Powering The Industrial Edge with Open Source Software

Overview

Discover how open-source software drives industrial edge computing, balancing OT robustness with IT flexibility while enabling AI-powered analytics and real-time processing for smarter manufacturing.

Syllabus

• Introduction to Industrial Edge Computing
Definition and importance in manufacturing
Overview of Operational Technology (OT) and Information Technology (IT) convergence
• Fundamentals of Open Source Software
History and principles of open source
Advantages of open source in industrial settings
• Key Open Source Tools for Industrial Edge
Linux for edge devices
Kubernetes and containerization at the edge
EdgeX Foundry for industrial edge use cases
• Architecting the Industrial Edge
Designing robust and flexible edge infrastructures
Integration of edge solutions with existing OT systems
• AI-Powered Analytics at the Edge
Introduction to AI and machine learning in manufacturing
Deployment of AI models on edge devices
• Real-time Data Processing and Analytics
Techniques for real-time data collection and processing
Use cases for real-time analytics in manufacturing
• Balancing OT Robustness with IT Flexibility
Challenges and solutions in integrating OT and IT
Ensuring security and resilience at the edge
• Case Studies
Successful applications of open source software in industrial edge environments
• Hands-On Labs and Projects
Setting up a basic edge computing environment
Implementing an AI model on a Raspberry Pi
Docker and Kubernetes exercises for edge deployment
• Future Trends in Industrial Edge Computing
Emerging technologies and their potential impact
Open source communities and ecosystem evolution
• Course Summary and Review
Key takeaways and best practices
Resources for continued learning and exploration in AI and open source at the edge

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Subjects

Programming