Examination of Healthcare Diagonosis using Iot
Suguna M1, Prakash D2, Cynthia. J3

1Dr. Suguna M, Assistant Professor-II, CSE Department, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India.
2Dr. Prakash D, Associate professor, Department of EEE, Vel Tech Muti Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, Tamil Nadu, India.
3Dr. Cynthia. J, Professor, CSE Department, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India.

Manuscript received on October 14, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 5251-5254 | Volume-9 Issue-1, November 2019. | Retrieval Number: A9241119119/2019©BEIESP | DOI: 10.35940/ijitee.A9241.119119
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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: In recent years, online applications, spare many services for wellness of health related issues. The application is kept updated so that the health related data are kept modernized for future references. The application collects information from IoT devices and then compares them with other existing data from the prevailing records with the same disease. The collected data is then reserved in a database that hold all records about the healthcare issues. Cloud computing technology is used to guard and reserve the healthcare records. Cloud and IoT technology are connected to provide users with a completely developed healthcare record. The existing system makes use of Fuzzy Rule Based Neural Classifier that helps in assembling and categorizing the diabetes data under the guidance of severity analyzer. This work, present the comparison of some classification algorithms and obtain the accuracy, the dataset collected is a real-time dataset. The output and results are tabulated after the comparison of the algorithms.
Keywords:  Cloud, IoT, k-Start, Naive Bayes, Healthcare
Scope of the Article: Healthcare Informatics