Streamlining AI Development: A Model-Based Approach to Virtual Sensor Modeling

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A forthcoming webinar promises to revolutionize the development of AI-based virtual sensor models by presenting a streamlined, end-to-end workflow. This comprehensive approach allows designers to create, train, validate, and deploy AI models within a single environment, significantly simplifying the development process. The webinar will focus on the integration of AI models into Simulink, a popular platform for system-level simulation, verification, and simulation-based testing.

Attendees will learn how to apply formal verification techniques to ensure the reliability and accuracy of neural network behavior. Additionally, the webinar will cover the compression of AI models to reduce memory footprint and increase execution speed. One of the key takeaways from the webinar will be the ability to generate library-free C code from AI models and perform PIL (Processor-In-the-Loop) tests.

This capability enables developers to profile code performance and evaluate design and model selection tradeoffs with greater ease. The webinar will also provide insights into designing and training AI-based virtual sensors using MATLAB. The presenter will walk attendees through the entire workflow, from designing and training AI models to compressing and deploying them to embedded processors.

By showcasing the power of model-based design, the webinar aims to empower developers to create more efficient and effective AI-based virtual sensor models. The free webinar is now open for registration, offering a unique opportunity for developers and engineers to enhance their skills and knowledge in AI-based virtual sensor modeling. By attending this webinar, participants will gain a deeper understanding of how to leverage model-based design to streamline their AI development workflow and create more sophisticated virtual sensor models.