Your browser doesn't support javascript.
Autonomous Temperature scan system using IoT to detect COVID-19 symptom
2021 International Conference on Forensics, Analytics, Big Data, Security, FABS 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1784482
ABSTRACT
The current situation of pandemic demands utmost care of health for every individual, rapid spread of SARS-CoV-2 needs regular temperature check-ups as one of the means of identifying the disease. The design of a low cost and efficient system to automate the human temperature sensing using IoT is presented in this paper. This system can be used in most of the places where temperature check ups are to be done and still using the manual check-up tools hence easing the way of checking the temperature. The system mainly consists of two subsystems. One subsystem that determines the temperature value (TS) and the other that triggers the temperature sensor (PS). The PS uses a proximity sensor that senses whether the person is near the temperature sensor and triggers the TS to sense the temperature of individual standing in front of it. The system can be mounted on any simple mirror that enables the individuals to align their head correctly with the temperature sensor and hence it can be used anywhere. To govern the behavior of the sensors we use a microcontroller (Node MCU). In this proposed method we are developing a cost-effective solution to detect the temperature of the individual without human resources installed in the place. The system can be used in various places such as Schools and colleges, public places, hospitals and many more. © 2021 IEEE.
Keywords

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2021 International Conference on Forensics, Analytics, Big Data, Security, FABS 2021 Year: 2021 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2021 International Conference on Forensics, Analytics, Big Data, Security, FABS 2021 Year: 2021 Document Type: Article