A high-precision urban heat-simulation model built to predict heat-related risks in dense metropolitan environments. Using customized CNN & LSTM architectures, integrated meteorological data, and a fully automated development pipeline, the solution achieved >0.99 R² accuracy with only six bugs across the entire delivery. A scalable AI approach designed for smart-city applications, resilience planning, and public safety management.
