TY  - JOUR
KW  - Internet of Things; fog computing; COVID-19; contactless; thermometer; facial image recording
A1  - Khullar, Vikas
A1  - Singh, Harjit Pal
A1  - Miró Vera, Yini Airet
A1  - Anand, Divya
A1  - Mohamed, Heba G.
A1  - Gupta, Deepali
A1  - Kumar, Navdeep
A1  - Goyal, Nitin
AV  - public
TI  - IoT Fog-Enabled Multi-Node Centralized Ecosystem for Real Time Screening and Monitoring of Health Information
ID  - uneatlantico5930
SN  - 2076-3417
UR  - http://doi.org/10.3390/app12199845
VL  - 12
IS  - 19
Y1  - 2022/09//
JF  - Applied Sciences
N2  - In today?s technological and stressful world, when everyone is busy in their daily routines and places blind faith in pharmaceutical advancements to protect their health, the sudden, horrifying effects of the COVID-19 pandemic have resulted in serious emotional and psychological impacts in the general population. In spite of advanced vaccination campaigns, fear and hesitation have become a part of human life since there are a number of people who do not want to take these immunity boosting vaccinations. Such people may become carriers of infectious viruses, leading to a more rapid rate of spread; therefore, this class of spreaders needs to be screened at the earliest opportunity. In this context, there is a need for advanced health monitoring systems which can assist the pharmaceutical industry to monitor and record the health status of people. To address this need and reduce the uncertainty of the situation, this study has designed and tested an Internet of Things (IoT) and Fog computing-based multi-node architecture was for real-time initial screening and recording of such subjects. The proposed system was able to record current body temperature and location coordinates along with the facial images. Further, the proposed system was able to transmit data to a cloud database using internet-connected services. An implementation and reviews-based working environment analysis was conducted to determine the efficacy of the proposed system. It was observed from the statistical analysis that the proposed IoT Fog-enabled ecosystem could be utilized efficiently.
ER  -