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Course Outline
Foundational Concepts of Edge AI in Industrial Contexts
- The significance of edge computing within manufacturing workflows
- Comparative analysis against cloud-based AI architectures
- Practical applications in machine vision, predictive maintenance, and process control
Hardware Ecosystems and Device-Level Limitations
- Examination of prevalent edge hardware options (Raspberry Pi, NVIDIA Jetson, Intel NUC)
- Key factors regarding processing power, memory capacity, and power consumption
- Criteria for selecting appropriate platforms based on specific application requirements
Developing and Optimizing Models for Edge Deployment
- Techniques for model compression, pruning, and quantization
- Utilizing TensorFlow Lite and ONNX for embedded system integration
- 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 various sensors (vibration, temperature, cameras)
- Performing real-time anomaly detection utilizing Edge Impulse
Communication Protocols and Data Interchange
- Application of MQTT for industrial messaging standards
- Interfacing with SCADA, OPC-UA, and PLC systems
- Ensuring security and resilience in edge communication channels
Deployment Strategies and Field Validation
- Packaging models and executing deployment on edge devices
- Tracking performance metrics and managing software updates
- Case study analysis: implementing real-time decision loops with local actuation
Scaling and Sustaining Edge AI Systems
- Strategies for managing distributed edge devices
- Executing remote updates and defining model retraining cycles
- Addressing lifecycle considerations for industrial-grade deployments
Conclusions and Future Directions
Requirements
- Foundational knowledge of embedded systems or IoT architectures
- Practical experience with Python or C/C++ programming
- Proficiency in machine learning model development
Target Audience
- Embedded software developers
- Industrial IoT engineering teams
21 Hours
Testimonials (1)
That we can cover advance topic and work with real-life example
