An Academic Resource Development Experience Through Service Learning Supported by Artificial Intelligence Tools for Identifying Earthquake Damage on Buildings

This study presents an open educational experience, a Service Learning approach, that connects university training with efforts to improve the resilience of masonry houses in disaster-prone regions and hence foster safer construction practices. Drawing on the wealth of digital resources available online, the project’s initial academic deliverable is a retrofitting guide that compiles practical, cost-effective and sustainable reinforcement strategies for masonry dwellings. This manual is a valuable educational resource for engineering students and offers practical recommendations for strengthening adobe masonry buildings for local communities. In parallel, this collaborative teaching and learning practice has resulted in an Artificial Intelligence pilot tool that can rapidly identify types of earthquake-induced damage to buildings from photographic data. This tool could become helpful to support decision-making and the allocation of resources in disaster management scenarios.