Real-Time Monitoring of Patient Activity Using IoT and Machine Learning in Healthcare
Keywords:
Internet of Things, Machine Learning, Cloud Computing, ICU, Real Time, Monitoring, Health parameters, CardiovascularAbstract
This study of Cardiovascular disease at different hospitals has been used to predict the early detection of heart disease using automated intelligent practice. Moreover, research has extended the capability of bedside monitors and store the capture body parameters on cloud storage. It took into consideration age, gender, habit of tobacco, cholesterol, blood pressure, BMI, etc., which hit the chances of the possibility of heart disease. The study helps the various stakeholders in the health care sector to understand the key results The proposed research model is divided into three different phases. First phase is data capturing phases where the caretaker person creates the profile and gathers the patient information. In the secondary phase all the healthcare data uploaded on the cloud computing using Internet of Things(IoT) for further process. In the final stage the model is trained with the help of the existing healthcare records Using Machine Learning.
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