Inspiration
Each year India experiences the birth of numerous children with Thalassemia but most of them do not receive appropriate blood matches or sufficient medical treatment on time. We along with volunteers and technology professionals felt compelled to support Blood Warriors because of their dedication to eliminating this healthcare divide. We developed ThalAlve as an AI-first solution because of the essential need to speed up transfusions and improve patient trust and care while addressing the low donor retention and digital unawareness among patients.
What it does
ThalAlve uses AI to predict when donors will be available based on their previous actions while sending notifications to regular donors.
ThalAlve finds matching donors who are compatible with Thalassemia patients based on their location.
Regular donors receive rewards through the gamified dashboard which ThalAlve provides.
The platform enables multilingual communication between patients and doctors through its chatbot and teleconsultation features.
Families receive educational content through AI which generates information in their native languages.
The platform secures its data through blockchain medical records and encryption access systems.
The platform connects with e-RaktKosh and Blood Bridge systems to improve national blood distribution network operations.
How we built it
The project utilizes React.js to build web interfaces and Flutter to create mobile application mockups.
The backend system employs Node.js alongside Express APIs.
The patient and donor information gets stored in MongoDB whereas real-time data updates are handled through Firebase.
The project utilizes Python scikit-learn to train a basic donor prediction model through synthetic data generation.
The Hyperledger-based data flow simulation provides a framework to maintain donor and patient record integrity through blockchain technology.
The system includes a mock API which functions to simulate data exchanges between e-RaktKosh and Blood Bridge platforms.
The design process used Figma for wireframes while Twilio provided alert services and Google Translate API
Challenges we ran into
The development of authentic datasets for predicting donor behaviour faces challenges because public health data remains unavailable
The design achieved accessibility to both rural and urban users through intentional development strategies
Designing a system which delivers real-time responses without compromising data protection measures
The chatbot needed to develop a natural conversation experience despite limited training data availability.
Accomplishments that we're proud of
The project team developed a real-time patient-donor matching simulation through a complete end-to-end Minimum Viable Product.
The architecture framework contains three independent layers which consist of AI components along with blockchain integration and user interface modules that scale up.
A functional predictive model was implemented to forecast when donors would be available.
The donor dashboard employs gamification elements to enhance participation levels of users while maintaining their involvement in the platform.
The project maintains complete alignment to Blood Warriors' fundamental goals and their
What we learned
The process of designing health technology systems for real-world applications that require high compliance standards
The process of uniting humanitarian objectives with scalable artificial intelligence systems
The significance of constructing systems with empathy to provide simple access for patients and caregivers and volunteers
The ability of a well-integrated system (APIs + community + automation) to resolve vital issues
What's next for ThalAlve
Pilot Launch: Blood Warriors should collaborate with us to conduct practical tests in specific selected regions.
Advanced ML Models: The system should learn from real-time donor responses and patient requirements to enhance predictive accuracy.
Blockchain Integration: The system should adopt Hyperledger Fabric or Polygon to achieve secure and traceable blockchain functionality.
Offline/IVR Support: The system needs to provide services to users who have either limited internet access or non- smartphone devices.
National Expansion: The system should work with e-RaktKosh and MoHFW to achieve widespread adoption at
Built With
- ask
- aws/gcp-(planned)
- e-raktkosh-api-(mock)
- express.js
- figma
- firebase
- flutter
- github.
- hyperledger-fabric-(simulated)
- mongodb
- node.js
- oauth2.0
- python
- react.js
- scikit-learn
- sendgrid
- twilio
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