Creating & Deploying AI Condition-Based Monitoring Solutions with Qeexo and Arm

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Presented by

Pranav Kanuparthi, Machine Learning Engineer, Qeexo and Christopher Seidl, Director Product Management Embedded Tools, Arm

About this talk

Discover how Qeexo and Arm make it easier to create machine learning solutions for industrial condition-based monitoring (CbM), predictive maintenance, and anomaly detection. This in-depth webinar will showcase: 1. How Arm Virtual Hardware (AVH) and Synchronous Data Streaming Framework (SDS Framework) made it possible to create a configurable, virtual research board and sensors from Qeexo AutoML; 2. A demonstration of how Qeexo AutoML users can build and simulate machine condition-based monitoring (CbM) solutions for many Arm Cortex-M processors using existing sensor data, and deploy those solutions to edge hardware. 3. How to use the following tools to put together a virtual sensor board: CMSIS-Pack, Keil MDK, Arm Virtual Hardware and Qeexo AutoML, SDS Framework Qeexo and Arm subject matter experts will be on hand during the webinar to answer any questions. Resources: Free license for Qeexo AutoML: https://forms.office.com/r/kH8fXh6Tpv Qeexo Automl: https://automl.qeexo.com/ Getting Started with Qeexo Automl: https://docs.qeexo.com/guides/userguides/getting-started AVH MLOps exemplary repo: https://github.com/ARM-software/AVH-MLOps/ Arm Keil Studio: https://keil.arm.com/ Arm Virtual Hardware Documentation: https://arm-software.github.io/AVH/main/overview/html/index.html
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