Cloud-Supported Cyber-Physical Localization Framework for Patients Monitoring
Cloud-Supported Cyber-Physical Localization Framework for Patients Monitoring
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DOI：
10.1109/jsyst.2015.2470644
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发表时间：
2017-03-01
影响因子：
4.4
通讯作者：
Hossain, M. Shamim
中科院分区：
文献类型：
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作者：
Hossain, M. Shamim
云支持的网络物理系统（CCPS）的潜力引起了学术界和工业界的极大兴趣。CCPS促进了物理世界中设备的无缝集成（例如，例如，在一个实施例中，传感器、摄像头、麦克风、扬声器和GPS设备）与网络空间的连接。这使得一系列新兴的应用或系统，如病人或健康监测，需要跟踪病人的位置。这些系统集成了大量的物理设备，例如具有定位技术的传感器（例如，例如，在一个实施例中，GPS和无线局域网）来生成、感测、分析和共享大量医疗和用户位置数据，以进行复杂的处理。然而，这些系统在患者定位、无处不在的访问、大规模计算和通信方面存在许多挑战。因此，需要一种基础设施或系统，其可以在网络或云空间中的巨大实时数据处理和通信方面提供可扩展性和普遍性。为此，本文提出了一种云支持的网络物理定位系统，用于使用智能手机以可扩展、实时和高效的方式采集语音和脑电图信号的患者监测。所提出的方法使用高斯混合建模的本地化，并显示优于其他类似的方法在误差估计。
The potential of cloud-supported cyber-physical systems (CCPSs) has drawn a great deal of interest from academia and industry. CCPSs facilitate the seamless integration of devices in the physical world (e. g., sensors, cameras, microphones, speakers, and GPS devices) with cyberspace. This enables a range of emerging applications or systems such as patient or health monitoring, which require patient locations to be tracked. These systems integrate a large number of physical devices such as sensors with localization technologies (e. g., GPS and wireless local area networks) to generate, sense, analyze, and share huge quantities of medical and user-location data for complex processing. However, there are a number of challenges regarding these systems in terms of the positioning of patients, ubiquitous access, large-scale computation, and communication. Hence, there is a need for an infrastructure or system that can provide scalability and ubiquity in terms of huge real-time data processing and communications in the cyber or cloud space. To this end, this paper proposes a cloud-supported cyber-physical localization system for patient monitoring using smartphones to acquire voice and electroencephalogram signals in a scalable, real-time, and efficient manner. The proposed approach uses Gaussian mixture modeling for localization and is shown to outperform other similar methods in terms of error estimation.