6. Conclusions
This paper presents an Internet of COVID-19 Things platform called IoCT which offers two main contributions: (1) The design and development of a low-cost, real-time, comprehensive situational awareness for workplace reopenings after COVID-19; and (2) Interoperability through the open geospatial standards for indoor COVID-19 person-to-place risk assessment. In addition, the proposed platform is able to be applied to any kind of sensor and for use with different applications.
The proposed IoCT platform offers an easy connection between software and hardware which is necessary to achieve a global-level COVID-19 pandemic situational awareness. At the software level, a cloud architecture was developed for the IoCT, and the Sensors incorporated in this study are able to be included into it with minimal effort. At the hardware level, it offers a plug and play connection which will be explored for future research. It offers the possibility for scaling and access to a large number of low-cost sensors (manufactured by different companies) with an interoperable IoT design using the OGC STA as a conceptual modelling layer on top of the AWS. Furthermore, it provides the option of expansion because of the many compatible components which lead to the schematics being fully available.
In order to validate the proposed architecture, the IoCT sensor network was created and validated using multiple Things, Sensors, and Datastreams. Using the case of a scalable and connected COVID-19 IoT system, we deployed an interoperable sensorized platform to create a comprehensive picture for a post COVID-19 workplace reopening. A cleaning use case was developed for the University of Calgary campus to validate this. This platform was developed using an Android smartphone and Jetson NX, and applied the use of various sensors including BLE, camera, and microphone to provide many benefits. A network with 2 IoCT Things and 20 Sensors was successfully deployed. Each IoCT Thing was designed based on the IoT paradigm and can be considered a smart object that is permanently connected using the Internet Protocol.
Another benefit of using open standards is that they offer interoperable applications that facilitate access to data and reusability. A Web client was deployed to consume data for the OGC STA provided by the IoCT platform. The OGC STA offers easy and agile access to sensor data using IoT paradigms. Moreover, the OGC IndoorGML allows for the aggregation of various cameras and contact tracing systems that can work together in a common indoor risk model and exchange various data within the space model for risk calculations. The OGC IndoorGML model can be used for various trajectory mining as well. The IoCT can be used for person-to-place interactions in order to identify those who may have been in close contact with an infected person, or with a virus-contaminated place. Moreover, the proposed system will inform people to take appropriate actions such as cleaning, social distancing, testing, isolation, or choosing safe pathways and locations. This paper improves both the quality and speed of pandemic emergency response by enabling IoT system interoperability and unlocking necessary information for real-time decision making, as well as accelerating new application development that is interoperable, scalable, and extensible.
Our future work will explore the interoperability between various BLE systems and standards to achieve plug and play contact tracing apps with various contextual information [79]. Another area for future research would be applying different data analysis to the indoor trajectory data provided by the IoCT platform [80]. For that we would attempt to obtain different metrices for person-to-place scenarios using an aggregation of the camera and BLE sensors for trajectory estimation [61]. This analysis will include spatial-temporal methodologies for real-time event detection using the deep learning module.