基于Spark的智能服装高效多级健康云系统

Minh-Khoi Le, Hsien-Tsung Chang, Yi-Min Chang, Yi-Hao Hu, Huan-Ting Chen
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引用次数: 4

摘要

如今,我们可以发现一部分人进入了次优健康状态。然而,他们中的大多数人没有足够的时间定期进行健康检查。智能服装作为一种可穿戴且方便的生理信号监测设备,解决了这一问题。在本研究中,我们开发了一个高效的多层次健康云系统来分析从CGU智能服装收集的数据。云系统将原始数据分为三类:正常数据、连续数据和多媒体数据。然后,云系统使用Apache Spark进行数据分析和疾病预测。然后,系统会将最终结果传输到智能手机上。实验结果表明,该云系统实现了非常高速的性能。此外,该系统具有友好的健康信息展示和有效的授权流程,方便医患之间的联系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Efficient Multilevel Healthy Cloud System Using Spark for Smart Clothes
Nowadays, we can find part of people into the suboptimal health status. However, most of them have not enough time for health examinations regularly. Smart clothes which are wearable and convenient devices for monitoring physiological signals solve this problem. In this study, we develop an efficient multilevel healthy cloud system to analyzing data collected from CGU smart clothes. The cloud system classifies the raw data into three types: normal data, continuous data, and multimedia data. After that, the cloud system analyzes data and predict diseases using Apache Spark. And then, the system will transfer final results to smartphones. The experimental result shows that the cloud system achieves very high-speed performance. Moreover, the system has friendly health information presentation and effective authorization process to help doctors and patients contact each other.
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