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Smart health management technology and its applications

机译：智能健康管理技术及其应用

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As a simple observation of the world, it is composed of human beings, artifacts, and natural environment. As all of their healths are issues like expansion of healthy aging, low maintenance cost, and low energy consumption the notion of health management can be extended to be applicable to all the entities. In this article, health management technology is proposed as a general solution framework. Its important aspect is cyclic evolution based on causality which illustrates conditions of target systems. The causality can be used as problem-solving knowledge, which is composed of feature attributes extracted from sensory data and intermediate characteristics. The causality should evolve to be updated according to sophistication of sensing and control mechanisms. It also provides the important nature of transparency to humans and machines bidirectionally, which enhances human-machine collaboration. Besides the idea of health management technology, the applications of human health, manufacturing, and energy consumption are also introduced and discussed. All applications were realized by multiple sensory networking to require multivariate time series analysis. Some experiments were conducted to investigate the performance of the proposed method
机译：作为世界的简单观察，它由人类，文物和自然环境组成。由于其所有的健康都是扩大健康老化，低维护成本和低能耗的问题，因此可以扩展健康管理的概念，以适用于所有实体。在本文中，建议健康管理技术作为一般解决方案框架。其重要方面是基于因果关系的循环演变，其示出了目标系统的条件。因果关系可以用作解决问题的知识，其由从感官数据和中间特征提取的特征属性组成。应变应根据感测和控制机制的复杂性更新发生因果关系。它还为双向人类和机器提供了透明性的重要性质，从而提高了人机协作。除了健康管理技术的概念外，还引入和讨论了人体健康，制造和能耗的应用。所有应用程序都是通过多个感官网络实现，以便需要多变量时间序列分析。进行了一些实验以研究所提出的方法的性能

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