Papers
Topics
Authors
Recent
2000 character limit reached

Unified Pandemic Tracking System Based on Open Geospatial Consortium SensorThings API (2401.10898v1)

Published 18 Dec 2023 in cs.CY and cs.NI

Abstract: With the current nations struggling to track the pandemic's trajectories. There has been a lack of transparency or real-live data streaming for pandemic cases and symptoms. This phenomenon has led to a rapid and uncontrolled spread of these deadly pandemics. One of the main issues in creating a global pandemic tracking system is the lack of standardization of communications protocols and the deployment of Internet-of-Things (IoT) device sensors. The Open Geospatial Consortium (OGC) has developed several sensor web Enablement standards that allow the expeditious deployment of communications protocols within IoT devices and other sensor devices like the OGC SensorThings application programming interface (API). In this paper, to address this issue, we outline the interoperability challenge and provide a qualitative and quantitative study of the OGC SensorThings API's deployment and its respective server. The OGC SensorThings API is developed to provide data exchange services between sensors and their observations. The OGC SensorThings API would play a primary and essential role in creating an automated pandemic tracking system. This API would reduce the deployment of any set of sensors and provide real-time data tracking. Accordingly, global health organizations would react expeditiously and concentrate their efforts on high infection rates.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (35)
  1. V. Chamola, V. Hassija, V. Gupta, and M. Guizani, “A comprehensive review of the covid-19 pandemic and the role of iot, drones, ai, blockchain, and 5g in managing its impact,” IEEE Access, vol. 8, pp. 90 225–90 265, 2020.
  2. B. Benreguia, H. Moumen, and M. A. Merzoug, “Tracking covid-19 by tracking infectious trajectories,” IEEE Access, vol. 8, pp. 145 242–145 255, 2020.
  3. C. Sohrabi, Z. Alsafi, M.Khan, A.Kerwan, A.Al-Jabir, C.Iosifidis, and R.Agha, “World health organization declares global emergency: A review of the 2019 novel coronavirus (covid-19),” International Journal of Surgery, vol. 76, no. 71, pp. 71–76, 2020.
  4. J. Singh, A. Refaey, and J. Koilpillai, “Adoption of the software-defined perimeter (sdp) architecture for infrastructure as a service,” Canadian Journal of Electrical and Computer Engineering, vol. 43, no. 4, pp. 357–363, 2020.
  5. J. Singh, A. Refaey, and A. Shami, “Multilevel security framework for nfv based on software defined perimeter,” IEEE Network, vol. 34, no. 5, pp. 114–119, 2020.
  6. J. Singh, Y. Bello, A. R. Hussein, A. Erbad, and A. Mohamed, “Hierarchical security paradigm for iot multiaccess edge computing,” IEEE Internet of Things Journal, vol. 8, no. 7, pp. 5794–5805, 2021.
  7. A. Refaey, K. Hammad, S. Magierowski, and E. Hossain, “A blockchain policy and charging control framework for roaming in cellular networks,” IEEE Network, vol. 34, no. 3, pp. 170–177, 2020.
  8. A. Feriani, A. Refaey, and E. Hossain, “Tracking pandemics: a mec-enabled iot ecosystem with learning capability,” IEEE Internet of Things Magazine, vol. 3, no. 3, pp. 40–45, Oct. 2020.
  9. A. Sallam, A. Refaey, and A. Shami, “On the security of sdn: A completed secure and scalable framework using the software-defined perimeter,” IEEE Access, vol. 7, pp. 146 577–146 587, 2019.
  10. A. Moubayed, A. Refaey, and A. Shami, “Software-defined perimeter (sdp): State of the art secure solution for modern networks,” IEEE Network, vol. 33, no. 5, pp. 226–233, 2019.
  11. E. Figetakis, A. R. Hussein, and M. Ulema, “Evolved prevention strategies for 6g networks through stochastic games and reinforcement learning,” IEEE Networking Letters, vol. 5, no. 3, pp. 164–168, 2023.
  12. E. Baccour, M. S. Allahham, A. Erbad, A. Mohamed, A. R. Hussein, and M. Hamdi, “Zero touch realization of pervasive artificial intelligence as a service in 6g networks,” IEEE Communications Magazine, vol. 61, no. 2, pp. 110–116, 2023.
  13. A. Mehrabi, M. Siekkinen, and A. Ylä-Jaaski, “Qoe-traffic optimization through collaborative edge caching in adaptive mobile video streaming,” IEEE Access, vol. 6, pp. 52 261–52 276, 2018.
  14. C. DeSantis and A. R. Hussein, “Ai soc-based accelerator for speech classification speech classification accelerator based on an ai soc,” IEEE Canadian Journal of Electrical and Computer Engineering, vol. 45, no. 3, pp. 222–231, 2022.
  15. Y. Bello, A. R. Hussein, M. Ulema, and J. Koilpillai, “On sustained zero trust conceptualization security for mobile core networks in 5g and beyond,” IEEE Transactions on Network and Service Management, vol. 19, no. 2, pp. 1876–1889, 2022.
  16. Y. Bello, A. A. Abdellatif, M. S. Allahham, A. R. Hussein, A. Erbad, A. Mohamed, and M. Guizani, “B5g: Predictive container auto-scaling for cellular evolved packet core,” IEEE Access, vol. 9, pp. 158 204–158 214, 2021.
  17. S. Asad and A. Refaey, “On iot edge devices: Manifold unsupervised learning for som platforms,” in 2021 IEEE International Conference on Imaging Systems and Techniques (IST), 2021, pp. 1–5.
  18. M. N. Islam, I. Islam, K. M. Munim, and A. K. M. N. Islam, “A review on the mobile applications developed for covid-19: An exploratory analysis,” IEEE Access, vol. 8, pp. 145 601–145 610, 2020.
  19. E. Figetakis and A. Refaey, “Uav path planning using on-board ultrasound transducer arrays and edge support,” in 2021 IEEE International Conference on Communications Workshops (ICC Workshops), 2021, pp. 1–6.
  20. Z. Khaliq, P. Mirdita, A. Refaey, and X. Wang, “Unsupervised manifold alignment for wifi rssi indoor localization,” in 2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2020, pp. 1–7.
  21. C. DeSantis and A. Refaey, “Mec-based evacuation planning using variance fractal dimension trajectory for speech classification,” in 2021 IEEE International Conference on Communications Workshops (ICC Workshops), 2021, pp. 1–6.
  22. A. Refaey, W. Hou, and L. Loukhaoukha, “Multilayer authentication for communication systems based on physical-layer attributes,” Journal of Computer and Communications, vol. 2, pp. 64–75, 2014.
  23. A. Refaey, A. Sallam, and A. Shami, “On IoT applications: a proposed SDP framework for MQTT,” Electronics Letters, vol. 55, no. 22, pp. 1201–1203, Oct. 2019.
  24. S. Liang, C.-Y. Huang, and T. Khalafbeigi, “Ogc sensorthings api part 1: Sensing, version 1.0.” 2016.
  25. C. Bormann, A. P. Castellani, and Z. Shelby, “CoAp: An application protocol for billions of tiny internet nodes,” IEEE Internet Computing, vol. 16, no. 2, pp. 62–67, Apr. 2012.
  26. M. A. Jazayeri, S. H. L. Liang, and C.-Y. Huang, “Implementation and evaluation of four interoperable open standards for the internet of things,” Sensors, vol. 15, no. 9, pp. 24 343–24 373, 2015. [Online]. Available: https://www.mdpi.com/1424-8220/15/9/24343
  27. S. Z., H. K., and B. C, “Constrained application protocol (coap,” pp. 18–28, (accessed on 1 November 2013)]. Available online:. [Online]. Available: https://tools.ietf.org/html/draft-ietf-core-coap-18.
  28. C. F., D. M., K. R., N. W., M. N., and W. S, “Unraveling the web services web: An introduction to soap, wsdl, and uddi,” IEEE Internet Compute, vol. 6, p. 86–93, crossRef] [Google Scholar.
  29. M. G., G. F., and T. D, “A lightweight soap over coap transport binding for resource constraint networks,” google Scholar.
  30. M. U. Ashraf, A. Hannan, S. M. Cheema, Z. Ali, K. m. Jambi, and A. Alofi, “Detection and tracking contagion using iot-edge technologies: Confronting covid-19 pandemic,” pp. 1–6, 2020.
  31. B. C., C. A.P., and S. Z, “Coap: An application protocol for billions of tiny internet nodes,” IEEE Internet Comput, vol. 16, p. 62–67, crossRef] [Google Scholar.
  32. J. Liu, G. Shou, Y. Liu, Y. Hu, and Z. Guo, “Performance evaluation of integrated multi-access edge computing and fiber-wireless access networks,” IEEE Access, vol. 6, pp. 30 269–30 279, 2018.
  33. F. Rustam, A. A. Reshi, A. Mehmood, S. Ullah, B. On, W. Aslam, and G. S. Choi, “Covid-19 future forecasting using supervised machine learning models,” IEEE Access, vol. 8, pp. 101 489–101 499, 2020.
  34. F. P. McCreedy and D. B. Marks, “The naval research laboratory’s ongoing implementation of the open geospatial consortium’s catalogue services specification,” pp. 1–7, 2009.
  35. P. N.B., K. A., G. M., and Z. F, “Tiny web services: Design and implementation of interoperable and evolvable sensor networks,” p. 253–266.

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now

Whiteboard

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Generate Now

Continue Learning

We haven't generated follow-up questions for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Generate Now

Collections

Sign up for free to add this paper to one or more collections.

User Circle Single Streamline Icon: https://streamlinehq.com Sign Up

Tweets

Sign up for free to view the 2 tweets with 0 likes about this paper.

User Circle Single Streamline Icon: https://streamlinehq.com Sign Up for Free