Imagine having a high-tech SimCity for a real town that actually predicts the future. It uses smart AI to show how adding more trees or changing bus routes will lower heat and pollution. Instead of guessing, city leaders and residents can test different 'what-if' plans on a screen before spending any money in the real world.
Cities struggle to turn vague climate goals into actual, measurable urban changes. They lack tools to predict how specific interventions in greening or transport will actually impact air quality and heat.
An AI-driven Scenario Engine (AI-SE) using RAG and explainable forecasting, and a federated Digital Twin architecture for urban data.
If you are a city planning consultancy dealing with unpredictable urban heat and pollution — this project developed an AI-driven Scenario Engine that generates multiple 'what-if' scenarios to test climate policies. This allows you to provide data-backed evidence for urban greening and mobility changes.
If you are a sensor hardware manufacturer dealing with fragmented data streams — this project developed a federated architecture that integrates low-cost sensors with municipal datasets. This creates a high-quality data ecosystem for your hardware to plug into across 5 pilot cities.
If you are a municipal transit operator dealing with inefficient mobility patterns — this project developed a digital twin that uses explainable forecasting to optimize transport. This helps you align your fleet with climate-neutral objectives in 14 different cities.
Based on available project data, no pricing or cost information is provided as this is an EU-funded research project.
Yes, the project includes an acceleration programme to upscale the solutions from 5 initial pilots to 9 replicator cities.
Based on available project data, specific IP and licensing terms are not listed, though it aims to deliver a toolkit of governance blueprints and digital services.
It uses a federated architecture to combine Local Digital Twins with Copernicus data, municipal datasets, and low-cost sensors.
The project runs from 2026-06-01 to 2029-11-30.
The consortium is heavily weighted toward non-industrial partners, with 16 'Other' entities and only 5 industry partners (19% ratio). This suggests a strong focus on public administration and governance, led by an Italian SME (MAGGIOLI SPA). With 26 partners across 11 countries, the project has high geographic reach but may face challenges in rapid commercialization due to the low industry presence.
Contact MAGGIOLI SPA in Italy for partnership opportunities.
Contact us to identify the specific AI-SE toolkit deliverables for your urban planning business.
