Literature DB >> 33374208

An Interoperable Architecture for the Internet of COVID-19 Things (IoCT) Using Open Geospatial Standards-Case Study: Workplace Reopening.

Steve H L Liang1,2, Sara Saeedi1, Soroush Ojagh1, Sepehr Honarparvar1, Sina Kiaei1, Mahnoush Mohammadi Jahromi1, Jeremy Squires2.   

Abstract

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.

Entities:  

Keywords:  COVID-19; Internet of Things (IoT), interoperability; OGC IndoorGML; OGC SensorThings; contact tracing; cough detection; deep learning; physical distance detection; spatial multi-criteria risk analysis

Year:  2020        PMID: 33374208     DOI: 10.3390/s21010050

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  3 in total

1.  IoMT-fog-cloud based architecture for Covid-19 detection.

Authors:  Khelili Mohamed Akram; Slatnia Sihem; Kazar Okba; Saad Harous
Journal:  Biomed Signal Process Control       Date:  2022-04-13       Impact factor: 5.076

2.  Voluntary consensus based geospatial data standards for the global illegal trade in wild fauna and flora.

Authors:  Meredith L Gore; Lee R Schwartz; Kofi Amponsah-Mensah; Emily Barbee; Susan Canney; Maria Carbo-Penche; Drew Cronin; Rowan Hilend; Melinda Laituri; David Luna; Faith Maina; Christian Mey; Kathleena Mumford; Robinson Mugo; Redempta Nduguta; Christopher Nyce; John McEvoy; William McShea; Angelo Mandimbihasina; Nick Salafsky; David Smetana; Alexander Tait; Tim Wittig; Dawn Wright; Leah Wanambwa Naess
Journal:  Sci Data       Date:  2022-06-03       Impact factor: 8.501

3.  User-Centric Proximity Estimation Using Smartphone Radio Fingerprinting.

Authors:  Aleš Švigelj; Andrej Hrovat; Tomaž Javornik
Journal:  Sensors (Basel)       Date:  2022-07-27       Impact factor: 3.847

  3 in total

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