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Course Outline

Introduction to Edge AI in Industrial Environments

  • The importance of edge computing within manufacturing contexts
  • Comparison between edge and cloud-based AI architectures
  • Applications in computer vision, predictive maintenance, and process control

Hardware Platforms and Device-Level Limitations

  • Review of standard edge hardware options (Raspberry Pi, NVIDIA Jetson, Intel NUC)
  • Considerations for processing power, memory, and energy consumption
  • Selecting the appropriate platform based on specific application requirements

Model Development and Optimization for Edge

  • Techniques for model compression, pruning, and quantization
  • Utilizing TensorFlow Lite and ONNX for embedded system deployment
  • Striking a balance between model accuracy and inference speed in resource-constrained settings

Computer Vision and Sensor Fusion at the Edge

  • Implementing edge-based visual inspection and continuous monitoring
  • Aggregating data from diverse sensor types (vibration, temperature, cameras)
  • Performing real-time anomaly detection using Edge Impulse

Communication and Data Exchange

  • Employing MQTT for industrial messaging applications
  • Interfacing with SCADA, OPC-UA, and PLC systems
  • Ensuring security and resilience in edge network communications

Deployment and Field Testing

  • Packaging and deploying models onto edge devices
  • Monitoring performance metrics and managing software updates
  • Case study analysis: executing real-time decision loops with local actuation

Scaling and Maintenance of Edge AI Systems

  • Strategies for managing fleets of edge devices
  • Implementing remote updates and continuous model retraining cycles
  • Addressing lifecycle management for industrial-grade deployments

Summary and Future Steps

Requirements

  • A solid understanding of embedded systems or IoT architectures
  • Practical experience with Python or C/C++ programming
  • Proficiency in machine learning model development

Target Audience

  • Embedded developers
  • Industrial IoT teams
 21 Hours

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Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 3900 € + VAT*

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