Risk early warning system and risk early warning method based on multi-factor model

Abstract

The present invention discloses a risk warning system based on a multi-factor model, comprising a comprehensive evaluation and assessment platform (1), a monitoring data acquisition module (2), a data storage module (3), a risk warning and display module (4) and an information release module (5); the comprehensive evaluation and assessment platform (1) is respectively connected to the monitoring data acquisition module (2), the data storage module (3), the risk warning and display module (4) and the information release module (5) by data communication. The risk warning system and risk warning method based on a multi-factor model of the present invention, in this application, adopt the principle of multidisciplinary comprehensive model construction, and carry out comprehensive shared management of the risk warning systems of multiple management departments for the acquired risk factors, so as to analyze risks from data of multiple dimensions, so as to make risk analysis and risk warning more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent security and smart city, and specifically to a risk warning system and a risk warning method based on a multi-factor model. Background Art

[0002] With the rapid development of my country's urbanization process, cities are becoming larger and larger. All aspects of cities need to be managed and predicted in advance to ensure the peace and stability of cities. On the one hand, the daily operation of cities includes various daily life, daily community security, urban transportation, urban community health and other urban operations. In traditional urban management, daily community security channels are managed by the community's security office, urban traffic is managed by the urban traffic management department, and urban community health is managed by community health centers and health departments; it can be seen that all aspects of the city are managed and responsible by each management and responsible department separately, and there is no interaction and interaction between departments. However, in actual urban management and operation, the management and work of various departments lack coordination, resulting in low work execution efficiency and slow response, which is not conducive to rapid risk warning and risk control of urban management; on the one hand, the occurrence of emergency and risk situations usually has a certain correlation or precursor. Therefore, if risk warning and risk monitoring can be carried out in relevant areas, and certain advance deployment can be carried out before the emergency is discovered, the impact of the emergency on the normal operation of the city can be greatly reduced, or it can be restored as soon as possible in the event of an emergency.

[0003] In view of the above situation, there is also a so-called city brain system in the prior art. It is a comprehensive urban detection and evaluation system that can monitor multiple factors of the city at the same time, and based on multiple factors, comprehensively consider and analyze the potential risks of the city. It is a very valuable system; such as:

[0004] For example, patent application CN112820415A discloses a GIS-based chronic disease spatiotemporal evolution feature analysis and environmental health risk monitoring system and method, which can realize the analysis of chronic disease spatiotemporal evolution features and the monitoring of environmental health risks. On the one hand, the present invention combines traditional chronic disease management methods with GIS, which can identify the spatial heterogeneity characteristics of chronic diseases and formulate regional targeted prevention and control measures; on the other hand, chronic diseases are affected by a variety of environmental factors, and combining geographic detectors with Bayesian spatiotemporal interaction models can not only analyze the impact of single factors, but also detect the impact of two-factor interactions and multi-factor synergies on the onset of chronic diseases. This invention can be used in chronic disease monitoring and early warning that are closely related to environmental health.

[0005] Patent application CN 110443528A discloses a system for quantitative assessment and tracking of enterprise risks based on machine learning. It is a system that integrates risk factor identification, risk assessment, risk tracking and early warning, and specifically includes a risk quantitative assessment subsystem, an investment project value assessment subsystem, a bond risk quantitative assessment subsystem and a risk early warning tracking subsystem. The biggest feature of the system is that the system uses machine learning algorithms to automatically identify and judge the potential risk factors that may exist in the target enterprise based on the data of the origin parameter big data platform, and automatically calls the risk assessment model applicable to the target enterprise through the analysis of the company's basic information, so as to realize the quantitative risk assessment, real-time tracking and early warning of the target enterprise, and provide investors with reliable and practical tools.

[0006] Patent application CN113360830A discloses a method for identifying and assessing major safety risks of metal smelting enterprises. The steps are to collect accident case data of metal smelting enterprises, analyze accident cases, and find risk factors related to accidents; divide risk units according to metal smelting processes, and compile a general risk identification list for metal smelting enterprises; form a general risk and hidden danger violation evidence information list; divide risk assessment units with smelting processes as units and risk points as the main assessment line; establish an inherent risk indicator system for high-risk risks of metal smelting enterprises, and calculate the inherent hazard index of risk points through the established metal smelting enterprise assessment model; unit inherent risk assessment, determine unit risk frequency, unit initial high-risk safety risk assessment, dynamic risk factor identification; unit risk aggregation to enterprise risk. This invention improves the inherent safety level and safety management level of metal smelting enterprises, prevents major accidents, and reduces the consequences of accidents. Patent application CN112712903A discloses an infectious disease monitoring method based on collaborative perception of human-machine-object ternary space. The method includes: collecting social space monitoring data, information space monitoring data and physical space monitoring data through a combination of online and offline methods to construct a ternary spatial data set; processing the ternary spatial data set to extract keywords and classifications related to infectious diseases, and locate the geographical location of the data source; establishing a monitoring and early warning model to analyze the risk level of infectious diseases in different time and space ranges, and combining multiple types of risk characteristic factors to conduct epidemic risk warnings. The invention collects relevant data in a timely manner through a combination of online and offline methods, and through the coordinated perception of time and space coverage and target coverage, it dynamically monitors the status of infectious diseases in real time, and can accurately and timely conduct infectious disease early warnings.

[0007] Patent CN111882830A discloses a method, device, system and storage medium for monitoring, forecasting and warning of urban waterlogging. The method includes: waterlogging monitoring equipment monitors water depth data; video gateway equipment sends a request to obtain measured rainfall data to a cloud server and receives measured rainfall data sent by the cloud server; the video gateway equipment performs waterlogging simulation edge calculation on the current waterlogging monitoring point according to the measured rainfall data and the monitored water depth data, obtains the predicted maximum water depth, determines whether there is a waterlogging risk at the current waterlogging monitoring point, and feeds back the waterlogging risk judgment result to the cloud server; if there is a waterlogging risk, the scene is captured, and a warning instruction is sent to the waterlogging warning device, and the waterlogging warning device displays the alarm information. The present invention performs waterlogging simulation calculation through the front-end video gateway device, improves the real-time nature of waterlogging forecasting and warning, reduces the pressure of cloud server calculation, and reduces the requirement for communication bandwidth.

[0008] Patent CN110427406A discloses a method and device for mining the relationship between personnel related to an organization. The method includes: obtaining data information sets of various dimensions of natural persons related to an organization and the organizations to which the natural persons belong; obtaining feature subsets of various dimensions of the organizations to which the personnel belong after clustering according to the names of natural persons or other attribute information; combining organizations to which natural persons of the same type belong, and performing vector conversion according to the similarity features of each combination; training a classification model for people with the same name according to the similarity vector, and using the model to predict the classification results; according to the classification results, merging the same natural person, aggregating the data sets of related natural persons, organizations to which the natural persons belong, and related organizations, and generating a relationship structure of personnel related to the organization. The embodiment of the present invention can accurately and intuitively mine the mutual relationships between personnel related to different organizations, thereby meeting the need to establish connections between personnel related to isolated and scattered organizations.

[0009] It can be seen that at present, in the field of community life risk control and early warning, there are already many existing technologies, hoping to obtain information through relevant monitoring systems in order to quickly deal with risks. However, there are still the following defects:

[0010] 1. In the existing technology, there are also community risk environment reinforcement learning training models that usually use the data collected by themselves for learning, optimization and control. The processing of data is rarely cross-departmental risk factor knowledge assistance. Basically, each management department analyzes and judges based on its own sensor data and finds the risks it is responsible for handling and discovers risk warnings. However, in reality, risk warnings usually require comprehensive consideration of various risk factors to make accurate judgments. Therefore, the risk warning acquisition and judgment methods in the existing technology are not accurate;

[0011] 2. In the prior art, since the data obtained by multiple departments are obtained, when it is necessary to comprehensively judge the risks of urban operation or detect risks, how to share the various risk parameter data obtained between the management modules is a difficult problem, especially in the processing and risk reduction of risk warnings by various departments. However, in the prior art, since the departments are separate, it is difficult to coordinate risk processing, especially when it is necessary to conduct risk screening of the management department based on the risk warnings provided by the other party.

[0012] 3. In the prior art, there is no system that specifically analyzes the data of disease treatment, especially infectious diseases. In fact, many diseases, especially infectious diseases, usually start out in a small area with concentrated and disease characteristics. If a risk warning can be issued in time when a disease is found to be concentrated, with the same disease and abnormal growth, the spread of the disease can be stopped earlier and the disease can be eliminated. However, there are no relevant means and mechanisms in the prior art. In the face of the above technical problems, people hope to provide a comprehensive risk warning system and warning method that can obtain various parameters of the city and form a comprehensive risk warning system that can detect multiple risk factors at the same time, so as to provide early risk warnings and clear risks in a timely manner. However, so far, there is no effective way to solve the above technical problems in the prior art.

[0013] In view of the above technical problems, it is hoped to provide a cross-domain knowledge assistance method and system based on neural networks and deep learning to solve the above technical problems. Summary of the invention

[0014] In view of the above technical problems, the purpose of the present invention is to provide a risk warning system and a risk warning method based on a multi-factor model to solve the problems raised in the above background technology.

[0015] To achieve the above object, the present invention provides the following technical solutions:

[0016] A risk early warning system based on a multi-factor model comprises a comprehensive evaluation and assessment platform, a monitoring data acquisition module, a data storage module, a risk early warning and display module and an information release module; the comprehensive evaluation and assessment platform is respectively connected with the monitoring data acquisition module, the data storage module, the risk early warning and display module and the information release module for data communication;

[0017] The monitoring data acquisition module is used to acquire risk behaviors and potential risk parameters of the monitored personnel and monitored areas. The acquired risk parameters and risk behaviors of various types constitute multi-dimensional risk factors.

[0018] The comprehensive evaluation and assessment platform performs risk assessment, risk warning and risk control based on the risk sensor data acquired by the monitoring data acquisition module. The comprehensive evaluation and assessment platform includes a multi-factor intelligent analysis module, a real-time risk warning module and an AI intelligent analysis and detection module;

[0019] The multi-factor intelligent analysis module, based on the constructed multi-factor intelligent analysis model, identifies key people and key units in the city, screens out potential hidden dangers, and realizes the transformation from manual investigation to comprehensive perception;

[0020] The real-time risk warning module is based on the risk sensing data acquired in real time by the monitoring data acquisition module, and sends it to the multi-factor intelligent analysis module for data query and analysis in combination with the multi-factor intelligent analysis model constructed by it, and obtains the possible risk type and risk level parameters, and sends them to the risk warning and display module and the information release module;

[0021] The AI ​​intelligent analysis and detection module integrates AI intelligent applications, forms a risk warning model and risk area based on the detected risk factors and the existing risk correspondence stored in the data storage module, and obtains an intelligent analysis model; thereby carrying out monitoring and adjusting the arrangement of the corresponding monitoring data acquisition module;

[0022] The monitoring data acquisition module includes a network data extraction module, a street safety module, a community safety monitoring network module, a road safety monitoring network module and a household registration data interface module;

[0023] The network data extraction module is used to obtain news and events published on the Internet in order to extract risk factors that pose risks to the community; the street safety module is a street safety camera module that has been installed in the government management department, so as to provide risk factors that pose risks to the community; the community security monitoring network module is a security monitoring video system installed in the community, and the monitoring images obtained by the security monitoring video system of the community are used to provide risk factors that pose risks to the community; the road safety monitoring network module is a video monitoring system installed on the road for detecting road vehicles, thereby providing data on vehicles and road conditions on the road to form risk factors on the road; the household registration data interface module is used to obtain household registration data of the population, so as to provide household registration risk factors of the resident population;

[0024] The data storage module is used to store the multi-dimensional risk factors obtained by the monitoring data acquisition module; the risk warning and display module is used to display the risks analyzed by the comprehensive evaluation and assessment platform and issue risk warnings to the management department; the information release module is used to issue risk warnings for the risks analyzed by the comprehensive evaluation and assessment platform; when the risk warning system is running and performing risk warnings, the network data extraction module, street safety module, community safety monitoring network module, road safety monitoring network module and household registration data interface module respectively obtain various risk factors and store them in the data storage module;

[0025] The real-time risk warning module, multi-factor intelligent analysis module and AI intelligent analysis and detection module of the comprehensive evaluation and assessment platform perform big data analysis based on the data stored in the data storage module to obtain real-time risk warning data and social security data, and send the obtained risk warning data to the information release module. The information release module sends the risk warning data to the regulatory responsible departments and community life personnel in the corresponding area for timely response. At the same time, the risk warning and display module is used to display to the regulatory dispatching department, so as to arrange risk handling work with the regulatory departments and responsible departments in the corresponding area, and adjust the number of staff in the corresponding risk supervision responsible departments.

[0026] Preferably, the risk warning system also includes a mass user terminal, which can be presented in the form of an APP or a WeChat applet. The mass user terminal and the monitoring data acquisition module are data-communication connected, so that the public can report risk data to the monitoring data acquisition module through the mass user terminal, and store it in the data storage module. The comprehensive evaluation and assessment platform performs big data analysis based on the data stored in the data storage module to obtain real-time risk and social security data.

[0027] Preferably, the official user terminal is configured with an official account and is allocated to party and mass organizations and community workers for use. When official information needs to be sent out in a timely manner, the government's official information and risk information can be sent to all users by selecting the broadcast mode.

[0028] Preferably, the monitoring data acquisition module also includes a medical treatment data acquisition module, which acquires the medical treatment data of the community hospital and stores it in the data storage module. The AI ​​intelligent analysis and detection module acquires the medical treatment data and uses the historical medical treatment data stored in the data storage module to analyze the disease treatment model, which is a disease treatment model including the treatment hospital, disease type, number of disease personnel and age of disease personnel. The disease treatment model is provided to the real-time risk warning module, so that the real-time risk warning module compares the data with the disease treatment model based on the treatment hospital, disease type, number of disease personnel and age of disease personnel of the patients obtained in real time, thereby analyzing the abnormal treatment hospital, disease type, rate of increase of disease personnel and age of disease personnel, and providing them to experts in the field of disease treatment, so as to timely judge the characteristics of disease transmission and the outbreak site of the disease, so as to timely block the development of the disease and provide disease risk warning.

[0029] Preferably, each city's responsible management department is equipped with a corresponding risk warning receiving and dispatching module. When the risk warning receiving and dispatching module receives the risk warning and risk type issued by the comprehensive evaluation and assessment platform, the city's responsible management department completes the corresponding risk investigation work based on its own responsibilities or progresses the risk processing when receiving the risk processing dispatching instructions issued by the comprehensive evaluation and assessment platform.

[0030] Preferably, the risk warning and display module also includes a risk handling and scheduling module. When the comprehensive evaluation and assessment platform monitors risks, it issues a risk warning to the risk warning and display module. When multiple city management departments need to jointly handle and eliminate the risk, the risk handling and scheduling module coordinates the city management departments to reduce and eliminate the risk. Moreover, if the city management department responsible for eliminating or reducing the risk is unable to complete the risk reduction or elimination work alone, a request for assistance in risk elimination or reduction is issued to other city management departments through the risk handling and scheduling module, thereby realizing risk command and scheduling work.

[0031] Preferably, the risk warning system also includes a process of setting key monitoring events, key monitoring areas and key monitoring personnel. Through the predetermined key monitoring events, key monitoring areas and key monitoring personnel, the corresponding monitoring data acquisition modules are set in the areas where the key monitoring events, key monitoring areas and key monitoring personnel are located, so as to obtain the multi-dimensional risk factors, thereby monitoring the key monitoring areas to detect risks more quickly.

[0032] Preferably, the risk warning and display module includes risk handling and dispatching modules respectively arranged in the central dispatching department and each grassroots management department. The central dispatching department realizes data communication connection and command and dispatch with each grassroots management department, and each grassroots management department realizes communication connection and command and dispatch between each other, thereby establishing a comprehensive command and dispatch system that is vertically and horizontally connected.

[0033] On the other hand, the present application also provides a risk warning method based on a multi-factor model, including a risk warning system based on a multi-factor model, characterized in that it includes the following steps:

[0034] Step S1, when the risk warning system is running, the network data extraction module, the street safety module, the community safety monitoring network module, the road safety monitoring network module and the household registration data interface module respectively obtain the risk behaviors and potential risk parameters of the monitored personnel and the monitored areas, and the various types of risk parameters and risk behaviors obtained constitute multi-dimensional risk factors and are stored in the data storage module;

[0035] Step S2, the comprehensive evaluation and assessment platform performs risk assessment, risk warning and risk control based on the risk sensing data acquired by the monitoring data acquisition module. Specifically, the AI ​​intelligent analysis and detection module integrates AI intelligent applications, and forms a risk warning model and risk area based on the detected risk factors and the existing risk correspondence relationship stored in the data storage module, and obtains an intelligent analysis model; thereby, the monitoring is carried out and the arrangement of the corresponding monitoring data acquisition module is adjusted;

[0036] Step S3, the multi-factor intelligent analysis module identifies key people and key units in the city based on the constructed multi-factor intelligent analysis model, screens out potential hidden dangers, and realizes the transformation from manual investigation to comprehensive perception;

[0037] Step S4, the real-time risk warning module obtains the risk sensing data in real time based on the monitoring data acquisition module, and sends it to the multi-factor intelligent analysis module for data query and analysis in combination with the multi-factor intelligent analysis model constructed by it, obtains the possible risk type and risk level parameters, and sends them to the risk warning and display module and the information release module;

[0038] Step S5, the risk warning and display module displays the risks analyzed by the comprehensive evaluation and assessment platform and issues risk warnings to the management department; the information release module issues risk warnings for the risks analyzed by the comprehensive evaluation and assessment platform;

[0039] In step S6, the risk warning and display module is used to display to the supervision and dispatching department, so as to arrange risk handling work with the supervision department and responsible department of the corresponding area, and adjust the number of staff of the corresponding risk supervision responsible department.

[0040] Preferably, the risk warning and display module includes risk handling and dispatching modules respectively arranged in the central dispatching department and each grassroots management department. The central dispatching department realizes data communication connection and command and dispatch with each grassroots management department, and each grassroots management department realizes communication connection and command and dispatch between each other, thereby establishing a comprehensive command and dispatch system that is vertically and horizontally connected.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. The risk warning system and risk warning method based on the multi-factor model of the present invention adopt the principle of multidisciplinary comprehensive model construction to carry out comprehensive shared management of the risk warning systems of multiple management departments for the acquired risk factors, thereby analyzing risks from data of multiple dimensions, making risk analysis and risk warning more accurate.

[0043] 2. The risk warning system and risk warning method constructed based on the multi-factor model of the present invention realize the vertical and horizontal connections between the comprehensive coordination department and the grassroots departments for risk elimination and reduction, thereby realizing the comprehensive coordination department for risk elimination and reduction to directly issue management orders and coordinate between different departments, reduce levels, simplify processes, and realize the improvement of daily management efficiency, unified linkage of emergency command and optimization of social governance methods.

[0044] 3. The risk warning system and risk warning method of the present invention, which are constructed based on a multi-factor model, use a medical treatment data acquisition module to obtain the types of diseases treated in each treatment hospital, the number of diseased people and the age of diseased people, and derive a disease treatment model through intelligent analysis. At the same time, the corresponding treatment data is obtained in real time. When there are abnormalities in the treatment hospital, disease type, number of diseased people and the age of diseased people, the data are provided to experts in the field of disease treatment in a timely manner, so as to timely judge the characteristics of disease transmission and the outbreak site of the disease, so as to timely block the development of the disease and provide disease risk warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0046] Figure 2 It is a schematic diagram of the data flow structure of the comprehensive evaluation and assessment platform of the present invention;

[0047] Figure 3 A schematic diagram of the data flow structure of the monitoring data acquisition module of the present invention.

[0048] In the figure: 1. Comprehensive evaluation platform; 2. Monitoring data acquisition module; 3. Data storage module; 4. Risk warning and display module; 5. Information release module; 6. Multi-factor intelligent analysis module; 7. Real-time risk warning module; 8. AI intelligent analysis and detection module; 9. Network data extraction module; 10. Street safety module; 11. Community safety monitoring network module; 12. Road safety monitoring network module; 13. Household registration data interface module; 14. Medical treatment data acquisition module; 15. Official user terminal; 16. Mass user terminal; 17. Risk processing and scheduling module. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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. Specific embodiment one:

[0051] 1. A risk early warning system based on a multi-factor model, comprising a comprehensive evaluation and assessment platform 1, a monitoring data acquisition module 2, a data storage module 3, a risk early warning and display module 4 and an information release module 5; the comprehensive evaluation and assessment platform 1 is respectively connected with the monitoring data acquisition module 2, the data storage module 3, the risk early warning and display module 4 and the information release module 5 for data communication;

[0052] The monitoring data acquisition module 2 is used to acquire risk behaviors and potential risk parameters of the monitored personnel and monitored areas. The acquired risk parameters and risk behaviors of various types constitute multi-dimensional risk factors.

[0053] The comprehensive evaluation and assessment platform 1 performs risk assessment, risk warning and risk control based on the risk sensor data acquired by the monitoring data acquisition module 2. The comprehensive evaluation and assessment platform 1 includes a multi-factor intelligent analysis module 6, a real-time risk warning module 7 and an AI intelligent analysis and detection module 8;

[0054] The multi-factor intelligent analysis module 6 identifies key people and key units in the city based on the constructed multi-factor intelligent analysis model, screens out potential hidden dangers, and realizes the transformation from manual investigation to comprehensive perception;

[0055] The real-time risk warning module 7 is based on the risk sensing data acquired in real time by the monitoring data acquisition module 2, and sends it to the multi-factor intelligent analysis module 6 for data query and analysis in combination with the multi-factor intelligent analysis model constructed by it, and obtains the possible risk type and risk level parameters, and sends them to the risk warning and display module 4 and the information release module 5;

[0056] The AI ​​intelligent analysis and detection module 8 integrates AI intelligent applications, forms a risk warning model and a risk area based on the detected risk factors and the existing risk correspondence relationship stored in the data storage module 3, and obtains an intelligent analysis model; thereby carrying out monitoring and adjusting the arrangement of the corresponding monitoring data acquisition module 2;

[0057] The monitoring data acquisition module 2 includes a network data extraction module 9, a street safety module 10, a community safety monitoring network module 11, a road safety monitoring network module 12 and a household registration data interface module 13;

[0058] The network data extraction module 9 is used to obtain news and events published on the Internet in order to extract risk factors that pose risks to the community; the street safety module 10 is a street safety camera module that has been installed in the government management department, so as to provide risk factors that pose risks to the community; the community security monitoring network module 11 is a security monitoring video system installed in the community, and the monitoring images obtained by the security monitoring video system of the community are used to provide risk factors that pose risks to the community; the road safety monitoring network module 12 is a video monitoring system installed on the road for detecting road vehicles, thereby providing data on vehicles and road conditions on the road to form risk factors on the road; the household registration data interface module 13 is used to obtain household registration data of the population, so as to provide household registration risk factors of the resident population;

[0059] The data storage module 3 is used to store the multi-dimensional risk factors obtained by the monitoring data acquisition module 2; the risk warning and display module 4 is used to display the risks analyzed by the comprehensive evaluation and assessment platform 1 and issue risk warnings to the management department; the information release module 5 is used to issue risk warnings for the risks analyzed by the comprehensive evaluation and assessment platform 1;

[0060] When the risk warning system is running to provide risk warning, the network data extraction module 9, the street safety module 10, the community safety monitoring network module 11, the road safety monitoring network module 12 and the household registration data interface module 13 respectively obtain various risk factors and store them in the data storage module 3;

[0061] The real-time risk warning module 7, multi-factor intelligent analysis module 6 and AI intelligent analysis and detection module 8 of the comprehensive evaluation and assessment platform 1 perform big data analysis based on the data stored in the data storage module 3 to obtain real-time risk warning data and social security data, and send the obtained risk warning data to the information release module 5. The information release module 5 sends the risk warning data to the regulatory responsible departments and community life personnel in the corresponding area for timely response. At the same time, the risk warning and display module 4 is used to display to the regulatory dispatching department, so as to arrange risk handling work with the regulatory departments and responsible departments in the corresponding area, and adjust the number of staff of the corresponding risk supervision responsible departments.

[0062] Preferably, the risk warning system also includes a mass user terminal 16, which can be presented in the form of an APP or a WeChat applet. The mass user terminal 16 and the monitoring data acquisition module 2 are data-communication connected, so that the public can report risk data to the monitoring data acquisition module 2 through the mass user terminal 16, and store it in the data storage module 3. The comprehensive evaluation and assessment platform 1 performs big data analysis based on the data stored in the data storage module 3 to obtain real-time risk and social security data.

[0063] Preferably, the official user terminal 15 is configured with an official account, which is connected to the risk warning system for communication and is provided to party and mass organizations and community workers for use. When official information needs to be sent out in a timely manner, the government's official information and risk information are sent to all users by selecting the broadcast mode.

[0064] Preferably, the monitoring data acquisition module 2 also includes a medical treatment data acquisition module 14, which acquires the medical treatment data of the community hospital and stores it in the data storage module 3. The AI ​​intelligent analysis and detection module 8 acquires the medical treatment data and uses the historical medical treatment data stored in the data storage module 3 to analyze the disease treatment model, which is a disease treatment model including the treatment hospital, disease type, number of disease personnel and age of disease personnel, and provides the disease treatment model to the real-time risk warning module 7, so that the real-time risk warning module 7 compares the data with the disease treatment model based on the treatment hospital, disease type, number of disease personnel and age of disease personnel of the patients obtained in real time, thereby analyzing the abnormal treatment hospital, disease type, rate of increase of disease personnel and age of disease personnel, and providing them to experts in the field of disease treatment, so as to timely judge the characteristics of disease transmission and the outbreak site of the disease, so as to timely block the development of the disease and provide disease risk warning.

[0065] Preferably, each city's responsible management department is equipped with a corresponding risk warning receiving and dispatching module. When the risk warning receiving and dispatching module receives the risk warning and risk type issued by the comprehensive evaluation and assessment platform 1, the city's responsible management department completes the corresponding risk investigation work based on its own responsibilities or progresses the risk processing when receiving the risk processing dispatching instruction issued by the comprehensive evaluation and assessment platform 1.

[0066] Preferably, the risk warning and display module 4 also includes a risk handling and scheduling module 17. When the comprehensive evaluation and assessment platform 1 detects a risk, it issues a risk warning to the risk warning and display module 4. When multiple city management departments need to jointly handle and eliminate the risk, the risk handling and scheduling module 17 coordinates the city management departments to reduce and eliminate the risk; and, if the city management department responsible for eliminating or reducing the risk is unable to complete the risk reduction or elimination work alone, a request for assistance in risk elimination or reduction is issued to other city management departments through the risk handling and scheduling module 17, thereby realizing risk command and scheduling work.

[0067] Preferably, the risk warning system also includes a process of setting key monitoring events, key monitoring areas and key monitoring personnel. Through the predetermined key monitoring events, key monitoring areas and key monitoring personnel, the corresponding monitoring data acquisition module 2 is set in the area where the key monitoring events, key monitoring areas and key monitoring personnel are located, so as to obtain the multi-dimensional risk factors, thereby monitoring the key monitoring areas to detect risks more quickly.

[0068] Preferably, the risk warning and display module 4 includes risk handling and dispatching modules 17 respectively arranged in the central dispatching department and each grassroots management department. The central dispatching department realizes data communication connection and command and dispatch with each grassroots management department, and realizes communication connection and command and dispatch between each grassroots management department, thereby establishing a comprehensive command and dispatch system that is vertically and horizontally connected. Specific embodiment 2:

[0070] A risk early warning method based on a multi-factor model, including a risk early warning system based on a multi-factor model, characterized in that it includes the following steps:

[0071] Step S1, when the risk warning system is running, the network data extraction module 9, the street safety module 10, the community safety monitoring network module 11, the road safety monitoring network module 12 and the household registration data interface module 13 respectively obtain the risk behavior and potential risk parameters of the monitored personnel and the monitored area, and the various types of risk parameters and risk behaviors obtained constitute multi-dimensional risk factors and are stored in the data storage module 3;

[0072] Step S2, the comprehensive evaluation and assessment platform 1 performs risk assessment, risk warning and risk control based on the risk sensing data acquired by the monitoring data acquisition module 2. Specifically, the AI ​​intelligent analysis and detection module 8 integrates AI intelligent applications, and forms a risk warning model and a risk area based on the detected risk factors and the existing risk correspondence relationship stored in the data storage module 3, and obtains an intelligent analysis model; thereby carrying out implementation monitoring and adjusting the corresponding arrangement of the monitoring data acquisition module 2;

[0073] Step S3, the multi-factor intelligent analysis module 6 identifies key people and key units in the city based on the constructed multi-factor intelligent analysis model, screens out potential hidden dangers, and realizes the transformation from manual investigation to comprehensive perception;

[0074] Step S4, the real-time risk warning module 7 obtains the risk sensing data in real time based on the monitoring data acquisition module 2, and sends it to the multi-factor intelligent analysis module 6 for data query and analysis in combination with the multi-factor intelligent analysis model constructed by it, obtains the possible risk type and risk level parameters, and sends them to the risk warning and display module 4 and the information release module 5;

[0075] Step S5, the risk warning and display module 4 displays the risks analyzed by the comprehensive evaluation and assessment platform 1, and issues risk warnings to the management department; the information release module 5 issues risk warnings for the risks analyzed by the comprehensive evaluation and assessment platform 1;

[0076] In step S6, the risk warning and display module 4 is used to display to the supervision and dispatching department, so as to arrange risk handling work with the supervision department and responsible department of the corresponding area, and adjust the number of staff of the corresponding risk supervision responsible department.

[0077] Preferably, the risk warning and display module 4 includes risk handling and dispatching modules 17 respectively arranged in the central dispatching department and each grassroots management department. The central dispatching department realizes data communication connection and command and dispatch with each grassroots management department, and realizes communication connection and command and dispatch between each grassroots management department, thereby establishing a comprehensive command and dispatch system that is vertically and horizontally connected.

[0078] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0079] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A risk early warning system based on a multi-factor model, comprising a comprehensive evaluation and assessment platform (1), a monitoring data acquisition module (2), a data storage module (3), a risk early warning and display module (4) and an information release module (5); the comprehensive evaluation and assessment platform (1) is respectively connected to the monitoring data acquisition module (2), the data storage module (3), the risk early warning and display module (4) and the information release module (5) by data communication; in, The monitoring data acquisition module (2) is used to acquire risk behaviors and potential risk parameters of the monitored personnel and monitored areas. The acquired risk parameters and risk behaviors of various types constitute multi-dimensional risk factors. The comprehensive evaluation and assessment platform (1) performs risk assessment, risk warning and risk control based on the risk sensing data acquired by the monitoring data acquisition module (2), and the comprehensive evaluation and assessment platform (1) comprises a multi-factor intelligent analysis module (6), a real-time risk warning module (7) and an AI intelligent analysis and detection module (8); The multi-factor intelligent analysis module (6) identifies key individuals and key units in the city based on the constructed multi-factor intelligent analysis model, screens out potential hidden dangers, and realizes the transformation from manual investigation to comprehensive perception; The real-time risk warning module (7) is based on the risk sensing data acquired in real time by the monitoring data acquisition module (2), and sends it to the multi-factor intelligent analysis module (6) for data query and analysis in combination with the multi-factor intelligent analysis model constructed by it, and obtains the possible risk type and risk level parameters, and sends them to the risk warning and display module (4) and the information release module (5); The AI ​​intelligent analysis and detection module (8) integrates AI intelligent applications, forms a risk warning model and a risk area based on the detected risk factors and the existing risk correspondence relationship stored in the data storage module (3), and obtains an intelligent analysis model; thereby carrying out monitoring and adjusting the arrangement of the corresponding monitoring data acquisition module (2); the monitoring data acquisition module (2) includes a network data extraction module (9), a street safety module (10), a community safety monitoring network module (11), a road safety monitoring network module (12) and a household registration data interface module (13); The network data extraction module (9) is used to obtain news and events published on the Internet so as to extract risk factors that pose risks to the community; The street safety module (10) is a street safety camera module installed in a government management department, so as to provide risk factors for the community streets; the community safety monitoring network module (11) is a security monitoring video system installed in the community, and the monitoring images obtained by the security monitoring video system of the community are used to provide risk factors for the community; the road safety monitoring network module (12) is a video monitoring system installed on the road for detecting road vehicles, thereby providing data on vehicles and road conditions on the road, forming risk factors on the road; The household registration data interface module (13) is used to obtain household registration data of the population so as to provide household registration risk factors of the resident population; The data storage module (3) is used to store the multi-dimensional risk factors acquired by the monitoring data acquisition module (2); the risk warning and display module (4) is used to display the risks analyzed by the comprehensive evaluation and assessment platform (1) and issue risk warnings to the management department; The information release module (5) is used to release risk warnings for the risks analyzed by the comprehensive evaluation and assessment platform (1); Features: When the risk warning system is in operation and performing risk warning, the network data extraction module (9), the street safety module (10), the community safety monitoring network module (11), the road safety monitoring network module (12) and the household registration data interface module (13) respectively obtain various risk factors and store them in the data storage module (3); The real-time risk warning module (7), multi-factor intelligent analysis module (6) and AI intelligent analysis and detection module (8) of the comprehensive evaluation and assessment platform (1) perform big data analysis based on the data stored in the data storage module (3) to obtain real-time risk warning data and social security data, and send the obtained risk warning data to the information release module (5). The information release module (5) sends the risk warning data to the supervisory responsible departments and community life personnel in the corresponding area for timely response. At the same time, the risk warning and display module (4) is used to display to the supervisory dispatching department so as to arrange risk handling work with the supervisory departments and responsible departments in the corresponding area and adjust the number of staff of the corresponding risk supervision responsible departments.

2. The risk early warning system based on a multi-factor model according to claim 1, characterized in that: The risk warning system also includes a mass user terminal (16), which is in communication connection with the risk warning system. The mass user terminal (16) can be presented in the form of an APP or a WeChat applet. The mass user terminal (16) is in data communication connection with the monitoring data acquisition module (2), so that the masses can report risk data to the monitoring data acquisition module (2) through the mass user terminal (16) and store it in the data storage module (3). The comprehensive evaluation and assessment platform (1) performs big data analysis based on the data stored in the data storage module (3) to obtain real-time risk and social security data.

3. The risk early warning system based on a multi-factor model according to claim 2 is characterized in that: The official user terminal (15) is configured with an official account, which is connected to the risk warning system and is provided to party and mass organizations and community workers for use. When official information needs to be sent out in a timely manner, the government's official information and risk information can be sent to all users by selecting the broadcast mode.

4. The risk early warning system based on a multi-factor model according to claim 1, characterized in that: The monitoring data acquisition module (2) also includes a medical treatment data acquisition module (14), wherein the medical treatment data acquisition module (14) acquires the medical treatment data of the community hospital and stores it in the data storage module (3); the AI ​​intelligent analysis and detection module (8) acquires the medical treatment data and uses the existing historical medical treatment data stored in the data storage module (3) to analyze a disease treatment model, wherein the disease treatment model is a disease treatment model including a treatment hospital, a disease type, a number of diseased personnel and an age of the diseased personnel, and provides the disease treatment model to the real-time risk warning module (7); thereby, the real-time risk warning module (7) compares the data with the disease treatment model based on the treatment hospital, disease type, number of diseased personnel and age of the diseased personnel obtained in real time, thereby analyzing the abnormal treatment hospital, disease type, rate of increase of diseased personnel and age of the diseased personnel, and provides the data to experts in the field of disease treatment, so as to timely judge the characteristics of disease transmission and the outbreak site of the disease, so as to timely block the development of the disease and provide a disease risk warning.

5. The risk early warning system based on a multi-factor model according to claim 1, characterized in that: Each city's responsible management department is equipped with a corresponding risk warning receiving and dispatching module. When the risk warning receiving and dispatching module receives the risk warning and risk type issued by the comprehensive evaluation and assessment platform (1), the city's responsible management department completes the corresponding risk investigation work based on its own responsibilities or progresses the risk processing when receiving the risk processing dispatching instructions issued by the comprehensive evaluation and assessment platform (1).

6. The risk early warning system based on a multi-factor model according to claim 5 is characterized in that: The risk warning and display module (4) also includes a risk handling and scheduling module (17). When the comprehensive evaluation and assessment platform (1) detects a risk, it issues a risk warning to the risk warning and display module (4). When multiple city management departments need to jointly handle and eliminate the risk, the risk handling and scheduling module (17) coordinates the city management departments to reduce and eliminate the risk. Furthermore, if the city management department responsible for eliminating or reducing the risk is unable to complete the risk reduction or elimination work alone, a request for assistance in risk elimination or reduction is issued to other city management departments through the risk handling and scheduling module (17), thereby realizing risk command and scheduling work.

7. The risk early warning system based on a multi-factor model according to claim 6 is characterized in that: The risk warning system also includes a process of setting key monitoring events, key monitoring areas and key monitoring personnel. By pre-determining key monitoring events, key monitoring areas and key monitoring personnel, corresponding monitoring data acquisition modules (2) are set in the areas where the key monitoring events, key monitoring areas and key monitoring personnel are located, so as to obtain the multi-dimensional risk factors, thereby monitoring the key monitoring areas to detect risks more quickly.

8. The risk early warning system based on a multi-factor model according to claim 6 is characterized in that: The risk warning and display module (4) includes risk handling and dispatching modules (17) respectively arranged in the central dispatching department and each grassroots management department. The central dispatching department realizes data communication connection and command and dispatch with each grassroots management department, and each grassroots management department realizes communication connection and command and dispatch among itself, thereby establishing a comprehensive command and dispatch system that is vertically connected and horizontally connected.

9. A risk warning method based on a multi-factor model, comprising a risk warning system based on a multi-factor model as claimed in any one of claims 1 to 8, characterized in that: The steps include: Step S1, when the risk warning system is in operation, the network data extraction module (9), the street safety module (10), the community safety monitoring network module (11), the road safety monitoring network module (12) and the household registration data interface module (13) respectively obtain the risk behaviors and potential risk parameters of the monitored personnel and the monitored areas, and the obtained multiple types of risk parameters and risk behaviors constitute multi-dimensional risk factors and are stored in the data storage module (3); Step S2, the comprehensive evaluation and assessment platform (1) performs risk assessment, risk warning and risk control based on the risk sensing data acquired by the monitoring data acquisition module (2). Specifically, the AI ​​intelligent analysis and detection module (8) integrates AI intelligent applications, and forms a risk warning model and a risk area based on the detected risk factors and the existing risk correspondence relationship stored in the data storage module (3), and obtains an intelligent analysis model; thereby carrying out monitoring and adjusting the arrangement of the corresponding monitoring data acquisition module (2); Step S3, the multi-factor intelligent analysis module (6) identifies key individuals and key units in the city based on the constructed multi-factor intelligent analysis model, and screens out potential hidden dangers, thus realizing the transition from manual investigation to comprehensive perception; Step S4, the real-time risk warning module (7) is based on the risk sensing data acquired in real time by the monitoring data acquisition module (2), and sends it to the multi-factor intelligent analysis module (6) for data query and analysis in combination with the multi-factor intelligent analysis model constructed by it, and obtains the possible risk type and risk level parameters, and sends them to the risk warning and display module (4) and the information release module (5); Step S5, the risk warning and display module (4) displays the risks analyzed by the comprehensive evaluation and assessment platform (1) and issues a risk warning to the management department; The information release module (5) releases risk warnings for the risks analyzed by the comprehensive evaluation and assessment platform (1); In step S6, the risk warning and display module (4) is used to display to the supervision and dispatching department, so as to arrange risk handling work with the supervision department and responsible department of the corresponding area, and adjust the number of staff of the corresponding risk supervision responsible department.

10. A risk early warning method based on multi-factor model construction according to claim 9, characterized in that: The risk warning and display module (4) includes risk handling and dispatching modules (17) respectively arranged in the central dispatching department and each grassroots management department. The central dispatching department realizes data communication connection and command and dispatch with each grassroots management department, and each grassroots management department realizes communication connection and command and dispatch among itself, thereby establishing a comprehensive command and dispatch system that is vertically connected and horizontally connected.

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