Wave Tracker - Mobile Network Analysis Tool 📱

A powerful web application for analyzing mobile network performance and coverage. Built for the LabLab AI for Connectivity Hackathon.

🎥 Demo

🚀 Features

• Single Tower Analysis: Analyze individual cell tower performance using MCC, MNC, Cell ID, and LAC codes
• Area Coverage Analysis: Evaluate network coverage across geographical areas
• Real-time Speed Predictions: Get instant speed estimates based on signal strength and tower data
• AI-Powered Insights: Receive intelligent suggestions for network optimization
• Interactive Visualization: View network performance metrics through dynamic charts and graphs

🛠️ Tech Stack

Frontend

• Framework: Next.js 14 (App Router)
• Language: TypeScript
• Styling: Tailwind CSS
• UI Components:
  • Geist Font (by Vercel)
  • Framer Motion (for animations)
  • Chart.js (for data visualization)
  • React Icons

Backend (API Routes)

• Runtime: Node.js
• API Framework: Next.js API Routes
• External APIs:
  • OpenCellID API (for tower data)
  • OpenAI GPT-4 API (for network insights)

Development Tools

• Package Manager: npm
• Version Control: Git
• Code Quality: TypeScript strict mode
• Development Server: Next.js development server

📦 Dependencies

{
  "dependencies": {
    "next": "14.2.23",
    "react": "^18",
    "react-dom": "^18",
    "framer-motion": "latest",
    "chart.js": "^4.x",
    "react-chartjs-2": "^5.x",
    "openai": "^4.x",
    "react-icons": "^4.x",
    "@geist-ui/core": "latest"
  },
  "devDependencies": {
    "typescript": "^5",
    "@types/react": "^18",
    "@types/node": "^20",
    "tailwindcss": "^3",
    "autoprefixer": "^10",
    "postcss": "^8"
  }
}

🔧 Installation

1. Clone the repository

   git clone https://github.com/your-username/wave-tracker.git
   cd wave-tracker

2. Install dependencies

   npm install

3. Set up environment variables Create a .env.local file in the root directory:

   OPENCELLID_API_KEY=your_opencellid_api_key
   OPEN_AI_API_KEY=your_openai_api_key

4. Run the development server

   npm run dev

5. Open the application Navigate to http://localhost:3000

🌐 API Integration

OpenCellID API

• Used for fetching cell tower data
• Endpoints used:
  • /cell/get: Get single tower information
  • Parameters: MCC, MNC, Cell ID, LAC

OpenAI API

• Used for generating network insights
• Model: GPT-4
• Implementation: Custom prompts for network analysis

📊 Data Flow

1. User Input

   • Tower Analysis: MCC, MNC, Cell ID, LAC codes
   • Area Analysis: Geographic coordinates, radius

2. Data Processing

   • Tower data fetching from OpenCellID
   • Signal strength calculation
   • Speed prediction algorithms

3. AI Analysis

   • Network performance evaluation
   • Optimization suggestions generation
   • Coverage improvement recommendations

🎨 UI/UX Features

• Responsive Design: Mobile-first approach
• Dark/Light Mode: System preference detection
• Interactive Elements:
  • Animated transitions
  • Loading states
  • Error handling
• Onboarding Tutorial: First-time user guidance
• Accessibility: WCAG compliance

🔒 Security

• Environment variables for API keys
• Input validation
• Rate limiting on API routes
• Secure headers configuration

🚀 Deployment

The application is optimized for deployment on Vercel:

1. Push to GitHub
2. Connect to Vercel
3. Configure Environment Variables
4. Deploy

Alternative deployment options:

• AWS
• DigitalOcean
• Netlify

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Commit changes
4. Push to the branch
5. Open a pull request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

👥 Team

• AI Ninjas
  • Built during the LabLab AI for Connectivity Hackathon
  • Team Profile

🙏 Acknowledgments

• LabLab.ai for hosting the hackathon
• OpenCellID for providing tower data
• OpenAI for AI capabilities
• Vercel for hosting and deployment

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For more information, contact the team or visit our GitHub repository.