Updated on 28 July 2025
Partner with us in Advancing Sustainable Mobility using Real-Time Environmental Data
About
We are developing a proposal focused on enabling cleaner, data-driven and circular mobility by integrating real-time environmental data including emission and ambient air quality monitoring into digital platforms.
Our project leverages multiple environmental data streams to create digital twin models that inform mobility planning, fleet management/maintenance, emission reduction strategies and broader sustainability goals.
We are aiming to:
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Monitor real-time emissions and environmental impact
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Support circular mobility strategies through data analytics
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Provide actionable insights for improving operational efficiency and informing policy frameworks
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Enable predictive modeling and scenario testing using digital twins
We are seeking partners with expertise in areas such as:
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Vehicle systems and mobility solutions
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Data science, digital twins or geospatial analytics
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Industrial or municipal fleet operations
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Circular economy innovation and environmental science
A more detailed concept is attached that outlines the proposal in its current form. However, we welcome input from any organization that sees an opportunity to contribute even if it is beyond what is outlined in the document.
Stage
- Early idea
Topic
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | (AI based) process and system control technologies
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
Type
- Consortium seeks Partners
Attached files
Organisation
Similar opportunities
Project cooperation
Digital ecosystem for circular value creation
- Already defined
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | Design of an adaptable Digital Product Pass:
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
Yoav Nahshon
Team Leader Materials Informatics at Fraunhofer IWM
Freiburg, Germany
Project cooperation
AI, Digital Twin & Data-Driven Solutions for Circular Value Creation
- Data technologies | Assistance and Expert systems
- Enabling technologies | Network design of reverse supply chains
- Data technologies | Design of an adaptable Digital Product Pass:
- Enabling technologies | Robotic / handling - and assistance systems
- Data technologies | (AI based) process and system control technologies
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
Süleyman Altınışık
Expert R&D Engineer at OBSS Technology
İstanbul, Türkiye
Project cooperation
Digital Twin for Regional and Cross-Border Plastics Cycles (REPLAY)
- Early idea
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | Design of an adaptable Digital Product Pass:
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
Patrick Cato
Professor at Big Data Research Group Ingolstadt
Ingolstadt, Germany