Development and Implementation of an Internet of Things (IOT) Based Remote Patient Monitoring System

Y. Mohammed, A. S. Mohammed, H. Abdulkarim, Clement Danladi, Aduh Victor, Romanus Edoka
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引用次数: 3

Abstract

Web-based solutions that employs the use of Internet of Things (IoT), is continuously creating new application areas, including healthcare. This shows that, iHealth, real-time monitoring as well as remote patients monitoring, are expected to revolutionize the healthcare sector. IoT is nothing but communication between devices that contain embedded technology with existing internet infrastructure. This research work employs a smart data gathering method using a fuzzy logic assisted approach. The fuzzy scheme employed, helps make the system smart by helping the device make decisions on when and what data is to be sent depending on the inference made on various inputs from the physiological sensors. Performance analysis was carried out on the energy consumption pattern of the nodes which indicate that throughout the monitoring period of Ten (10) hours each day, for three days. The average energy consumed by the device when fuzzy assisted logic is used is 90.78 milli Watt (mW), while the average energy consumed when the conventional method is used is 128.5 mW. From the results, it was observed that power consumption is substantially reduced by about 37.72 mW (29.35%), when using the fuzzy assisted method as compared to when using the normal/conventional method.. It was equally observed that while using the fuzzy assisted logic, energy consumption only increased whenever there is an anomaly in the sensor reading.
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基于物联网(IOT)的远程患者监护系统的开发与实现
利用物联网(IoT)的基于web的解决方案正在不断创造新的应用领域,包括医疗保健领域。这表明,iHealth,实时监控和远程患者监控,有望彻底改变医疗保健行业。物联网只不过是包含嵌入式技术的设备与现有互联网基础设施之间的通信。本研究工作采用模糊逻辑辅助的智能数据收集方法。所采用的模糊方案通过帮助设备根据对生理传感器的各种输入所做的推断来决定何时以及发送哪些数据,从而使系统变得智能。对节点的能耗模式进行性能分析,在整个监测期内,每天10小时,连续3天。采用模糊辅助逻辑时,器件平均能耗为90.78毫瓦(mW),而采用常规方法时,器件平均能耗为128.5毫瓦。从结果中可以观察到,与使用正常/传统方法相比,使用模糊辅助方法时,功耗大大降低了约37.72 mW(29.35%)。同样可以观察到,当使用模糊辅助逻辑时,只有当传感器读数出现异常时,能量消耗才会增加。
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