Purpose
The webinar aims to showcase the AI-SPRINT project's use case on predictive maintenance and inspection of wind turbines. It highlights the role of artificial intelligence systems in improving maintenance practices, reducing risks of turbine breakage, and enhancing the efficiency of AI models. The webinar also emphasizes the potential societal and environmental impacts of the project.
Scope
The webinar focusses on the unique approach of the AI-SPRINT project, which utilizes AI models and drone-collected images for damage detection and analysis. By leveraging edge-cloud channels, the project accelerates inspection time and reduces human error. The use case specifically addresses the challenges in wind turbine maintenance and inspection, demonstrating the integration of cloud-based analysis and local processing for predictive maintenance. The AI-SPRINT use case holds substantial business implications. It enhances AI model efficiency, creating new market opportunities for the damage identification workflow.
Audience
The webinar targets professionals and stakeholders involved in the wind power industry, including turbine operators, maintenance personnel, industry experts, researchers, and technology enthusiasts. It appeals to individuals interested in leveraging artificial intelligence for improving maintenance practices and reducing the environmental impact of wind power generation.
Agenda (all times CEST)
- 15:00 - 15:02 Welcome - John Favaro, Trust-IT
- 15:02 - 15:10 Context and setting the scene for the use case: Challenges and needs - Danilo Ardagna, Politecnico di Milano - DOWNLOAD THE SLIDES
- 15:10 - 15:25 Introduction to the Use Case - Michał Kłosiński, 7bulls.com - DOWNLOAD THE SLIDES
- 15:25 - 15:40 Testimonial from the Use Case - Edward Mier-Jędrzejowicz, TTAnalysis - DOWNLOAD THE SLIDES
- 15:40 - 15:50 Interactive session with the audience - Rita Giuffrida, Trust-IT
- 15:50 - 16:25 Panel discussion and Q&A - moderated by John Favaro, Trust-IT
- 16:25 - 16:30 Closure - John Favaro, Trust-IT