Inspiration
Thalassemia patients require regular transfusions, but many face delays or missed sessions due to lack of matching donors. Existing solutions are helpful but lack AI-driven prediction, real-time multilingual engagement and quick services and connection. Reduces dependency on manual calls and emergency scrambling for blood availability.
What it does
The platform can connect the patients to blood donors in real time, track the donor history and predict their availability for blood donation. When blood is needed, the system instantly alerts the most likely donor. And there are features for promoting the donor.
How we built it
We first understood the core problem and thought of a solution for the problem. Then we defined the core features of our platform and MVP. We chose on what stack we can use to work in this platform. Figured out the correct algos for performing and fulfilling our required features and enhancing the solution.
Challenges we ran into
Reliable Data : Unavailability of correct data from industry level and lack of historical data. User Data: Privacy needs to be maintained while training the models with User data Accurate location tracking: GPS access and user consent may be barriers. Highly accurate data prediction: Currently low models are used, so accuracy is compromised.
What we learned
How medical and technical perspectives must align for solutions to be practical and need for simple interfaces for easier adoption.
What's next for RaktSetu
Hospital integration APIs Full multilingual chatbot Advanced prediction models with real data Nationwide rollout with NGO & government collaborations
