Abstract
The current enhancement and technical development in radio communication have enabled the efficient, low power, intelligent, and wearable microsensor. These microsensors are tactically embedded in or located outside the human body in a fixed position, which is called Body Area Network (WBAN). Therefore, the key objective of this research work is to discover the current gaps in providing an improved service of WBAN. The paper presents a Fog-based Healthcare Architecture for Wearable Body Area Network (FHA). The fog based architecture is used for real-time patient monitoring and analysis of patients' health condition irrespective of location and time by using an integrated low-power and low-cost WBAN and fog computing. In order to diagnose and monitor the patient's health conditions, mobile wearable sensors are used to gather the patients' real-time data via ZigBee links and forward to the Tele-Lab Server (TLS). Where a Laboratory Information Database (LIDB) module resides that buffer and analyzes the data. The LIDB sends the whole information of all registered patients to the cloud server as a backup. When TLS frequently sends data to the fog server, it creates congestion, the proposed technique avoids the congestion on fog server. When FHA predicts the critical result of any patient, it immediately forwards the data to the fog server for emergency alert and updates the cloud server. From the simulation results, it is observed that the proposed FHA efficiently handle the current issues and increasing throughput, decreasing packet loss, and delay.
| Original language | English |
|---|---|
| Pages (from-to) | 1409-1418 |
| Number of pages | 10 |
| Journal | Journal of Medical Imaging and Health Informatics |
| Volume | 7 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 6 Oct 2017 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Cloud Server
- Congestion
- Fog Server
- Telemedicine
- WBAN
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