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Course Outline
Edge AI Fundamentals in Industrial Contexts
- The strategic importance of edge computing in manufacturing
- Evaluating edge solutions against cloud-based AI alternatives
- Key applications in visual inspection, predictive maintenance, and automated control
Hardware Selection and Device-Level Limitations
- Survey of standard edge hardware (Raspberry Pi, NVIDIA Jetson, Intel NUC)
- Critical factors in processing power, memory capacity, and energy efficiency
- Choosing the appropriate platform based on specific application needs
Edge-Oriented Model Development and Optimization
- Techniques for model compression, pruning, and quantization
- Utilizing TensorFlow Lite and ONNX for efficient embedded deployment
- Achieving the optimal balance between accuracy and speed in resource-constrained environments
Edge-Based Computer Vision and Sensor Fusion
- Implementing visual inspection and continuous monitoring at the edge
- Aggregating data streams from diverse sensors (vibration, temperature, cameras)
- Performing real-time anomaly detection using Edge Impulse
Communication Protocols and Data Interaction
- Adopting MQTT for efficient industrial messaging
- Interfacing with SCADA, OPC-UA, and PLC infrastructure
- Ensuring security and robustness in edge network communications
Deployment Strategies and Field Validation
- Packaging models and deploying them onto target edge devices
- Tracking performance metrics and managing software updates
- Case study analysis: executing real-time decision loops with local actuation
Scaling and Maintaining Edge AI Architectures
- Effective strategies for managing large-scale edge device fleets
- Implementing remote updates and establishing model retraining workflows
- Addressing lifecycle management for industrial-grade AI deployments
Recap and Future Directions
Requirements
- Proficiency in embedded systems or IoT architectural concepts
- Practical experience with Python or C/C++ programming languages
- Working knowledge of machine learning model creation
Target Audience
- Embedded software developers
- Industrial IoT engineering teams
21 Hours
Testimonials (1)
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