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20 December 2024
Reseach Article

Identification of Normal Body Temperature for Covid-19 based on Thermal Sensors and Raspberry Pi 3

by Harson Kapoh, Olga Engelien Melo, Anthon Arie Kimbal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 39
Year of Publication: 2022
Authors: Harson Kapoh, Olga Engelien Melo, Anthon Arie Kimbal
10.5120/ijca2022922500

Harson Kapoh, Olga Engelien Melo, Anthon Arie Kimbal . Identification of Normal Body Temperature for Covid-19 based on Thermal Sensors and Raspberry Pi 3. International Journal of Computer Applications. 184, 39 ( Dec 2022), 34-38. DOI=10.5120/ijca2022922500

@article{ 10.5120/ijca2022922500,
author = { Harson Kapoh, Olga Engelien Melo, Anthon Arie Kimbal },
title = { Identification of Normal Body Temperature for Covid-19 based on Thermal Sensors and Raspberry Pi 3 },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2022 },
volume = { 184 },
number = { 39 },
month = { Dec },
year = { 2022 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number39/32573-2022922500/ },
doi = { 10.5120/ijca2022922500 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:23:36.072343+05:30
%A Harson Kapoh
%A Olga Engelien Melo
%A Anthon Arie Kimbal
%T Identification of Normal Body Temperature for Covid-19 based on Thermal Sensors and Raspberry Pi 3
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 39
%P 34-38
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the activities to support the lecture process offline or face-to-face both in class and in the laboratory is monitoring the body temperature of all students, staff and lecturers who will enter the Electrical Engineering Department Building using an infrared thermometer temperature detector that is held by the officer. This is done, in order to monitor the body temperature of the academic community who enter the Electrical Engineering area not to exceed a temperature of 36.40C. Body temperature monitoring activities are disrupted, when officers are not in place or there is a queue from lecturers, students or employees who will enter the building, the temperature monitoring process cannot run properly, quickly and hinders the student process from entering to attend lectures in a timely manner. The choice of a thermal camera is because with a thermal camera the detection of human body heat can be done from a certain distance and the advantage is that the thermal camera continues to work even if the surrounding light dims. B. This study shows that the test results before using a human body heat detector using the AMG 8833 thermal sensor were used, compared first with a thermogun to see its accuracy with 30 experiments at a distance of 5 cm, 10 cm and 15 cm with objects on the human forehead with results with 5 cm are 1.23% more accurate than 10 cm distance, 5 cm are 2.7% more accurate than 15 cm distance and 10 cm are 1.51% more accurate than 15 cm distance. From the experiments carried out the results of measurements using AMG 8833 are still within normal limits for humans not affected by Covid-19, namely above 36.40C

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Index Terms

Computer Science
Information Sciences

Keywords

Identification temperature sensor Raspberry Pi 3