دانلود رایگان مقاله انگلیسی درگاه سلامت الکترونیکی هوشمند در لبه مراقبت بهداشتی اینترنت اشیا - نشریه الزویر

عنوان فارسی
بهره برداری از درگاه های سلامت الکترونیکی هوشمند در لبه مراقبت های بهداشتی اینترنت اشیا: رویکرد محاسبات مه
عنوان انگلیسی
Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
49
سال انتشار
2017
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E5800
رشته های مرتبط با این مقاله
مهندسی فناوری اطلاعات
گرایش های مرتبط با این مقاله
شبکه های کامپیوتری و اینترنت و شبکه های گسترده
مجله
سیستم های کامپیوتری نسل آینده - Future Generation Computer Systems
دانشگاه
Department of Computer Science - University of California Irvine - USA
کلمات کلیدی
اینترنت اشیا، مراقبت های بهداشتی، محاسبات لبه / مه، تحرک، بیمارستان هوشمند، مراقبت خانگی، دروازه هوشمند، شبکه سنسور
چکیده

Abstract


Current developments in ICTs such as in Internet-of-Things (IoT) and CyberPhysical Systems (CPS) allow us to develop healthcare solutions with more intelligent and prediction capabilities both for daily life (home/office) and in-hospitals. In most of IoT-based healthcare systems, especially at smart homes or hospitals, a bridging point (i.e., gateway) is needed between sensor infrastructure network and the Internet. The gateway at the edge of the network often just performs basic functions such as translating between the protocols used in the Internet and sensor networks. These gateways have beneficial knowledge and constructive control over both the sensor network and the data to be transmitted through the Internet. In this paper, we exploit the strategic position of such gateways at the edge of the network to offer several higher-level services such as local storage, real-time local data processing, embedded data mining, etc., presenting thus a Smart e-Health Gateway. We then propose to exploit the concept of Fog Computing in Healthcare IoT systems by forming a Geo-distributed intermediary layer of intelligence between sensor nodes and Cloud. By taking responsibility for handling some burdens of the sensor network and a remote healthcare center, our Fog-assisted system architecture can cope with many challenges in ubiquitous healthcare systems such as mobility, energy efficiency, scalability, and reliability issues. A successful implementation of Smart e-Health Gateways can enable massive deployment of ubiquitous health monitoring systems especially in clinical environments. We also present a prototype of a Smart e-Health Gateway called UT-GATE where some of the discussed higher-level features have been implemented. We also implement an IoT-based Early Warning Score (EWS) health monitoring to practically show the efficiency and relevance of our system on addressing a medical case study. Our proofof-concept design demonstrates an IoT-based health monitoring system with enhanced overall system intelligence, energy efficiency, mobility, performance, interoperability, security, and reliability.

نتیجه گیری

6. Conclusions


In this paper, the concept of fog computing and Smart e-Health Gateways in the context of Internet-of-Things based healthcare systems was presented. Smart gateways at the close proximity of sensor nodes in smart home or hospital premises can exploit their unique strategic position to tackle many challenges in IoT-based health systems such as mobility, energy efficiency, scalability, interoperability, and reliability issues. We investigated in detail a range of high level services which can be offered by smart gateways to sensors and end-users in a Geo-distributed fashion at the edge of the network (e.g., local processing, storage, notification, standardization, firewall, web services, compression, etc.). We presented a proof of concept implementation of an IoT-based remote health monitoring system which includes our demomonstration of a Smart e-Health Gateway called UT-GATE. By exploiting a number of UT-GATEs, we formed an intermediary processing layer to demonstrate the fog computing concept for IoT-based healthcare systems. Our fog-assisted system was applied to a medical case study called Early Warning Scores, targeted to monitoring patients with acute illnesses. Our full system demonstration includes all the data flow processes from data acquisition at sensor nodes to the cloud and end-users.


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