RaktaSevaAI -AI-Driven Thalassemia Care & Donor Ecosystem

RaktaSevaAI is an AI-powered ecosystem predicting blood demand, retaining donors via gamification, and ensuring timely care for Thalassemia patients through smart logistics and 24/7 chatbot support.

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Inspiration

In India, thousands of children and adults with Thalassemia require regular blood transfusions to survive. We kept hearing stories about families scrambling to find donors at the last minute, and about hospitals struggling to maintain adequate blood supplies. The existing system was clearly reactive rather than preventive , waiting until crises happened before responding.

What it does

RaktaSevaAI is a smart system designed to help thalassemia patients get blood transfusions when they need them. It predicts when blood will be needed, helps find willing donors, and makes sure blood is stored properly. Our chatbot also answers common questions from patients and families in simple language.

How we built it

We started by talking to doctors and thalassemia patients to understand the real problems. Then we created: 1) A donor matching system that learns when people are most likely to donate again 2) Tools to help hospitals plan their blood needs in advance 3) A simple way for patients to ask questions and get reliable answers 4) A tracking system to make sure donated blood doesn't go to waste We used common technologies like Python and React, focusing on making everything work smoothly rather than using fancy new tools.

Challenges we ran into

1) Getting hospitals to trust our system with their data 2) Making the technology simple enough for everyone to use, not just tech experts 3) Dealing with spotty internet in some areas 4) Creating accurate predictions without huge amounts of data The hardest part was designing something that actually helps in the real world, not just on paper.

Accomplishments that we're proud of

1) Creating a working system that real hospitals are testing 2) Making something that both doctors and patients find usefu 3) Building a team that includes both tech experts and medical professionals 4) Developing simple solutions to complex problems

What we learned

1) Technology alone can't solve health problems - people and processes matter more 2) Simple, reliable solutions beat complex ones in healthcare 3) You need to listen carefully to both medical staff and patients 4) Change happens slowly in healthcare, and that's okay

What's next for RaktaSevaAI -AI-Driven Thalassemia Care & Donor Ecosystem

We're now working on: 1) Testing the system in more hospitals 2) Improving our predictions as we get more data 3) Adding support for more regional languages 4) Making the donor matching even smarter

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