StarHabitat

Inspiration

We built StarHabitat to bridge the gap between conceptual habitat design and data driven validation. Current workflows fragment visualization, physical estimation, and collaboration, delaying critical decisions for mission planners and researchers. StarHabitat was inspired by open science, modular architecture design, and citizen science platforms that make complex domains accessible to diverse teams.

What it does

StarHabitat provides a web based editor for designing orbital and planetary habitats with ready made templates for orbital station, lunar base, and martian habitat. It runs a probabilistic simulator that estimates temperature, pressure, oxygen consumption, CO2 production, radiation exposure, and energy usage from materials and spatial layout. The platform scores habitability across safety, sustainability, efficiency, and cost, enables scenario versioning and comparison, and exports GLTF and JSON for integration with other tools.

How we built it

The frontend uses React and Three.js for an interactive 3D canvas, responsive UI, and WASD plus mouse navigation. The backend is Node.js with a lightweight REST API for saving scenarios, running simulations, and managing comparisons. The simulator is a TypeScript module with documented formulas and unit tests that run under Jest. Data for modules, plants, and materials is stored in a small MongoDB instance for the demo and exposed through seeded endpoints.

Challenges we ran into

Balancing simulation fidelity with real time responsiveness required simplifying physical models while preserving useful insights. Designing an intuitive 3D editor that non experts can use took several UI iterations and tutorial prototypes. Enabling collaborative editing introduced conflict resolution needs that we handled with simple operational transforms for the hackathon scope. Export formats and integration edge cases required explicit parameter mapping to ensure reproducibility.

Accomplishments that we're proud of

We delivered a fully interactive editor with three habitat templates and exportable GLTF that renders accurately in external viewers. The simulator includes unit tests for critical calculations and produces consistent habitability scores across scenarios. Real time metric updates and a scenario comparator let users iterate quickly and make data backed tradeoffs. Documentation and a 3 minute demo script make the prototype reproducible by other teams.

What we learned

Simplified probabilistic models provide actionable guidance when assumptions and uncertainties are made explicit. UX matters as much as physics for adoption among interdisciplinary teams. Building modular data schemas early made it straightforward to add new plant species, materials, and mission profiles. Collaboration features require careful thought about ownership and merging even in small teams.

What's next for StarHabitat

Validate models with domain experts and incorporate measured environmental data from analog habitats and space agencies. Extend multiuser collaboration with real time locking and richer annotations. Add plumbing for authenticated workspaces, persistent cloud storage, and an open API for mission planning tools. Investigate hardware integration for telemetries and in situ experiment logging to close the loop between simulation and physical tests.

Built With

• base44