# 🌊 HADEX Project Summary

## Overview
HADEX is a Physics-Informed AI framework for modeling ultra-deep ocean environments (below 6,000m) through the Hadal Environment Index (HEI), with swarm navigation achieving 0.78m accuracy in GPS-denied conditions.

## Key Specifications
- **HEI Parameters**: 8 (Hcr, nac, Oflux, PEH, TTC, CBL, Hts, APD)
- **Validation Trenches**: 3 major sites (Challenger Deep 10,911m, Tonga 10,882m, Philippine 10,540m)
- **Swarm Navigation Accuracy**: 0.78m RMS (40× improvement)
- **Density Prediction Error**: ±0.3% (Tait equation @ 110MPa)
- **Acoustic Propagation Error**: ±12ms over 5km
- **Energy Harvesting**: 2.8mW continuous from pressure fluctuations

## Applications
- Autonomous hadal exploration
- Earthquake early warning (subduction zones)
- Biodiversity monitoring
- Carbon cycle studies
- Europa/Enceladus ocean analog

## Resources
- Dashboard: https://hadex.netlify.app
- Docs: https://hadex.readthedocs.io
- Code: https://gitlab.com/gitdeeper8/HADEX
- DOI: 10.5281/zenodo.18883858

## Team
- **Samir Baladi** (Principal Investigator)
- Collaborators: Jamieson, Fryer, Glud, Ito, Linley, Stewart, Mogi, Yamaguchi
