A public facility abnormal data processing and analysis method based on a space-time graph neural network

CN121580247BActive Publication Date: 2026-08-28SHAANXI RUILIAN INFORMATION TECH CO LTD
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Patent Information

Application Number
CN202511802285.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-12-02
Publication Date
2026-08-28
Estimated Expiration
2045-12-02

AI Technical Summary

Technical Problem

[0002]在现代城市治理体系中,多政府机构协同管理公共设施已成为提升公共服务效能的关键环节,交通局、环保局等部门需频繁共享桥梁结构健康度、垃圾处理站运行状态等关键数据,此类数据由部署在广域地理空间的物联网传感器实时生成,具有显著的时空动态特性,为实现数据高可用性,各机构通常采用异构云平台独立存储多副本数据,形成分布式数据孤岛,与此同时,外部网络攻击威胁持续升级,欧盟通用数据保护条例等国际合规性要求日益严格,迫使数据共享过程必须嵌入高强度加密机制,然而,公共设施异常监测需求(如桥梁裂缝演化分析)要求对加密数据实施毫秒级响应分析,现有技术体系难以兼顾数据隐私安全与实时性需求,严重制约跨部门协同治理能力

Benefits of technology

[0014]本发明的有益效果是:该方法有效融合区块链加密验证与联邦学习机制,在保护多机构数据隐私前提下构建加密时空图模型,通过动量加权优化与轻量化图推理实现高效异常检测;通过引入抗量子投影与多云并行计算显著提升分析实时性,结合时空感知噪声注入与可验证灾备同步技术,在确保差分隐私强度的同时精准捕捉设施异常状态,最终通过智能合约驱动的分级告警机制实现跨部门协同响应,形成安全可靠、精准高效的公共设施闭环治理能力。

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Abstract

The application relates to a public facility abnormal data processing and analysis method based on a space-time graph neural network, and particularly relates to the field of public facility abnormal data processing and analysis. The method effectively fuses a blockchain encryption verification and a federal learning mechanism, constructs an encrypted space-time graph model under the premise of protecting the data privacy of multiple institutions, realizes efficient abnormal detection through momentum weighted optimization and lightweight graph reasoning, significantly improves analysis real-time performance by introducing anti-quantum projection and multi-cloud parallel computing, combines space-time perception noise injection and a verifiable disaster backup synchronization technology, accurately captures facility abnormal states while ensuring differential privacy strength, and finally realizes cross-department collaborative response through a hierarchical alarm mechanism driven by a smart contract, thereby forming a safe, reliable, accurate and efficient public facility closed-loop management capability.
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Citation Information

Patent Citations

  • Federal learning-based privacy data calculation method and system

    CN120162828A

  • Multi-modal data real-time identification and cooperative processing system based on edge calculation and federated learning

    CN120582765A