Disaster-Aware Blood Donation Network using Geo-Alert and Predictive Shortage Modeling

Blood is an irreplaceable resource in healthcare, and its demand increases critically during disasters such as earthquakes, floods, and pandemics. Traditional blood donation networks often fail to respond effectively due to lack of real-time communication, poor coordination, and absence of predictive planning. This project proposes a Disaster- Aware Blood Donation Network that integrates geo-location based alerts with machine learning-driven predictive shortage modeling to enhance responsiveness during emergencies. The system connects donors, blood banks, and hospitals on a unified platform where nearby donors receive instant notifications through geo-alerts. Predictive models analyze historical donation and usage trends to forecast shortages, thereby allowing proactive inventory management. Additionally, smart routing ensures optimal donor-to-hospital matching while maintaining data security and privacy. By combining real-time geo-tracking and predictive analytics, the proposed framework aims to minimize delays, reduce wastage, and significantly improve the availability of blood in disaster scenarios. The outcome will strengthen healthcare resilience, support emergency response units, and save lives through timely and efficient blood supply management.