METROPOLIS: Urban Digital Twin

About

METROPOLIS develops an open and interoperable urban digital twin platform for planning, simulation, and decision support. The project responds to a growing need for cities to test the consequences of major planning decisions before they are implemented in the real world.

Urban digital twins can connect spatial data, real-time information, historical records, and predictive models into a shared environment for analysis. In practice, however, these systems are difficult to build and maintain. Urban data is fragmented across agencies and vendors, stored in incompatible formats, and governed by different standards. AI models also require different kinds of inputs, making it difficult to combine them into coherent planning workflows.

METROPOLIS addresses these challenges through a modular framework for data integration, model orchestration, transparent workflows, and comparable evaluation. The goal is to make advanced urban analytics more accessible to researchers, municipalities, and planning teams.

The project emphasizes openness, explainability, reliability, and practical adoption. By creating reusable infrastructure for urban AI, METROPOLIS supports more informed decisions about sustainability, mobility, resilience, energy, housing, and social inclusion.

Funding