Carbon-Aware Digital-Twin Decision Support for Earthen Heritage: A Proof-of-Concept Case Study in Ushaiger, Saudi Arabia

Saudi Arabia’s expanding rehabilitation of historic places requires decision tools that connect monitored performance with conservation priorities and carbon consequences. This study develops a carbon-aware heritage decision twin for a traditional mud-brick dwelling in Ushaiger using indoor–outdoor monitoring from September 2025 to September 2026. Quality control yielded 10,757 unique paired records, including 10,755 observations on a 17,109-step half-hour grid. A hybrid piecewise cubic Hermite interpolating polynomial (PCHIP)–Extreme Gradient Boosting (XGBoost 3.4.1) reconstruction was tested with artificial gaps of 7–61 days; the mean indoor-temperature mean absolute error (MAE) increased from 0.93 to 1.35 °C across these gap lengths. XGBoost with SHapley Additive exPlanations (SHAP 0.52.0) associated indoor temperature with accumulated outdoor forcing, with 3 and 24 h means receiving the largest contributions in the revised model. Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimization at a fixed effective ventilation coupling reduced degree-hours above 35 °C by 2.62%; a joint coupling–persistence sensitivity produced 0.62–6.91% under the tested assumptions. Of 124 hot days, 45 entered the operational-ventilation class, 35 the combined or alternative reversible-measure classes, and 44 escalation review. Threshold and reconstruction-error tests showed that these counts remain scenario dependent. A screening life-cycle assessment (LCA) resulted in 9.7–29.1 kg carbon dioxide equivalent (CO2e) for assisted ventilation versus 242.6–727.7 kg CO2e for localized cooling within a fixed 588 h comparison window. The framework combines evidence confidence, explainable artificial intelligence (AI), passive-cooling opportunity, life-cycle carbon, and heritage compatibility to prioritize the least intrusive adequate action. The framework is presented as a single-building proof of concept; its decision architecture may support future multi-building applications, but its numerical thresholds and intervention rules require validation across additional Saudi heritage buildings, climatic contexts, and monitoring locations before portfolio-scale deployment.