An intelligent public management AI collaborative decision system based on digital twinning and knowledge graph

By constructing a smart urban management AI collaborative decision-making system, dynamic mapping and real-time simulation of all urban elements have been achieved. Combined with deep semantic understanding of knowledge graphs, a closed-loop mechanism has been formed, which solves the shortcomings of existing systems in decision-making on complex events and improves the scientific nature and collaborative efficiency of urban governance.

CN122114476APending Publication Date: 2026-05-29ZHEJIANG COLLEGE OF CONSTR
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ZHEJIANG COLLEGE OF CONSTR
Filing Date
2026-02-07
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing smart city management systems, when integrating digital twins and knowledge graphs to achieve collaborative decision-making, lack the ability to dynamically map and model the entire life cycle of all urban elements with high fidelity. They are unable to perform causal reasoning and root cause analysis of complex events, and lack a deep cognitive logic loop, making it difficult to automatically generate optimized handling solutions for multi-stakeholder collaboration.

Method used

A smart city management AI collaborative decision-making system based on digital twins and knowledge graphs is constructed, including a city data perception layer, a digital twin modeling engine, a city management knowledge graph construction unit, a multi-source event fusion analysis unit, a collaborative decision-making inference unit, and an intelligent scheduling and execution unit. This system enables dynamic mapping and real-time simulation of all elements of the city's operational status. Combined with the deep semantic understanding and reasoning of the knowledge graph, a closed-loop mechanism of perception-cognition-decision-execution is formed.

Benefits of technology

It significantly improves the level of intelligent analysis of complex events, and can automatically generate optimized collaborative solutions across departments and levels, thereby enhancing the scientific nature, predictability and collaborative efficiency of urban governance, and meeting the needs of efficient, accurate and adaptive governance in complex urban scenarios.

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Abstract

The application relates to the field of smart cities and artificial intelligence technology, in particular to a smart city management AI collaborative decision-making system based on digital twinning and a knowledge graph, which aims to solve the problem that a traditional city management system lacks dynamic perception, deep cognition and cross-department collaborative decision-making capability. The system comprises a city data perception layer, a digital twinning modeling engine, a city management knowledge graph construction unit, a multi-source event fusion analysis unit, a collaborative decision-making deduction unit and an intelligent scheduling execution unit, and through construction of a high-fidelity digital twinning body and a city management knowledge graph, fusion analysis of multi-source heterogeneous events, multi-strategy simulation deduction and closed-loop scheduling execution are realized. Through adoption of the technical scheme, the application can realize full-element dynamic mapping of city operation states, intelligent research and judgment of complex events and cross-department collaborative disposal, and significantly improves the scientificity, predictability and collaborative efficiency of city governance.
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