Development of an Automatic Contactless Thermometer Alert System Based on GPS and Population Density

Authors

  • N. K. Al-Shammari Mechanical Engineering Department, University of Hail, Saudi Arabia
  • H. B. Almansour Department of Health Management, College of Public Health and Health Informatics, University of Hail, Saudi Arabia
  • M. B. Syed School of Computing and Information Technology, REVA University, India

Abstract

In today's out-breaking Covid-19 circumstance, treatments are preferred to be contactless. Social distancing has become a mandate in order to prevent disease spreading. In such a scenario, checking the body temperature is preferable to be made contactless because it helps the doctors and social workers to stay away from the symptomatic patients. Infrared (IR) contactless thermometers are employed in measuring the temperature while preventing direct contact with the body. Improved functionalities in the contactless thermometer can provide accurate precision in measurements and calculations. Technological advancement in pharmacy has cohesively improved over time. Coupling Machine Learning (CML) will revolutionize the process of testing. The demand for automated temperature test equipment is likely to grow at a significant pace, with the continuous advancements in technology and the adoption of ATE (Automated Test Equipment). The Global Positioning System (GPS) easy tracking and navigation can be used for easy tracking. Population density can be used to calculate the amount of population in a particular area. The proposed automatic contact-less thermometer system has the potential to replace the traditional temperature measuring techniques and safeguard from human-to-human transmission diseases.

Keywords:

Covid-19, IR technology, ATE, GPS, population density

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How to Cite

[1]
Al-Shammari, N.K., Almansour, H.B. and Syed, M.B. 2021. Development of an Automatic Contactless Thermometer Alert System Based on GPS and Population Density. Engineering, Technology & Applied Science Research. 11, 2 (Apr. 2021), 7006–7010. DOI:https://doi.org/10.48084/etasr.4103.

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