Abstract
As the enterprise of the “Internet of Things” is rapidly gaining widespread acceptance, sensors are being deployed in an unrestrained manner around the world to make efficient use of this new technological evolution. A recent survey has shown that sensor deployments over the past decade have increased significantly and has predicted an upsurge in the future growth rate. In health-care services, for instance, sensors are used as a key technology to enable Internet of Things oriented health-care monitoring systems. In this paper, we have proposed a two-stage fundamental approach to facilitate the implementation of such a system. In the first stage, sensors promptly gather together the particle measurements of an android application. Then, in the second stage, the collected data are sent over a Femto-LTE network following a new scheduling technique. The proposed scheduling strategy is used to send the data according to the application’s priority. The efficiency of the proposed technique is demonstrated by comparing it with that of well-known algorithms, namely, proportional fairness and exponential proportional fairness.
Highlights
In today’s world of high demanding and fast evolving lifestyles, elder citizens are facing many challenges especially related to health issues
The EXP/Proportional Fairness (PF) algorithm shows a performance close to that of the proposed approach and obviously performs better than the PF algorithm for Class A applications. The reason behind this is the fact that the Exponential Proportional Fairness (EXP/PF) algorithm prioritizes users by exploiting the advantages of the exponential function to guarantee the delay boundaries of real time applications as well as to maximize the system throughput
If the doctor requests a patient’s glucose level on the spot, it will not be able to meet the change in demands because the EXP/PF approach only works best with a static monitor
Summary
In today’s world of high demanding and fast evolving lifestyles, elder citizens are facing many challenges especially related to health issues. The best approach that suits the narrated scenario is to propose a system that is capable of remote monitoring the vital signs of patients around the clock, such as heart rate, body temperature, glucose level, blood pressure, etc., and that is capable of communicating with the cloud and automatically placing requests for assistance whenever necessary [2,3,4] Such a system is referred to as a “mobile health monitoring system” and constitutes largely of several wearable sensors [5]. The first one is the android application that collects data from bio-sensors, and the second one is the mobile station that sends these data over LTE-Femto Cell networks to health-care centers for further analysis We assume that bio-data, such as physical or physiological health parameters, are gathered from the overall network of sensors attached to the patient These sensors include a heart rate monitoring sensor, temperature sensor, blood pressure sensor, glucose sensor, and ECG sensor (Fig 1). It measures the body temperature, blood pressure, and heart rate
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