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24-hour hackathon · team project

Spectravein

Ranks near-Earth asteroids as mining targets from live NASA data.

Analysis of asteroid 1036 Ganymed: S-type composition, mission briefing and valuation
Context
24-hour hackathon · team project
Stack
Next.js, React Three Fiber, FastAPI, scikit-learn, NASA/JPL SBDB

The problem

Judging an asteroid as a mining target means combining orbital data, likely composition and mission cost, which normally live in separate datasets and tools.

How it works

  • A FastAPI pipeline pulls live records from NASA/JPL's Small-Body Database and reclassifies them with K-Means clustering (k = 3).
  • Each target gets a briefing and a valuation from a theoretical economics model, clearly labelled as a simulation.
  • The dashboard ranks targets; selecting one loads its orbit in a React Three Fiber scene.
  • Admin pipeline runs are rate-limited and CORS is locked to known origins.

The result

934 near-Earth objects indexed and ranked, each with a mission briefing, an orbit view and a cost model.

Target acquisition table of 934 indexed near-Earth objects
Target acquisition table of 934 indexed near-Earth objects
Spectravein landing page: Live orbital intelligence
Spectravein landing page: Live orbital intelligence
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