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Introduction and testimonial from the AI-SPRINT Maintenance & Inspection use case

appsOther research productkeyboard_double_arrow_right Other ORP type 13 Jul 2023Publisher:ZenodoFunded by:EC | AI-SPRINT
Authors: Michał Kłosiński; Mier-Jędrzejowicz, Edward;

doi: 10.5281/zenodo.8141705 , 10.5281/zenodo.8141706

Introduction and testimonial from the AI-SPRINT Maintenance & Inspection use case

Abstract

On 11 July 2023, the AI-SPRINT project has organised the webinar "Transforming Wind Turbine Maintenance: AI-SPRINT's Predictive Insights and Edge-Cloud Integration". The event aimed to showcase the AI-SPRINT project's use case on predictive maintenance and inspection of wind turbines. It highlighted the role of artificial intelligence systems in improving maintenance practices, reducing risks of turbine breakage, and enhancing the efficiency of AI models. This presentation showcases the main objectives, challenges, benefits and applications of the AI-SPRINT Maintenance & Inspection use case.

Keywords

IoT, machine learning, edge computing, wind turbines, cloud, inspection, artificial intelligence, maintenance

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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