InvaSphere was inspired by the need to engage students in environmental monitoring while supporting forest rangers in managing real threats efficiently. We wanted a system that leverages gamification to teach sustainability while ensuring that professionals aren’t overwhelmed with irrelevant data.

What We Learned:

  • How to integrate serverless architecture with Supabase and Next.js.
  • How to use AI (Gemini 1.5 Flash) for image recognition in a real-time PWA.
  • How to implement role-based filtering and Row Level Security (RLS) to protect sensitive data.

How We Built It:

  • Frontend: Next.js 15 with React Server Components, Tailwind CSS, Mapbox GL JS for mapping.
  • Backend: Supabase PostgreSQL with PostGIS, RLS policies, Edge Functions on Vercel.
  • AI Integration: Gemini 1.5 Flash via Vercel AI SDK to detect species and hazards.
  • Gamification & Incentivization: XP system and achievements sponsored by Google AdSense for revenue

Challenges Faced

  • Ensuring scouts only see their own data while rangers see only threats.
  • Handling “unknown” or unidentifiable species gracefully in the AI workflow.
  • Supporting real-time updates and notifications across multiple users without performance bottlenecks.

Built With

  • gemini1.5flash
  • lucidereact
  • mapboxgljs
  • next.js-15
  • react-19
  • rls
  • sonnertoastnotifications
  • supabase-(postgresql-+-postgis)
  • supabase-realtime
  • tailwind
  • typescript
  • vercel
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