✈️ Airspace Visualizer (Pre-Release)

⚠️ Work-In-Progress — expect breaking changes and incomplete features.
This is a pre-release version of the Airspace Visualizer, an experimental real-time air traffic display and AI assistant for aviation data.

The system combines:

• Live ADS-B aircraft tracking (via readsb)
• Live ACARS/VDL2 message reception (via dumpvdl2)
• Radar-style HTML visualizer with configurable controls
• Semantic RAG + Chat assistant using local AI models (via Ollama)
• Optional geographic overlay from OpenStreetMap

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🚀 Features (Current Pre-Release)

• Live radar-scope display with configurable range, trails, and filters.
• Contact list and communications log.
• ACARS message correlation with aircraft on the scope (blue text).
• AI assistant for querying current traffic and message context (requires Ollama local install).
• Geographic feature overlays (airports, cities, ports, etc.).
• Modular bridge service for ADS-B and ACARS feeds.
• Semantic search & chat endpoints with FAISS + embeddings.

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📦 Components

File	Purpose
visualizer_bridge.py	Serves ADS-B and ACARS data over HTTP (dump1090/dumpvdl2-compatible endpoints).
airspace_visualizer.html	Browser-based radar display & control panel.
ai_server.py	Semantic search + chat API using local LLM embeddings via Ollama.
quick_start.sh	Helper script to launch the bridge & AI server.
readsb_ingest.sh	Ingest script for ADS-B data from readsb/dump1090.
dumpvdl2_ingest.sh	Ingest script for VDL2/ACARS data from dumpvdl2.
requirements.info	Dependency list for Python components.

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⚙️ Quick Start (Developer Preview)

1. Prerequisites

   • Python 3.9+
   • ollama with nomic-embed-text and gemma3:4b models
   • dump1090 / readsb for ADS-B
   • dumpvdl2 for ACARS/VDL2

2. Clone & Install

   git clone https://github.com/YOURUSERNAME/airspace-visualizer.git
   cd airspace-visualizer
   pip install -r requirements.txt

3. **Run python mock_data_generator.py first to generate test data, then start the other services.

4. Run Data Bridges

   ./readsb_ingest.sh &
   ./dumpvdl2_ingest.sh &
   python3 visualizer_bridge.py

5. Start AI Server

   python3 ai_server.py

6. Open Visualizer

   • Serve airspace_visualizer.html from a local web server.
   • Configure the dump1090 & dumpvdl2 URLs in the Radar Controls panel.
   • Click Connect to start receiving live data.

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🛠 Status

This is an early, unstable build aimed at testers and contributors.
Known limitations:

• Not all controls are functional.
• Geographic overlay may be incomplete.
• No authentication on API endpoints.
• AI assistant relies on local model availability.

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🤝 Contributing

Pull requests, bug reports, and feature ideas are welcome — especially on data visualization, UI improvements, and AI query refinement.

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📜 License

MIT License — use at your own risk.