Abstract
COVID-19 is a pandemic situation where isolation and social distancing are enforced to surge the pandemic. Pandemic Patient Health Management Platform is presently needed to retrieve health data without visiting healthcare centres. The Pandemic Patient Health Management Platform (PPHMP) uses Internet of things (IoT) and cloud computing technology and it is a remote patient health management platform. APPHMP model is proposed, which can help patients and elderly people to receive information about their health from their premises especially in consideration of COVID-19. In the present work, an algorithm is proposed to determine the patient’s current health status and send necessary information to the healthcare centre for subsequent decisions. The proposed work is implemented by utilizing a naïve Bayes machine learning algorithm for decision making, and the obtained accuracy is about 83%.
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Acknowledgements
We are thankfull to Dr. Naveen maurya, Mr Govind raj, Mr Puneeth, Mr Bhairav R for the Support. We also acknowledge to HPC lab UOM and University of Mysore.
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Hanumanthappa, J., Muaad, A.Y., Bibal Benifa, J.V., Chola, C., Hiremath, V., Pramodha, M. (2022). IoT-Based Smart Diagnosis System for HealthCare. In: Karrupusamy, P., Balas, V.E., Shi, Y. (eds) Sustainable Communication Networks and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 93. Springer, Singapore. https://doi.org/10.1007/978-981-16-6605-6_34
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