Fog Cloud Model Based Healthcare IoT
S. Siamala Devi1, K. Vishnunandh2, R. SriVignesh3
1Dr. S. Siamala Devi is currently working as Associate Professor/CSE at Sri Krishna College of Technology, Coimbatore, Tamilnadu, India.
2K Vishnunandh currently pursuing bachelors degree program in computer science and engineering at Sri Krishna College of Technology, Coimbatore, Tamilnadu, India.
3R SriVignesh , currently pursuing bachelors degree program in computer science and engineering at Sri Krishna College of Technology, Coimbatore, Tamilnadu, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 4114-4117 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9084038620/2020©BEIESP | DOI: 10.35940/ijrte.F9084.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Fog Computing (FC) is an advancing figuring innovation that works during a conveyed domain. One of the hindrances with cloud applications such as the health monitoring system is latency. Fog Computing is an incredible way to diminish the processing time or latency. Mist processing is an answer for the latency since it gives calculation, stockpiling, and systems administration asset for IoT, closer to things and clients. One among the promising preferences of mist is lessening administration delay for client applications, while cloud furnishes broad calculation and capacity limit with a superior inactivity. In this manner it’s important to realize the transaction between mist processing and cloud, and to gauge the impact of Fog Computing on the IoT administration deferral and QoS. FC means to bring distributed computing highlights on the precarious edge of edge gadgets. The methodology is anticipated to fulfill the base inertness necessity for social insurance Internet-of-Things (IoT) gadgets. Social insurance IoT gadgets produce different volumes of human services information. This gigsantic volume of information prompts high information traffic that causes organize clog and high idleness. an ascent in full circle time delay because of huge information transmission and tremendous bounce tallies among IoTs and cloud servers render social insurance information negligible and deficient for end-clients. The proposed model, which is a fog cloud information model that propounds healthcare as a cloud service, effectively manipulates the data that comes from the user requests.
Keywords: AI, Cloud Healthcare, Neural System.
Scope of the Article: Healthcare Informatics.