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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.
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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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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