Author: Mourse, A. A. A.; El-Bahnasawy, N. A.; Elsisi, A.; El-Sayed, A.
Title: Development of fog computing based patient behavior monitoring system Cord-id: c2qcknal Document date: 2021_1_1
ID: c2qcknal
Snippet: In response to the Covid19 pandemic, the Smart Wi-Fi service is offering users access to fast and free Wi-Fi in selected public areas nationwide. A healthcare application is improved to reduce the effort of people and to ensure the status checking of patients. This is performed all the time and in real-time by detecting and monitoring the patient's heartbeat by the doctor and the patient himself. The healthcare web application consists of the client-side, which provides the login, registration,
Document: In response to the Covid19 pandemic, the Smart Wi-Fi service is offering users access to fast and free Wi-Fi in selected public areas nationwide. A healthcare application is improved to reduce the effort of people and to ensure the status checking of patients. This is performed all the time and in real-time by detecting and monitoring the patient's heartbeat by the doctor and the patient himself. The healthcare web application consists of the client-side, which provides the login, registration, and all information required. The client-side sends information using WIFI technology to the fog server-side, which works on managing and saving these data. In fog computing multi of heterogeneous devices are connected at the end of the network, these devices are costly and energy inefficient. We proposed PBM techniques by using BSN, to detect the Covid19 patient's behaviors. And use Time Slotted Channel Hopping (TSCH) in IEEE802.15.4e.Our proposed Algorithm improve Throughput, reduce cost, Bandwidth efficiency and minimizing the communication time needed by the sensor by using WIFI- 6 technology. The experimental results are evaluated in terms of Throughput, Packet delivery ratio. © 2021 IEEE.
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