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Charilaos A. Maniatakis¹,²,³, Athanasia E. Zacharenaki¹,⁴, Christos Moraitis² and Georgios E. Stavroulakis⁵,²¹School of Civil Engineering, National Technical University of Athens, Greece²International Hellenic University & Fire Brigade of Greece, Interdisciplinary Postgraduate Program “Analysis and Management of Anthropogenic and Natural Disasters”³Municipal Water Supply and Sewerage Company, Hersonissos Municipality, Crete, Greece⁴Municipal Water Supply and Sewerage Company of Minoa Pediada, Crete,Greece⁵School of Production Engineering and Management, Technical University of Crete, Crete, GreecePart of the book: The Challenges of Disaster Planning, Management, and ResilienceAbstractCatastrophic earthquakes have always been a major threat affecting the world’s population and economy with the most disastrous consequences in urban areas. In order to tackle this phenomenon, scientists from the mid-19th century showed interest in finding ways to inform about a forthcoming earthquake event but only after 1960 did it find application with the evolution of technology. As a result of this effort came the development of the Earthquake Early Warning System (EEWS) as a new method for seismic risk mitigation. This system has evolved to detect earthquake parameters such as hypocenter, magnitude and time while disseminating alarm signals to the sites affected by the earthquake for societies to take the necessary action. Its function is based on the fact that information travels faster than seismic waves and that S-waves travel faster than P-waves in an earthquake signal. Nowadays, EEWS are operational in several countries including Mexico and Japan, while action has been taken to be implemented in more countries. EEWS are becoming a significant tool for the reduction of seismic risk, despite its current restrictions, and to help prevent loss of human lives and resources, reducing this way the economic loss. In this paper EEWS are discussed and their application in Greece is presented to give an insight to state-of-the-art methodology. Design concepts, cost of operation and reliability limitations are examined while a possible improvement of their efficiency with the use of artificial intelligence and neural networks is briefly discussed.Keywords: Earthquake Early Warning Systems (EEWS), seismic waves, neural networks, state-of-the-artReferencesAllen RM, Melgar D. (2019). Earthquake early warning: Advances, scientific challenges, and societal needs.Annual Review of Earth and Planetary Sciences, 47; 2019.Ammon CJ, Velasco AA, Lay T, Wallace TC. (2021). Earthquake prediction, forecasting, & early warning.Foundations of Modern Global Seismology; 2021.Behr Y, Clinton JF, Cauzzi C, Hauksson E, Jónsdóttir K, Marius CG, Sokos E. (2016). The Virtual Seismologistin SeisComP3: A new implementation strategy for earthquake early warning algorithms. SeismologicalResearch Letters; 2016.Bose M, Wenzel F, Erdik M. (2008) PreSEIS:a neural network-based approach to earthquake early warningfor finite faults. Bull. Seismol Soc Am; 2008.Bracale M, Colombelli S, Elia L, Karakostas V, & Zollo A. (2021). Design, implementation and testing of anetwork-based Earthquake Early Warning System in Greece. Frontiers in Earth Science, 880.Cremen G, Galasso C. (2020). Earthquake early warning: Recent advances and perspectives. Earth-ScienceReviews; 2020.Cua G, Fischer M, Heaton T,Wiemer S. (2009). Real-time performance of the Virtual Seismologist earthquakeearly warning algorithm in southern California. Seismological Research Letters; 2009.Cua G, Heaton T. (2007). The Virtual Seismologist (VS) method: A Bayesian approach to earthquake earlywarning. In: Earthquake Early Warning Systems. Springer, Berlin, Heidelberg.Cua GB. (2005). Creating the Virtual Seismologist: Developments in Ground Motion Characterization andSeismic Early Warning (Doctoral dissertation, California Institute of Technology); 2005.Gasparini P, Manfredi G, Zschau J. (2007). Earthquake Early Warning Systems. Berlin: Springer; 2007.Hanka W, Saul J, Weber B, Becker J, Harjadi P, Rudloff A, Clinton J. (2010). Real-time earthquake monitoringfor tsunami warning in the Indian Ocean and beyond. Natural Hazards & Earth System Sciences; 2010.Iaccarino AG, Gueguen P, Picozzi M, Ghimire S. (2021). Earthquake Early Warning System for StructuralDrift Prediction Using Machine Learning and Linear Regressors. Front. Earth Sci; 2021.Kamigaichi O, Saito M, Doi K, Matsumori T, Tsukada SY, Takeda K, Watanabe Y. (2009). Earthquake earlywarning in Japan: Warning the general public and future prospects. Seismological Research Letters; 2009.Kanamori H. (2005) Real-time seismology and earthquake damage limitation, Annual Review of Earth andPlanetary sciences; 2005.Kong Q, Allen RM, Schreier L and Kwon Y-W(2016). MyShake: A smartphone seismic network forearthquake early warning and beyond, Sci. Adv. 2, no. 2; 2016.Kong Q, Inbal A, Allen RM, Lv Q, Puder A. (2019) Machine Learning Aspects of the MyShake GlobalSmartphone Seismic Network; 2019.Maniatakis, CA. (2015). Response of Structures under Near-Fault Seismic Excitations. PhD Dissertation,School of Civil Engineering, National Technical University of Athens; 2015.Maniatakis CA, & Spyrakos CC. (2012). A new methodology to determine elastic displacement spectra in thenear-fault region. Soil Dynamics and Earthquake Engineering, 35, 41-58.Maniatakis CA, Taflampas IM, & Spyrakos CC. (2008). Identification of near-fault earthquake recordcharacteristics. In The 14th World Conference on Earthquake Engineering; 2008.Meier MA, Kodera Y, Böse M, Chung A, Hoshiba M, Cochran E, Heaton T. (2020). How Often CanEarthquake Early Warning Systems Alert Sites With High‐Intensity Ground Motion Journal ofGeophysical Research: Solid Earth; 2020.Melis NS, Charalampakis M. (2014). The hellenic national tsunami warning centre (HL-NTWC): Recentupdates and future developments, Geophysical Research Abstracts; 2014.Minson SE, Baltay AS, Cochran ES, Hanks TC, Page MT, McBride SK, Meier MA. (2019). The limits ofearthquake early warning accuracy and best alerting strategy. Scientific Reports; 2019.Minson SE, Meier MA, Baltay AS, Hanks TC, Cochran ES. (2018). The limits of earthquake early warning:Timeliness of ground motion estimates. Science Advances; 2018.Moraitis C. (2021). Earthquake Early Warning System: State of the practice, MSc Thesis. InternationalHellenic University & Fire Brigade of Greece Interdisciplinary Postgraduate Program “Analysis andManagement of Anthropogenic and Natural Disasters”; 2021.Mukherjee T, Singh C, Biswas PK. (2021). A Novel Approach for Earthquake Early Warning System Designusing Deep Learning Techniques; 2021.Muradova AD, Stavroulakis GE. (2021). Physics-informed neural networks for elastic plate problems withbending and Winkler-type contact effects. Journal of the Serbian Society for Computational Mechanics; 2021.Nakamura Y, Saita J. (2007). UrEDAS, the earthquake warning system: Today and tomorrow. In EarthquakeEarly Warning Systems, Springer, Berlin, Heidelberg; 2007.Papadopoulos G, Argyris I, Aggelou S, Karastathis V. (2014). REWSET: A Prototype Seismic and TsunamiEarly Warning System in Rhodes Island, Greece. EGUGA; 2014.Papadopoulos G, Tselentis GA, & Charalampakis M. (2016). The Hellenic national tsunami warning center:Research, operational and training activities. Bulletin of the Geological Society of Greece, 50(2), 1100-1109; 2016.Pitilakis, K, Roumelioti Z, Raptakis D, Manakou M, Liakakis K, Anastasiadis A, & Pitilakis D. (2013). TheEUROSEISTEST strong‐motion database and web portal. Seismological Research Letters, 84(5), 796-804; 2013.Protopapadakis E, Schauer M, Pierri E, Doulamis AD, Stavroulakis GE, Böhrnsen JU, Langer S. (2016). Agenetically optimized neural classifier applied to numerical pile integrity tests considering concrete piles.Computers & Structures; 2016.Rafiei MH, Adeli H. (2017). NEEWS:A novel earthquake early warning model using neural dynamicclassification and neural dynamic optimization. Soil Dynamics and Earthquake Engineering; 2017.Raissi M, Perdikaris P, Karniadakis GE. (2019). Physics-informed neural networks: A deep learning frameworkfor solving forward and inverse problems involving nonlinear partial differential equations. Journal ofComputational Physics; 2019.Roumelioti Z, Karapetrou S, Manakou M, Pitilakis K, Raptakis D, Bindi D, Boxberger T. (2015). Thecontribution of EUROSEISTEST and building monitoring arrays in earthquake early warning and rapiddamage assessment in Thessaloniki. Proceedings of 6th ICEGE, 14.Satriano C, Wu YM, Zollo A, Kanamori H. (2011). Earthquake early warning: Concepts, methods and physicalgrounds. Soil Dynamics and Earthquake Engineering; 2011.Sokos E, Zahradník J, Gallovič F, Serpetsidaki A, Plicka V, Kiratzi A, (2016). Asperity break after 12 years:The Mw6.4 2015 Lefkada (Greece) earthquake. Geophys. Res. Lett. 42; 2016.Spyrakos, CC, Maniatakis CA, & Taflambas J. (2008). Evaluation of near-source seismic records based ondamage potential parameters: Case study: Greece. Soil Dynamics and Earthquake Engineering, 28(9),738-753.Stavroulakis GE. (2001). Inverse and Crack Identification Problems in Engineering Mechanics. Springer;2001.(2004). Neural network assisted crack and flaw identification in transient dynamics. Journal of Theoretical andApplied Mechanics; 2004.Strauss JA, Allen RM. (2016). Benefits and costs of earthquake early warning. Seismological Research Letters;2016.Tsapanos TM, Burton PW, (1991). Seismic hazard evaluation for specific seismic regions of the world.Tectonophysics; 1991.Velazquez O, Pescaroli G, Cremen G, Galasso C. (2020). A Review of the Technical and Socio-OrganizationalComponents of Earthquake Early Warning Systems.Frontiers in Earth Science; 2020.Wald DJ. (2020). Practical limitations of earthquake early warning. Earthquake Spectra; 2020.Xu Y, Burton PW, Tselentis GA. (2003). Regional Seismic Hazard for Revithoussa, Greece: An EarthquakeEarly Warning Shield and Selection of Alert Signals; 2003.Zacharenaki A, Fragiadakis M, Papadrakakis M. (2013) Reliability-based optimum seismic design of structuresusing simplified performance estimation methods. Engineering Structures; 2013.Zollo A, Colombelli S, Elia L, Emolo A, Festa G, Iannaccone G,Gasparini P. (2014). An integrated regionaland on-site Earthquake Early Warning System for Southern Italy: Concepts, methodologies andperformances. In Early Warning for Geological Disasters Springer, Berlin, Heidelberg; 2014.
