Comprehensive Evaluation Index System for Sustainable Development of Digital Museums: An Empirical Study Based on ACG–TSOBP Model and SDN–IoT Architectures

With the rapid digitalization of cultural heritage, evaluating the sustainability of digital museums remains a challenge. This study constructs a comprehensive evaluation index system encompassing economy, society, resources, services, and technology. To enhance evaluation accuracy and objectivity, an innovative ACG–TSOBP model is proposed, integrating an adaptive combined weighting approach with a BP neural network optimized by the Tuna Swarm Optimization algorithm. Furthermore, the study incorporates SDN–IoT architectures with edge and fog computing to optimize network performance, enhance data processing efficiency, and support intelligent resource allocation in digital museums. Empirical analysis of 43 digital museums in China demonstrates that the model outperforms traditional methods, achieving a mean absolute percentage error of 1.081% and a root mean square error of 0.0071433. The results reveal significant disparities among museums, highlighting the critical roles of digital resource development, technological applications, and social engagement in sustainability. The findings provide theoretical and practical guidance, advocating for digital resource-sharing platforms, blockchain-based copyright mechanisms, and AI-driven user experiences. This research offers a novel evaluation approach and strategic recommendations for advancing sustainable digital museum development.