An Algorithmic Approach for Optimizing Blood Transactions in Regions with Scarce Donation Rates

Disciplines

Artificial Intelligence and Robotics | Databases and Information Systems | Data Science | Public Health

Abstract (300 words maximum)

This poster presents the development of a software solution designed to optimize blood management systems in regions with low donation rates, including areas severely impacted by war, political instability, or economic challenges. Many regions around the world suffer from chronic shortages of blood donations, especially during crises, where conflict and natural disasters further exacerbate the scarcity of resources. In war-torn regions, limited healthcare infrastructure and reduced donor participation lead to critical blood shortages, making the optimization of blood resources more urgent than ever.

The project aims to streamline access to blood resources through a user-friendly application, enabling patients and donors to quickly locate and request blood from nearby facilities. The system uses a NoSQL Cassandra database for efficient management of large datasets, allowing real-time updates on blood availability. Key features include tracking blood groups, specific blood components (e.g., red blood cells, plasma, platelets), and their respective expiration dates to ensure proper utilization.

A recommender system is incorporated to match donors with appropriate donation centers based on their location and blood type, improving donor participation even in areas with low donation rates. The system also optimizes resource management by prioritizing the use of blood components nearing expiration, minimizing waste. This poster details the technical architecture, including database design, real-time data handling, and the implementation of scenarios where users interact with the system. Challenges encountered during the development process and potential enhancements, such as refining the recommender system and improving resource allocation algorithms, are also discussed.

Academic department under which the project should be listed

CCSE - Computer Science

Primary Investigator (PI) Name

Maria Valero

Additional Faculty

Robert Keyser, SPCEET, rkeyser@kennesaw.edu

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An Algorithmic Approach for Optimizing Blood Transactions in Regions with Scarce Donation Rates

This poster presents the development of a software solution designed to optimize blood management systems in regions with low donation rates, including areas severely impacted by war, political instability, or economic challenges. Many regions around the world suffer from chronic shortages of blood donations, especially during crises, where conflict and natural disasters further exacerbate the scarcity of resources. In war-torn regions, limited healthcare infrastructure and reduced donor participation lead to critical blood shortages, making the optimization of blood resources more urgent than ever.

The project aims to streamline access to blood resources through a user-friendly application, enabling patients and donors to quickly locate and request blood from nearby facilities. The system uses a NoSQL Cassandra database for efficient management of large datasets, allowing real-time updates on blood availability. Key features include tracking blood groups, specific blood components (e.g., red blood cells, plasma, platelets), and their respective expiration dates to ensure proper utilization.

A recommender system is incorporated to match donors with appropriate donation centers based on their location and blood type, improving donor participation even in areas with low donation rates. The system also optimizes resource management by prioritizing the use of blood components nearing expiration, minimizing waste. This poster details the technical architecture, including database design, real-time data handling, and the implementation of scenarios where users interact with the system. Challenges encountered during the development process and potential enhancements, such as refining the recommender system and improving resource allocation algorithms, are also discussed.