Humanoid Robot Application as COVID-19 Symptoms Checker Using Computer Vision and Multiple Sensors

Authors

  • Muhammad Yeza Baihaqi President University
  • Vincent Vincent President University
  • Joni Welman Simatupang President University

DOI:

https://doi.org/10.26418/elkha.v13i2.47213

Keywords:

ESP32-CAM, Human Body Temperature, nCoV, Oxygen Saturation Level, 7-DoF upper-body of Humanoid Robot.

Abstract

Novel Corona Virus (nCoV) infects human"™s respiratory system. It spreads easily when an infected person makes a close contact with other people. To prevent its massive spread, it is necessary to ensure anyone coming to a certain place is not being infected. The symptoms include high body temperature (≥37.5 °C) and low oxygen saturation level (≤95%). This day, most places only check the human body temperature. Thus, the authors are interested to make an attempt to design a system that is able to measure both human body temperature and oxygen saturation level. This work also applies the 7-DoF Upper-Body of Humanoid Robot to prevent virus spread from and to the employee. The system will detect the coming of visitors by using face detection. It requires 7.24 seconds to detect the visitor without a mask, and 1.26 second when the visitor wears a mask. The body temperature measurement was done using GY-906 temperature sensor with an error of 0.51%. For the oxygen saturation level measurement, MAX30100 pulse oximeter module was applied and showed an error of 0.78%. In addition, the upper-body of humanoid robot will perform some gestures to instruct the visitors in every process of the system. The implemented 7-DoF upper-body of humanoid robot has 93.33% gesture comprehension rate. In conclusion, the overall system has been tested and showed success rate up to 75%.

Author Biographies

Muhammad Yeza Baihaqi, President University

Master Student, Automation and Control, NTUST

Joni Welman Simatupang, President University

Associate Professor of Electrical Engineering, President University

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Published

2021-10-22

Issue

Section

Vol. 13 No. 2 October 2021