# Straw Hats

- **Event:** [National Security Hackathon (by Army xTech)](https://cerebralvalley.ai/e/3rd-annual-natsec-hackathon)
- **When:** May 2 at 9:00 AM – May 3 at 4:00 PM (PDT)
- **Where:** Shack15, San Francisco, CA
- **Team:** [J S](https://cerebralvalley.ai/u/jarrensj), [Aurelia Sindhunirmala](https://cerebralvalley.ai/u/americano), [Aldo Maximus](https://cerebralvalley.ai/u/Kamtomeh)
- **GitHub:** https://github.com/AureliaSindhu/ghostfleetdetector
- **Demo video:** https://www.loom.com/share/6d8f12b8901c4041aa3d9e2fe1ca523d
- **Gallery:** https://cerebralvalley.ai/e/3rd-annual-natsec-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/3rd-annual-natsec-hackathon/hackathon/gallery/8

Ghost Fleet Detector identifies ships that "go dark," intentionally disabling their AIS transponders to evade sanctions, smuggle cargo, or fish illegally. Every commercial vessel over 300 tons is required to broadcast its position, so we detect the absence of data rather than the presence. Our platform ingests AIS vessel tracking data, finds unexplained gaps in transmission, and scores each dark period using multiple factors: gap duration, distance traveled, proximity to known transshipment zones, implied speed, vessel type, and time of day. Scores are weather-adjusted using real storm data (NOAA) so legitimate outages don't generate false alerts. Flagged vessels are cross-checked against the OpenSanctions database, and suspicious locations can be verified with Sentinel Hub satellite imagery. Results are displayed on an interactive deck.gl map with risk charts, AI-generated intelligence summaries, and CSV export. Built with Next.js, Supabase, and OpenAI.

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