Rios is an interactive spatial intelligence platform that combines traditional maps with immersive 3D visualization. It provides a unified workspace to explore, monitor, and interact with real-world assets in context.
Rios unites geospatial data, mapping, and a synchronized 3D scene into a single interactive interface. Users can search, inspect, and annotate assets while both the map and the 3D visualization remain consistent.
Rios is intended for operations, planning, and analytics teams that need a spatially coherent view of assets and activity. It bridges the gap between traditional GIS workflows and immersive 3D visualization by keeping contextual data synchronized across views.
The platform is optimized for incremental data loading and responsive interactions. Typical workflows include asset inspection, area management, route and vehicle monitoring, and lightweight annotation. Rios is designed to scale from single-site deployments to city-scale datasets by streaming scene geometry and prioritizing visible assets.
Maintainer note: I have over 10 years of experience managing open source projects and designed this README to follow established best practices for clarity and contributor onboarding.
Prerequisites
- Node.js 18 or later
- Yarn or npm
Install and run in development
npm install
npm run devBuild for production
npm run build
npm run preview- Interactive 2D map paired with a real-time 3D scene
- Vehicle and asset inspection and monitoring
- Area management and building annotations
- Centralized state for immediate cross-view updates
- Search and navigation tools
Top-level files and directories
package.json- project metadata and scriptssrc/- application source codepublic/- static assets and images
Rios loads backend geospatial and scene data through an API layer. Data is stored in global stores and consumed by both the map UI and the 3D renderer so that interactions update every view instantly.
Future priorities include real-time IoT integration, live vehicle tracking, multi-user collaboration, AI powered spatial insights, and tools for large-scale digital twin deployments.
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The project uses zustand for compact and efficient global stores. three with @react-three/fiber provides the 3D scene. leaflet and react-leaflet provide the map view. Axios is the data layer for HTTP requests.
Performance notes
- Keep 3D scene complexity bounded and load geometry lazily
- Batch state updates to avoid excessive re renders
- Use requestAnimationFrame for smooth scene updates
Contributions are welcome. Open an issue to propose changes or start a pull request. Follow existing code style and ensure linting remains green by running npm run lint.
If you intend to contribute substantial features, open an issue describing the design before implementing the change.
This repository is currently private. Choose a license and update package.json to reflect the project license when you make the repository public.
For questions or collaboration inquiries open an issue or contact the maintainers through the repository.