紧急医疗保健中基于云的数字孪生存储

Erdan Wang, Pouria Tayebi, Yeong-Tae Song
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引用次数: 0

摘要

在本文中,我们探讨了利用数字孪生(DT)技术进行实时数据存储和处理在紧急医疗保健中的潜力。我们以物联网(IoT)和云计算技术为重点,研究各种使能技术,包括云平台、数据传输格式和存储文件格式,以开发一种可行的应急医疗DT存储解决方案。通过我们的分析,我们发现亚马逊AWS是最合适的云平台,因为它有成熟的实时数据处理和分析工具。此外,我们确定MQTT协议适合实时医疗数据传输,而FHIR是最适合紧急医疗状况的医疗文件存储格式。我们提出了一种基于云的DT存储解决方案,其中实时医疗数据传输到AWS IoT Core,由Kinesis data Analytics处理,并安全存储在AWS HealthLake中。尽管提出的解决方案是可行的,但是要想成功地实际实现,必须解决诸如访问控制不足、缺乏加密和供应商一致性等挑战。未来的工作可能涉及整合Hyperledger Fabric技术和HTTPS协议以增强安全性,而DT技术的成熟有望解决供应商一致性问题。通过解决这些挑战,我们提出的DT存储解决方案有可能改善紧急医疗保健环境中的数据可访问性和决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud-based Digital Twins Storage in Emergency Healthcare
In this paper, we explore the potential of utilizing Digital Twin (DT) technology for real-time data storage and processing in emergency healthcare. Focusing on Internet of Things (IoT) and cloud computing technologies, we investigate various enabling technologies, including cloud platforms, data transmission formats, and storage file formats, to develop a feasible DT storage solution for emergency healthcare. Through our analysis, we find Amazon AWS to be the most suitable cloud platform due to its sophisticated real-time data processing and analytical tools. Additionally, we determine that the MQTT protocol is suitable for real-time medical data transmission, and FHIR is the most appropriate medical file storage format for emergency healthcare situations.We propose a cloud-based DT storage solution, in which real-time medical data is transmitted to AWS IoT Core, processed by Kinesis Data Analytics, and stored securely in AWS HealthLake. Despite the feasibility of the proposed solution, challenges such as insufficient access control, lack of encryption, and vendor conformity must be addressed for successful practical implementation. Future work may involve incorporating Hyperledger Fabric technology and HTTPS protocol to enhance security, while the maturation of DT technology is expected to resolve vendor conformity issues. By addressing these challenges, our proposed DT storage solution has the potential to improve data accessibility and decision-making in emergency healthcare settings.
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