Bio‐sensor data streaming and analytics is a key component of smart e‐healthcare. However, existing Internet of Things (IoT) ecosystem is unable to materialize the real‐time bio‐sensor data streaming and analytics within resource constrained environment. Moreover, traditional solutions fail to mitigate the edge‐cloud integration within a single sub‐system under IoT periphery which lead to investigate how edge‐cloud hybridization could be realized via similar set of tools. The objective of this article is to implement an integrated dual‐mode edge‐cloud system to serve streaming and analytics in real‐time. This study aims to achieve the aforesaid goal by presenting two different experiments that deals with the real‐time pulse sensor data streaming and analytics while utilizing light‐weight IoT‐supported JavaScript frameworks that includes Node.js, Johnny‐Five, Serialport.js, Plotly client, Flot.js, jQUERYy, Express Server, and Socket.io. Firstly, a standalone IoT‐edge system is developed and later, an integrated IoT‐based edge‐cloud system is developed to compare between the effectiveness of the systems. The implementation results show near correlation between the standalone edge and dual‐mode edge system. However, the dual‐mode edge‐cloud system provides more flexibility and capability to counter the bio‐sensor data streaming and analytics services within the constrained framework.

中文翻译：

---

基于物联网的医疗保健中的流服务供应：集成的边缘云视角

生物传感器数据流和分析是智能电子医疗保健的关键组成部分。但是，现有的物联网（IoT）生态系统无法在资源受限的环境中实现实时生物传感器数据流和分析。此外，传统解决方案无法减轻IoT外围环境下单个子系统内的边缘云集成，从而导致人们研究如何通过类似的工具集实现边缘云混合。本文的目的是实现一个集成的双模式边缘云系统，以实时服务于流和分析。这项研究旨在通过提出两个不同的实验来实现上述目标，这些实验处理实时脉冲传感器数据流和分析，同时利用轻量级物联网支持的JavaScript框架（包括Node.js，Johnny-5，Serialport.js，Plotly客户端，Flot.js，jQUERYy，Express Server和Socket.io。首先，开发了一个独立的物联网边缘系统，然后，开发了一个基于物联网的集成边缘云系统，以比较系统的有效性。实施结果表明，独立边缘与双模边缘系统之间的相关性很高。但是，双模边缘云系统提供了更大的灵活性和功能，可以在受限的框架内应对生物传感器数据流和分析服务。实施结果表明，独立边缘与双模边缘系统之间的相关性很高。但是，双模边缘云系统提供了更大的灵活性和功能，可以在受限的框架内应对生物传感器数据流和分析服务。实施结果表明，独立边缘与双模边缘系统之间的相关性很高。但是，双模边缘云系统提供了更大的灵活性和功能，可以在受限的框架内应对生物传感器数据流和分析服务。