Detecting Severe Acute Respiratory Syndrome Using Smart Controllable Device

EasyChair Preprint 6243

Abstract

Knowledge of diagnostic tests for severe acute respiratory syndrome coronavirus 2 continues to advance, and a better understanding of the essence of the tests and interpretation of their findings is significant. Use of thermal infrared thermometers has been adopted in many places to test and identify infected persons. This method of detection is still lacking because it has some limitations; the reuse of this device might also cause the spread and perhaps the most essential thing is that the direct contact of the infected person and touching surfaces can result in the spread of the disease to the personnel of the screening process and to the populace, so also it spends too much time examining the temperature of each person. This study proposes the design of a system using a remotely controllable device, a programmable microcontroller, with less or no human interactions, with the device embedded in the following module a remote controller, sensors; optical camera sensor, thermal imaging processing, Bluetooth module, Microphone module and neural processing engine for monitoring the screening process. The device informs authorities of the need to acquire data in real-time for instant notification. The proposed system can be used as a device for markets, banks, worship centers, schools, healthcare, and many more public areas. Data obtained from this device can be used for the timing of vaccine campaigns, collected data from this device can be used for the allocation of medical materials as it generates real-time data. Lastly, this device will help in saving the lives of people and preventing the transmission of infection to other people.

Keyphrases: Arduino, Healthcare, diagnosis, intelligent device, sensor

@booklet{EasyChair:6243,
  author    = {Auwal Abdulsalam Jamilu and Lawal Abubakar},
  title     = {Detecting Severe Acute Respiratory Syndrome Using Smart Controllable Device},
  howpublished = {EasyChair Preprint 6243},
  year      = {EasyChair, 2021}}