{"id":42639,"date":"2025-11-03T11:46:27","date_gmt":"2025-11-03T10:46:27","guid":{"rendered":"https:\/\/www.eucentre.it\/?p=42639"},"modified":"2025-11-03T11:46:27","modified_gmt":"2025-11-03T10:46:27","slug":"artificial-intelligence-and-earthquake-engineering-a-new-frontier-for-safety","status":"publish","type":"post","link":"https:\/\/www.eucentre.it\/en\/artificial-intelligence-and-earthquake-engineering-a-new-frontier-for-safety\/","title":{"rendered":"Artificial Intelligence and Earthquake Engineering: A New Frontier for Safety"},"content":{"rendered":"
\"immagine<\/div><\/div>
<\/span><\/div>

In recent years, artificial intelligence (AI) has become a powerful tool in various sectors. In earthquake engineering, too, intelligent algorithms and data analysis are revolutionising the way we study earthquakes and construct safer buildings. According to the United Nations, the UNDRR 2023 report<\/a>\u00a0explains how the use of AI and big data improves natural disaster prevention and response, illustrating practical examples from around the world.<\/p>\n

Structural design<\/strong><\/h2>\n

AI also plays a role in the design of buildings and infrastructure. The study published in Engineering Structures by Zheng<\/a>\u00a0and colleagues shows through simulations how AI can quickly test many construction solutions and find the safest one against tremors. Also worth mentioning is Xinzheng Lu’s study, entitled\u00a0From \u201cSimulation-driven\u201d Urban Disaster Mitigation to \u201cGenerative AI-powered\u201d Seismic Design<\/em>,\u00a0<\/strong>presented in a keynote speech at WCEE2024<\/a>.<\/strong>\u00a0In his plenary session, Lu illustrated the transition from \u201csimulation-driven\u201d models to seismic design based on generative artificial intelligence, capable of creating optimised structures in seconds. His approach combines engineering data and generative models to make urban design faster, more resilient and more accurate.<\/p>\n

Structure monitoring<\/strong><\/h2>\n

From a monitoring perspective, the paper\u00a0A real-time structural seismic response prediction<\/em><\/a>\u00a0explains how sensors and AI, by analysing data in real time, can detect even small changes in the structural health of buildings, allowing for rapid intervention in the event of problems. Prof. O’Reilly’s\u00a0SONATA<\/em><\/a>\u00a0project is also certainly important, introducing advanced sensors and artificial intelligence to assess the seismic safety of buildings in real time, allowing risks to be quickly identified and managed, including through data and images collected by citizens and drones. This innovation aims to create smart buildings and increase urban resilience, improving post-earthquake decision-making and reducing losses and downtime.<\/p>\n

Emergency management<\/strong><\/h2>\n

After an earthquake, AI helps to quickly assess damage using images taken by satellites and drones. The European programme\u00a0Copernicus EMS of the ESA<\/a>\u00a0provides practical examples of how AI-generated maps are now used by civil protection and operators to understand where to intervene first and best.\u00a0A study by Stanford University<\/a>\u00a0shows how artificial intelligence systems were able to quickly identify areas affected by a sequence of earthquakes, providing concrete help in both damage assessment and relief planning. This is where\u00a0IDEA (Image Database for Earthquake Damage Annotation)<\/em><\/a>\u00a0comes in, a dataset developed by researchers at the Eucentre Foundation that collects over 5,400 real images of structural and non-structural damage, acquired during post-earthquake inspections and annotated by structural engineers. Available in open access on\u00a0Zenodo<\/a>, IDEA is a reference resource for training and validating deep learning algorithms dedicated to automatic damage recognition. Thanks to a system of standardised annotations and a detailed structural ontology, the database improves the reliability of automatic analysis models and supports monitoring, post-event inspection and emergency management activities.<\/p>\n

Future opportunities and challenges<\/strong><\/h2>\n

The growth of AI in earthquake engineering generates enthusiasm, but also new responsibilities. For example, the international document Responsible AI in structural engineering<\/em><\/a>\u00a0clearly explains why it is important for data and algorithms to remain transparent and easily verifiable, preventing automation from taking the place of expert engineers’ judgement. The\u00a0OECD Principles for AI 2024<\/a>\u00a0document (designed specifically for citizens) provides \u201cethical\u201d rules for the responsible development and use of artificial intelligence.<\/p>\n

A valuable ally<\/strong><\/h2>\n

Artificial intelligence is not a magic wand, but a powerful tool that, if well managed, can make us safer and better prepared for earthquakes. New technologies, as also mentioned in the\u00a0Special Report 2025 UNDRR<\/a>, are already enabling cities and communities around the world to respond and rebuild faster, reducing risks and saving lives. However, their full potential can only be realised if they are based on solid earthquake engineering foundations: it is scientific and technical knowledge of structural behaviour that provides the essential foundation for artificial intelligence tools to be truly effective and reliable in supporting seismic risk prevention and management.<\/p>\n<\/div><\/div>

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