Halo.mp4
Halo is a healthcare operations and monitoring platform that combines outbound patient calling, doctor workflows, and a nurse-facing 3D hospital digital twin in one integrated stack.
Upload: Import a hospital floor plan (PNG/JPG) and reconstruct room layout locally in the browser.
Visualize: Explore the floor in a persistent Three.js scene with priority-coded care rooms and occupancy state.
Assign: Sync live patient and room data from the backend so only occupied care rooms become interactive.
Inspect: Open a patient room to view a 3D body model with condition markers mapped to clinical severity and body area.
Operate: Switch to Doctor mode to manage patients, author call questions, and launch outbound check-in calls.
Monitor: Track call session progress and history while backend webhooks orchestrate turn-by-turn phone workflows.
Iterate: Update patient records and room assignments; the 3D scene refreshes from the latest backend feed.
- Node.js 18+
- Python 3.10+
- MongoDB (local or Atlas)
- API keys for Twilio Voice (outbound calls)
- Optional: Gemini API key (live room generation and condition guidance)
cd frontend
npm install
npm run devOpen http://localhost:3000.
Set the backend URL before Doctor mode will connect correctly:
DOCTOR_API_BASE_URL=http://127.0.0.1:8000cd backend
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env # add MongoDB URI, Twilio, and service credentials
uvicorn main:app --host 0.0.0.0 --port 8000- Next.js and React: App Router UI with Nurse and Doctor modes
- Three.js: Interactive 3D hospital floor plan and patient body visualization via React Three Fiber and Drei
- Next API routes: Server-side proxy to backend (
/api/doctor/*) and live room-data merge endpoints
- FastAPI: Patient CRUD, session history, call initiation, and Twilio webhook orchestration
- MongoDB: Persistent storage for residents, sessions, and call artifacts
- Twilio Voice: Outbound calls with HTTP webhook-driven conversation state machines
- Speech and reasoning pipeline: Transcription, acoustic analysis, and structured clinical summaries for check-in workflows
Care teams often split their work across phone workflows, spreadsheets, and disconnected monitoring tools. Halo brings those flows into one system: doctors can run structured outreach from a dashboard, while nurses can see who needs attention spatially on a hospital floor instead of parsing static lists.
The goal is to make remote patient check-ins and room-level clinical awareness faster, clearer, and easier to act on in real time.
MIT