Remote Monitoring Solution with Predictive Analysis for Health Care Devices

Predictive analytics in machine learning can be used in conjunction with data mining to solve real-world use cases. These techniques are proven to be highly effective and with ensemble techniques, the accuracy of machine learning models can be further improved with minimal efforts. These techniques can be used to monitor health care devices remotely. Machine learning algorithms enable us to analyze different physical parameters which are collected from health care devices. These techniques enable us to predict future health status of medical devices and with accurate results, malfunctioning of health care devices can be avoided by monitoring them remotely. The health care devices connected to IoT, allows us to collect and store huge amount of data (Physical Parameter) in the cloud, which can be fetched later using polyglot persistence (NoSQL and SQL) techniques to retrieve the data effectively and by using machine learning predictive techniques the collected data can be analyzed and the future health status of health care devices can be predicted.