🛡️ MineSafeAI: Revolutionizing Mining Safety with AI-Powered Insights

Mining accidents have historically been a significant concern in India, demanding effective safety measures and thorough analysis to prevent future incidents. MineSafeAI addresses this critical need by leveraging Natural Language Processing (NLP) and Agentic AI to digitize, analyze, and provide real-time insights from extensive collections of Indian mining accident records.

Our platform transforms how safety data is processed and utilized — moving beyond traditional manual reporting to deliver intelligent, proactive accident prevention and regulatory compliance. By analyzing 143+ incident records from DGMS India (2015–2025), MineSafeAI aims to enhance safety, reduce manual auditing effort, and uncover deep insights into accident patterns and root causes.

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🌟 Features

MineSafeAI combines real-time data analysis, AI-powered insights, and collaborative features to make mining operations safer and more efficient.

🧠 Core AI & Data Processing

• Intelligent PDF Data Extraction: Uses OCR to read text from DGMS PDF reports and BERT-based NER models to extract critical accident details.

• Structured JSON Schema Conversion: Converts extracted data into a standardized, queryable format:

  {
    "mine": "Name of the Mine",
    "owner": "Owner of the Mine",
    "district": "District of the Mine",
    "state": "State (location) of the Mine",
    "mineral": "Mineral of the Mine",
    "place": "Place of Accident",
    "date": "Date of Accident",
    "time": "Time of Accident",
    "casualties": "Number of People killed",
    "injured": "Number of People seriously injured",
    "cause": "Prime facie cause of the Accident",
    "best_practices": "Best Practices only if explicitly mentioned",
    "cause_label": "Classified as one of 'Fire', 'Explosion', 'Roof Fall', 'Fall', 'Machinery', 'Transport', 'Electricity', 'Ground Movement', 'Eruption Of Water', 'Flying Pieces', 'Combustible Gas', 'Inundation'"
  }

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Extracted Data

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• Autonomous Safety Monitoring Agents:

  • Watch Agent: Monitors DGMS alert websites for new updates.
  • Fetch Agent: Processes new PDF alerts and converts them to structured data.
  • Database Update Agent: Integrates processed data into Supabase in real time.
  • Proactive Alert Engine: Flags potential hazards (e.g., “Increase in transport machinery accidents in Jharkhand mines – Q3 2022”).
  • Recommendation Engine: Suggests preventive measures and inspection schedules.

• Interactive “Digital Mine Safety Officer”: A conversational AI interface that allows users to:

  • Query domain-specific information (e.g., “Show methane-related accidents in 2021 underground coal mines.”)
  • Receive compliance suggestions (e.g., “Mine X exceeds threshold for ground movement incidents; schedule slope stability inspection.”)

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🖥️ Platform & UI Features

• Real-time Monitoring Dashboard: Interactive visual summary of accident trends and timelines.
• Interactive Map Visualization: Uses React Leaflet for spatial analysis of incidents.
• AI-Powered Chat Interface: Conversational insights from the “Digital Mine Safety Officer.”
• Automated Safety Reports: Generates detailed audit reports with zero manual effort.
• Trend Analysis: Identifies emerging risks using time-series and spatial patterns.
• Admin Controls: Manage user roles, permissions, and platform configurations.

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🚀 Project Structure

├── backend/                  # Backend server implementation
│   ├── server.js              # Express server setup
│   ├── router.js              # API route definitions
│   └── supabase.js            # Supabase client configuration
│
├── frontend/                 # React frontend application
│   ├── src/
│   │   ├── components/        # Reusable React components
│   │   ├── lib/               # Utility functions and configurations
│   │   └── pages/             # Page components
│   └── public/                # Static assets

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💾 Database Schema

MineSafeAI uses Supabase as a real-time, scalable database. The schema stores incident data, classified cause labels, extracted entities, and derived analytics. (An ER diagram can be added here when finalized.)

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🛠️ Technologies Used

Frontend

• ⚛️ React 18 + TypeScript — scalable and type-safe UI.
• ⚡ Vite — lightning-fast dev and build tool.
• 🎨 TailwindCSS — utility-first styling framework.
• 🎞️ Framer Motion — smooth UI animations.
• 🧭 React Router — client-side navigation.
• 📊 Recharts — interactive data visualizations.
• 🗺️ React Leaflet — map visualizations for mining locations.
• 🧩 Supabase Client — real-time synchronization and querying.

Backend

• 🟢 Node.js + Express — lightweight and fast backend framework.
• 🤖 Google AI — for generative insights and NLP tasks.
• 🧮 Supabase — managed Postgres + real-time database.
• 🌐 Axios — for efficient API requests.
• 🧾 OCR Libraries — for text extraction from DGMS PDFs.
• 🧠 BERT (via NLP frameworks) — Named Entity Recognition and cause classification.

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💡 Agentic AI Integration

MineSafeAI incorporates agentic AI to move from reactive reporting to proactive safety intelligence.

• Autonomous Monitoring Agents: Continuously scan official sources for new incidents, classify causes, and generate alerts.
• Digital Mine Safety Officer: A domain-aware conversational agent that interacts with structured safety data, answering queries, suggesting compliance actions, and providing intelligent recommendations.

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🎬 Getting Started

Prerequisites

• Node.js (latest LTS)
• npm or yarn
• Supabase account + project
• Google AI API Key

Installation

# Clone the repository
git clone https://github.com/Animesh-Parashar/MIningAI.git
cd MIningAI

# Install backend dependencies
cd backend
npm install

# Install frontend dependencies
cd ../frontend
npm install

Configuration

Create a .env file in the backend directory:

SUPABASE_URL=your_supabase_url
SUPABASE_KEY=your_supabase_key
GOOGLE_AI_API_KEY=your_google_ai_key

Then, configure the frontend Supabase client in frontend/src/lib/supabaseClient.js with your Supabase credentials.

Running the Application

# Start backend
cd backend
npm run dev

# Start frontend
cd ../frontend
npm run dev

App available at: http://localhost:5173

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⚙️ Development

Backend Scripts

• npm start — Run production server
• npm run dev — Run development server (with hot reload)

Frontend Scripts

• npm run dev — Start dev server
• npm run build — Build for production
• npm run preview — Preview production build
• npm run lint — Run ESLint
• npm run typecheck — TypeScript validation

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🤝 Contributing

We welcome contributions to MineSafeAI!

1. Fork the repository.

2. Create your feature branch:

   git checkout -b feature/amazing-feature

3. Commit your changes:

   git commit -m "Add some amazing feature"

4. Push to your branch:

   git push origin feature/amazing-feature

5. Open a Pull Request.

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📄 License

This project is proprietary and confidential. All rights reserved © 2025 MineSafeAI.

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📞 Contact

Animesh Parashar 🔗 GitHub Profile 📘 Project Repository

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