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A Cloud-Based IoT Approach to Support Infrastructure Monitoring Needs by Public Civil Protection Organizations

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Trends and Applications in Information Systems and Technologies (WorldCIST 2021)

Abstract

The evolution of technology in the last decade predicts a future where technology is disseminated in the environment in order to merge with the environment itself, being omnipresent. This world paradigm has been associated with the Internet of Things concept or, according to several authors, with the Internet of Everything concept. The potential massive dispersion of technology, which, with the progress of nanotechnology, will be increasingly miniaturized, combined with high-performance and universal communication networks, will revolutionize the concept of monitoring, resulting in profound changes in various sectors of activity and knowledge. In this context, this article presents a cloud-based Internet of Things architecture in order to respond to the growing needs of monitoring by the Civil Protection Public Organizations, who are responsible for monitoring several parameters and produce multiple information and reports in the context of the security of populations and territories. Finally, it is presented a prototype implemented according to the proposed architecture capable of monitoring monoliths dispersed in the territory, as a way of acting preventively, avoiding merely reactive actions after disaster situations.

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References

  1. Zimmermann, A., Schmidt, R., Sandkuhl, K., Wißotzki, M., Jugel, D., Möhring, M.: Digital enterprise architecture-transformation for the internet of things. In: IEEE 19th International Enterprise Distributed Object Computing Workshop. IEEE (2015)

    Google Scholar 

  2. Zahmatkesh, H., Al-Turjman, F.: Fog computing for sustainable smart cities in the IoT era: caching techniques and enabling technologies - an overview. Sustain. Cities Soc. 59 (2020). ISSN 2210-6707

    Google Scholar 

  3. Talavera, J.M., Tobón, L.E., Gómez, J.A., Culman, M.A., Aranda, J.M., Parra, D.T., Quiroz, L.A., Hoyos, A., Garreta, L.E.: Review of IoT applications in agro-industrial and environmental fields. Comput. Electron. Agric. 142, Part A, 283–297 (2017). ISSN 0168-1699

    Google Scholar 

  4. Bublitz, M.F., Oetomo, A., Sahu, S.K., Kuang, A., Fadrique, X.L., Velmovitsky, E.P., Nobrega, M.R., Morita, P.P.: Disruptive technologies for environment and health research: an overview of artificial intelligence, blockchain, and internet of things. Int. J. Environ. Res. Public Health 16(20), 3847 (2019). https://doi.org/10.3390/ijerph16203847

  5. Okafor, N.U., Alghorani, Y., Delaney, D.T.: Improving data quality of low-cost IoT sensors in environmental monitoring networks using data fusion and machine learning approach. ICT Express 6(3), 220–228 (2020). ISSN 2405-9595

    Google Scholar 

  6. Manes, G., Collodi, G., Gelpi, L., Fusco, R., Ricci, G., Manes, A., Passafiume, M.: Realtime gas emission monitoring at hazardous sites using a distributed point-source sensing infrastructure. Sensors 16, 121 (2016)

    Article  Google Scholar 

  7. Syafrudin, M., Alfian, G., Fitriyani, N.L., Rhee, J.: Performance analysis of IoT-based sensor, big data processing, and machine learning model for real-time monitoring system in automotive manufacturing. Sensors 18, 2946 (2018)

    Article  Google Scholar 

  8. Abruzzese, D., Micheletti, A., Tiero, A., Cosentino, M., Forconi, D., Grizzi, G., Scarano, G., Vuth, S., Abiuso, P.: IoT sensors for modern structural health monitoring. A new frontier. Procedia Struct. Integr. 25, 378–385 (2020). ISSN 2452-3216

    Google Scholar 

  9. Mdhaffar, A., Chaari, T., Larbi, K., Jmaiel, M., Freisleben, B.: IoT-based health monitoring via LoRaWAN. In: 17th IEEE International Conference on Smart Technologies, EUROCON 2017 - Conference Proceedings, pp. 519–524 (2017)

    Google Scholar 

  10. Alsuhly, G., Khattab, A.: An IoT monitoring and control platform for museum content conservation. In: 2018 International Conference on Computer and Applications (ICCA), pp. 196–201 (2018). https://doi.org/10.1109/COMAPP.2018.8460402

  11. Wilkerson, G.B., Gupta, A., Colston, M.A.: Mitigating sports injury risks using internet of things and analytics approaches. Risk Anal. 38(7), 1348–1360 (2018)

    Article  Google Scholar 

  12. Khanna, A., Anand, R.: IoT based smart parking system. In: 2016 International Conference on Internet of Things and Applications, pp. 266–270 (2016)

    Google Scholar 

  13. Carter, W.N.: Disaster Management: A Disaster Manager’s Handbook. A. D. Bank (1991)

    Google Scholar 

  14. Khan, A., Gupta, S., Gupta, S. K.: Multi-hazard disaster studies: monitoring, detection, recovery, and management, based on emerging technologies and optimal techniques. Int. J. Disaster Risk Reduct. 47, 101642 (2020). Elsevier Ltd.

    Google Scholar 

  15. Mahmud, M.A., Bates, K., Wood, T., Abdelgawad, A., Yelamarthi, K.: A complete Internet of Things (IoT) platform for Structural Health Monitoring (SHM). In: IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings, 2018-January, pp. 275–279 (2018)

    Google Scholar 

  16. Phanish, D., Garver, P., Matalkah, G., Landes, T., Shen, F., Dumond, J., Abler, R., Zhu, D., Dong, X., Wang, Y., Coyle, E.J.: A wireless sensor network for monitoring the structural health of a football stadium. In: IEEE World Forum on Internet of Things, WF-IoT 2015 - Proceedings, pp. 471–477 (2015). https://doi.org/10.1109/WF-IoT.2015.7389100

  17. Hou, S., Wu, G.: A low-cost IoT-based wireless sensor system for bridge displacement monitoring. Smart Mater. Struct. 28(8) (2019). Article id. 085047

    Google Scholar 

  18. Intrieri, E., Gigli, G., Mugnai, F., Fanti, R., Casagli, N.: Design and implementation of a landslide early warning system. Eng. Geol. 147–148, 124–136 (2012)

    Article  Google Scholar 

  19. Chenhui, W., Qingjia, M.: Design of rapid monitoring system of geological disaster based on LoRa. MATEC Web Conf. 306, 5 (2020)

    Article  Google Scholar 

  20. Al Qundus, J., Dabbour, K., Gupta, S., Meissonier, R., Paschke, A.: Wireless sensor network for AI-based flood disaster detection. Annals Oper. Res. 1–23 (2020)

    Google Scholar 

  21. ANEPC. https://www.prociv.pt/pt-pt/protecaocivil/anpc/quemsomos. Accessed 11 Nov 2020

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Acknowledgments

UNIAG, R&D unit funded by the FCT – Portuguese Foundation for the Development of Science and Technology, Ministry of Science, Technology and Higher Education. UIDB/04752/2020.

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Correspondence to João Pedro Gomes .

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Gomes, J.P., Cunha, C.R., Noira, G., Santos, A. (2021). A Cloud-Based IoT Approach to Support Infrastructure Monitoring Needs by Public Civil Protection Organizations. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies . WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1367. Springer, Cham. https://doi.org/10.1007/978-3-030-72660-7_37

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