Blood Donor Matching Information Systems and Determining Tools for Blood Cluster and Human Rhesus Based on IoT

DOI

10.2991/aer.k.201124.019How to use a DOI?

Keywords

Blood Type, Blood Donor, Internet of Things

Abstract

Until now, the process of testing human blood groups is still done manually by mixing blood and antisera. Testing is done by observing the agglutination reaction of blood samples. Then the testing process takes a long time, without storing donor data. this is less effective if the blood is tested a lot and in an emergency. This study aims to create a system that can provide blood donor match information and can determine the blood type and rhesus of humans automatically. This research uses the ABO system method and the rhesus system. The data input of this study uses the LDR voltage values illuminated by LEDs. Furthermore, the voltage value is processed by Arduino Uno. The data output is displayed on the LCD and android smartphone application, using the NodeMCU Wi-Fi module ESP8266. The application comes with a data store called Microsoft Excel. Based on test results, the system is able to determine blood groups with a voltage range detecting agglutination LDR1 = 0-1,3345 Volts, LDR2 = 0-1,2955 Volts and LDR3 = 0-1,183 Volts. While the voltage range does not detect agglutination LDR1 = 1.3345-2.2 Volts, LDR2 = 1.2955-2.2 Volts and LDR3 = 1.183-2.2 Volts. The percentage of system accuracy is 97.5%, with an average detection time of 02.43 seconds for the instrument and 20.33 seconds for the application.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Aditya Chandra Hermawan
AU  - Ita Mubarokah
AU  - Farid Baskoro
PY  - 2020
DA  - 2020/11/24
TI  - Blood Donor Matching Information Systems and Determining Tools for Blood Cluster and Human Rhesus Based on IoT
BT  - Proceedings of the International Joint Conference on Science and Engineering (IJCSE 2020)
PB  - Atlantis Press
SP  - 102
EP  - 106
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.201124.019
DO  - 10.2991/aer.k.201124.019
ID  - Hermawan2020
ER  -