PLANIX is a web-based application that leverages AI (Gemini) and real-time spatial data to support urban planning and land-use analysis.
Users can draw/select areas on an interactive map; PLANIX analyzes environmental and infrastructural conditions to generate land segmentation (residential, commercial, industrial, green zones) and tailored development recommendations.
- Automatically divides the selected area into functional land-use zones:
- Residential Zone — housing and neighborhood development
- Commercial Zone — business, retail, and economic hubs
- Industrial Zone — manufacturing, logistics, and warehouses
- Green/Open Space — parks, urban forests, and conservation areas
- Visualized with distinct colors and descriptive annotations on the map (GeoJSON).
- Displays infrastructure and natural features within the area:
- Buildings count
- Road networks (e.g., residential, secondary, service, track, path)
- Water bodies (rivers, lakes, ponds)
- Forests/vegetation (wood, scrub, park)
- Special land uses (quarry, cemetery, etc.)
- Enriched with topography, elevation, AQI (air quality), and weather via external APIs.
- Recommends industry types that can thrive in a saved area.
- Considers land size, proximity to major roads/transport links, air quality, and surrounding land use.
- Examples: logistics/warehousing near arterials; light manufacturing in flat areas far from dense residential zones.
- Suggests business types that fit best in saved areas.
- Considers building density, road connectivity, and proximity to population centers.
- Examples: retail hubs in dense centers; local markets/minimarts near residential clusters.
- Assesses suitability for housing and neighborhood development.
- Considers air quality, green/open space proximity, accessibility, and elevation.
- Examples: eco-friendly residential planning where air is cleaner and green assets are nearby.
- Answers user questions about analysis results and planning rationale:
- “Why is this zone suitable as a green area?”
- “What are the environmental constraints for building here?”
- Grounded responses using saved analysis data (Firestore).
- Save Changes: users can refine recommendations via chatbot; revised results are written back to Firestore.
- Save analysis results to user accounts (Firestore).
- Compare multiple saved areas and mark favorites for future review.
- Guest Mode — try core features without login.
- Logged-in Mode (Firebase Auth) — persist and manage personal analyses.
- Frontend: React, TailwindCSS, Leaflet
- Backend & Hosting: Firebase (Auth, Firestore, Cloud Functions, Hosting)
- AI: Google Gemini API
- Data Sources:
- OpenStreetMap — spatial & infrastructure data
- Open-Meteo API — weather data
- WAQI API — air quality index (AQI)
- Open-Elevation API — elevation/topography
A[User selects/draws area on Map] --> B[React + Leaflet Frontend] B --> C[Cloud Functions / Backend Orchestrator] C --> D[External APIs: OSM, Meteo, WAQI, Elevation] D --> C C --> E[Gemini AI: analysis + recommendations] E --> F[GeoJSON + Insights] F --> G[Firestore (save & reload)] F --> B[Map rendering + Chatbot context]