https://github.com/exploring-solver/digital_twin_bolt
https://github.com/exploring-solver/digital_twin_bolt
Last synced: 8 months ago
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- Host: GitHub
- URL: https://github.com/exploring-solver/digital_twin_bolt
- Owner: exploring-solver
- Created: 2025-06-14T21:32:31.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-06-30T22:50:13.000Z (8 months ago)
- Last Synced: 2025-06-30T23:25:32.515Z (8 months ago)
- Language: Python
- Size: 28.3 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Here's a comprehensive and professional GitHub `README.md` template for your **MQTT-based Digital Twin + SCADA + AI Predictive Maintenance** platform. It includes clear sections, feature overviews, and placeholders for screenshots, diagrams, and links.
---
````markdown
# 🌐 Digital Twin + SCADA + AI Maintenance Platform
A fully modular and scalable platform for real-time monitoring, control, and predictive maintenance using **MQTT**, **time-series databases**, **3D digital twins**, and **AI anomaly detection**. Designed for industries to digitize physical systems, reduce maintenance overhead, and gain intelligent insights.
---
## 🚀 Features
- 🔌 **Sensor-to-Cloud Streaming** via MQTT
- 📡 Real-Time SCADA Dashboard & Control
- 🧠 AI-Powered Predictive Maintenance (LSTM)
- 🧱 Modular Digital Twin Setup with Drag & Drop 3D
- 📊 Customizable Metrics, Alerts & Health Scoring
- 🔒 Secure User Auth & Device Tokenization
- 🧩 Developer SDKs for Python, C++, JS
---
## 📁 Project Structure
```bash
digital-twin-platform/
├── backend/
│ ├── api/ # REST & WebSocket APIs (FastAPI / Node.js)
│ ├── ingestion/ # MQTT listener & validator
│ ├── ai/ # LSTM autoencoder models
│ ├── synthesis/ # Metric rollups, aggregators
│ └── db/ # Supabase/PostgreSQL schema + migrations
├── frontend/
│ ├── ui/ # Bolt UI dashboard (React + Tailwind)
│ ├── twin-editor/ # Three.js 3D Digital Twin Viewer
│ └── scada-panel/ # Controls, metrics, visual alerts
├── sdk/
│ ├── python/
│ ├── cpp/
│ └── js/
└── docs/
└── architecture.md
````
---
## 📸 Screenshots
> **📌 Add screenshots below showing key features**
* ✅ Digital Twin Setup Panel
* 📈 Real-Time Sensor Dashboard
* 🧠 AI Predictive Maintenance Results
* 🎮 SCADA Controls + Emergency Stop
```
```
---
## 🧭 System Architecture
> **📌 Insert architecture diagram here**
```
```
Or generate with Mermaid:
```mermaid
flowchart LR
Sensors --> MQTT_Broker
MQTT_Broker --> Ingestion
Ingestion --> TS_DB
TS_DB --> AI_Engine
AI_Engine --> API
API --> Frontend
Frontend --> User
```
---
## 📦 Tech Stack
| Layer | Technology |
| ------------- | ----------------------------------------------- |
| **Edge** | ESP32, PLCs, Raspberry Pi |
| **Messaging** | MQTT (Mosquitto / EMQX) |
| **Backend** | FastAPI / Node.js, Supabase (PostgreSQL), Redis |
| **AI Engine** | Python, LSTM Autoencoder, Pandas |
| **Frontend** | React, Three.js, Tailwind, Recharts |
| **Infra** | Docker, Nginx, Supabase Functions |
---
## 🛠️ Setup Instructions
### 1. Clone the Repo
```bash
git clone https://github.com/yourusername/digital-twin-platform.git
cd digital-twin-platform
```
### 2. Configure Environment
Create `.env` in `backend/` and `frontend/`:
```env
# backend/.env
SUPABASE_URL=
SUPABASE_KEY=
MQTT_BROKER_URI=
JWT_SECRET=
```
### 3. Start the Services
```bash
# Backend (Ingestion, API, Synthesis)
docker-compose up --build
# Frontend
cd frontend/
npm install
npm run dev
```
---
## 👤 How It Works (User Journey)
> [📖 Full walkthrough in `docs/user-journey.md`](docs/user-journey.md)
1. ✅ **User signs up**, receives secure access token.
2. 🧠 **Creates Digital Twin** (GLTF import + config).
3. 🛰️ **Registers Sensors**, gets MQTT topics per device.
4. 🔌 **Edge device publishes data** via MQTT.
5. 📊 **Dashboard visualizes live data**, health scores.
6. ⚙️ **SCADA Panel controls** actuators (e.g. hoist).
7. 🤖 **AI engine analyzes 1-month data** to suggest maintenance.
---
## 📚 Documentation
* 📌 [Architecture Overview](docs/architecture.md)
* 📌 [Database Schema](docs/db-schema.md)
* 📌 [AI Model Design](docs/ai-predictive.md)
* 📌 [Developer SDKs](docs/sdk-guide.md)
* 📌 [API Reference](docs/api-spec.md)