Project cooperationUpdated on 16 May 2025
Advanced Functional Nanofiber Sensors
About
Development of innovative recyclable nanofiber-based smart sensors for wastewater monitoring, food packaging, and air quality measurements, and their integration with AI for circular economy applications.
This project aims to develop multifunctional, recyclable nanofiber-based smart sensors designed to address key environmental challenges within the framework of the circular economy. The sensors will be tailored for three critical application areas: real-time wastewater monitoring, smart food packaging, and air quality assessment. By integrating these sensors with artificial intelligence (AI) algorithms, we aim to enable predictive analytics and automated decision-making to optimize resource use, reduce waste, and enhance environmental sustainability.
Stage
- Early idea
- Already defined
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 | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across 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 | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Assistance and Expert systems
- 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
- Data technologies | Design of an adaptable Digital Product Pass:
- 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)
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- 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 | Robotic / handling - and assistance systems
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
- Enabling technologies | Network design of reverse supply chains
Type
- Consortium seeks Partners
- Expertise offered
Organisation
Similar opportunities
Project cooperation
Al and Circular Economy in Coating and Insulation
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Enabling technologies | Network design of reverse supply chains
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- 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.
Kaan AKSOY
Advanced Technologies and Sustainability R&D Department at BETEK BOYA VE KİMYA SANAYİ A.Ş
İSTANBUL, Türkiye
Project cooperation
- Early idea
- 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
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- 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.
ocean_mint ocean foods
Founder/Director at Ocean Mint UK Limited
Essex, United Kingdom
Project cooperation
- Already defined
- Expertise offered
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Enabling technologies | Network design of reverse supply chains
- Enabling technologies | Robotic / handling - and assistance systems
- 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
- 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.
Justus von Geibler
Co-Head Research Unit Innovation Labs at Wuppertal Institut für Klima, Umwelt, Energie
Wuppertal, Germany