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Erschienen in:
2021 | OriginalPaper | Buchkapitel
An IoT Framework for Healthcare Monitoring and Machine Learning for Life Expectancy Prediction
verfasst von : Anna Merine George, Anudeep Nagaraja, L. Ananth Naik, J. Naresh
Erschienen in: Evolutionary Computing and Mobile Sustainable Networks
Verlag: Springer Singapore
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Abstract
The beginning of the IoT era, shrinking of devices and the concept of intelligent independently learning machines have led to improvements in the quality of human life. The application of machine learning to IoT data has led to the automation of the creation of analytical models. One key area of research has seen such a revolution in the health care sector. This work aims to design a wireless healthcare system that detects patients vitals using sensors, transfers data to cloud, and predicts the approximate life expectancy using machine learning techniques. The notion of the Internet of Things (IoT) interconnects devices and offers effective health care service to the patients. Here the IoT architecture gathers the sensor data and transfers it to the cloud where processing and analyses take place. Based on the analyzed data, feedback inputs are sent back to the doctor and using the present pulse rate of the patient, nominal or approximate value of life expectancy is predicted using machine learning algorithms.