A REAL TIME IOT BASED PATIENT HEALTH MONITORING SYSTEM USING MACHINE LEARNING ALGORITHMS
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 4, Pages 2912-2925
AbstractIn the current's world the important factor is the nation's security. One of the essential and crucial parts is showed by the army soldiers. There are many considerations concerning the security of the soldiers. So Soldiers security purpose, more devices are set up on them to observe Soldiers health condition as well as their actual time position. This report provides ability to track the position and observes health condition of the soldiers in present time who become lost and get damaged in the battleground. It serves to reduce the time, search and recovery operation efforts of army control system. Bio-sensor systems provide various kinds of small-cost physiological sensors, communication factors and facilities and thus can provide unobtrusive, cheap wearable solutions for health monitoring. For patient health monitoring systems we use the wireless body area networks (WBAN) is a such system that implements the regular control over or inside the human body for the long time and it supports the transmission real time traffic such as the data, voice, video to look at the status of the basic organs functions. For the soldiers health monitoring k-means clustering algorithms and hierarchical clustering algorithms are used. K-means clustering method and hierarchical clustering methods is the one of the methods of the machine learning. The gathered data will be uploaded on the cloud for the analysis of the data and the estimates. By using the K-means clustering method and the hierarchical clustering algorithm.
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