A Decision-Support Framework for Village Cultural Heritage Revitalization: Integrating Digital Twins, Optimization, and Participatory Planning Models

Abstract

In many local settings, cultural heritage frequently suffers from minimal civic engagement, fragmented contextual understanding, and progressive deterioration of tangible heritage elements. Conventional preservation frameworks tend to neglect both the potential of digital transformation and the shifting expectations of resident communities. Addressing this gap, the present project proposes a comprehensive preservation strategy that incorporates Digital Twins (DT) with a participatory Decision Support System (DSS) to support sustainable revitalisation of heritage sites in rural areas. To construct the DT, structural, spatial, and environmental information is captured through drone surveys and embedded sensor networks. The acquired datasets undergo pre-processing through z-score standardisation and median filtering to suppress measurement noise. Principal Component Analysis (PCA) is subsequently employed to derive features that reflect the historical, artistic, and socio-cultural significance of the sites. Furthermore, an enhanced optimisation methodology based on a Convolutional–Long Short-Term Memory Network (CLSMNet) is introduced to model dynamic site conditions and project future patterns of material decay and conservation requirements. Within this framework, DTasDO-CLSMNet integrates the temporal-spatial analytical capability of CLSMNet with DTasDO parameter adjustment, enabling continuous fine-tuning for predictive accuracy and decision reliability. Empirical findings indicate increased simulation precision in forecasting heritage degradation behaviour (96.87%), as well as strong sensitivity (95.65%), specificity (96.41%), and F1 performance (95.22%). Additionally, participatory engagement assessments reveal a high stakeholder satisfaction level (95.03%) with the joint simulation and decision-making processes. Overall, the proposed DSS-based digital model supports not only preservation but also adaptive and community-led reuse, delivering an intelligent, transparent, and collaborative platform through which residents and policymakers can jointly manage, sustain, and revitalise cultural heritage assets.