Work

A hybrid AI-IoT framework for predictive conservation of tropical heritage façades: empirical validation from a multi-site study in Indonesia

Year: 2026

Type: article

Abstract: Predictive conservation for tropical built heritage is hindered by the persistent separation of continuous environmental sensing from computational deterioration diagnostics. We address this gap through a fourteen-month hybrid AI-IoT deployment across three heritage sites in Semarang, Indonesia (Lawang Sewu, Pasar Johar, and Tawang Railway Station), integrating unsupervised HSV-space hierarchical clustering with Random Forest classification and a derived Humidity Stress Factor (HSF). The framework was evaluated using 48,686 expert-labelled pixels, achieving a macro-F1 of 0.87 (95% CI: 0.85–0.89) and pixel accuracy of 91.2% (95% CI: 89.4%–93.0%), with inclusion of the HSF producing a 9.2-percentage-point increase in macro-F1 ( p < 0.001). Cumulative exposure to RH > 85% showed a strong association with deterioration (Spearman’s ρ = 0.82, 95% CI: 0.71–0.89, p < 0.001), while leave-one-site-out cross-validation yielded F1 scores of 0.79–0.82 (95% CI: 0.76–0.84), providing evidence of spatial transferability within the study region. Retrospective testing detected 79% of impending high-risk events and yielded conditional technical lead-time estimates of 4.8, 9.2, and 16.7 h for the 6-, 12-, and 24-hour horizons, respectively (expected: 3.8, 7.3, and 13.2 h after accounting for missed events). These lead-time estimates are technical and require operational validation before integration into management practice. The study advances prior work through three methodological refinements: direct integration of environmental sensing as a predictive input, prevention of data leakage through training-set-only clustering, and quantitative estimation of early-warning lead times from retrospective analysis. The resulting workflow provides a reproducible basis for risk-prioritised intervention planning. However, generalisation beyond the tropical coastal context requires independent cross-site validation and operational piloting. The findings therefore provide an empirical basis for further development of anticipatory conservation approaches for tropical heritage façades.

Source: Scientific Reports

DOI: 10.1038/s41598-026-74267-z

Authors: Hassan Gbran, Siti Rukayah, Atik Suprapti, Erni Setyowati, Iwan Setiawan

Institutions: Diponegoro University, Thamar University

Language: English

Topic: Building materials and conservation

Subfield: Earth-Surface Processes

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure, Climate action

Open Access status: gold

Estimated APC paid: $2,690