Machine Learning on STM32 with Cartesiam: for equipment monitoring and more

Join our 1-hour webinar to learn how to take advantage of the AI solutions developed by ST and Cartesiam to integrate Machine Learning-based condition monitoring capabilities into your system.

 

This webinar was broadcasted Tuesday, October 13th 2020
 

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In this one-hour session, we will introduce condition monitoring at the edge and explain how ST’s offer combined with Cartesiam’s solution, allows you to easily, quickly and affordably run on-device learning and anomaly detection in your own solutions on compact and low power devices.

Why attend

Predictive maintenance (PdM) is based on condition monitoring, abnormality detection and classification algorithms and is widely implemented in industrial and consumer markets. AI has the potential to make it more accurate then ever.
Today,  ST and Cartesiam give you the keys to easily build your AI-based PdM application without having to invest in resources on data science or needing to deeply understand machine learning techniques. You will learn the steps required to set up predictive maintenance in your system and quickly put theory into practice thanks to ST’s and Cartesiam’s joint solutions. Join us and discover how we can help you develop your AI application and bring it to market across a wide variety of innovative use cases.

Who should attend

  • CTO in industry
  • Innovation leader
  • Maintenance manager
  • Lean Management leader
  • Machine learning / Artificial intelligence VP, Team leaders, Head Managers

Agenda

  • Condition monitoring at the edge
  • How to easily build ML algorithm ( Cartesiam)
  • and embed it at the edge (ST)
  • Use cases and application example
  • Interconnectivity between ST's AI solutions and Cartesiam's offer
  • Expanding device connectivity features

There will be a live Q&A session at the end of the webinar where ST’s experienced engineers will be available to answer your questions.
 

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Speakers

Raphael Apfeldorfer

Raphael Apfeldorfer is responsible for Artificial Intelligence Marketing at ST. Focusing on innovation in digital transformations, he has 20 years’ experience in Telecom and IoT industry, from broadband to LPWAN connectivity, security and low-power applications.

 

Francois de Rochebouet

François de Roucheboet computer, electronics and robotics engineer. He has been working for 20 years in the start-up industry. Cartesiam is the fourth start-up he co-founded. He currently leads the R&D team.

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