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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM31306

Blood Donation System using Geo-Tracking and Machine Learning: A Comprehensive Survey

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM31306

Volume:

8 |

4 |

Apr 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM31306

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SSS

Sumit Shriram Sable

SJ

Suhas Jadhav

APG

Abhishek Prashant Ghaisas

AB

Anshuman Bhende

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Abstract

This paper addresses blood donation by making use of advanced technologies to make the process easy and efficient. It emphasizes the importance of tailored systems and highlights successful studies implementing innovative solutions. Incorporating various technologies like Geographical Tracking and Machine Learning, the project explores various prediction algorithms and libraries used to build an efficient, innovative, and easy-to-use solution. The paper aims to demonstrate and explain in detail the various tools and techniques used to attempt to bring this idea to fruition, and the benefits that the usage of this technology has brought to the table not only for us as developers, but for the potential users of this app as well.

KEYWORDS

API Java Python Geo-Tracking Machine Learning Deep Learning Maps

Cite This Article

Sumit Shriram Sable, Suhas Jadhav, Abhishek Prashant Ghaisas, Anshuman Bhende, "Blood Donation System using Geo-Tracking and Machine Learning: A Comprehensive Survey," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 4, Apr 2024. https://doi.org/10.55041/IJSREM31306

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12/31/45432

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