An Efficient Health Monitoring Method Using Fuzzy Inference System via Cloud

Background: In the midst of invention of sensor mechanization, massive statistics analytics had turn out to be an innovative prototype for quick information processing. Real-time analytics are required for getting access to the information and its processing. Large populace interest in fitness care led to the improvement of health monitoring systems. Methods: This study targets toward the improvement of a cloud based fitness health care system. Here Wireless Body Area Networks (WBAN) is used to blend the information to the server that includes STORM. The analytics are performed on the received physiological data. The non-critical information is ousted and the essential facts are saved and a notification is sent to the medical doctor. Findings: Thus, actual time analytics alongside with the cloud aid to improve the effectiveness of the proposed healthcare device by providing immediate clinical assistance to the users. A sensible selection making device for approximate reasoning that can manage the uncertainty of imperative threat for human fitness with the usage of fuzzy logic is carried out for discovering the health related problems. Novelty: In this study, an analysis to monitor the fitness hazard which is associated to Blood Pressure, Pulse rate and Kidney function is proposed. Levels of blood stress are analyzed with kidney characteristic by using Glomerular Filtration Rate (GFR). Under this concept, fuzzy logic system is proposed to signify the parameters which can also reason the danger for human fitness and evaluation via the usage of rule base component. Keywords: Wireless Body Area Networks; health care system; fuzzy logic