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
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 3900 € + 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
