Project cooperationUpdated on 12 April 2025
Cassava / corn Ethanol
About
Agricultural phase of life cycle of waste production in agricultural sectors, including cassava crops, processing waste to packaging materials, iare rapidly increasing due to use of cassava crops for ethanol production. Due to global warming potential in the use of Biodiesel and ethanol. Ethanol are imported from the united states , Brazil, for industrial phase and use phase. Critical potential of biofuels is to reduce greenhouse gas ( GHG) emissions in the transportation sector in emerging markets of Africa, where cassava is abundant. The biofuel emerging markets of Latin America
The potential GHG savings of sustainably produce biofuels
The impact of biofuels on the final cost
The capacity of biofuels production , considering demand and land , how do we collaborate on growing cassava to produce ethanol for industrial and commercial uses.
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 | 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 | 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 | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
Organisation
Similar opportunities
Project cooperation
Digital Product Passport for Circular Economy
- Already defined
- Expertise offered
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | Design of an adaptable Digital Product Pass:
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- 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 | 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)
Ralph Weissnegger
Director Innovation & Funding at CISC Semiconductor GmbH
Klagenfurt, Austria
Project cooperation
- Already defined
- Consortium seeks Partners
- Enabling technologies | Network design of reverse supply chains
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
Aysegul gündüz
Founder at Loopifyr
İstanbul, Türkiye
Project cooperation
Upcycling process technology within agrifood sector
- Early idea
- Already defined
- Expertise offered
- Consortium seeks Partners
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- 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)
Hansol Bae
CSO at Nature Preserve ApS
Søborg, Denmark