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- W4377699812 abstract "The healthcare industry has been getting advanced scientifically and technologically through wireless-sensing devices. Automation of the healthcare system with the Internet of things has been implemented & attains accurate results. Due to the panic situation of COVID-19, this automation of health monitoring systems plays an important role in the medical sector. In this research work, an advanced IoT-based, fully automated health monitoring system has been implemented for elderly & COVID-19 patients. The proposed design is verified on the python 3.6.0 software tool. The Lack of early treatment may cause patients to get unexpected risk failure, including death. This research work monitors elderly & older COVID-19 patients monitorization remotely using IoT technologies, even in crucial conditions. Wearable IoT devices have saved healthcare workers time and effort, according to medical regulations. The following mechanism helps with early diagnosis, quarantine, and patient monitorization has been performed with 68% saving time. This investigation aims to keep physicians and researchers can be updated about elderly patients covid 19 health issues while protecting their safety and health. Temperature and pulse sensors are used to check primary patient information. If heart rate or body temperature exceeds a safe level, IOT warning devices can give an indication. The designed application has achieved a sensitivity of 98.53%, an accuracy of 98.63%, a throughput of 97.98%, and a monitoring rate of 98.21%. The employed application is very helpful to researchers and doctors for easy treatment & covid 19 prevention. The proposed IoT-based automated health monitoring application strives with present technology and better method." @default.
- W4377699812 created "2023-05-24" @default.
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- W4377699812 date "2023-04-07" @default.
- W4377699812 modified "2023-10-18" @default.
- W4377699812 title "Automation of Health Monitoring System for Elderly and COVID-19 Patients using IOT" @default.
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- W4377699812 doi "https://doi.org/10.1109/i2ct57861.2023.10126306" @default.
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