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Project cooperationUpdated on 8 May 2026

AI-Based Monitoring and Fault Diagnosis for Renewable Energy Systems

Assistant Professor at Sinop Universty

Sinop, Türkiye

About

This cooperation opportunity focuses on AI-based monitoring and fault diagnosis approaches for renewable and industrial energy systems.

The aim is to contribute to Horizon Europe collaborations involving:

• SCADA-based monitoring and data analytics

• AI-supported fault detection and predictive maintenance

• Data-driven operational monitoring of energy infrastructures

• Simulation and experimental validation of electrical systems

• Reliability and efficiency improvement in renewable energy applications

I am particularly interested in collaborative projects combining real-world operational data, machine learning techniques, and engineering-based system analysis for sustainable and resilient energy infrastructures.

Potential collaboration areas include renewable energy integration, industrial energy monitoring, intelligent diagnostics, and predictive maintenance applications.

Stage

  • Ideation - identifying the project idea / Concept note/ Idea
  • Design - setting the project scope

Topic

  • Decarbonisationof energy intensive industries (IA)(Processes4Planet and Clean Steel partnerships)
  • Clean Technologies for Climate Action
  • Efficient energy input from renewable sources and energy management in the process industries (Processes4Planet and Innovative Advanced Materials for the EU partnerships)

Call

  • HORIZON-CID-2026-01-01
  • HORIZON-CID-2026-01-02
  • HORIZON-CL4-2027-02-MAT-PROD-32-two-stage
  • HORIZON-CL5-2026-09-D4-08

Type

  • Partner seeks Consortium
  • Partner offers specific expertise / technical solution

Organisation

Sinop Universty

University

Sinop, Türkiye

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