THALMEDI

Inspiration

Thalassemia is a chronic, inherited blood disorder requiring lifelong blood transfusions, often every 2–4 weeks. In India, thousands of Thalassemia patients, especially children, struggle to find timely blood donors, face coordination gaps between hospitals and donors, and lack educational resources in their language.

What inspired us most were real stories—parents running hospital to hospital to find a unit of matching blood. We knew technology could change this. We wanted to build a life-saving, inclusive platform powered by AI and driven by empathy: THALMEDI.

What it does

THALMEDI is an AI-powered mobile and web platform designed to streamline Thalassemia care. It offers: Real-time matching between Thalassemia patients and nearby blood donors AI-based prediction of donor availability SOS alert system for emergency blood requests Teleconsultation portal for doctor-patient communication Multilingual chatbot that educates users about Thalassemia care Health records dashboard to track transfusions, lab reports, etc. Integration with e-RaktKosh and Blood Bridge APIs End-to-end data security using AES encryption, JWT tokens

How we built it

Frontend:

Mobile: React Native

Web: React.js

Styling: Tailwind CSS + Material UI

Backend:

Node.js with Express.js

REST APIs + WebSockets for real-time communication

Database:

MongoDB for structured data

Firebase Realtime DB for live alerts and chat

AI/ML:

Python (scikit-learn, TensorFlow)

Security:

OAuth2 for authentication

AES-256 encryption for medical data

JWT for role-based access

DevOps:

Docker for containerization

GitHub Actions for CI/CD

Firebase Hosting for deployment

Challenges we ran into

Real-time performance: Ensuring timely alerts during emergencies

Data privacy: Encrypting and safely storing sensitive medical and donor data

Connectivity: Designing offline-safe features for rural areas with patchy internet

Multilingual support: Building a chatbot that handles multiple Indian languages

API limitations: Dealing with rate limits and downtime from public APIs

Accomplishments that we're proud of

Built a fully functional real-time donor matching engine

Successfully trained and deployed a predictive AI model

Integrated chatbot in 3 languages to reach diverse users

Designed a clean, accessible UI for non-tech-savvy users

Created a secure backend infrastructure that adheres to health data standards

What we learned

How to blend AI/ML with real-world impact

Managing end-to-end full-stack architecture under tight deadlines

Implementing secure healthcare applications

Deploying scalable solutions with Docker + Firebase

The importance of user-centered design, especially for medical platforms

What's next for THALMEDI

App Store Launch for Android and iOS

Wearable integration (e.g., pulse oximeter, heart rate) to prioritize patients

Donor rewards system to improve engagement

Collaboration with NGOs and hospitals for nationwide rollout

Adding data analytics dashboards for hospitals and researchers

Fine-tuning chatbot with OpenAI + multilingual datasets

Built With

• express.js-database:-mongodb
• firebase-realtime-database-ai/ml:-scikit-learn
• languages:-javascript
• python-frontend:-react.js
• react-native-backend:-node.js