AI ANALYSIS: NPJ HERITAGE SCIENCE
Virtual reconstruction design strategy for the Suoyang city site
This paper presents a virtual reconstruction design strategy for the Suoyang city site, a challenging earthen ruin along the Silk Road. It integrates digital technologies (drone, 3D laser scanning, VR, AR, AI) to create a 3D model. Key contributions include analyzing visitor-perceived value, extracting core restoration elements, and proposing a multimodal data-driven virtual reconstruction design process. The research provides a technical and theoretical reference for global city site reconstruction, bridging technical accuracy with culturally meaningful reinterpretation. AI-assisted modeling, historical data inference, and generative adversarial networks (GANs) are central to reconstructing damaged parts and optimizing designs based on visitor perceptions and historical authenticity. The integration of VR/AR enhances immersive visualization and emotional engagement.
Authors: Jing Liu, Yifan Yang, Ziyan Dan, Yutong Zhuo, Zengfeng Yan
Publication Date: 28 January 2026
Executive Impact & Strategic Value
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Strategic Digital Preservation
This research pioneers a robust virtual reconstruction design strategy for the Suoyang city site, a UNESCO tentative list earthen ruin. Leveraging advanced AI, VR, and AR technologies, it enables precise 3D digital modeling and restoration without physical intervention. This approach is critical for vulnerable rammed earth structures prone to irreversible degradation, offering a sustainable alternative to traditional methods.
Multimodal Data-Driven Reconstruction
A novel multimodal data-driven process integrates drone oblique photography, 3D laser scanning, historical documents, and visitor perception analysis. AI algorithms, including CNNs and GANs, are instrumental in classifying data, extracting architectural details, and generating historically consistent restoration models. This ensures both geometric accuracy and semantic richness in the digital heritage assets.
Enhanced Visitor Engagement & Value Perception
The study uniquely incorporates visitor 'value perception'—subjective evaluations of cultural, aesthetic, and emotional meaning—to inform restoration design. By linking visitor feedback with visual restoration decisions, the AR/VR implementations offer perceptually enriched, immersive visualizations that activate local cultural heritage through emotional resonance and firsthand experiences, bridging the gap between technical restoration and human interpretation.
Global Applicability & Future-Proofing
The proposed framework provides a scalable technical path and theoretical reference for virtual reconstruction of other historical city sites worldwide. It ensures long-term data preservation, continuous optimization, and addresses challenges of authenticity and transparency by clearly distinguishing between measured, inferred, and conjectural content through confidence coding and paradata.
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Improved Historical Matching
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Enhanced Structural Stability
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Increased Visual Consistency
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Chinese Characters Processed
Deep Analysis & Enterprise Applications
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This section delves into the core AI and digital technologies employed in the virtual reconstruction of the Suoyang city site. It covers the application of drone photography, 3D laser scanning, and advanced AI algorithms like PointNet++, CNNs, and GANs for data processing, feature extraction, and model generation. The discussion highlights how these technologies facilitate non-invasive restoration, ensure geometric accuracy, and integrate historical styles into digital models.
92.8%
CNN Model Accuracy
Multimodal Data-Driven Virtual Reconstruction Process
UAV & Laser Scan Data Acquisition
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Point Cloud Processing & Classification (AI)
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Historical Text & Image Analysis (AI)
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Visitor Perception Analysis
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AI-Assisted Restoration Modeling (GANs)
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VR/AR Immersive Visualization
| Feature | Traditional Methods | Digital Methods (AI/VR) |
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| Intervention |
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| Data Preservation |
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| Accuracy |
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| Reimagination |
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| Public Engagement |
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| Cost/Time |
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This section explores how visitor perceptions and emotional engagement influence the design strategy. It details the methodology for collecting and analyzing 'value perception' through interviews and text mining (KH Coder, SPSS). The discussion covers how these insights inform the prioritization of restoration elements, the emphasis of spatial features, and the overall immersive experience in VR/AR environments, ensuring the digital reconstruction is culturally meaningful and emotionally resonant for the public.
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Interviews Conducted
Visitor-Centric Design Integration
Structured Interviews & Text Mining
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Value Perception Analysis
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Extraction of Core Restoration Elements
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Prioritization of Features
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AR/VR Experience Design
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Emotional Resonance & Engagement
Suoyang City: Bridging Past & Present
The Suoyang city site, a pivotal hub on the ancient Silk Road, presented unique challenges for preservation due to its earthen construction. This research leveraged AI-driven virtual reconstruction to bring its history to life, moving beyond static ruins. By meticulously analyzing historical documents and integrating visitor perceptions, the project ensured the digital model wasn't just accurate, but also resonated deeply with cultural and emotional values. For instance, elements like 'vicissitudes' (symbolizing historical changes) directly influenced the design of weathered textures and lighting schemes in the VR experience, creating an evocative sense of historical passage. This approach sets a new standard for preserving and interpreting vulnerable heritage sites worldwide.
This section outlines the holistic design strategy, emphasizing the integration of various data sources (point clouds, historical texts, visitor interviews) into a unified workflow. It details the process of generative adversarial networks (GANs) for generating historically consistent architectural elements and the use of genetic algorithms for optimizing design parameters (e.g., wall height, gate width, vegetation density) to balance historical accuracy, structural stability, and visual consistency. The role of AR/VR technologies in delivering immersive and interactive virtual restoration experiences is also covered.
65%
Optimal Vegetation Coverage
Digital Restoration Design Workflow
Multimodal Data Fusion
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AI-Assisted 3D Modeling
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GANs for Restoration Generation
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Genetic Algorithm Optimization
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Integration with AR/VR
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Immersive Display & Interaction
| Factor | Initial Value | Optimized Value |
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| Wall Height |
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| Gate Width |
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| Gate Thickness |
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| Vegetation Density |
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Estimated Annual Savings
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Hours Reclaimed Annually
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Your AI Implementation Roadmap
A clear, phased approach to integrate AI into your heritage preservation strategy, ensuring measurable progress and sustained impact.
Phase 1: Data Acquisition & Preprocessing
Duration: 1-3 Months
Utilize drone oblique photography and 3D laser scanning for comprehensive site data. Apply AI-driven point cloud processing (PointNet++) for classification, denoising, and feature extraction. Initiate historical document scanning and OCR for textual data. Setup initial data pipelines and storage solutions.
Phase 2: AI Model Development & Initial Reconstruction
Duration: 3-6 Months
Train CNNs for image feature extraction and architectural detail classification from historical photos. Develop and train GANs for generative architectural reconstruction of missing or damaged components. Integrate initial 3D models with processed point cloud data. Conduct preliminary historical text analysis using BERT for semantic context.
Phase 3: Value Perception Integration & Optimization
Duration: 2-4 Months
Execute structured visitor interviews and text mining on user-generated content to capture 'value perception'. Integrate value perception data to inform AI-driven design optimization, using genetic algorithms to balance historical accuracy, structural stability, and visual consistency based on visitor priorities. Refine GAN outputs with cultural and emotional insights.
Phase 4: AR/VR Experience Development & Deployment
Duration: 3-5 Months
Develop immersive AR/VR interfaces for the Suoyang city site, incorporating AI-generated models and value perception-informed design elements. Implement interactive features, personalized virtual tours, and real-time AI feedback. Conduct internal testing and user feedback sessions to refine the immersive experience. Prepare for public deployment.
Phase 5: Continuous Improvement & Expansion
Duration: Ongoing
Establish a framework for continuous data updates and model refinement based on new archaeological findings or visitor feedback. Explore integration of multi-sensory experiences (auditory, tactile, olfactory). Expand the framework to other heritage sites, leveraging learnings and modular AI components. Monitor performance and user engagement metrics.
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