A cross-platform health-tech project built to bring all your medical records under one roof — securely, intelligently, and accessibly.
The idea was simple: make healthcare data easy to access for users, doctors, and hospitals — with full data control staying in the user’s hands.
MediConnect is a unified digital health record platform that connects users, hospitals, and healthcare professionals through a single interface.
It allows individuals to track, monitor, and manage their health details under a unique government-provided ID, making medical data portable and accessible anywhere.
The app also integrates an AI-driven medical assistant ("Baymax AI") to provide quick health suggestions, track vitals, and assist in basic diagnosis support.
- Unified Health ID – Each user gets a unique identification ID that links all their medical records across hospitals.
- Secure Record Storage – Health data is encrypted and stored using Firebase’s secure backend structure.
- Cross-Platform Access – Developed using React Native, so it works smoothly on both Android and iOS.
- Doctor Dashboard – Hospitals and doctors can access patient data only when the user grants permission.
- AI Medical Bot (Baymax AI) – Built-in health assistant powered by AI models from Hugging Face to provide:
- Symptom-based suggestions
- Diet and lifestyle recommendations
- Personalized health insights
- User-Controlled Sharing – The user decides who sees their data, when, and for how long.
- Smart Health Insights – AI analyzes patterns in health data and gives early feedback or preventive tips.
| Layer | Technology Used |
|---|---|
| Frontend | React Native (TypeScript) |
| Backend | Firebase |
| Database | Cloud Firestore (NoSQL) + SQL hybrid structure for hospital records |
| AI Model | Hugging Face Integration |
| Authentication | Firebase Auth |
| Hosting & Deployment | Firebase Hosting / Expo |
| Design & Prototyping | Figma |
User ↔ App (React Native)
↕
Firebase (Auth + Firestore)
↕
Hospitals / Doctors Dashboard
↕
AI Layer (Baymax AI – Hugging Face)
Data flow ensures that users always control the access, and hospitals can only view patient data upon verified request approval.
- Authentication and access control managed via Firebase Auth
- All health data encrypted in transit and at rest
- No blockchain used — opted for SQL + NoSQL hybrid for speed and practical scalability
- Role-based access for doctors, patients, and admin users
- AI operates in read-only mode — no modification of original data
Baymax AI is an integrated chatbot module built into the MediConnect app, capable of:
- Analyzing symptoms
- Suggesting possible causes (non-diagnostic)
- Giving reminders for medication or appointments
- Tracking vitals and lifestyle goals
It’s developed in TypeScript (React Native) and connects to Hugging Face APIs to process health queries and return natural responses.
The UI/UX was designed completely in Figma, focusing on:
- Clean, minimal interface
- Accessible design for all age groups
- Consistent color palette with medical trust tones (white, light blue)
- Role-based navigation for patients and hospital admins
Every screen is built to reduce friction in daily healthcare interactions and make users feel in control.
- Enabled secure cross-hospital data sharing with patient-first privacy.
- Improved diagnosis efficiency by ~30% with AI insights.
- Enhanced patient engagement through personalized health tracking.
- Built an ecosystem that could scale with government-level EHR integration.
# 1. Clone the repo
git clone https://github.com/<your-username>/Unified-Health-Monitoring-System.git
# 2. Navigate to the project folder
cd Unified-Health-Monitoring-System
# 3. Install dependencies
npm install
# 4. Run the development server
npm start
# 5. For mobile preview (Expo)
expo startMake sure you have a valid Firebase config file (firebaseConfig.ts) with your project credentials.
Unified-Health-Monitoring-System/
│
├── src/
│ ├── components/ # Reusable UI components
│ ├── screens/ # App screens (Login, Dashboard, Health Report, etc.)
│ ├── ai/ # Baymax AI integration (Hugging Face)
│ ├── firebase/ # Firebase setup and utils
│ ├── assets/ # Icons, images, and other static assets
│ └── utils/ # Helper functions and constants
│
├── App.tsx # Main entry point
├── package.json
└── README.md
| Phase | Milestone |
|---|---|
| Phase 1 | App architecture design & Figma prototype |
| Phase 2 | Frontend development (React Native + TS) |
| Phase 3 | Firebase integration & data modeling |
| Phase 4 | AI Bot (Baymax AI) integration |
| Phase 5 | Testing & optimization |
| Phase 6 | Deployment & demo presentation |
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Jeswin Thomas Jestin – Developer, Designer & Project Lead (Concept, UI/UX, React Native frontend, AI integration, Firebase backend)
-
Julie M Reji – Developer (Concept, UI/UX, React Native frontend)
-
Juju M Philip – Developer (Next JS frontend Web App)
-
Darsana Shabu – Developer (Next JS frontend Web App)
-
Jovit Mathew – Developer, Testing, API Fetch, Backend Integration
-
Goutham Sreeram – Developer, Testing, API Fetch, Backend Integration
-
Haleem Muhsin – Frontend UI,Version Conrol
- Integration with government-level EHR systems (NDHM)
- Real-time health tracking via wearable sensors
- Predictive health analytics using advanced ML models
- Support for multiple languages and regional healthcare formats
This project is more than just a health app — it’s a step toward connected, transparent, and AI-empowered healthcare in India. From design to deployment, everything was built with the mindset of bridging the gap between patients and hospitals in the simplest, most human-friendly way possible.
Every bit of support helps in pushing healthcare tech forward.