Research on Collaborative Strategies for Cultural Heritage and Sustainable Renewal in Old Urban Areas Based on Multimodal Artificial Intelligence

DOI

10.2991/978-2-38476-611-6_92How to use a DOI?

Keywords

Multimodal artificial intelligence; cultural heritage protection; sustainable renewal; historical urban areas; climate adaptability; green transformation

Abstract

This study addresses the challenge of balancing the protection and sustainable renewal of cultural heritage in historical urban areas and constructs a multimodal AI system integrating image recognition, semantic analysis, and GIS data. Through an empirical study of the Pingjiang Historical District in Suzhou, it was found that the core protection area (accounting for 22% of the area) carries 68.5% of the cultural value. Although the temperature in the traditional building-dense area is 2.8℃ higher in summer than that in the modern district, the energy consumption per unit area is 18% lower, demonstrating the value of traditional ecological wisdom. The research established a dual-objective optimization model of cultural value and sustainable benefits, and generated three types of differentiated update schemes through multi-objective genetic algorithms. The conservative update plan achieved a cultural value retention rate of 96% and a carbon reduction rate of 18%. The moderate update plan reached a retention rate of 90% and a carbon reduction rate of 32%. The comprehensive update plan achieved a retention rate of 79% and a carbon reduction rate of 48%. Pareto Frontier analysis indicates that there exists an optimal equilibrium point within the range of 85% to 95% for cultural value retention rates. This study is the first to combine cultural semantic understanding with climate adaptability analysis, breaking through the qualitative limitations of traditional conservation planning. This study established a quantifiable collaborative decision-making framework, providing data support for the renewal of historical urban areas. It confirmed that through precise differentiated strategies, the synergy between cultural heritage protection and green renewal can be achieved. This method can provide reference for historical urban areas around the world that are facing similar challenges.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 3.0 International License (http://creativecommons.org/licenses/by-nc/3.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Boyang Zhang
PY  - 2026
DA  - 2026/09/07
TI  - Research on Collaborative Strategies for Cultural Heritage and Sustainable Renewal in Old Urban Areas Based on Multimodal Artificial Intelligence
BT  - Proceedings of the 2026 12th International Conference on Digital Humanities and Frontiers in Social Sciences (DHFSS 2026)
PB  - Atlantis Press
SP  - 856
EP  - 865
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-611-6_92
DO  - 10.2991/978-2-38476-611-6_92
ID  - Zhang2026
ER  -