| Autor: |
A S Sreehari, J P Dhivvya, Vinay R Sankar, Amith Venugopal, Vinay G Nandakumar |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
ICCCNT |
| DOI: |
10.1109/icccnt51525.2021.9580015 |
| Popis: |
The Covid-19 pandemic situation had affected communities globally challenging the livelihood and also increasing the case fatality rate. This research paper is focused on the design and development of an Internet of Things (IoT) prototype which can aid in early detection of Covid-19. The prototype designed along with the enabling technologies like Machine Learning(ML) and Edge computing can assist in better performance by producing fast and accurate results. For the purpose of data, the list of results of the antigen test from 216 patients was obtained from a sanctioned practitioner. 75% of the data set is used for training and 25% for testing to evaluate the performance of various machine learning algorithms in understanding how the features affects the better prediction of disease. The prototype created mainly takes the patient's blood Oxygen level, heart rate level and body temperature from the sensors. And this data is fed into the best classification algorithm tested earlier for the prediction of pandemic disease. The android application can be used to inform the patients and the health professionals for further measures to curb the rapid spreading of the pandemic disease. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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