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Course Outline

Introduction to Edge AI in Industrial Contexts

  • The significance of edge computing within manufacturing
  • A comparative analysis with cloud-based AI
  • Practical applications in vision, predictive maintenance, and control systems

Hardware Platforms and Device-Level Limitations

  • Overview of prevalent edge hardware (Raspberry Pi, NVIDIA Jetson, Intel NUC)
  • Considerations regarding processing power, memory, and energy consumption
  • Selecting the optimal platform based on application requirements

Model Development and Optimization for Edge Environments

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

Computer Vision and Sensor Fusion at the Edge

  • Edge-based visual inspection and monitoring solutions
  • Aggregating data from various sensors (vibration, temperature, cameras)
  • Real-time anomaly detection using Edge Impulse

Communication and Data Exchange

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

Deployment and Field Validation

  • Packaging and deploying models onto edge devices
  • Performance monitoring and update management
  • Case study: Real-time decision loops with local actuation

Scaling and Maintaining Edge AI Systems

  • Strategies for managing edge devices at scale
  • Remote updates and iterative model retraining cycles
  • Lifecycle considerations for industrial-grade deployments

Summary and Future Directions

Requirements

  • A solid grasp of embedded systems or IoT architectures
  • Proficiency in Python or C/C++ programming
  • Basic familiarity with machine learning model development

Target Audience

  • Embedded software developers
  • Industrial IoT engineering teams
 21 Hours

Custom Corporate Training

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 4800 € + VAT*

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