Intelligent community intelligent security scheduling management method based on deep learning

By introducing deep learning-based methods in smart community intelligent security scheduling management, the problem of cross-domain correlation mining of massive heterogeneous security data is solved, efficient, accurate and real-time identification and early warning of security risks is achieved, and the intelligence level of community security management is improved.

CN119671794AInactive Publication Date: 2025-03-21BEIJING CHINA STATE REAL ESTATE CO LTD
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Patent Information

Application Number
CN202411559505.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-04
Publication Date
2025-03-21
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

In the smart community intelligent security scheduling management, the cross-domain correlation mining of massive heterogeneous security data faces technical challenges of large differences in data format, quality and granularity. Traditional databases are difficult to effectively process highly correlated complex data, and the indexing technology of high-dimensional spatio-temporal data still needs to be optimized.

Method used

Using deep learning-based methods, video surveillance data and access control record data from multiple communities are obtained, cleaning and standardizing processing, and a network model of relationship between people and vehicles between communities is built. Graph algorithm analysis technology is used to explore personnel flow and vehicle trajectory patterns, and data retrieval and management are combined with spatiotemporal indexing technology. Potential safety hazards are identified through an abnormal detection algorithm and early warning information is generated.

Benefits of technology

It realizes efficient, accurate and real-time cross-domain security data correlation mining, improves the intelligence level of community security management, and can promptly detect and deal with potential cross-regional security risks.

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Abstract

The invention relates to the technical field of smart communities, and discloses a smart community intelligent security scheduling management method based on deep learning, which comprises the following steps: acquiring video monitoring data and access control record data of a plurality of communities, cleaning the data, unifying the format and content of the data by adopting a data standardization technology, and storing the unified data into a database; the method comprises the steps of obtaining standardized community security and protection data, mining a personnel flow mode and a vehicle track mode among different communities by adopting a graph algorithm analysis technology on the basis of a community relation network to obtain a cross-community personnel flow mode and a vehicle track mode, and obtaining a cross-community security and protection result according to analysis results of the cross-community personnel flow mode and the vehicle track mode. And an anomaly detection algorithm is adopted to identify potential safety hazards, and if an abnormal condition is detected, early warning information is generated. According to the invention, deep correlation analysis of cross-community security data is realized, and the intelligent level of community security management is effectively improved.
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