Updated on 29 April 2025
Looking for an SME Partner with expertise in Virtual Reality, Artificial Intelligence, and Digital Twin technologies for a collaborative IraSME R&D project.
Artificial Intelligence, Machine Learning and Software Development at CEKA YAZILIM ARAŞTIRMA GELİŞTİRME MÜHENDİSLİK BİLGİSAYAR ELEKTRİK ELEKTRONİK ENDÜSTRİYEL OTOMASYON SAN. VE TİC. LTD. ŞTİ
Nevşehir, Türkiye
About
The project aims to develop an interactive, multi-user, AI-driven Digital Twin and Virtual Reality (VR)-based platform for basic electronics education and industrial training. The platform will enable students, engineers, and technicians to collaboratively design, simulate, analyze, and troubleshoot electronic circuits without requiring a physical laboratory. Digital Twin technology will provide realistic virtual representations of electronic systems, while Artificial Intelligence (AI) will automatically detect design errors, provide intelligent circuit recommendations, and support personalized learning and engineering practice.
We are looking for an SME partner from one of the countries participating in the IraSME programme (Germany, Austria, Belgium, Brazil, Czech Republic, Luxembourg, or Switzerland) with expertise in Virtual Reality (VR), Artificial Intelligence (AI), and Digital Twin technologies. The partner is expected to have sufficient financial capacity to meet its national funding requirements and to lead one of the project work packages while contributing to the joint development of the AI-assisted VR platform.
The project concept and core structure have already been developed. The final proposal will be jointly refined and completed together with the selected partner, incorporating its technical expertise, innovative contributions, and market-oriented requirements.
Similar opportunities
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)
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