SkyLaneAI

AI-Powered Sky Hazard Detection for Flying Taxis

What is SkyLaneAI?

SkyLaneAI protects flying taxis and aerial vehicles from collisions by detecting sky hazards in real-time. Upload a video or connect a live camera feed, and our AI identifies birds, drones, balloons, and kites—calculating collision risk and providing instant alerts.

Key Features

• Video Analysis: Upload videos to detect and track sky hazards
• Smart Detection: AI identifies birds, drones, balloons, and kites with visual overlays
• Multi-Agent AI System: Powered by LangGraph with specialized agents working together to analyze detections, assess context, and generate intelligent alerts
• Interactive Timeline: See all detected hazards throughout your video
• Context-Aware Alerts: AI agents understand patterns and generate natural language safety warnings
• Filter & Search: Focus on specific hazard types or severity levels

How It Works

1. Upload a video through the web interface
2. AI analyzes each frame using advanced zero-shot object detection (YOLO-World)
3. Multi-agent system processes detections through specialized LangGraph agents:
   • Alert Agent: Orchestrates the analysis workflow
   • Context Agent: Analyzes detection patterns and environmental context
   • Message Agent: Generates natural language alerts and recommendations
4. View results with bounding boxes, labels, and an interactive timeline
5. Review intelligent alerts with context-aware safety recommendations

Coming Soon: Live camera feed analysis with real-time collision warnings based on Time-to-Contact calculations.

Quick Start

Prerequisites

• Node.js (v20+) and pnpm
• Python (v3.11+)
• OpenAI API key

Installation

# Clone the repository
git clone https://github.com/samiur-r/SkyLaneAI.git
cd SkyLaneAI

# Install dependencies
npm install -g pnpm
pnpm install

# Set up backend
cd apps/api
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

Configuration

Create .env.local in apps/web:

NEXT_PUBLIC_API_URL=http://localhost:8000

Create .env in apps/api:

OPENAI_API_KEY=your_openai_api_key

Run the Application

Terminal 1 - Frontend:

pnpm --filter web dev

Terminal 2 - Backend:

cd apps/api
source venv/bin/activate
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

Visit http://localhost:3000 to start using SkyLaneAI.

Technology Stack

• Frontend: Next.js, TypeScript, Tailwind CSS, shadcn/ui
• Backend: FastAPI (Python), YOLO-World, OpenCV
• AI Multi-Agent System:
  • LangGraph: Agent orchestration and workflow management
  • OpenAI GPT: Powers intelligent decision-making across specialized agents
  • Agent Architecture: Modular design with Alert, Context, and Message agents working in coordination

Documentation

Visit /docs in the application for detailed guides on features, technology, and usage.

Project Structure

SkyLaneAI/
├── apps/
│   ├── web/          # Next.js frontend
│   └── api/          # FastAPI backend
├── packages/         # Shared code
└── README.md

Contributing

We welcome contributions! Please:

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

Support

• Issues: GitHub Issues
• Email: samiur.rahman.akif@gmail.com
• Docs: Available at /docs in the app

License

MIT License - See LICENSE file for details.

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Building safer skies through AI innovation