urban data platform, and specific modules for solar potential, traffic flow, and air quality.
If you are a municipal planning agency dealing with the complexity of transforming a district to be climate neutral — this project developed a multi-dimensional Local Digital Twin that allows you to test decisions in a virtual environment before ground deployment.
If you are a solar installation firm dealing with identifying the most efficient locations for panels across a city — this project developed a solar module within a 3D city model that explores the solar potential of different rooftops in Aarhus.
If you are an air quality monitoring firm dealing with fragmented urban pollution data — this project developed an air quality module and an urban data platform for real-time data management to visualize pollution levels.
Based on available project data, no pricing or cost structures are mentioned; the project is currently in the development and demonstration phase.
Yes, the project specifically addresses scalability issues across the 80,000 municipalities in the EU27 to ensure solutions can be replicated across different physical and social structures.
Based on available project data, specific licensing terms are not provided, though the prototype is currently accessible via a public URL.
It uses the Civora platform to store and continuously update existing models and datasets, combining low- and high-velocity data.
The project period runs from 2024-01-01 to 2026-12-31, with future deliverables including Load Forecasting, Climate Risk, and Indoor Climate models.
The consortium is well-balanced for technology transfer, featuring 13 partners from 6 countries. With a 46% industry ratio (6 industrial partners, 5 of which are SMEs), the project is heavily geared toward practical application rather than pure academic research, supported by 2 universities and 2 research centers.
Contact Danmarks Tekniske Universitet (DTU) regarding the LDT-PED modeling tools.
Contact us to find a partner for replicating this Digital Twin in your municipality.
