An Efficient Sensory Based Cost-effective IoT Model for Prior Prediction of Covid-19
2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation, ICAECA 2021
; 2021.
Article
in English
| Scopus | ID: covidwho-1714025
ABSTRACT
The battle over the worst spread of novel covid 19 pandemic has infested over billions of people all over the globe every day. So that the early self-prediction is more important to combat Covid-19. The Internet of Things (IoT) is an efficient and helpful technology in the medical care for self-prediction of COVID-19 disease. In order to provide efficient system, considering the cost effectiveness is also be important. So, in this paper, different IoT based sensors are being used to sense the sensory based data (Temperature, Blood Pressure, Pulse Rate and Oxygen) to reduce the cost. The proposed IoT model is designed to identify the symptoms and generate the efficient report by analyzing the previous readings which also reduces the consulting cost and number of doctor visits. Thus, AN EFFICIENT SENSORY BASED COST-EFFECTIVE IOT MODEL FOR PRIOR PREDICTION OF COVID-19 is proposed. © 2021 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
/
Prognostic study
Language:
English
Journal:
2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation, ICAECA 2021
Year:
2021
Document Type:
Article
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