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首页> 外文期刊>Journal of Biosensors & Bioelectronics >Real Medical Data Processing and Prediction of Early Disease Using Sensors, Internet of Things (IoT) and R Programming Techniques
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Real Medical Data Processing and Prediction of Early Disease Using Sensors, Internet of Things (IoT) and R Programming Techniques

机译:使用传感器,物联网(IoT)和R编程技术进行真正的医学数据处理和早期疾病的预测

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With the recognition of wearable devices, along with the development of clouds and cloudlet technology, there has been increasing got to give higher treatment. The process chain of medical knowledge chiefly includes knowledge assortment, data storage and knowledge sharing, etc. ancient tending system often needs the delivery of medical knowledge to the cloud, which involves users sensitive info and causes communication energy consumption much, medical knowledge sharing could be a vital and difficult issue therefore during this paper, we tend to build up a completely unique healthcare system by utilizing the exibility of cloudlet. The functions of cloudlet embody privacy protection, knowledge sharing and intrusion detection within the stage of information assortment, we RST utilize range Theory analysis Unit (NTRU) methodology to encrypt users body knowledge collected by wearable devices. Firstly, those data are going to be transmitted to close cloudlet in AN energy efficient fashion. Secondly, we tend to gift a replacement trust model to assist users to select trustable partners UN agency need to share hold on knowledge in the cloudlet. The trust model conjointly helps similar patients to communicate with one another concerning their diseases. Thirdly, we divide users medical knowledge hold on in remote cloud of hospital into 3 elements, and provides them correct protection. Finally, in order to guard the tending system from malicious attacks, we develop a completely unique cooperative intrusion detection system (IDS) method supported cloudlet mesh, which may effectively forestall the remote tending massive knowledge cloud from attacks. Our experiments demonstrate the effectiveness of the projected theme. Index terms privacy protection, knowledge sharing, cooperative intrusion detection system (IDS), healthcare.
机译:随着可穿戴设备的认可,以及随着云技术和Cloudlet技术的发展,越来越多的人给予了更高的待遇。医学知识的过程链主要包括知识分类,数据存储和知识共享等。古代的抚育系统经常需要将医学知识传递到云中,这会涉及到用户敏感信息,导致通信能耗很大,医学知识共享可能是因此,在本文中,这是一个至关重要的难题,我们倾向于通过利用cloudlet的可扩展性来构建一个完全独特的医疗保健系统。 Cloudlet的功能体现了在信息分类阶段的隐私保护,知识共享和入侵检测,我们RST利用范围理论分析单元(NTRU)方法对可穿戴设备收集的用户身体知识进行加密。首先,这些数据将以一种节能的方式传输到封闭的小云中。其次,我们倾向于赠予替代信任模型,以帮助用户选择联合国机构需要共享在Cloudlet中的知识的可信赖的合作伙伴。信任模型共同帮助相似的患者就他们的疾病进行交流。第三,将用户在医院远程云中所掌握的医学知识分为三个要素,并为他们提供正确的保护。最后,为了保护托管系统免受恶意攻击,我们开发了一种完全独特的支持入侵检测系统(IDS)的支持Cloudlet网格的方法,可以有效地防止远程托管大量知识云受到攻击。我们的实验证明了预计主题的有效性。索引条款包括隐私保护,知识共享,协作入侵检测系统(IDS),医疗保健。

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