Infrastructure is seriously threatened by
earthquakes, thus sophisticated resilience
measures are required. This study investigates
design optimization for seismic-resistant
buildings and predictive modeling driven by
AI. The research improves structural
performance evaluation and failure prediction
by combining deep learning, finite element
analysis, and real-time sensor data. Artificial
intelligence (AI)-powered simulations
minimize seismic effect by optimizing damping
systems, reinforcement patterns, and material
choices. Through the facilitation of proactive
decision-making and cost-effective robust
designs, the proposed framework seeks to
transform earthquake engineering.