System Architecture

🏗️ Detailed Technical Architecture

global architecture

Our Edge AI solution represents a sophisticated hybrid cloud-edge architecture that brings enterprise-grade AI capabilities directly to the field. Here’s how each component works together to create an intelligent, autonomous system:

🚂 The Edge: LEGO Train Platform

Physical Components

  • 🔧 LEGO Technic Motor: Provides precise movement control
  • 🧠 LEGO Hub: Central control unit receiving commands via Bluetooth Low Energy (BLE)
  • 📹 On-board Camera: Captures real-time video feed for AI processing
  • 🔋 Portable Battery: Powers the entire mission duration

Edge Computing Brain

The heart of our edge system is the NVIDIA Jetson Orin - a powerful System on Chip (SoC) that combines:

Component Specification Purpose
CPU ARM Cortex-A78AE System control & coordination
GPU NVIDIA Ampere AI inference acceleration
Memory Up to 64GB LPDDR5 High-speed data processing
Storage NVMe SSD Model storage & caching

🌐 Edge Software Stack

Operating System Layer

┌─────────────────────────────────────┐
│        Red Hat Device Edge          │  ← Enterprise Edge OS
├─────────────────────────────────────┤
│           MicroShift               │  ← Lightweight Kubernetes
├─────────────────────────────────────┤
│     Edge Microservices             │  ← AI & Control Logic
└─────────────────────────────────────┘

Red Hat Device Edge provides:

  • 🔒 Security: Enterprise-grade security features
  • 🔄 OTA Updates: Over-the-air deployment capabilities
  • ⚡ Performance: Optimized for resource-constrained environments
  • 🛡️ Reliability: Production-ready edge computing platform

MicroShift enables:

  • 🎛️ Container Orchestration: Kubernetes at the edge
  • 📦 Service Management: Automated deployment and scaling
  • 🔄 Self-healing: Automatic recovery from failures
  • 📊 Monitoring: Real-time system health tracking

☁️ The Cloud: OpenShift Cluster

Infrastructure Components

Located in AWS Cloud with 5G connectivity to the edge:

┌─────────────────────────────────────┐
│         OpenShift Cluster          │
├─────────────────────────────────────┤
│  ┌─────────────┐ ┌─────────────────┐│
│  │ OpenShift   │ │   CI/CD         ││
│  │     AI      │ │  Pipelines      ││
│  └─────────────┘ └─────────────────┘│
├─────────────────────────────────────┤
│  ┌─────────────┐ ┌─────────────────┐│
│  │   Video     │ │   GitOps        ││
│  │ Monitoring  │ │ Deployment      ││
│  └─────────────┘ └─────────────────┘│
└─────────────────────────────────────┘

Cloud Services

🤖 OpenShift AI Platform

  • Data Science Projects: Isolated environments for ML development
  • Jupyter Notebooks: Interactive development experience
  • Pipeline Servers: Automated ML workflow execution
  • Model Serving: REST API endpoints for inference
  • GPU Clusters: High-performance training infrastructure

🔄 CI/CD Pipeline Infrastructure

  • Multi-architecture Builds: Support for x86_64 and ARM64
  • Tekton Pipelines: Cloud-native CI/CD workflows
  • Container Registry: Secure image storage and distribution
  • Automated Testing: Quality assurance at every step

📹 Video Surveillance System

  • Real-time Streaming: Live camera feed from the train
  • Kafka Brokers: High-throughput message streaming
  • Web Interface: Remote monitoring capabilities
  • Alert System: Immediate notifications for anomalies

🔄 Data Flow Architecture

graph TD A[Train Camera] -->|Video Stream| B[Jetson Orin] B -->|AI Inference| C[Traffic Sign Detection] C -->|Control Commands| D[LEGO Hub] B -->|5G Connection| E[OpenShift Cluster] E -->|Training Data| F[OpenShift AI] F -->|Updated Models| B E -->|Monitoring| G[Dashboard] E -->|GitOps| H[Deployment] style A fill:#e1f5fe style B fill:#f3e5f5 style C fill:#e8f5e8 style D fill:#fff3e0 style E fill:#e3f2fd style F fill:#f1f8e9 style G fill:#fce4ec style H fill:#fff8e1

Real-time Processing Pipeline

  1. 📸 Image Capture: Camera captures traffic sign images
  2. 🔍 AI Inference: Jetson processes images using trained model
  3. ⚡ Decision Making: AI determines appropriate action (stop/go)
  4. 📡 Command Transmission: BLE commands sent to LEGO Hub
  5. 🔄 Feedback Loop: Results sent to cloud for continuous learning

🏢 Multi-Architecture Support

Build Infrastructure

Our system supports heterogeneous computing environments:

Architecture Use Case Platform
x86_64 Development & Training OpenShift Cluster
ARM64 Edge Deployment Jetson Orin
Multi-arch Universal Images Container Registry

Deployment Strategy

  • 🏭 Cloud Development: Models trained on powerful x86_64 clusters
  • 📦 Cross-compilation: Applications built for ARM64 target
  • 🚀 Edge Deployment: Lightweight containers deployed to Jetson
  • 🔄 Continuous Integration: Automated testing across architectures

🛡️ Security & Reliability

Edge Security

  • 🔐 Secure Boot: Verified system startup
  • 🔒 Container Security: Isolated execution environments
  • 📜 Certificate Management: Mutual TLS authentication
  • 🛡️ Network Isolation: Segmented communication channels

Cloud Security

  • 🔑 RBAC: Role-based access control
  • 🔐 Secrets Management: Encrypted credential storage
  • 📊 Audit Logging: Comprehensive activity tracking
  • 🛡️ Network Policies: Micro-segmentation

This architecture demonstrates how Red Hat’s Edge AI stack enables sophisticated AI applications in resource-constrained environments while maintaining enterprise-grade security, reliability, and scalability! 🚀