InfraVision 🏗️

InfraVision is a cloud-native platform designed for uploading, visualizing, and diagnosing 3D infrastructure models, such as bridges, pipelines, and roads. Engineers can upload CAD-like files, run structural diagnostics, and explore models in real-time through a web-based interface.

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🚀 Key Features

• CAD File Uploads: Supports STEP, IGES, and STL formats
• 3D Visualization: Interactive rendering with Three.js
• Diagnostics Engine: Automated anomaly detection with AI modules
• Kubernetes Architecture: Scalable pipeline for large-scale processing
• Real-time Metrics: Stress analysis, load distribution, and performance overlays
• File Format Flexibility: Multi-format CAD compatibility

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🛠️ Tech Stack

Frontend:

• React + TypeScript
• TailwindCSS
• Three.js

Backend:

• Node.js (Express)
• C++ (geometry parsing and analysis)
• PostgreSQL (persistent data store)

Infrastructure:

• Docker
• Kubernetes
• Redis (for job queueing)
• AWS/GCP (cloud deployment)

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🔢 Prerequisites

• Node.js >= 18.x
• Docker >= 20.x
• Kubernetes >= 1.24
• PostgreSQL >= 14.x
• C++ compiler (g++, clang)

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🔧 Local Setup

# Clone repo
$ git clone https://github.com/yourusername/infravision.git
$ cd infravision

# Install frontend/backend deps
$ npm install

# Configure environment
$ cp .env.example .env

# Run PostgreSQL and Redis
$ docker-compose up -d postgres redis

# Migrate DB
$ npm run migrate

# Launch dev servers
$ npm run dev

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🚧 Docker Setup

$ docker-compose build
$ docker-compose up
# Frontend: http://localhost:3000
# API: http://localhost:5000

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🚀 Kubernetes

$ kubectl apply -f k8s/
$ kubectl get pods -n infravision
$ kubectl port-forward svc/infravision-frontend 3000:3000

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📁 Structure

frontend/   -> React client
backend/    -> Express API
processor/  -> C++ analysis engine
k8s/        -> Kubernetes configs
docker-compose.yml

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🔌 Key Endpoints

• POST /api/upload: Upload file
• GET /api/analysis/:fileId: Retrieve diagnostics
• GET /api/model/:fileId/geometry: Fetch model geometry

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📊 Performance

• Avg. 500ms per 50MB CAD file
• API latency ~100ms (P95)
• 1000+ concurrent user support
• 10TB+ model data processed

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🔒 Security

• JWT Authentication
• File validation
• TLS, rate limiting, and SQL injection prevention