🚀 Causal Edge: Enterprise Digital Twin Platform

🌐 Production Deployment: https://causaledge.vercel.app/

🎥 Platform Demonstration

Causal Edge is an enterprise-grade, AI-powered predictive maintenance Digital Twin platform built for industrial hardware ecosystems. Designed to solve complex real-world manufacturing and logistics challenges, this platform acts as a centralized command center. It leverages advanced causal AI to predict, isolate, and explain catastrophic hardware failures across entire fleets of vehicles or machinery in real-time before they occur.

✨ Key Capabilities

• 🧠 Bayesian Causal Inference: Dynamically calculates how a fault in one physical component (e.g., a wheel bearing) cascades into downstream failures (e.g., suspension, drivetrain) using a probabilistic causal graph, allowing engineers to identify true root causes.
• 📡 Real-Time Telemetry Processing: A high-throughput Python-based engine ingests live sensor data (vibration, temperature, torque, pressure) across the fleet, streaming synchronized analytics to the frontend via WebSockets.
• 🕵️ Z-Score Anomaly Detection: Utilizes mathematically rigorous statistical deviation models on the edge to detect critical hardware anomalies with zero false positives.
• 🤝 Distributed Fleet Quorum: Individual machines share anomaly data to reach a consensus. Once an anomaly pattern is confirmed across the fleet, the fault signature is hashed and committed to an immutable ledger for audit and compliance.
• 🤖 Explainable AI Narrative: Demystifies "black box" machine learning by generating a real-time, step-by-step causal narrative explaining exactly why the AI made its diagnosis and recommending preventative maintenance actions.
• 🎨 Executive UI/UX: A state-of-the-art dashboard featuring real-time interactive causal trees, glowing status indicators, and responsive telemetry data visualization.

🛠️ Technology Stack

Frontend

• Framework: React + Vite
• Styling: Custom CSS (Glassmorphism aesthetics) + TailwindCSS
• Data Visualization: Recharts, Custom SVG Animations

Backend

• Framework: Python + FastAPI
• Database: SQLite + SQLAlchemy
• AI/ML: Python Standard Library (Mathematical Modeling)
• Communication: WebSockets, AsyncIO Event Bus

🚀 Deployment & Operations

1. Start the Backend (Python)

Ensure you have Python 3.10+ installed.

cd backend
python -m venv .venv

# On Windows:
.venv\Scripts\activate
# On Mac/Linux:
source .venv/bin/activate

pip install -r requirements.txt
python run.py

The backend API and WebSocket server will initialize on http://localhost:8000.

2. Start the Frontend (React)

Ensure you have Node.js installed. Open a new terminal window:

cd frontend
npm install
npm run dev

The Vite dev server will start on http://localhost:5173.

📖 Architecture & Design

Please refer to ARCHITECTURE.md for a comprehensive technical breakdown of the simulation loop, distributed event bus, and causal propagation mathematics.