Construction method of intelligent frontier defense integrated condition finger center system based on digital twinning

Abstract

The invention discloses a construction method of an intelligent frontier defense integrated condition index center system based on digital twinning. The construction method comprises the following steps: constructing a frontier defense risk factor comprehensive knowledge base and a data set; constructing a frontier defense risk fine-grained knowledge graph based on the multi-modal element library based on the comprehensive knowledge base and the data set; developing a frontier defense risk event accurate identification and deduction early warning model based on the knowledge graph; researching and developing a soft switch core system for fusion and intercommunication of frontier defense heterogeneous equipment; constructing a frontier prevention condition index center digital twinborn model based on the early warning model and the soft switch core system; and the intelligent frontier defense integrated situation finger center system is researched and developed based on the digital twinborn model. By constructing the intelligent frontier defense integrated situation index center system, accurate recognition and intelligent early warning of frontier defense risks can be realized, the frontier defense management and control efficiency and accuracy can be remarkably improved, and powerful technical support is provided for frontier defense safety.

Description

Technical Field

[0001] The present invention belongs to the field of information technology technology, and specifically is a method for constructing a smart border defense integrated intelligence and command center system based on digital twins. Background Art

[0002] The security situation in border areas is becoming increasingly complex. Current border control technology is still insufficient, especially in risk identification and early warning. More advanced technologies and methods are needed to improve the intelligent management level of border security. With the development of technologies such as big data and artificial intelligence, technological innovation in the field of border risk identification and deduction has broad application prospects.

[0003] Therefore, how to provide a method for building a smart border integrated intelligence and command center system based on digital twins has become a technical problem that technical personnel in this field urgently need to solve. Summary of the invention

[0004] In order to overcome the shortcomings of the above-mentioned prior art, the present invention proposes a method for constructing a smart border defense integrated intelligence and command center system based on digital twins. By constructing a smart border defense integrated intelligence and command center system, accurate identification and intelligent early warning of border defense risks can be achieved, the efficiency and accuracy of border defense management can be significantly improved, and strong technical support can be provided for border defense security.

[0005] A method for constructing a smart border defense integrated intelligence and command center system based on digital twins includes the following steps:

[0006] Step S1, constructing a comprehensive knowledge base and data set of border risk factors;

[0007] Step S2, constructing a border risk fine-grained knowledge graph based on a multimodal factor library based on the comprehensive knowledge base and the data set;

[0008] Step S3, developing a border risk event accurate identification and deduction warning model based on the knowledge graph;

[0009] Step S4, developing a soft switch core system for integrating and interoperating heterogeneous border defense equipment;

[0010] Step S5, building a digital twin model of the border defense intelligence and command center based on the early warning model and the soft switch core system;

[0011] Step S6: Develop an intelligent border defense integrated intelligence and command center system based on the digital twin model integration.

[0012] Furthermore, in step S1, a comprehensive and detailed border risk factor comprehensive knowledge base and data set is constructed by integrating multi-dimensional and multi-modal historical data resources involving personnel, vehicles, and objects in the border area.

[0013] Furthermore, in step S2, based on the comprehensive knowledge base and data set, using big data processing and artificial intelligence technology, we deeply analyze the internal logic and evolution of border risks, and construct a fine-grained risk knowledge graph and event knowledge graph covering the entire life cycle of risks.

[0014] Furthermore, the situation and characteristics of different entities in the comprehensive knowledge base and the dataset are analyzed to obtain the static and dynamic characteristics of the elements, and the dynamic graph is used to formally express the situation evolution of the elements, the relationship between people, and the event correlation information, so as to perform fine-grained classification case representation for border risk classification; the element entity relationship is vectorized using a graph learning method, and a unified representation is used to perform semantic calculations on it to obtain the case entity relationship; the constructed multimodal element library is subjected to entity alignment and relationship completion, and the entity disambiguation and entity alignment methods are used to integrate it with the case entity knowledge to obtain the fine-grained deep organization of knowledge, so as to construct a fine-grained risk knowledge graph and event knowledge graph covering the entire life cycle of the risk; the fine-grained risk knowledge graph and event knowledge graph are completed and iteratively updated through the increment and global update of new elements.

[0015] Furthermore, in step S3, based on the knowledge graph, the multi-source risk factor data of climate, terrain, events, and human hazards in the border areas are aggregated and reorganized to construct a risk factor database with spatiotemporal characteristics, and the existing border risk warning intensity is classified and graded, and a precise identification and deduction warning model for border risk events is designed; a risk warning indicator system is designed, and a dynamic monitoring model for major risks in border areas is constructed.

[0016] Furthermore, in step S5, the digital twin model uses digital twin technology and integrates GIS technology to achieve accurate mapping and real-time monitoring of physical world terrain maps, equipment and vehicle metadata in border areas, while integrating risk warning functions to provide decision makers with an intuitive and comprehensive view of the border situation.

[0017] Furthermore, in step S6, the smart border integrated intelligence and command center system deeply integrates border monitoring, risk identification, early warning simulation, equipment integration and command and dispatch functional modules to form an efficient, coordinated and intelligent border management system.

[0018] The advantages of the present invention are:

[0019] The present invention is based on multimodal data and combines historical data of major risk factors from multiple sources to construct a comprehensive knowledge base and data set of border risk factors; fully utilizes risk signals, environment, situation, and factors to construct a fine-grained risk knowledge map and event knowledge map covering the entire life cycle of risk; in view of the complexity and nonlinearity of risk factors, develops a risk intelligent identification method that collaborates with multimodal data to achieve high-precision and full-coverage risk classification, conducts spatial evolution mechanism mining, spatial statistical modeling, and heuristic intelligent modeling, and applies them to fine-grained identification and deduction of risk factors; for risk prediction and deduction of the entire process monitoring, and uses fusion communication technology to integrate and interconnect multiple heterogeneous communication devices, and finally develops a smart border defense integrated intelligence command center system based on digital twins, forming a border defense risk warning demonstration area in the future to provide reference and reference for other solid defense areas. By constructing a smart border defense integrated intelligence command center system, accurate identification and intelligent warning of border defense risks can be achieved, the efficiency and accuracy of border defense management can be significantly improved, and strong technical support can be provided for border defense security. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is a flow chart of the method of the present invention;

[0021] Figure 2 A diagram for constructing a fine-grained knowledge graph of border risk based on a multimodal factor library according to the present invention;

[0022] Figure 3 This is a diagram for constructing a model for accurately identifying and deducing early warning of border risk events of the present invention;

[0023] Figure 4 This is a structural block diagram of the intelligent border defense integrated intelligence and command center system of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] refer to Figure 1 The present invention provides a method for constructing a smart border defense integrated intelligence and command center system based on digital twins, comprising the following steps:

[0026] Step S1, constructing a comprehensive knowledge base and data set of border risk factors;

[0027] Step S2, constructing a border risk fine-grained knowledge graph based on a multimodal factor library based on the comprehensive knowledge base and the data set;

[0028] Step S3, developing a border risk event accurate identification and deduction warning model based on the knowledge graph;

[0029] Step S4, developing a soft switch core system for integrating and interoperating heterogeneous border defense equipment;

[0030] Step S5, building a digital twin model of the border defense intelligence and command center based on the early warning model and the soft switch core system;

[0031] Step S6: Develop an intelligent border defense integrated intelligence and command center system based on the digital twin model integration.

[0032] In step S1, a comprehensive and detailed border risk factor comprehensive knowledge base and data set are constructed by integrating multi-dimensional and multi-modal historical data resources involving personnel, vehicles, and objects in the border area. This database will serve as the core data support for subsequent risk analysis, identification, and deduction, ensuring the consistency and integrity of the data and laying a solid foundation for the refinement and intelligence of risk management.

[0033] refer to Figure 2 In step S2, based on the comprehensive knowledge base and data set, big data processing and artificial intelligence technology are used to deeply analyze the internal logic and evolution of border risks, and to construct fine-grained risk knowledge graphs and event knowledge graphs covering the entire life cycle of risks. Through the construction of fine-grained risk knowledge graphs and event knowledge graphs, in-depth mining and precise characterization of risk characteristics are achieved, which significantly improves the accuracy and efficiency of risk identification and provides a scientific basis for the formulation of risk prevention and control strategies.

[0034] The present invention adopts "formal representation of risk event cases → risk knowledge fusion → iterative update and completion of knowledge graph" to study and construct a knowledge graph of fine-grained risk accurate classification cases. The situation and characteristics of different entities in the comprehensive knowledge base and data set are analyzed to obtain the static and dynamic characteristics of the elements, and the situation evolution, character relationships, event associations and other information of the elements are formally expressed using dynamic graphs to represent the fine-grained classification cases of border defense risks; the element entity relationships are vectorized using graph learning methods, and semantic calculations are performed on them using unified representations to obtain case entity relationships; the constructed multimodal element library is entity aligned and relationship completed, and entity disambiguation and entity alignment methods are used to integrate with case entity knowledge to obtain fine-grained deep-level organization of knowledge, so as to construct a fine-grained risk knowledge graph and event knowledge graph covering the entire life cycle of risks; the fine-grained risk knowledge graph and event knowledge graph are completed and iteratively updated through the increment and global update of new elements.

[0035] refer to Figure 3 In step S3, based on the knowledge graph, the multi-source risk factor data of the border area, such as climate, terrain, events, and personnel hazards, are aggregated and reorganized to construct a risk factor database with spatiotemporal characteristics, and the existing border risk warning intensity is classified and graded, and a precise identification and deduction warning model for border risk events is designed; a risk warning indicator system is designed, and a dynamic monitoring model for the main risks in the border area is constructed. Based on the border risk knowledge graph and association rule analysis, real-time accurate risk monitoring, quantitative assessment, warning and intervention are achieved for the entire border. An efficient and accurate border risk event identification and deduction warning model will integrate advanced machine learning algorithms and intelligent reasoning technology to achieve early warning and refined management of border risks, while supporting the visual display of the model to facilitate the application and integration of subsequent tasks.

[0036] This invention adopts the technical path of "risk evolution situation judgment → risk evolution prediction → risk classification and deduction strategy intervention" to study the fine-grained identification and intelligence warning technology of border defense risks, and the judgment of the situation of border defense risk events and interactive deduction and warning. Using the entity association and attributes of the risk knowledge graph, according to indicators such as risk nature, impact degree, and probability of occurrence, the border defense risk classification is classified using graph neural network and other technologies; based on the situation classification scheme and the current evolution of risks, the path generation is simulated through a dynamic time series network to perform the evolution trend and analysis of risks in the border area; combined with the situation classification scheme, evolution prediction analysis, historical risk cases and risk deduction analysis, multi-agent interaction technology is used to generate recommended strategies, and the human-in-the-loop scheme is used for optimization and feasibility analysis to achieve early intervention in risks, while building a decision feedback visualization model for real-time monitoring and accurate identification.

[0037] In step S4, for the multi-source heterogeneous equipment in the border area, an efficient and reliable soft switch core system is developed to achieve seamless integration and interconnection between heterogeneous equipment. This system will significantly improve the command and dispatch efficiency, real-time monitoring capabilities and resource allocation flexibility in the border management environment, and provide strong technical support for the smooth development of border defense work.

[0038] In step S5, the digital twin model uses digital twin technology and integrates GIS technology to achieve accurate mapping and real-time monitoring of the physical world terrain map, equipment and vehicle metadata of the border area, and integrates risk warning functions to provide decision makers with an intuitive and comprehensive view of the border situation. The construction of the digital twin model will further improve the level of intelligence in border management and enhance the scientificity and timeliness of decision-making.

[0039] refer to Figure 4In step S6, the smart border defense integrated intelligence and command center system deeply integrates border defense monitoring, risk identification, early warning simulation, equipment integration and command and dispatch functional modules to form an efficient, collaborative and intelligent border defense management system. The smart border defense integrated intelligence and command center system provides risk and decision-making related information sharing services for the smart border defense integrated management platform, as well as comprehensive dispatch and command, intelligence analysis and judgment, and digital twin visualization capabilities. Through the application of this system, the linkage capability, collaborative efficiency and business integration level of border defense departments will be significantly improved, providing a strong guarantee for the modernization, transformation and upgrading of border defense work.

[0040] (1) Digital Twin Technology of the Smart Border Defense Integrated Intelligence and Command System

[0041] Digital twin technology is used to digitally model the border geographical environment, border defense equipment, personnel deployment, etc., to achieve intelligent simulation of border defense conditions, and provide decision makers with a realistic and reliable simulation environment to help them make decisions, plan, and command and dispatch. Combined with big data analysis and risk prediction models, intelligent prediction and optimization of border defense conditions can be carried out to help commanders make more informed decisions, and intelligent support can be provided for border defense deployment, command and dispatch, etc. Through such a research concept, the advancement of digital twin technology in its interdisciplinary integration, real-time monitoring and feedback, data-driven decision-making, and intelligent optimization is reflected.

[0042] On this basis, to build a smart border defense integrated intelligence and command center system based on digital twins, it is necessary to digitize the data, structure and behavior of some border defense scenes in border defense control, so as to build a digital model of the border defense scene. Through this digital model, the operating status of border defense control can be monitored, simulated and optimized in real time. The integration of digital twin technology and the smart border defense integrated intelligence and command center system adopts the technical path of "digital modeling → real-time monitoring → simulation prediction → optimized decision-making", studies the situation where there are problems with multi-source front-end perception, multi-modal data, and quality and consistency, and uses the big data platform for effective cleaning and processing to ensure the accuracy and reliability of the data. Combined with the structure, behavior and performance of the physical entities in the border defense control scene, data analysis and machine learning and other technologies are used to ensure the accuracy and reliability of the model.

[0043] The integrated intelligence and command center system architecture is built based on the infrastructure layer, business integration layer, application support layer and application service layer. The data warehouse is built with the factor library, knowledge base, model library and risk event sample library. The multimodal data fusion center, physical model center and service structure center are used as application support to build the integrated application of digital twin technology and the smart border defense integrated intelligence and command center system.

[0044] (2) The integration capability of multi-mode and multi-protocol of border defense heterogeneous equipment and data collection and aggregation

[0045] By using the core soft-switch communication technology to support the mainstream audio / video streaming media communication signaling control protocol and transmission, compression and coding standards, we study the integration and interconnection of audio and video communication systems of various systems, and realize the integration of audio / video, wired / wireless, telephone / monitoring / monitoring / consultation / intercom full-service functions in one communication terminal. We study the core soft-switch communication platform with an open architecture, provide CCS (call control service) and CSTA (international standard CTI interface) API interfaces, and facilitate secondary application development to meet the needs of command and dispatch, real-time monitoring and resource allocation in the border management environment.

[0046] On this basis, a unified data format and standard is formulated to ensure that data collected by different devices can be interoperable and shared. At the same time, relying on the cloud platform and using distributed storage and other technologies, deployment includes memory databases, image databases, relational / non-relational databases, and message engines to ensure the safe and reliable storage of data. In addition, effective measures need to be taken to ensure the quality and accuracy of data, such as data cleaning, deduplication, and verification. In short, data collection and aggregation of smart border defense is an important part of the construction of smart border defense. It is necessary to fully consider technical, standard, quality and other aspects to ensure the timely, accurate, and safe collection and aggregation of data.

[0047] With the help of the smart border integrated intelligence and command center system's accurate identification of border risks and deduction of early warning information, border commanders use advanced converged communication technology to integrate communications with people, objects, situations, and events, so that border residents, outposts, armed police, and a variety of security and communication equipment can be interconnected, realizing real-time monitoring, command and dispatch, and resource allocation of border management, to meet the communication needs of border management in different environments and improve the command efficiency and combat capability of border defense forces.

[0048] The present invention can improve border security: the construction of the smart border defense integrated intelligence command center system can improve border security by using advanced monitoring technology and intelligent analysis systems, reduce the occurrence of illegal immigration, smuggling and terrorist activities, and thus protect national security and stability. Reduce labor costs: the construction of the project can reduce the demand for human resources, and through automated monitoring and intelligent analysis systems, the demand for human patrols and monitoring can be reduced, reducing labor costs. Improve border management efficiency: the smart border defense integrated intelligence command center system project can improve the efficiency of border management, and through the intelligent analysis system, border violations can be quickly identified and handled, and border monitoring and management can be strengthened. In order to achieve all-round and all-weather coverage of the border area, it can greatly improve the efficiency and accuracy of patrols, and reduce the difficulty and risk factor of border guards in performing their tasks. Promote economic development: a safe and stable border environment can promote economic development in border areas, attract more investment and commercial activities, and promote prosperity in border areas. Enhance the image of the country: the smart border defense project can enhance the country's image in the international arena, demonstrate the country's attention to border security and management, and enhance the country's soft power and international reputation. Realize the informatization and intelligence of border management: The system can automatically collect, store and transmit various types of information in the border area, and conduct in-depth mining and intelligent processing of information through big data analysis and artificial intelligence technology to provide accurate and timely intelligence support for decision makers. This will help border defense departments to achieve accurate decision-making and efficient management, and improve the effectiveness of border security prevention and control. Promote scientific and technological innovation and industrial upgrading: It can not only enhance border security prevention and control capabilities, but also promote scientific and technological innovation and industrial development. In the process of research and development and application, a large number of new technologies, new products and new services will be generated, promoting the rapid development of related industries. At the same time, the construction and operation of the system will also drive the coordinated development of upstream and downstream enterprises in the relevant industrial chain to form a virtuous circle.

[0049] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing a smart border defense integrated intelligence and command center system based on digital twins, characterized in that: The steps include: Step S1, constructing a comprehensive knowledge base and data set of border risk factors; Step S2, constructing a border risk fine-grained knowledge graph based on a multimodal factor library based on the comprehensive knowledge base and the data set; Step S3, developing a border risk event accurate identification and deduction warning model based on the knowledge graph; Step S4, developing a soft switch core system for integrating and interoperating heterogeneous border defense equipment; Step S5, building a digital twin model of the border defense intelligence and command center based on the early warning model and the soft switch core system; Step S6: Develop an intelligent border defense integrated intelligence and command center system based on the digital twin model integration.

2. According to the method for constructing a digital twin-based intelligent border defense integrated intelligence and command center system according to claim 1, it is characterized in that: In step S1, a comprehensive and detailed border risk factor knowledge base and data set is constructed by integrating multi-dimensional and multi-modal historical data resources involving personnel, vehicles, and objects in the border area.

3. According to the method for constructing a digital twin-based intelligent border defense integrated intelligence and command center system according to claim 2, it is characterized in that: In step S2, based on the comprehensive knowledge base and data set, using big data processing and artificial intelligence technologies, we deeply analyze the internal logic and evolution of border risks, and construct a fine-grained risk knowledge graph and event knowledge graph covering the entire life cycle of risks.

4. According to the method for constructing a digital twin-based intelligent border defense integrated intelligence and command center system according to claim 3, it is characterized in that: We conduct situation and characteristic analysis on the features of different entities in the comprehensive knowledge base and data set, obtain the static and dynamic features of the elements, and use dynamic graphs to formally express the situation evolution, character relationships, and event association information of the elements, and perform fine-grained classification case representation for border defense risk classification; we use graph learning methods to vectorize the element entity relationships, use unified representations to perform semantic calculations on them, and obtain case entity relationships; The constructed multimodal factor library is entity aligned and relationship completed, and entity disambiguation and entity alignment methods are used to integrate with case entity knowledge to obtain fine-grained deep-level organization of knowledge, so as to construct fine-grained risk knowledge graphs and event knowledge graphs covering the entire risk life cycle; The fine-grained risk knowledge graph and event knowledge graph are completed and iteratively updated through incremental and global updates of new elements.

5. According to the method for constructing a digital twin-based intelligent border defense integrated intelligence and command center system according to claim 4, it is characterized in that: In step S3, based on the knowledge graph, the multi-source risk factor data of climate, terrain, events, and human hazards in the border areas are aggregated and reorganized to build a risk factor database with spatiotemporal characteristics. The existing border risk warning intensity is classified and graded, and a precise identification and deduction warning model for border risk events is designed; a risk warning indicator system is designed, and a dynamic monitoring model for major risks in border areas is built.

6. According to the method for constructing a digital twin-based intelligent border defense integrated intelligence and command center system according to claim 5, it is characterized in that: In step S5, the digital twin model uses digital twin technology and integrates GIS technology to achieve accurate mapping and real-time monitoring of the physical world terrain map, equipment and vehicle metadata of the border area, while integrating risk warning functions to provide decision makers with an intuitive and comprehensive view of the border situation.

7. The method for constructing a digital twin-based intelligent border defense integrated intelligence and command center system according to claim 6 is characterized in that: In step S6, the smart border integrated intelligence and command center system deeply integrates border monitoring, risk identification, early warning simulation, equipment integration and command and dispatch functional modules to form an efficient, coordinated and intelligent border management system.

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