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智慧城市中的数字健康:重新思考融合边缘、雾计算和云计算的远程健康监测架构。

Digital health in smart cities: Rethinking the remote health monitoring architecture on combining edge, fog, and cloud.

作者信息

Rodrigues Vinicius Facco, da Rosa Righi Rodrigo, da Costa Cristiano André, Zeiser Felipe André, Eskofier Bjoern, Maier Andreas, Kim Daeyoung

机构信息

Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo, Brazil.

Friedrich-Alexander-Universität Erlangen-Nürenberg (FAU), Erlangen, Germany.

出版信息

Health Technol (Berl). 2023;13(3):449-472. doi: 10.1007/s12553-023-00753-3. Epub 2023 Apr 27.

Abstract

PURPOSE

Smart cities that support the execution of health services are more and more in evidence today. Here, it is mainstream to use IoT-based vital sign data to serve a multi-tier architecture. The state-of-the-art proposes the combination of edge, fog, and cloud computing to support critical health applications efficiently. However, to the best of our knowledge, initiatives typically present the architectures, not bringing adaptation and execution optimizations to address health demands fully.

METHODS

This article introduces the VitalSense model, which provides a hierarchical multi-tier remote health monitoring architecture in smart cities by combining edge, fog, and cloud computing.

RESULTS

Although using a traditional composition, our contributions appear in handling each infrastructure level. We explore adaptive data compression and homomorphic encryption at the edge, a multi-tier notification mechanism, low latency health traceability with data sharding, a Serverless execution engine to support multiple fog layers, and an offloading mechanism based on service and person computing priorities.

CONCLUSIONS

This article details the rationale behind these topics, describing VitalSense use cases for disruptive healthcare services and preliminary insights regarding prototype evaluation.

摘要

目的

如今,支持医疗服务执行的智慧城市越来越多。在此,使用基于物联网的生命体征数据来服务多层架构已成为主流。当前的技术水平提出结合边缘计算、雾计算和云计算以高效支持关键医疗应用。然而,据我们所知,相关举措通常只是展示架构,并未带来充分满足医疗需求的适配和执行优化。

方法

本文介绍了VitalSense模型,该模型通过结合边缘计算、雾计算和云计算,在智慧城市中提供了一种分层的多层远程健康监测架构。

结果

尽管采用了传统的组合方式,但我们的贡献体现在对每个基础设施层面的处理上。我们在边缘探索自适应数据压缩和同态加密、多层通知机制、基于数据分片的低延迟健康可追溯性、支持多个雾层的无服务器执行引擎以及基于服务和人员计算优先级的卸载机制。

结论

本文详细阐述了这些主题背后的基本原理,描述了VitalSense在颠覆性医疗服务中的用例以及关于原型评估的初步见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486b/10139834/0585c5d5085a/12553_2023_753_Fig1_HTML.jpg

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