An IOT Based Decision Making Model For Analyzing Patient�s Record
Shweta Agrawal, Pankaj Dubey, Anshul Khurana
Health Rate, ECG, BP, WSN, IOT, MATLAB
Our research focuses on real-time health control of different numbers of patients. In clinics / hospitals, patient data must be constantly monitored, such as heart rate (HR), blood pressure (BP) and electrocardiogram (ECG). The proposed system monitors the heart rate, blood pressure and ECG data of the patient's body. Cloud computing with the combination of IOT technology is a new way to manage and process sensors data online. More generally, the problem is specifically to address the challenges of the wireless sensor network and the processing of associated data. Much emphasis has been placed on the hardware and not on the data processing part. In this Paper we try to overcome the inconveniences we faced in the past. The proposal contains a cloud-based forecasting mechanism for data assimilation, filtering and prediction of health for a large number of people. The data is generated and processed using the MATLAB simulation and communicated with the cloud-based server, which in turn combines the different pieces of information to provide accurate health predictions. To achieve this fusion of cloud computing and Iot is used when the data from the different sensors placed in each individual are communicated to the cloud-based server which in turn combines the different information to provide an accurate prediction of health status . The scheme is implemented with the help of MATLAB simulation to process medical care data, such as heart rate, ECG and BP. This allowed doctors and health professionals to connect remotely with patients and provide appropriate care.