Course Outline
Introduction to Edge AI in Industrial Settings
- Why edge computing matters in manufacturing
- Comparison with cloud-based AI
- Use cases in vision, predictive maintenance, and control
Hardware Platforms and Device-Level Constraints
- Overview of common edge hardware (Raspberry Pi, NVIDIA Jetson, Intel NUC)
- Processing, memory, and power considerations
- Selecting the right platform for application type
Model Development and Optimization for Edge
- Model compression, pruning, and quantization techniques
- Using TensorFlow Lite and ONNX for embedded deployment
- Balancing accuracy vs. speed in constrained environments
Computer Vision and Sensor Fusion at the Edge
- Edge-based visual inspection and monitoring
- Integrating data from multiple sensors (vibration, temperature, cameras)
- Real-time anomaly detection with Edge Impulse
Communication and Data Exchange
- Using MQTT for industrial messaging
- Integrating with SCADA, OPC-UA, and PLC systems
- Security and resilience in edge communications
Deployment and Field Testing
- Packaging and deploying models on edge devices
- Monitoring performance and managing updates
- Case study: real-time decision loop with local actuation
Scaling and Maintenance of Edge AI Systems
- Edge device management strategies
- Remote updates and model retraining cycles
- Lifecycle considerations for industrial-grade deployment
Summary and Next Steps
Requirements
- An understanding of embedded systems or IoT architectures
- Experience with Python or C/C++ programming
- Familiarity with machine learning model development
Audience
- Embedded developers
- Industrial IoT teams
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.
Price per private group, online live training, starting from 4350 € + VAT*
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Testimonials (2)
How to use and explore AI for daily works
Giovani Natalia - PT Astra Honda Motor
Course - AI for Supply Chain and Manufacturing Logistics
That we can cover advance topic and work with real-life example
