Research on the System Restoration of Military Settlements in Jin Dynasty from the Perspective of Digital Intelligence Empowerment

Abstract

Under the background of the transformation of digital humanities research, the research on historical military settlements needs to break through the limitations of traditional literature textual research and qualitative analysis, and the research on historical military settlements, which traditionally relies on literature textual research and empirical judgment, faces a breakthrough in methodology. In recent years, although intelligent technology has made phased achievements in archaeology and heritage protection of historical buildings, and has gradually become an important supporting tool for heritage research and inheritance, there are still few researches on the early Great Wall in China, especially the military settlements in Jin Dynasty. Taking the Northeast Road of the Great Wall in Jin Dynasty as an example, the existing research mostly focuses on the individual form or local layout of military facilities, and lacks the overall restoration of the hierarchical relationship and spatial logic of the whole settlement system. This paper attempts to reconstruct the system structure of the Great Wall military settlement in Jin Dynasty with the help of digital modeling and spatial analysis, and further explore the spatial interaction characteristics between its internal composition and its surrounding environment. Through multi-dimensional technical interpretation, it not only presents the wisdom crystallization of the construction concept of the Jin Dynasty border defense system, but also expands the understanding depth of the Great Wall heritage. This intelligent research path has built a dialogue bridge between the protection of historical and cultural heritage and contemporary scientific and technological tools, which not only enriches the traditional research paradigm, but also opens up new theoretical space and practical ideas for the sustainable inheritance of heritage.