智能生态系统和流行病时代的电子健康

István Péntek, A. Adamkó
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摘要

近十年来,许多技术创新越来越多地融入智慧城市架构。现代和匆忙的生活方式意味着大多数家庭至少有一个健身追踪器或可穿戴设备。通常,设备配备了一组生物传感器,从而产生有价值的时间序列,可用于跟踪选定的区域。生物感官时间序列的使用不限于私人目的;数据还可以用来改善我们日常生活中的服务。生物传感设备产生的数据主要渗透到智能家居解决方案中。然而,全面的智能家居解决方案也允许智能城市解决方案的改进。关键因素是构成智慧城市和智能家居架构的主题技术的不断变化,包括源自机密来源的数据的敏感性方面。供应商必须跟上这种持续的变化,并发布更新的解决方案,但像HIS(医院信息系统)或DSS(决策支持系统)这样的信息系统却没有以同样的速度跟上。这项研究将展示通过使用基于生物传感数据的数据收集和分析服务,可以使智能生态系统的服务更有价值的发展。根据目前的研究成果,智能生态系统可以在流行病或大流行期间更有效地采取行动。该研究论文的重点是如何收集和使用生物感官时间序列数据,如何将数据集成到智能生态系统中,以及如何将其集成到智能医疗解决方案中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
eHealth in the time of smart ecosystems and pandemics
In the recent decade, many technological innovations have increasingly been incorporated into smart city architectures. Our modern and rushing lifestyle implies at least one fitness tracker or wearable device in most households. Usually, devices are equipped with a set of biosensors, thus producing valuable time series that can be used to track selected areas. The use of bio-sensory time series is not limited to private purposes; data can also be used to improve services in our everyday life. The data generated by bio-sensory devices primarily infiltrate into smart home solutions. However, comprehensive smart home solutions also allow improvements for smart city solutions. The critical factor is the consecutive change in the subject technologies that form the smart city and smart home architectures, including the sensitivity aspects of data originating from confidential sources. Vendors must keep up with this continuous change and release newer and newer solutions, but information systems like HIS (Hospital Information System) or DSS (Decision Support Systems) are not following up at the same speed. This research will demonstrate developments that can make the services of smart ecosystems more valuable by using data collection and analyzing services based on bio-sensory data. Based on the presented research results, smart ecosystems can act considerably more effectively during an epidemic or a pandemic. The research paper focuses on how bio-sensory time series data can be collected and used, how the data can be integrated into smart ecosystems, and how it can be integrated into smart healthcare solutions.
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