Redefining New IoT Architecture To Support Predictive Medicine By Real-time Data Collection

A Summary of The Journal A New Internet Of Things Architecture For Real‑Time Prediction Of Various Diseases Using Machine Learning on Big Data Environment By Abderrahmane Ed‑Daoudy And Khalil Maalm
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A Summary of The Journal A New Internet Of Things Architecture For Real‑Time Prediction Of Various Diseases Using Machine Learning on Big Data Environment By Abderrahmane Ed‑Daoudy And Khalil Maalmi.
The purpose of this research is to redefine the new IoT architecture that will support predictive medicine by real-time data collection on remote health monitoring devices. These devices are connected to the Internet via low bandwidth connections (cellular networks). In this context, an IoT platform is needed to aggregate those data from those devices, store them in a database, process them using machine learning algorithms, and deliver those results to health care providers.
The authors have migrated a prototype featuring a new IoT architecture from a local network to the Internet. The architecture is organized as an intelligent model composed of three layers, each layer being drained with a specific role. The paper highlights various advantages of using machine learning algorithms, such as auto-calibration and auto-classification and anomaly detection and prediction capabilities. In addition to that, the authors have tested their prototype in real conditions by collecting data from diabetes patients by ...