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2021 | OriginalPaper | Buchkapitel

Structural Health Monitoring over 5G uRLLC Network

verfasst von : Fabio Franchi, Fabio Graziosi, Andrea Marotta, Claudia Rinaldi

Erschienen in: European Workshop on Structural Health Monitoring

Verlag: Springer International Publishing

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Abstract

In this work we propose a Disaster Management System on 5G ultra Reliable Low Latency Networks that targets unprecedented reliability levels as well as low latency. In fact, referring to the 5G vision a Structural Health Monitoring system can be considered depending on the operational scenario: in the case of data collection and processing from sensors in monitored buildings, considering the high number of sensors installed, it can refer to the massive Machine Type Communications context. Vice versa, during a seismic event or just after it, the use case requires high reliability connectivity and, sometimes, low latency. Those features refer to the ultra Reliable Low Latency context. It seems interesting to evaluate and experiment the ability of 5G network to dynamically adapt to the changing scenario that this use case can provide. Moreover this work presents an innovative 5G architecture for Earthquake Early Warning that uses Structural Health Monitoring systems to detect a seismic event and to propagate a message reporting the event detection to all the buildings that may be damaged by the event.

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Fußnoten
1
Topic of great importance for the municipality and citizens due to the aftermath of the 2009 L’Aquila earthquake.
 
Literatur
1.
Zurück zum Zitat Alliance, N.: 5G white paper. In: Next Generation Mobile Networks, White Paper, vol. 1 (2015) Alliance, N.: 5G white paper. In: Next Generation Mobile Networks, White Paper, vol. 1 (2015)
2.
Zurück zum Zitat 3GPP TS 38.913: Technical specification group radio access network; study on scenarios and requirements for next generation access technologies. Release 15, June 2018 3GPP TS 38.913: Technical specification group radio access network; study on scenarios and requirements for next generation access technologies. Release 15, June 2018
3.
Zurück zum Zitat Li, S., Da Xu, L., Zhao, S.: 5G internet of things: a survey. J. Ind. Inf. Integr. 10, 1–9 (2018) Li, S., Da Xu, L., Zhao, S.: 5G internet of things: a survey. J. Ind. Inf. Integr. 10, 1–9 (2018)
4.
Zurück zum Zitat Antonelli, C., Cassioli, D., Franchi, F., Graziosi, F., Marotta, A., Pratesi, M., Rinaldi, C., Santucci, F.: The city of L’aquila as a living lab: the incipict project and the 5G trial. In: 2018 IEEE 5G World Forum (5GWF), pp. 410–415, July 2018 Antonelli, C., Cassioli, D., Franchi, F., Graziosi, F., Marotta, A., Pratesi, M., Rinaldi, C., Santucci, F.: The city of L’aquila as a living lab: the incipict project and the 5G trial. In: 2018 IEEE 5G World Forum (5GWF), pp. 410–415, July 2018
5.
Zurück zum Zitat Krishnamurthy, V., Fowler, K., Sazonov, E.: The effect of time synchronization of wireless sensors on the modal analysis of structures. Smart Mater. Struct. 17(5), 055018 (2008)CrossRef Krishnamurthy, V., Fowler, K., Sazonov, E.: The effect of time synchronization of wireless sensors on the modal analysis of structures. Smart Mater. Struct. 17(5), 055018 (2008)CrossRef
6.
Zurück zum Zitat Lynch, J.P., Loh, K.J.: A summary review of wireless sensors and sensor networks for structural health monitoring. Shock Vibr. Digest 38(2), 91–130 (2006)CrossRef Lynch, J.P., Loh, K.J.: A summary review of wireless sensors and sensor networks for structural health monitoring. Shock Vibr. Digest 38(2), 91–130 (2006)CrossRef
7.
Zurück zum Zitat Tajima, F., Hayashida, T.: Earthquake early warning: what does “seconds before a strong hit” mean? Progr. Earth Planetary Sci. 5(1), 63 (2018)CrossRef Tajima, F., Hayashida, T.: Earthquake early warning: what does “seconds before a strong hit” mean? Progr. Earth Planetary Sci. 5(1), 63 (2018)CrossRef
8.
Zurück zum Zitat 3GPP TS 38.201: Technical specification group radio access network; NR; physical layer; general description. Release 15, December 2017 3GPP TS 38.201: Technical specification group radio access network; NR; physical layer; general description. Release 15, December 2017
9.
Zurück zum Zitat Sachs, J., Wikstrom, G., Dudda, T., Baldemair, R., Kittichokechai, K.: 5G radio network design for ultra-reliable low-latency communication. IEEE Netw. 32(2), 24–31 (2018)CrossRef Sachs, J., Wikstrom, G., Dudda, T., Baldemair, R., Kittichokechai, K.: 5G radio network design for ultra-reliable low-latency communication. IEEE Netw. 32(2), 24–31 (2018)CrossRef
10.
Zurück zum Zitat Kaippallimalil, J., Lee, Y., Saboorian, T., Shalash, M., Kozat, U.: Traffic engineered transport for 5G networks. In: 2019 IEEE Conference on Standards for Communications and Networking (CSCN), pp. 1–6 (2019) Kaippallimalil, J., Lee, Y., Saboorian, T., Shalash, M., Kozat, U.: Traffic engineered transport for 5G networks. In: 2019 IEEE Conference on Standards for Communications and Networking (CSCN), pp. 1–6 (2019)
11.
Zurück zum Zitat D’Errico, L., Franchi, F., Graziosi, F., Marotta, A., Rinaldi, C., Boschi, M., Colarieti, A.: Structural health monitoring and earthquake early warning on 5G uRLLC network. In: 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), pp. 783–786. IEEE (2019) D’Errico, L., Franchi, F., Graziosi, F., Marotta, A., Rinaldi, C., Boschi, M., Colarieti, A.: Structural health monitoring and earthquake early warning on 5G uRLLC network. In: 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), pp. 783–786. IEEE (2019)
12.
Zurück zum Zitat Potenza, F., Federici, F., Lepidi, M., Gattulli, V., Graziosi, F., Colarieti, A.: Long-term structural monitoring of the damaged basilica S. Maria di Collemaggio through a low-cost wireless sensor network. J. Civ. Struct. Health Monit. 5(5), 655–676 (2015)CrossRef Potenza, F., Federici, F., Lepidi, M., Gattulli, V., Graziosi, F., Colarieti, A.: Long-term structural monitoring of the damaged basilica S. Maria di Collemaggio through a low-cost wireless sensor network. J. Civ. Struct. Health Monit. 5(5), 655–676 (2015)CrossRef
13.
Zurück zum Zitat Ha, D., Park, H., Choi, S., Kim, Y.: A wireless MEMS-based inclinometer sensor node for structural health monitoring. Sensors 13(12), 16 090–16 104 (2013)CrossRef Ha, D., Park, H., Choi, S., Kim, Y.: A wireless MEMS-based inclinometer sensor node for structural health monitoring. Sensors 13(12), 16 090–16 104 (2013)CrossRef
14.
Zurück zum Zitat Lorenzoni, F., Caldon, M., da Porto, F., Modena, C., Aoki, T.: Post-earthquake controls and damage detection through structural health monitoring: applications in L’aquila. J. Civ. Struct. Health Monit. 8(2), 217–236 (2018)CrossRef Lorenzoni, F., Caldon, M., da Porto, F., Modena, C., Aoki, T.: Post-earthquake controls and damage detection through structural health monitoring: applications in L’aquila. J. Civ. Struct. Health Monit. 8(2), 217–236 (2018)CrossRef
15.
Zurück zum Zitat Behl, M., Smarra, F., Mangharam, R.: Dr-advisor: a data-driven demand response recommender system. Appl. Energy 170, 30–46 (2016)CrossRef Behl, M., Smarra, F., Mangharam, R.: Dr-advisor: a data-driven demand response recommender system. Appl. Energy 170, 30–46 (2016)CrossRef
16.
Zurück zum Zitat Jain, A., Smarra, F. Mangharam, R.: Data predictive control using regression trees and ensemble learning. In: 2017 IEEE 56th Annual Conference on Decision and Control (CDC), pp. 4446–4451. IEEE (2017) Jain, A., Smarra, F. Mangharam, R.: Data predictive control using regression trees and ensemble learning. In: 2017 IEEE 56th Annual Conference on Decision and Control (CDC), pp. 4446–4451. IEEE (2017)
17.
Zurück zum Zitat Jain, A., Smarra, F., Behl, M., Mangharam, R.: Data-driven model predictive control with regression trees–an application to building energy management. ACM Trans. Cyber-Phys. Syst. 2(1), 1–21 (2018)CrossRef Jain, A., Smarra, F., Behl, M., Mangharam, R.: Data-driven model predictive control with regression trees–an application to building energy management. ACM Trans. Cyber-Phys. Syst. 2(1), 1–21 (2018)CrossRef
18.
Zurück zum Zitat Smarra, F., Jain, A., de Rubeis, T., Ambrosini, D., D’Innocenzo, A., Mangharam, R.: Data-driven model predictive control using random forests for building energy optimization and climate control. Appl. Energy 226, 1252–1272 (2018)CrossRef Smarra, F., Jain, A., de Rubeis, T., Ambrosini, D., D’Innocenzo, A., Mangharam, R.: Data-driven model predictive control using random forests for building energy optimization and climate control. Appl. Energy 226, 1252–1272 (2018)CrossRef
19.
Zurück zum Zitat Smarra, F., Di Girolamo, G.D., Gattulli, V., Graziosi, F., D’Innocenzo, A.: Learning models for seismic-induced vibrations optimal control in structures via random forests. J. Optim. Theory Appl. 1–20 (2020) Smarra, F., Di Girolamo, G.D., Gattulli, V., Graziosi, F., D’Innocenzo, A.: Learning models for seismic-induced vibrations optimal control in structures via random forests. J. Optim. Theory Appl. 1–20 (2020)
20.
Zurück zum Zitat Smarra, F., Di Girolamo, G.D., De Iuliis, V., Jain, A., Mangharam, R., D’Innocenzo, A.: Data-driven switching modeling for MPC using regression trees and random forests. Nonlinear Anal: Hybrid Syst. 36, 100882 (2020)MathSciNetMATH Smarra, F., Di Girolamo, G.D., De Iuliis, V., Jain, A., Mangharam, R., D’Innocenzo, A.: Data-driven switching modeling for MPC using regression trees and random forests. Nonlinear Anal: Hybrid Syst. 36, 100882 (2020)MathSciNetMATH
21.
Zurück zum Zitat Di Girolamo, G., Smarra, F., Gattulli, V., Potenza, F., Graziosi, F., D’Innocenzo, A.: Data-driven optimal predictive control of seismic induced vibrations in frame structures. Struct. Control Health Monit. 27(4), e2514 (2020)CrossRef Di Girolamo, G., Smarra, F., Gattulli, V., Potenza, F., Graziosi, F., D’Innocenzo, A.: Data-driven optimal predictive control of seismic induced vibrations in frame structures. Struct. Control Health Monit. 27(4), e2514 (2020)CrossRef
Metadaten
Titel
Structural Health Monitoring over 5G uRLLC Network
verfasst von
Fabio Franchi
Fabio Graziosi
Andrea Marotta
Claudia Rinaldi
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-64594-6_7