AI Challenge Results: Stuttgart Region
"Green AI – Life in the Age of Climate Change"
Find out more about the results of the AI Challenge in the Stuttgart region here. And become part of our community!
"Green AI - Life in the Age of Climate Change"
The AI Challenge brings together stakeholders from the Stuttgart region and beyond to tackle common, real-world challenges.
Both the professional exchange under the systematic guidance of experts and the direct linking of relevant actors provide lasting support for the development of the AI community in Baden-Württemberg.
The presentation of the results serves to further the exchange of knowledge and as a starting point for interested parties—whether users, developers, or intermediaries. Become part of our community!
AI Challenge Partner Network Stuttgart Region
The AI Challenge of the KI-Allianz Baden-Württemberg is organized in the Stuttgart region by the Community Management of the KI-Allianz Baden-Württemberg and the Fraunhofer IOSB in close cooperation with our regional network partners.
Together, we are advancing our region with sustainable AI solutions and strengthening the regional AI ecosystem. Seize this opportunity and join us. Become part of our community!
Why "Green AI" as a topic?
Climate change has long been noticeable in the Stuttgart region and beyond: heat waves are putting strain on cities, heavy rainfall is overwhelming infrastructure, and open spaces are scarce. At the same time, the region has enormous potential—with strong research, innovative companies, and committed local authorities.
In the AI Challenge, we pooled precisely this potential: Together, we developed innovative ideas on how artificial intelligence can help us better cope with the consequences of climate change. From the early detection of heat hotspots to the targeted planning of adaptation measures, initial solutions with real added value for the region emerged.
The challenge was therefore an important starting point: the best ideas can now be further developed and turned into concrete projects.
Green AI: Topics and results
With the joint decision to focus on the topic of "Green AI – Living with Climate Change" for the Stuttgart region, the following thematic strands were defined, addressing key content-related issues. In interactive workshops, solutions were developed along these four central themes – all with direct benefits for the Stuttgart region. Find out more here!
Theme 1: Analysis and forecast of the effectiveness of climate adaptation measures
AI can be used to measure climate adaptation measures—such as greening, heat protection, and mobility concepts—and thus analyze and predict their effectiveness. For the Stuttgart region, this means investing specifically in projects that make the greatest contribution to quality of life, health, and resilience.
Topic leader: Matthis Leicht (Fraunhofer IOSB)
Project idea: #TreeAir
DEVELOPMENT
Project objective
- Software for forward-looking climate-adapted urban planning
- Impact analysis for planned measures regarding effects on climatic conditions in the surrounding area
- Identification of locations for measures with the greatest effect, also with regard to feasibility
- Inclusion of information from civil engineering authorities, network operators, etc.
- Visualization through map display
DEVELOPMENT
AI system and data
- Map, temperature, civil engineering, network data
- Historical data on climate adaptation
- simulation results
- Recommendation System
- Human Supervision
Value proposition
- decision aid
- Process acceleration/simplification
- Early conflict prevention
- time saving
- Better urban climate
- citizen participation
OPERATION
Business model
- Software as a Service (SaaS)
- Municipal services
OPERATION
Resources and partners
- Data owners/authorities
- Service provider/supplier/integration partner
- Municipal IT departments
- citizenship
The #BaumLuft project aims to develop an AI-supported analysis and forecasting tool for climate-adapted urban planning. The focus is on analyzing the effects of specific climate adaptation measures and identifying suitable locations with particularly high effectiveness and feasibility. This involves intelligently linking extensive data sources such as map, temperature, civil engineering, and network infrastructure data, as well as historical climate adaptation information.
The core of the system is an interactive map display that enables a wide range of visualizations—from impact analyses of planned measures to comparisons of different scenarios and simulation results. This provides planners with a transparent, visually accessible basis for informed decisions.
#BaumLuft also incorporates information from specialist agencies, network operators, and other relevant bodies to enable realistic assessments. Supplemented by a recommendation system with human supervision, the tool supports municipal actors in designing climate adaptation processes at an early stage in a transparent and conflict-free manner.
The project thus makes an important contribution to strategically forward-looking urban development. It promotes better decision-making, saves time and resources, and contributes to a healthier urban climate and greater citizen participation.
Theme 2: AI-based knowledge platform for sustainable industrial parks
A digital platform brings together knowledge and up-to-date data on energy, land use, mobility, and citizen participation. This enables local authorities and companies in the Stuttgart region to modernize their commercial districts in a climate-friendly way, strengthen them economically, and benefit jointly from best practices.
Topic leader: Thomas Usländer (Fraunhofer IOSB)
Project idea N-GE Twin
DEVELOPMENT
Project objective
- Graduated, modular IT system for planning support for sustainable commercial areas
- Analysis and Monitoring Assistant
- knowledge assistant
- Solution Wizard
- Complementary tools to existing GIS/CAD systems based on standard IT interfaces
DEVELOPMENT
AI system and data
- Retrieval Augmented Generation (RAG) system
Subsystems:
- Digital twin system for municipalities
- AI data platform
- CAD/GIS (based on OGC standard)
- LLM system
- document storage
- IoT systems (time series, etc.)
- Sensors, if applicable
Value proposition
Gaining efficiency in the planning of sustainable commercial areas
- Improved quality, greater flexibility
- Matching according to uniform NH standards
- Ensure comparability and transferability
- Planning based on currently relevant data
- Making experiential knowledge accessible in a problem-oriented manner
- Check compatibility with NH targets (state, federal, EU)
OPERATION
Business model
Tiered licensing model (depending on customer segment and size)
- Customer segments:
- Local authorities (urban planning, WiFoe, climate managers, sustainability managers, neighborhood managers, etc.)
- Engineering firms, ...
- Counties, regional councils, associations, state ministries
OPERATION
Resources and partners
€1.5-3million, depending on functionality
- Depending on requirements and system concept, as well as availability of standards
- project financing
- PPP financing model
- state funding
The planning of commercial areas and their further development requires a wide range of information from a variety of different areas. The individual planning steps are currently supported and mapped by customized IT, CAD, and GIS systems. If sustainability aspects are to be taken into account from the outset, thereby enhancing the ecological and economic value of commercial areas, this requires more detailed technical data and expertise in areas such as energy, water, climate protection, mobility, land management, and biodiversity.
The N-GE Twin project idea addresses the development of customized AI-supported assistance systems that provide target group-specific support for analysis, planning, monitoring, and evaluation and are embedded in the existing IT landscape. The key factor here is that it must be possible to compare different commercial area scenarios and transfer the proposals to other commercial areas so that the AI system can learn from existing data and planning experience. As an assistance system, the knowledge platform that is gradually being developed will also check compatibility with the sustainability goals of the EU, the federal government, the states, and local authorities.
Topic 3: AI-supported room monitoring for the Stuttgart region
The combination of geodata, satellite data, and environmental information, processed using AI methods, creates a dynamic picture of the region. This allows local hotspots such as overheating in city centers, traffic disruptions, or environmental pollution to be identified early on and targeted countermeasures to be taken.
Topic leader: Nadia Burkhart (Fraunhofer IOSB)
Project idea: UrbanMind
DEVELOPMENT
Project objective
- Automated mapping of green spaces and heat islands in cities
- Identification of sealing and biodiversity
- Identification of potential for maintenance and greening
- Supporting local stakeholders in developing effective adaptation measures
- Integration into GIS, digital twins, and planning
DEVELOPMENT
AI system and data
GeoAI platform with modular AI architecture
Data sources: Satellite images (Sentinel, Spot), drone data, internal city geodata (e.g., development plans, maintenance maps)
AI methods: CNNs for image classification, transfer learning, GNNs for spatial relationships, LLMs with RAG (e.g., for context processing), Green AI
Results production: web dashboards, heat maps, recommendations
Value proposition
Decision support for urban planning
- Targeted greening and unsealing to reduce heat, promote biodiversity, and retain water
- Explainable AI modules for transparency and trust in automated room observation
- Integration into existing planning processes and IT systems
- Scalability and reusability for other cities/municipalities
OPERATION
Business model
Licensing of the UrbanMind platform (white label or SaaS) Data-as-a-Service (analysis, dashboards, reports)
- Integration into municipal projects (e.g., climate adaptation concepts)
- Co-funding through research and innovation funding
- Long-term maintenance and further development contracts
OPERATION
Resources and partners
Key partners:
- Local authorities and urban planning
- State authorities (climate adaptation)
- research partner
- satellite data provider
- IT partner for hosting, interfaces, infrastructure
Funding agencies and supporters:
- BMUV (ANK-DAS), BMBF, EU LIFE/Horizon, foundations, etc.)
UrbanMind is an idea for a novel AI platform that helps cities and municipalities tackle the challenges of climate change in a targeted manner. The focus is on the vision of using state-of-the-art GeoAI technologies to automatically identify where greening, unsealing, or biodiversity measures will be most beneficial, based on satellite and drone data as well as urban geoinformation. The platform would use techniques such as convolutional neural networks, graph neural networks, and context-based language models to generate easy-to-understand heat maps, interactive dashboards, and concrete recommendations for action from complex data. The aim is to provide municipalities with a transparent, scalable solution that can be integrated into existing planning processes, facilitating data-driven decisions and accelerating the implementation of effective climate adaptation measures. UrbanMind is therefore not just a technical concept, but a building block for climate-fit, livable cities of the future.
Topic 4: Municipal & regional digital twins
Virtual images of cities and regions enable AI to be used to simulate scenarios—such as new development, energy infrastructure or mobility concepts, or greening measures. For the Stuttgart region, this means making informed decisions before implementing expensive or irreversible measures.
Topic management: Alexander Kröker & Reinhard Herzog (Fraunhofer IOSB)
Project: E-Infra Planning
DEVELOPMENT
Project objective
Forward-looking energy infrastructure planning with the following characteristics:
acceleration
automation
cost reduction
scaling
New insights
- New connections
DEVELOPMENT
AI system and data
- Neural networks
- Hybrid processes
- Data management (energy requirements/consumption, planning, etc.)
- Digital twin of the energy infrastructure
Value proposition
interoperability
forecast
- Informed decision-making support
- Presentation of the overall picture
- increase in efficiency
- acceleration
- Enhanced collaboration
- Common understanding
- Forward planning
OPERATION
Business model
- license revenue
- development contracts
- funding acquisition
- data sale
- special evaluations
OPERATION
Resources and partners
Local authorities and intermediaries
construction industry
energy supplier
planning offices
E-Infra Planning – Forward-looking energy infrastructure planning – An AI platform for the energy transition
The idea behind our platform is to create a data-driven basis for long-term energy infrastructure planning and to standardize cross-organizational data exchange. By intelligently linking generation, consumption, grid, market, and environmental data—always with the highest quality, timeliness, and spatial resolution—the system provides a comprehensive picture of the energy system across political boundaries. An open, modular data model ensures interoperability and facilitates the integration of new data sources.
AI-powered analysis and forecasting tools evaluate various expansion and renovation scenarios for grids, generation facilities, and storage facilities in real time, quantify environmental, social, and economic impacts, and simulate load and generation profiles through 2050. Transparent workflows, open APIs, and interactive dashboards enable municipalities, grid operators, and other stakeholders to make informed and reproducible decisions.
This creates a scalable platform that shortens planning horizons, reduces investment risks, and significantly accelerates the path to a resilient, climate-neutral energy system.
Impressions "Green AI – Life in Climate Change"
- SWR interview (5:44 min) with Dr. Thomas Usländer, Project Manager AI Challenge / Fraunhofer IOSB: Green AI made in Stuttgart: Can artificial intelligence save the climate? – SWR Aktuell
- Article: Kick-off event for the Stuttgart Region AI Challenge: "Green AI – Living with Climate Change" on July 7, 2025, in Stuttgart, AI Alliance Baden-Württemberg eG, Story – PresseBox
Become part of our community!
Are you interested in our content or approach? Would you like to engage in dialogue with the stakeholders and experts involved? We'd love to hear from you! Get in touch and become part of our community!
The community management of the KI-Allianz Baden-Württemberg specifically connects business, science and politics in the regions in order to promote the exchange of knowledge and the application of AI technologies.
Community Management Region Stuttgart:
Samira Djidjeh (samira.djidjeh@ki-allianz.de) & Anna Friederike Steiff (anna.friederike.steiff@ki-allianz.de)
We are all dependent on each other.
The great thing about AI (artificial intelligence) is that I can bring many aspects together.
How can AI help us ask the right questions?
What is special about this workshop format is that the providers do not develop solutions that can subsequently be offered to users, but that users themselves are directly involved in the design.
Our plan worked. The participants were inspired by the kick-off event and there was a lack of time, not a lack of ideas.