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The Urban Seismic Observatory of Catania (Italy): A Real-Time Seismic Monitoring at Urban Scale
Author(s)
Language
English
Obiettivo Specifico
1IT. Reti di monitoraggio e sorveglianza
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Title of the book
Issue/vol(year)
/14 (2022)
ISSN
2072-4292
Publisher
MDPI
Pages (printed)
2583
Issued date
May 27, 2022
Alternative Location
Abstract
We describe the first dense real-time urban seismic–accelerometric network in Italy,
named OSU-CT, located in the historic center of Catania. The city lies in the region with the greatest
danger, vulnerability, and earthquake exposure in the entire Italian territory. OSU-CT was planned
and realized within the project called EWAS “an Early WArning System for cultural heritage”,
aimed at the rapid assessment of earthquake-induced damage and the testing of an on-site
earthquake early warning system. OSU-CT is mainly based on low-cost instrumentation realized
ad hoc by using cutting-edge technologies and digital MEMS (micro-electro-mechanical systems)
triaxial accelerometers with excellent resolution and low noise. Twenty of the forty scheduled
stations have already been set up on the ground floor of significant historic public buildings. In
order to assess the performance of an earthquake early warning (EEW) on-site system, we also
installed wide-band velocimeters (ETL3D/5s) in three edifices chosen as test sites, which will be
instrumented for a structural health monitoring (SHM). In addition to several laboratory and field
validation tests on the developed instruments, an effective operational test of OSU-CT was the Mw
4.3 earthquake occurring on 23 December 2021, 16 km west, south-west of Catania. Peak ground
accelerations (4.956 gal to 39.360 gal) recorded by the network allowed obtaining a first urban
shakemap and determining a reliable distribution of ground motion in the historical center of the
city, useful for the vulnerability studies of the historical edifices.
named OSU-CT, located in the historic center of Catania. The city lies in the region with the greatest
danger, vulnerability, and earthquake exposure in the entire Italian territory. OSU-CT was planned
and realized within the project called EWAS “an Early WArning System for cultural heritage”,
aimed at the rapid assessment of earthquake-induced damage and the testing of an on-site
earthquake early warning system. OSU-CT is mainly based on low-cost instrumentation realized
ad hoc by using cutting-edge technologies and digital MEMS (micro-electro-mechanical systems)
triaxial accelerometers with excellent resolution and low noise. Twenty of the forty scheduled
stations have already been set up on the ground floor of significant historic public buildings. In
order to assess the performance of an earthquake early warning (EEW) on-site system, we also
installed wide-band velocimeters (ETL3D/5s) in three edifices chosen as test sites, which will be
instrumented for a structural health monitoring (SHM). In addition to several laboratory and field
validation tests on the developed instruments, an effective operational test of OSU-CT was the Mw
4.3 earthquake occurring on 23 December 2021, 16 km west, south-west of Catania. Peak ground
accelerations (4.956 gal to 39.360 gal) recorded by the network allowed obtaining a first urban
shakemap and determining a reliable distribution of ground motion in the historical center of the
city, useful for the vulnerability studies of the historical edifices.
References
Evans, J.R.; Allen, R.M.; Chung, A.I.; Cochran, E.S.; Guy, R.; Hellweg, M.; Lawrence, J.F. Performance of Several Low-Cost
Accelerometers. Seismol. Res. Lett. 2014, 85, 147–158.
2. Fu, J.; Li, Z.; Meng, H.; Wang, J.; Shan, X. Performance Evaluation of Low-Cost Seismic Sensors for Dense Earthquake Early
Warning: 2018–2019 Field Testing in Southwest China. Sensors 2019, 19, 1999.
3. Rovithis, E.; Makra, K.; Savvaidis, A.; Kirtas, E. The accelerometric network of the Indes-Musa project in the Kalochori area:
Configuration, documentation and preliminary data interpretation, Proceedings of the 14th International Congress,
Thessaloniki May 2016. Bull. Geolog. Soc. Greece 2016, 50, 1110–1119.
4. Pierleoni, P.; Marzorati, S.; Ladina, C.; Raggiunto, S.; Belli, A.; Palma, L.; Cattaneo, M.; Valenti, S. Performance Evaluation of a
Low-Cost Sensing Unit for Seismic Applications: Field Testing During Seismic Events of 2016–2017 in Central Italy. IEEE Sens.
J. 2018, 18, 6644–6658.
5. Papanikolaou, V.K.; Karakostas, C.Z.; Theodoulidis, N.P. A Low-Cost Instrumentation System for Seismic Hazard Assessment
in Urban Areas. Sensors 2021, 21, 3618. https://doi.org/10.3390/s21113618.
6. Esposito, M.; Palma, L.; Belli, A.; Sabbatini, L.; Pierleoni, P. Recent Advances in Internet of Things Solutions for Early Warning
Systems: A Review. Sensors 2022, 22, 2124. https://doi.org/10.3390/s22062124.
7. Federici, F.; Graziosi, F.; Faccio, M.; Gattulli, V.; Lepidi, M.; Potenza, F. An integrated approach to the design of Wireless Sensor
Networks for structural health monitoring. Int. J. Distrib. Sens. Netw. 2012, 8, 594842. https://doi.org/10.1155/2012/594842.
8. Lin, J.F.; Li, X.Y.; Wang, J.; Wang, L.X.; Hu, X.X.; Liu, J.X. Study of Building Safety Monitoring by Using Cost-Effective MEMS
Accelerometers for Rapid After-Earthquake Assessment with Missing Data. Sensors 2021, 21, 7327.
https://doi.org/10.3390/s21217327.
9. Francisco, J.; Pallarés, M.B.; Bartoli, G.; Pallarés, L. Structural health monitoring (SHM) and Nondestructive testing (NDT) of
slender masonry structures: A practical review. Constr. Build. Mater. 2021, 297, 123768.
https://doi.org/10.1016/j.conbuildmat.2021.123768.
10. Liang, Q.; Tani, A.; Yamabe, Y. Fundamental Tests on a Structural Health Monitoring System for Building Structures Using a
Single-board Microcontroller. J. Asian Arch. Build. Eng. 2015, 14, 663–670.
11. Picozzi, M.; Emolo, A.; Martino, C.; Zollo, A.; Miranda, N.; Verderame, G.; Boxberger, T. and the REAKT Working, Group
Earthquake Early Warning System for Schools: A Feasibility Study in Southern Italy. Seism. Res. Lett. 2015, 86, 2A.
12. Dolce, M.; Nicoletti, M.; De Santis, A.; Marchesini, S.; Spina, D.; Talanas, F. Osservatorio sismico delle strutture: The Italian
structural seismic monitoring network. Bull. Earth. Eng. 2017, 15, 621–641.
13. Groos, J.C.; Ritter, J.R.R. Time domain classification and quantification of seismic noise in an urban environment. Geophys. J. Int.
2009, 179, 1213–1231. https://doi.org/10.1111/j.1365-246x.2009.04343.x.
14. Diaz, J.; Schimmel, M.; Ruiz, M.; Carbonell, R. Seismometers Within Cities: A Tool to Connect Earth Sciences and Society. Front.
Earth Sci. 2020, 8, 9. https://doi.org/10.3389/feart.2020.00009.
15. Vassallo, M.; De Matteis, R.; Bobbio, A.; Di Giulio, G.; Adinolfi, G.M.; Cantore, L.; Cogliano, R.; Fodarella, A.; Maresca, R.;
Pucillo, S.; et al. Seismic noise cross-correlation in the urban area of Benevento city (Southern Italy). Geophys. J. Int. 2019, 217,
1524–1542. https://doi.org/10.1093/gji/ggz101.
16. Olivito, R.S.; Porzio, S.; Scuro, C.; Carnì, D.L.; Lamonaca, F. Inventory and monitoring of historical cultural heritage buildings
at the territorial scale. A preliminary study of SHM based on CARTIS approach. Acta IMEKO 2021, 10, 9.
17. Azzara, R.M.; Girardi, M.; Iafolla, V.; Padovani, C.; Pellegrini, D. Long-Term Dynamic Monitoring of Medieval Masonry
Towers. Front. Built Environ. 2020, 6, 9. https://doi.org/10.3389/fbuil.2020.00009.
18. Chatzopoulos, G.; Papadopoulos, I.; Vallianatos, F.; Makris, J.P.; Kouli, M. Strong Ground Motion Sensor Network for Civil
Protection Rapid Decision Support Systems. Sensors 2021, 21, 2833. https://doi.org/10.3390/s21082833.
19. De Luca, G.; Marcucci, S.; Milana, G.; Sano, T. Evidence of Low-Frequency Amplification in the City of L’Aquila, Central Italy,
through a Multidisciplinary Approach Including Strong- and WeakMotion Data, Ambient Noise, and Numerical Modeling.
Bull. Seismol. Soc. Am. 2005, 95, 1469–1481. https://doi.org/10.1785/0120030253.
20. Bindi, D.; Pacor, F.; Luzi, L.; Massa, M.; Ameri, G. The Mw 6.3, 2009 L’Aquila earthquake: Source, path and site effects from
spectral analysis of strong motion data. Geophys. J. Int. 2009, 179, 1573–1579
21. Sextos, A.; De Risi, R.; Pagliaroli, A.; Foti, F.; Passeri, F.; Ausilio, E.; Cairo, R.; Capatti, M.C.; Chiabrando, F.; Chiaradonna, A.;
et al. Local Site Effects and Incremental Damage of Buildings during the 2016 Central Italy Earthquake Sequence. Earthq. Spectra
2019, 34, 1639–1669.
22. Di Giulio, G.; Azzara, R.M.; Cultrera, G.; Giammarinaro, M.S.; Vallone, P.; Rovelli, A. Effect of Local Geology on Ground Motion
in the City of Palermo, Italy, as Inferred from Aftershocks of the 6 September 2002 Mw 5.9 Earthquake. Bull. Seismol. Soc. Am.
2005, 95, 2328–2341. https://doi.org/10.1785/0120040219.
23. Nof, R.N.; Chung, A.I.; Rademacher, H.; Dengler, L.; Allen, R.M. MEMS Accelerometer Mini-Array (MAMA): A Low-Cost
Implementation for Earthquake Early Warning Enhancement. Earthq. Spectra 2019, 35, 21–38.
24. Chung, A.I.; Cochran, E.S.; Kaiser, A.E.; Christensen, C.M.; Yildirim, B.; Lawrence, J.F. Improved rapid magnitude estimation
for a community-based, low-cost MEMS accelerometer network. Bull. Seismol. Soc. Am. 2015, 105, 1314–1323.
25. Clayton, R.W.; Heaton, T.; Kohler, M.; Chandy, M.; Guy, R.; Bunn, J. Community seismic network: A dense array to sense
earthquake strong motion. Seismol. Res. Lett. 2015, 86, 1354–1363.
26. Horiuchi, S.; Horiuchi, Y.; Yamamoto, S.; Nakamura, H.; Wu, C.; Rydelek, P.A.; Kachi, M. Home seismometer for earthquake
early warning. Geophys. Res. Lett. 2009, 36. https://doi.org/10.1029/2008GL036572.
27. Zheng, H.; Shi, G.; Zeng, T.; Li, B. Wireless earthquake alarm design based on MEMS accelerometer. In Proceedings of the 2011
International Conference on Consumer Electronics, Communications and Networks (CECNet), Xianning, China, 16–19 April
2011; pp. 5481–5484.
28. Peng, C.; Peng, J.; Chen, Q.; Ma, Q.; Yang, J. Performance Evaluation of a Dense MEMS-Based Seismic Sensor Array Deployed
in the Sichuan-Yunnan Border Region for Earthquake Early Warning. Micromachines 2019, 10, 735.
https://doi.org/10.3390/mi10110735.
29. Yang, B.M.; Mittal, H.; Wu, Y.-M. Real-Time Production of PGA, PGV, Intensity, and Sa Shakemaps Using Dense MEMS-Based
Sensors in Taiwan. Sensors 2021, 21, 943. https://doi.org/10.3390/s21030943.
30. Lawrence, J.F.; Cochran, E.S.; Chung, A.; Kaiser, A.; Christensen, C.M.; Allen, R.; Baker, J.W.; Fry, B.; Heaton, T.; Kilb, D.; et al.
Rapid Earthquake Characterization Using MEMS Accelerometers and Volunteer Hosts Following the M 7.2 Darfield, New
Zealand, Earthquake. Bull. Seismol. Soc. Am. 2014, 104, 184–192. https://doi.org/10.1785/0120120196.
31. Tanırcan, G.; Hakan Alçık, H.; Beyen, K. Reliability of MEMS accelerometers for instrumental intensity mapping of earthquakes.
Ann. Geophys. 2017, 60 (Suppl. 6), SE673. https://doi.org/10.4401/ag-7501.
32. Holland, A. Earthquake data recorded by the MEMS accelerometer: Field testing in Idaho. Seismol. Res. Lett. 2003, 74, 20–26.
33. Pozzi, M.; Zonta, D.; Trapani, D.; Athanasopoulos, N.; Amditis, A.; Bimpas, M.; Garetsos, A.; Stratakos, Y.; Ulieru, D. MEMSbased
sensors for post-earthquake damage assessment. J. Phys. Conf. Ser. 2011, 305, 012100.
34. Kim, Y.; Kang, T.S.; Rhie, J. Development and Application of a Real-Time Warning System Based on a MEMS Seismic Network
and Response Procedure for the Day of the National College Entrance Examination in South Korea. Seismol. Res. Lett. 2017, 88,
1322–1326.
35. Peng, C.; Chen, Y.; Chen, Q.; Yang, J.; Wang, H.; Zhu, X.; Xu, Z.; Zheng, Y. A new type of tri-axial accelerometers with high
dynamic range MEMS for earthquake early warning. Comput. Geosci. 2017, 100, 179–187.
36. Lynch, J.P.; Loh, K.J. A Summary Review of Wireless Sensors and Sensor Networks for Structural Health Monitoring. Shock Vib.
Dig. 2006, 38, 91–128. https://doi.org/10.1177/0583102406061499.
37. Gattulli, G.; Marco Lepidi, M.; Potenza, F. Dynamic testing and health monitoring of historic and modern civil structures in
Italy. Struct. Monit. Maint. 2016, 3, 71–90. https://doi.org/10.12989/smm.2016.3.1.071.
38. Azzaro, R.; Barbano, M.S.; Moroni, A.; Mucciarelli, M.; Stucchi, M. The seismic history of Catania. J. Seismol. 1999, 3, 235–252.
39. Azzaro, R.; Barbano, M.S. Analysis of seismicity of Southeastern Sicily: Proposal of a tectonic interpretation. Ann. Geophys. 2000,
43, 171–188.
40. Patanè, D.; Malfitana, D.; Mazzaglia, A. Dalla conoscenza all’azione. Il progetto PON EWAS: Un sistema di allerta precoce per
la salvaguardia del patrimonio culturale. In Monitoraggio e Manutenzione Delle Aree Archeologiche Cambiamenti Climatici, Dissesto
Idrogeologico, Degrado Chimico-Ambientale, AA.VV. Atti del Convegno Internazionale di Studi, Roma, Curia Iulia, 20–21 Marzo 2019,
Collana Bibliotheca Archaeologica; L’ERMA di BRETSCHNEIDER: Roma, Italy, 2020; Volume 65, pp. 187–197.
41. Fertitta, G.; Costanza, A.; D’anna, G.; Patanè, D. The Earth Lab 5s (ETL3D/5s) seismic sensor. Design and test. Ann. Geophys.
2020, 63, 2. https://doi.org/10.4401/ag-7857.
42. Ribeiro, R.R.; Lameiras, R.M. Evaluation of low-cost MEMS accelerometers for SHM: Frequency and damping identification of
civil structures. Ibero-Latin American congress on computational methods in engineering. Lat. Am. J. Solids Struct. 2019, 16, 7.
https://doi.org/10.1590/1679-78255308.
43. CEN European Committee for Standardization. EUROCODE 8: Design of Structures for Earthquake Resistance—Part 1: General
Rules, Seismic Action and Rules for Buildings; CEN European Committee for Standardization: Bruxelles, Belgium, 2003.
44. Russo, E.; Felicetta, C.; D’Amico, M.; Sgobba, S.; Lanzano, G.; Mascandola, C.; Pacor, F.; Luzi, L. Italian Accelerometric Archive
v3.2—Istituto Nazionale di Geofisica e Vulcanologia, Dipartimento della Protezione Civile Nazionale; CEN: Bruxelles, Belgium, 2022;
https://doi.org/10.13127/itaca.3.2.
45. Faenza, L.; Michelini, A. Regression analysis of MCS intensity and ground motion parameters in Italy and its application in
ShakeMap. Geophys. J. Int. 2010, 180, 1138–1152.
46. Faenza, L.; Michelini, A. Regression analysis of MCS intensity and ground motion spectral accelerations (SAs) in Italy. Geophys.
J. Int. 2011, 186, 1415–1439.
47. Locati, M.; Camassi, R.; Rovida, A.; Ercolani, E.; Bernardini, F.; Castelli, V.; Caracciolo, C.H.; Tertulliani, A.; Rossi, A.; Azzaro,
R.; et al. Database Macrosismico Italiano (DBMI15); versione 4.0; Istituto Nazionale di Geofisica e Vulcanologia (INGV): Rome,
Italy, 2022. https://doi.org/10.13127/DBMI/DBMI15.4.
48. Magli, A.; Branca, S.; Speranza, F.; Risica, G.; Siravo, G.; Giordano, G. Paleomagnetic dating of prehistoric lava flows from the
urban district of Catania (Etna volcano, Italy). GSA Bull. 2022, 134, 616–662.
49. Sivori, D.; Cattari, S.; Lepidi, M. A methodological framework to relate the earthquake-induced frequency reduction to
structural damage in masonry buildings. Bull. Earthq. Eng. 2022, 1–36. https://doi.org/10.1007/s10518-022-01345-8.
50. Kouris, L.A.S.; Penna, A.; Magenes, G. Dynamic modification and damage propagation of a two-storey full-scale masonry
building. Adv. Civ. Eng. 2019, 2019, 2396452. https://doi.org/10.1155/2019/2396452.
Accelerometers. Seismol. Res. Lett. 2014, 85, 147–158.
2. Fu, J.; Li, Z.; Meng, H.; Wang, J.; Shan, X. Performance Evaluation of Low-Cost Seismic Sensors for Dense Earthquake Early
Warning: 2018–2019 Field Testing in Southwest China. Sensors 2019, 19, 1999.
3. Rovithis, E.; Makra, K.; Savvaidis, A.; Kirtas, E. The accelerometric network of the Indes-Musa project in the Kalochori area:
Configuration, documentation and preliminary data interpretation, Proceedings of the 14th International Congress,
Thessaloniki May 2016. Bull. Geolog. Soc. Greece 2016, 50, 1110–1119.
4. Pierleoni, P.; Marzorati, S.; Ladina, C.; Raggiunto, S.; Belli, A.; Palma, L.; Cattaneo, M.; Valenti, S. Performance Evaluation of a
Low-Cost Sensing Unit for Seismic Applications: Field Testing During Seismic Events of 2016–2017 in Central Italy. IEEE Sens.
J. 2018, 18, 6644–6658.
5. Papanikolaou, V.K.; Karakostas, C.Z.; Theodoulidis, N.P. A Low-Cost Instrumentation System for Seismic Hazard Assessment
in Urban Areas. Sensors 2021, 21, 3618. https://doi.org/10.3390/s21113618.
6. Esposito, M.; Palma, L.; Belli, A.; Sabbatini, L.; Pierleoni, P. Recent Advances in Internet of Things Solutions for Early Warning
Systems: A Review. Sensors 2022, 22, 2124. https://doi.org/10.3390/s22062124.
7. Federici, F.; Graziosi, F.; Faccio, M.; Gattulli, V.; Lepidi, M.; Potenza, F. An integrated approach to the design of Wireless Sensor
Networks for structural health monitoring. Int. J. Distrib. Sens. Netw. 2012, 8, 594842. https://doi.org/10.1155/2012/594842.
8. Lin, J.F.; Li, X.Y.; Wang, J.; Wang, L.X.; Hu, X.X.; Liu, J.X. Study of Building Safety Monitoring by Using Cost-Effective MEMS
Accelerometers for Rapid After-Earthquake Assessment with Missing Data. Sensors 2021, 21, 7327.
https://doi.org/10.3390/s21217327.
9. Francisco, J.; Pallarés, M.B.; Bartoli, G.; Pallarés, L. Structural health monitoring (SHM) and Nondestructive testing (NDT) of
slender masonry structures: A practical review. Constr. Build. Mater. 2021, 297, 123768.
https://doi.org/10.1016/j.conbuildmat.2021.123768.
10. Liang, Q.; Tani, A.; Yamabe, Y. Fundamental Tests on a Structural Health Monitoring System for Building Structures Using a
Single-board Microcontroller. J. Asian Arch. Build. Eng. 2015, 14, 663–670.
11. Picozzi, M.; Emolo, A.; Martino, C.; Zollo, A.; Miranda, N.; Verderame, G.; Boxberger, T. and the REAKT Working, Group
Earthquake Early Warning System for Schools: A Feasibility Study in Southern Italy. Seism. Res. Lett. 2015, 86, 2A.
12. Dolce, M.; Nicoletti, M.; De Santis, A.; Marchesini, S.; Spina, D.; Talanas, F. Osservatorio sismico delle strutture: The Italian
structural seismic monitoring network. Bull. Earth. Eng. 2017, 15, 621–641.
13. Groos, J.C.; Ritter, J.R.R. Time domain classification and quantification of seismic noise in an urban environment. Geophys. J. Int.
2009, 179, 1213–1231. https://doi.org/10.1111/j.1365-246x.2009.04343.x.
14. Diaz, J.; Schimmel, M.; Ruiz, M.; Carbonell, R. Seismometers Within Cities: A Tool to Connect Earth Sciences and Society. Front.
Earth Sci. 2020, 8, 9. https://doi.org/10.3389/feart.2020.00009.
15. Vassallo, M.; De Matteis, R.; Bobbio, A.; Di Giulio, G.; Adinolfi, G.M.; Cantore, L.; Cogliano, R.; Fodarella, A.; Maresca, R.;
Pucillo, S.; et al. Seismic noise cross-correlation in the urban area of Benevento city (Southern Italy). Geophys. J. Int. 2019, 217,
1524–1542. https://doi.org/10.1093/gji/ggz101.
16. Olivito, R.S.; Porzio, S.; Scuro, C.; Carnì, D.L.; Lamonaca, F. Inventory and monitoring of historical cultural heritage buildings
at the territorial scale. A preliminary study of SHM based on CARTIS approach. Acta IMEKO 2021, 10, 9.
17. Azzara, R.M.; Girardi, M.; Iafolla, V.; Padovani, C.; Pellegrini, D. Long-Term Dynamic Monitoring of Medieval Masonry
Towers. Front. Built Environ. 2020, 6, 9. https://doi.org/10.3389/fbuil.2020.00009.
18. Chatzopoulos, G.; Papadopoulos, I.; Vallianatos, F.; Makris, J.P.; Kouli, M. Strong Ground Motion Sensor Network for Civil
Protection Rapid Decision Support Systems. Sensors 2021, 21, 2833. https://doi.org/10.3390/s21082833.
19. De Luca, G.; Marcucci, S.; Milana, G.; Sano, T. Evidence of Low-Frequency Amplification in the City of L’Aquila, Central Italy,
through a Multidisciplinary Approach Including Strong- and WeakMotion Data, Ambient Noise, and Numerical Modeling.
Bull. Seismol. Soc. Am. 2005, 95, 1469–1481. https://doi.org/10.1785/0120030253.
20. Bindi, D.; Pacor, F.; Luzi, L.; Massa, M.; Ameri, G. The Mw 6.3, 2009 L’Aquila earthquake: Source, path and site effects from
spectral analysis of strong motion data. Geophys. J. Int. 2009, 179, 1573–1579
21. Sextos, A.; De Risi, R.; Pagliaroli, A.; Foti, F.; Passeri, F.; Ausilio, E.; Cairo, R.; Capatti, M.C.; Chiabrando, F.; Chiaradonna, A.;
et al. Local Site Effects and Incremental Damage of Buildings during the 2016 Central Italy Earthquake Sequence. Earthq. Spectra
2019, 34, 1639–1669.
22. Di Giulio, G.; Azzara, R.M.; Cultrera, G.; Giammarinaro, M.S.; Vallone, P.; Rovelli, A. Effect of Local Geology on Ground Motion
in the City of Palermo, Italy, as Inferred from Aftershocks of the 6 September 2002 Mw 5.9 Earthquake. Bull. Seismol. Soc. Am.
2005, 95, 2328–2341. https://doi.org/10.1785/0120040219.
23. Nof, R.N.; Chung, A.I.; Rademacher, H.; Dengler, L.; Allen, R.M. MEMS Accelerometer Mini-Array (MAMA): A Low-Cost
Implementation for Earthquake Early Warning Enhancement. Earthq. Spectra 2019, 35, 21–38.
24. Chung, A.I.; Cochran, E.S.; Kaiser, A.E.; Christensen, C.M.; Yildirim, B.; Lawrence, J.F. Improved rapid magnitude estimation
for a community-based, low-cost MEMS accelerometer network. Bull. Seismol. Soc. Am. 2015, 105, 1314–1323.
25. Clayton, R.W.; Heaton, T.; Kohler, M.; Chandy, M.; Guy, R.; Bunn, J. Community seismic network: A dense array to sense
earthquake strong motion. Seismol. Res. Lett. 2015, 86, 1354–1363.
26. Horiuchi, S.; Horiuchi, Y.; Yamamoto, S.; Nakamura, H.; Wu, C.; Rydelek, P.A.; Kachi, M. Home seismometer for earthquake
early warning. Geophys. Res. Lett. 2009, 36. https://doi.org/10.1029/2008GL036572.
27. Zheng, H.; Shi, G.; Zeng, T.; Li, B. Wireless earthquake alarm design based on MEMS accelerometer. In Proceedings of the 2011
International Conference on Consumer Electronics, Communications and Networks (CECNet), Xianning, China, 16–19 April
2011; pp. 5481–5484.
28. Peng, C.; Peng, J.; Chen, Q.; Ma, Q.; Yang, J. Performance Evaluation of a Dense MEMS-Based Seismic Sensor Array Deployed
in the Sichuan-Yunnan Border Region for Earthquake Early Warning. Micromachines 2019, 10, 735.
https://doi.org/10.3390/mi10110735.
29. Yang, B.M.; Mittal, H.; Wu, Y.-M. Real-Time Production of PGA, PGV, Intensity, and Sa Shakemaps Using Dense MEMS-Based
Sensors in Taiwan. Sensors 2021, 21, 943. https://doi.org/10.3390/s21030943.
30. Lawrence, J.F.; Cochran, E.S.; Chung, A.; Kaiser, A.; Christensen, C.M.; Allen, R.; Baker, J.W.; Fry, B.; Heaton, T.; Kilb, D.; et al.
Rapid Earthquake Characterization Using MEMS Accelerometers and Volunteer Hosts Following the M 7.2 Darfield, New
Zealand, Earthquake. Bull. Seismol. Soc. Am. 2014, 104, 184–192. https://doi.org/10.1785/0120120196.
31. Tanırcan, G.; Hakan Alçık, H.; Beyen, K. Reliability of MEMS accelerometers for instrumental intensity mapping of earthquakes.
Ann. Geophys. 2017, 60 (Suppl. 6), SE673. https://doi.org/10.4401/ag-7501.
32. Holland, A. Earthquake data recorded by the MEMS accelerometer: Field testing in Idaho. Seismol. Res. Lett. 2003, 74, 20–26.
33. Pozzi, M.; Zonta, D.; Trapani, D.; Athanasopoulos, N.; Amditis, A.; Bimpas, M.; Garetsos, A.; Stratakos, Y.; Ulieru, D. MEMSbased
sensors for post-earthquake damage assessment. J. Phys. Conf. Ser. 2011, 305, 012100.
34. Kim, Y.; Kang, T.S.; Rhie, J. Development and Application of a Real-Time Warning System Based on a MEMS Seismic Network
and Response Procedure for the Day of the National College Entrance Examination in South Korea. Seismol. Res. Lett. 2017, 88,
1322–1326.
35. Peng, C.; Chen, Y.; Chen, Q.; Yang, J.; Wang, H.; Zhu, X.; Xu, Z.; Zheng, Y. A new type of tri-axial accelerometers with high
dynamic range MEMS for earthquake early warning. Comput. Geosci. 2017, 100, 179–187.
36. Lynch, J.P.; Loh, K.J. A Summary Review of Wireless Sensors and Sensor Networks for Structural Health Monitoring. Shock Vib.
Dig. 2006, 38, 91–128. https://doi.org/10.1177/0583102406061499.
37. Gattulli, G.; Marco Lepidi, M.; Potenza, F. Dynamic testing and health monitoring of historic and modern civil structures in
Italy. Struct. Monit. Maint. 2016, 3, 71–90. https://doi.org/10.12989/smm.2016.3.1.071.
38. Azzaro, R.; Barbano, M.S.; Moroni, A.; Mucciarelli, M.; Stucchi, M. The seismic history of Catania. J. Seismol. 1999, 3, 235–252.
39. Azzaro, R.; Barbano, M.S. Analysis of seismicity of Southeastern Sicily: Proposal of a tectonic interpretation. Ann. Geophys. 2000,
43, 171–188.
40. Patanè, D.; Malfitana, D.; Mazzaglia, A. Dalla conoscenza all’azione. Il progetto PON EWAS: Un sistema di allerta precoce per
la salvaguardia del patrimonio culturale. In Monitoraggio e Manutenzione Delle Aree Archeologiche Cambiamenti Climatici, Dissesto
Idrogeologico, Degrado Chimico-Ambientale, AA.VV. Atti del Convegno Internazionale di Studi, Roma, Curia Iulia, 20–21 Marzo 2019,
Collana Bibliotheca Archaeologica; L’ERMA di BRETSCHNEIDER: Roma, Italy, 2020; Volume 65, pp. 187–197.
41. Fertitta, G.; Costanza, A.; D’anna, G.; Patanè, D. The Earth Lab 5s (ETL3D/5s) seismic sensor. Design and test. Ann. Geophys.
2020, 63, 2. https://doi.org/10.4401/ag-7857.
42. Ribeiro, R.R.; Lameiras, R.M. Evaluation of low-cost MEMS accelerometers for SHM: Frequency and damping identification of
civil structures. Ibero-Latin American congress on computational methods in engineering. Lat. Am. J. Solids Struct. 2019, 16, 7.
https://doi.org/10.1590/1679-78255308.
43. CEN European Committee for Standardization. EUROCODE 8: Design of Structures for Earthquake Resistance—Part 1: General
Rules, Seismic Action and Rules for Buildings; CEN European Committee for Standardization: Bruxelles, Belgium, 2003.
44. Russo, E.; Felicetta, C.; D’Amico, M.; Sgobba, S.; Lanzano, G.; Mascandola, C.; Pacor, F.; Luzi, L. Italian Accelerometric Archive
v3.2—Istituto Nazionale di Geofisica e Vulcanologia, Dipartimento della Protezione Civile Nazionale; CEN: Bruxelles, Belgium, 2022;
https://doi.org/10.13127/itaca.3.2.
45. Faenza, L.; Michelini, A. Regression analysis of MCS intensity and ground motion parameters in Italy and its application in
ShakeMap. Geophys. J. Int. 2010, 180, 1138–1152.
46. Faenza, L.; Michelini, A. Regression analysis of MCS intensity and ground motion spectral accelerations (SAs) in Italy. Geophys.
J. Int. 2011, 186, 1415–1439.
47. Locati, M.; Camassi, R.; Rovida, A.; Ercolani, E.; Bernardini, F.; Castelli, V.; Caracciolo, C.H.; Tertulliani, A.; Rossi, A.; Azzaro,
R.; et al. Database Macrosismico Italiano (DBMI15); versione 4.0; Istituto Nazionale di Geofisica e Vulcanologia (INGV): Rome,
Italy, 2022. https://doi.org/10.13127/DBMI/DBMI15.4.
48. Magli, A.; Branca, S.; Speranza, F.; Risica, G.; Siravo, G.; Giordano, G. Paleomagnetic dating of prehistoric lava flows from the
urban district of Catania (Etna volcano, Italy). GSA Bull. 2022, 134, 616–662.
49. Sivori, D.; Cattari, S.; Lepidi, M. A methodological framework to relate the earthquake-induced frequency reduction to
structural damage in masonry buildings. Bull. Earthq. Eng. 2022, 1–36. https://doi.org/10.1007/s10518-022-01345-8.
50. Kouris, L.A.S.; Penna, A.; Magenes, G. Dynamic modification and damage propagation of a two-storey full-scale masonry
building. Adv. Civ. Eng. 2019, 2019, 2396452. https://doi.org/10.1155/2019/2396452.
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