The TWINVERSE project aims to support European cities in accelerating their transition towards climate neutrality, resilience, and social inclusion through a federated ecosystem of interoperable, AI-enhanced Local Digital Twins. To achieve this, TWINVERSE follows five main complementary approaches: (1) upgrading and federating existing Local Digital Twins, (2) developing human-centred, explainable AI services for urban intelligence, (3) integrating these services into city governance and climate-planning processes, (4) building the capacity of city authorities and expanding a cross-sectoral community of practice, and (5) supporting replication, market uptake, and long-term sustainability. The technical pillar will connect city Digital Twins through the TWINVERSE Data Space Suite, enabling secure and standardised exchange of urban data, models, and services. In parallel, the project will develop AI-powered services addressing mobility, energy and buildings, winter services, urban heat and air quality, equitable service distribution, citizen engagement, and climate-neutrality scenario assessment. These solutions will be tested in five EU Mission Cities including Milan, Cork, Kalamata, Lappeenranta, and Vitoria-Gasteiz supporting scenario analysis, forecasting, impact assessment, and participatory planning. The results will contribute to the implementation and improvement of Climate City Contracts, Sustainable Energy and Climate Action Plans, and Sustainable Urban Mobility Plans, while training, peer learning, open-source resources, and replication activities will enable wider uptake by other European cities.

MKLAB has a critical role in TWINVERSE by leading the work package on human-centred requirements and stakeholder engagement strategies, which establishes the socio-technical foundations for the development and integration of the project’s Digital Twin and AI services. MKLAB leads the analysis of existing AI applications, tools, and Digital Twin interoperability solutions for urban planning and management, covering domains such as energy, mobility, land use, air quality, and infrastructure monitoring. The resulting open-access repository will identify current capabilities, limitations, interoperability approaches, standards, data models, and emerging trends, providing the evidence base for the project’s subsequent technical work. MKLAB also leads the mapping of urban datasets and the definition of technical requirements for interoperability, translating the needs identified by the Mission Cities into specifications for data access, exchange, metadata, quality, governance, security, and integration within the TWINVERSE architecture. In addition, MKLAB contributes to the development of the project’s Data Management Plan and leads the definition of security-related requirements and good practices. On the technical side, MKLAB will develop and validate air-dispersion modelling capabilities for simulating the propagation of hazardous gases. Coupled with AI-enhanced meteorological forecasts, these models will support urban heat and air-quality risk assessment and real-time early warnings for events such as industrial accidents and fires, strengthening the capacity of cities to anticipate and respond to environmental emergencies.