Save Us: AI-Powered Donor Filtering for Safe Blood Donation

Blood donation is often inefficiently managed, with social media platforms like WhatsApp and Instagram used for requests but lacking organization, leading to delays and misinformation. SaveUs addresses this by providing an AI-powered platform for real-time donor coordination and verified matching. Built with Flutter and Firebase, it ensures secure registration, tracking, and real-time notifications. A deep learning model filters eligible donors based on hemoglobin level (estimated via conjunctiva eye images), weight, health conditions, and age, ensuring only healthy donors are recommended. Unlike scattered social media appeals, SaveUs integrates direct donor-recipient interactions, eliminating delays and outdated requests. Future expansions include food donation and crowdfunding, making Save Us a comprehensive humanitarian platform for emergency aid. By combining deep learning, cloud technology, and mobile accessibility, it revolutionizes blood donation, improving healthcare efficiency and response time.

Authors

Publication Details

Published
2025-04-16
DOI
https://doi.org/10.1109/iccct63501.2025.11020565
Citations
1
Primary Topic
Blood donation and transfusion practices
Type
article
Field-Weighted Citation Impact
2.76
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Save Us: AI-Powered Donor Filtering for Safe Blood Donation

S. Harini, P. Kalaiselvi, V. Sangeetha, Alanka Sai Naimesha et al.
1 citations
Blood donation and transfusion practices
2.76
article

Save Us: AI-Powered Donor Filtering for Safe Blood Donation

S. Harini, P. Kalaiselvi, V. Sangeetha, Alanka Sai Naimesha, M Balakumaran., M Sribalaji.
article en
1 citations

Abstract

Blood donation is often inefficiently managed, with social media platforms like WhatsApp and Instagram used for requests but lacking organization, leading to delays and misinformation. SaveUs addresses this by providing an AI-powered platform for real-time donor coordination and verified matching. Built with Flutter and Firebase, it ensures secure registration, tracking, and real-time notifications. A deep learning model filters eligible donors based on hemoglobin level (estimated via conjunctiva eye images), weight, health conditions, and age, ensuring only healthy donors are recommended. Unlike scattered social media appeals, SaveUs integrates direct donor-recipient interactions, eliminating delays and outdated requests. Future expansions include food donation and crowdfunding, making Save Us a comprehensive humanitarian platform for emergency aid. By combining deep learning, cloud technology, and mobile accessibility, it revolutionizes blood donation, improving healthcare efficiency and response time.

Openalex Percentile: Top 10%
Blood donation and transfusion practices
2.76
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