Ai-Powered Earthquake Resilience: A Comparative Analysis on Ai-Based Predictive Methods and Traditional Methods

<p><span lang="EN-US">Human settlements are seriously threatened by earthquakes, which result in enormous death tolls and financial losses. Land-use planning, early warning systems, retrofitting, and seismic-resistant building are some of the conventional earthquake resilience techniques that have been in widespread use for many years. But the emergence of artificial intelligence (AI) has opened up new avenues for disaster response, real-time monitoring, structural optimization, and predictive modeling. This study compares and contrasts AI-based earthquake resilience techniques with conventional methods, assessing their efficacy, benefits, drawbacks, and prospects. The goal of the project is to demonstrate how AI can strengthen and supplement traditional methods for a more effective earthquake mitigation plan. With disastrous effects on infrastructure, communities, and economies, earthquakes continue to rank among the most destructive natural disasters. Engineering-based solutions, legal frameworks, and community readiness initiatives have been the main focuses of traditional resilience methods. These strategies, however, are limited in their capacity to adjust to dynamic seismic activity since they frequently rely on empirical methods, static models, and historical data with real-time data processing, predictive analytics, and automated decision-making to improve readiness and reaction, AI-based earthquake resilience techniques have become a viable substitute. This study evaluates the advantages, disadvantages, and integration possibilities of AI-driven and conventional approaches.</span></p>