An Interoperable Architecture for the Internet of COVID-19 Things (IoCT) Using Open Geospatial Standards-Case Study: Workplace Reopening.
An Interoperable Architecture for the Internet of COVID-19 Things (IoCT) Using Open Geospatial Standards-Case Study: Workplace Reopening.
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DOI：
10.3390/s21010050
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发表时间：
2020-12-24
期刊：
影响因子：
--
通讯作者：
Squires J
中科院分区：
文献类型：
--
作者：
Liang SHL;Saeedi S;Ojagh S;Honarparvar S;Kiaei S;Mohammadi Jahromi M;Squires J
为了在 COVID-19 大流行期间和之后安全地保护工作场所和劳动力，需要可扩展的集成传感解决方案，以便为决策者提供实时态势感知和早期预警。然而，当必要的运营信息被锁定在不同的实时数据孤岛中时，基于信息的行业重新开放解决方案就无效了。人们正在进行大量努力，利用低成本、基于位置的接触者追踪和传感技术的不同组合来对抗 COVID-19 大流行。这些针对 COVID-19 的临时物联网 (IoT) 解决方案是使用不同的数据模型和协议开发的，没有可互操作的方式来互连这些异构系统并交换有关人员和场所交互的数据。本研究旨在设计和开发一种可互操作的 COVID-19 物联网 (IoCT) 架构，该架构能够交换、聚合和重用不同的物联网传感器数据源，以便在基于人与地方的交互了解工作场所的实时风险后做出明智的决策。 IoCT 架构基于传感器网络范例，将各种物体、传感器和数据流与室内地理空间数据模型连接起来。据我们所知，本文介绍了开放地理空间联盟 (OGC) 传感器网络支持 (SWE) 和 IndoorGML 标准的首次现实世界综合实施研究，以使用工作场所重新开放案例研究在线计算 COVID-19 风险。拟议的 IoCT 提供了一种新的基于开放标准的信息模型、架构、方法和软件工具，使不同的 COVID-19 监测系统具有更精细的时空粒度的互操作性。开发了一个工作场所清洁用例，以展示所提出的物联网架构的功能。实施的 IoCT 架构包括基于邻近度的接触追踪、人员密度传感器、COVID-19 危险行为监控系统和上下文建筑地理空间数据。
To safely protect workplaces and the workforce during and after the COVID-19 pandemic, a scalable integrated sensing solution is required in order to offer real-time situational awareness and early warnings for decision-makers. However, an information-based solution for industry reopening is ineffective when the necessary operational information is locked up in disparate real-time data silos. There is a lot of ongoing effort to combat the COVID-19 pandemic using different combinations of low-cost, location-based contact tracing, and sensing technologies. These ad hoc Internet of Things (IoT) solutions for COVID-19 were developed using different data models and protocols without an interoperable way to interconnect these heterogeneous systems and exchange data on people and place interactions. This research aims to design and develop an interoperable Internet of COVID-19 Things (IoCT) architecture that is able to exchange, aggregate, and reuse disparate IoT sensor data sources in order for informed decisions to be made after understanding the real-time risks in workplaces based on person-to-place interactions. The IoCT architecture is based on the Sensor Web paradigm that connects various Things, Sensors, and Datastreams with an indoor geospatial data model. This paper presents a study of what, to the best of our knowledge, is the first real-world integrated implementation of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) and IndoorGML standards to calculate the risk of COVID-19 online using a workplace reopening case study. The proposed IoCT offers a new open standard-based information model, architecture, methodologies, and software tools that enable the interoperability of disparate COVID-19 monitoring systems with finer spatial-temporal granularity. A workplace cleaning use case was developed in order to demonstrate the capabilities of this proposed IoCT architecture. The implemented IoCT architecture included proximity-based contact tracing, people density sensors, a COVID-19 risky behavior monitoring system, and the contextual building geospatial data.
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