CN114358461A - Risk early warning system and risk early warning method constructed based on multi-factor model - Google Patents
Risk early warning system and risk early warning method constructed based on multi-factor model Download PDFInfo
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Abstract
The invention discloses a risk early warning system constructed based on a multi-factor model, which comprises a comprehensive evaluation and evaluation 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 evaluation platform (1) is respectively in data communication connection 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). According to the risk early warning system and the risk early warning method based on multi-factor model construction, a multi-disciplinary comprehensive model construction principle is adopted, and the acquired risk early warning systems of multiple management departments of risk factors are subjected to comprehensive sharing management, so that risks are analyzed from data of multiple dimensions, and risk analysis and risk early warning are more accurate.
Description
Technical Field
The invention relates to the technical field of intelligent security and smart cities, in particular to a risk early warning system and a risk early warning method which are constructed based on a multi-factor model.
Background
Along with the rapid development of the urbanization process of China, cities are getting bigger and bigger, and the urban things need to be managed and predicted in advance so as to ensure the peace and stability of the cities. On the one hand, the daily operation of the city includes the operation of various cities such as daily life, daily community security, urban traffic, urban community health and the like. In the traditional city management, daily community security channels are managed by public security of communities, city traffic is managed by a city traffic management department, and the community health of cities is managed by community health hospitals and health departments; therefore, each management and responsible part of each city manages and is responsible for the city independently, and no interaction and interaction process is performed by each department, but in the actual city management and operation, the management and work of each department are lack of harmony, so that the work execution efficiency is low, the response is slow, and the fast risk early warning and risk control of the city management are not facilitated; on one hand, the emergency and the risk situation usually have certain relevance or are called as a premonitory, so if risk early warning and risk monitoring can be carried out on the relevant area, certain advanced deployment is carried out before the emergency situation is found, the influence of the emergency situation on the normal operation of the city can be reduced to a great extent, or the emergency situation can be recovered as soon as possible when the emergency situation is met.
In view of the above situation, there is also a system called city brain in the prior art, which is a comprehensive city detection and evaluation system, and can monitor multiple factors of a city at the same time, and comprehensively consider and analyze potential risk conditions of the city based on the multiple factors, so that the system has a very valuable system; such as:
for example, patent application CN112820415A discloses a system and method for analyzing chronic disease spatial and temporal evolution characteristics and monitoring environmental health risks based on a GIS, which can realize the analysis of chronic disease spatial and temporal evolution characteristics and the monitoring of environmental health risks, on one hand, the invention combines the traditional chronic disease management method with the GIS, can identify the spatial heterogeneity characteristics of chronic diseases, and make regional control measures; on the other hand, the chronic disease is influenced by various environmental elements, and the combination of the geographic detector and the Bayesian time-space interaction model can not only analyze the influence of a single factor, but also detect the influence mode of double-factor interaction and multi-factor synergy on the chronic disease. The invention can be used for monitoring and early warning of chronic diseases closely related to environmental health.
Patent application CN 110443528A discloses an enterprise risk quantitative evaluation and tracking system based on machine learning, which is a system integrating risk factor identification, risk evaluation, risk tracking and early warning, and specifically comprises a risk quantitative evaluation subsystem, an investment project value evaluation subsystem, a bond risk quantitative evaluation subsystem and a risk early warning tracking subsystem. The system is characterized in that the system is based on data of an original point parameter big data platform, potential risk factors possibly existing in a target enterprise are automatically identified and judged by utilizing a machine learning algorithm, a risk assessment model suitable for the target enterprise is automatically called through analysis of basic information of a company, risk quantitative assessment and real-time tracking early warning of the target enterprise are achieved, and a reliable and practical tool is provided for investors.
Patent application CN113360830A discloses a method for identifying and evaluating major safety risks of metal smelting enterprises. Collecting accident case data of a metal smelting enterprise, analyzing the accident case, and searching risk factors related to accidents; dividing risk units according to a metal smelting process, and compiling a general risk identification list of a metal smelting enterprise; forming a general risk and hidden danger violation evidence information list; dividing a risk evaluation unit by taking a smelting process as a unit and taking a risk point as an evaluation main line; establishing a high-risk inherent risk index system of a metal smelting enterprise, and calculating the inherent risk index of a risk point through the established evaluation model of the metal smelting enterprise; unit inherent risk assessment, unit risk frequency determination, unit initial high-risk safety risk assessment and dynamic risk factor identification; unit risk is aggregated to enterprise risk. The invention improves the intrinsic safety degree and the safety management level of metal smelting enterprises, prevents serious accidents and lightens the accident harm consequences.
Patent application CN112712903A discloses an infectious disease monitoring method based on human-machine three-dimensional space cooperative sensing. The method comprises the following steps: collecting social space monitoring data, information space monitoring data and physical space monitoring data in an online and offline combined mode to construct a ternary space data set; processing the ternary spatial data set to extract keywords and classifications related to infectious diseases and locate geographic locations for data sources; and establishing a monitoring and early warning model to analyze the risk degree of the infectious diseases in different space-time ranges and perform epidemic risk early warning by combining various risk characteristic factors. The invention collects relevant data in time by combining online and offline modes, dynamically monitors the state of the infectious disease in real time by finishing the cooperative perception of space-time coverage and target coverage, and can accurately and timely carry out infectious disease early warning.
The patent CN111882830A discloses a method, a device, a system and a storage medium for monitoring, forecasting and early warning of urban waterlogging, wherein the method comprises the following steps: monitoring accumulated water depth data by waterlogging monitoring equipment; the video gateway equipment sends a request for acquiring actually-measured rainfall data to the cloud server and receives the actually-measured rainfall data sent by the cloud server; the video gateway equipment carries out waterlogging simulation edge calculation on the current waterlogging monitoring point according to the actually measured rainfall data and the monitored waterlogging water depth data to obtain the forecast maximum waterlogging depth, judges whether the current waterlogging monitoring point has a waterlogging risk or not and feeds back a waterlogging risk judgment result to the cloud server; and if the waterlogging risk exists, carrying out on-site snapshot, sending an early warning instruction to waterlogging early warning equipment, and displaying alarm information by the waterlogging early warning equipment. According to the invention, the waterlogging simulation calculation is carried out through the video gateway equipment at the front end, so that the real-time performance of waterlogging forecast and early warning is improved, the calculation pressure of the cloud server is reduced, and the requirement on communication bandwidth is lowered.
Patent CN110427406A discloses a method and device for mining the relationship between people related to organization. The method comprises the following steps: acquiring all dimension data information sets of natural people related to an organization and the organization to which the natural people belong; acquiring a feature subset of each dimension of an organization to which the personnel belong after clustering according to natural person names or other attribute information; combining organizational mechanisms to which the same kind of natural people belong, and performing vector transformation according to the similarity characteristic of each combination; training a classification model of the same-name person according to the similarity vector, and predicting a classification result by using the model; and according to the classification result, merging the same natural person, and aggregating the associated natural person, the organization to which the natural person belongs and the associated organization data set to generate the related personnel relationship structure of the organization. The embodiment of the invention can accurately and visually dig out the mutual relation of related personnel of different organizations, thereby meeting the requirement of establishing the relation among the related personnel of isolated and dispersed organizations.
It can be seen that, currently, in the field of community life risk control and early warning, many existing technologies have appeared, and hope is to acquire information through a related monitoring system so as to perform rapid risk processing, but the following defects also exist:
1. in the prior art, a community risk environment reinforcement learning training model is generally learned, optimized and controlled by using self-collected data, the processing of the data is rarely knowledge assistance of risk factors across departments, and basically, all management departments analyze and judge according to respective sensing data and find risks which are responsible for processing by themselves and find risk early warning, but in reality, the early warning of the risks can be accurately judged after the risk factors in all aspects are comprehensively considered, so that a risk early warning obtaining and judging method in the prior art is not accurate;
2. in the prior art, because the respective data acquired by a plurality of departments are acquired, when the risk of urban operation work needs to be comprehensively judged or the risk is detected, how to share the acquired various risk parameter data among the management modules is a difficult problem, and particularly, the processing and risk reduction after the risk early warning of each department are carried out. However, in the prior art, since the departments are separated, the coordination of risk processing is difficult, and particularly, the risk investigation of the management department needs to be performed according to the risk early warning provided by the opposite party.
In the prior art, no system for specially analyzing data of disease treatment, particularly infectious diseases, exists, and in fact, the most initial explosion point of many diseases, particularly infectious diseases, is a small area, which has the characteristics of concentration and disease condition.
In view of the above technical problems, it is desirable to provide a comprehensive risk early warning system and method capable of acquiring various city parameters and forming a plurality of risk factors to be detected simultaneously, so as to provide early risk early warning and clear risk in time. However, the prior art has not provided an effective solution to the above technical problem.
In view of the above technical problems, it is desirable to provide a method and a system for assisting cross-domain knowledge based on neural network and deep learning to solve the above technical problems.
Disclosure of Invention
In view of the above technical problems, an object of the present invention is to provide a risk early warning system and a risk early warning method constructed based on a multi-factor model, so as to solve the problems proposed in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
a risk early warning system constructed based on a multi-factor model comprises a comprehensive evaluation and evaluation 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 evaluation platform is in data communication connection with the monitoring data acquisition module, the data storage module, the risk early warning and display module and the information release module respectively;
the monitoring data acquisition module is used for acquiring risk behaviors and potential risk parameters of monitoring personnel and a monitoring area, and the acquired risk parameters and risk behaviors of various types form a multi-dimensional risk factor;
the comprehensive evaluation and evaluation platform carries out risk evaluation, risk early warning and risk control on the basis of risk sensing data acquired by the monitoring data acquisition module, and comprises a multi-factor intelligent analysis module, a real-time risk early warning module and an AI intelligent analysis and detection module;
the multi-factor intelligent analysis module finds key people and key units in the whole market based on the constructed multi-factor intelligent analysis model, screens out potential hidden danger events and realizes the change from manual scheduling to comprehensive perception;
the real-time risk early warning module is used for acquiring risk sensing data in real time based on the monitoring data acquisition module, sending the risk sensing data to the multi-factor intelligent analysis module to perform data query and analysis by combining the multi-factor intelligent analysis module with the multi-factor intelligent analysis model constructed by the multi-factor intelligent analysis module, obtaining possible risk types and risk grade parameters, and sending the risk types and risk grade parameters to the risk early warning and display module and the information release module;
the AI intelligent analysis and detection module fuses AI intelligent application, and a risk early warning model and a risk area are formed based on the detected risk factors and the existing risk corresponding relation stored in the data storage module to obtain an intelligent analysis model; thereby carrying out implementation monitoring and adjusting the arrangement of the corresponding monitoring data acquisition modules;
the monitoring data acquisition module comprises a network data extraction module, a street safety module, a community safety monitoring network module, a road safety monitoring network module and an housekeeping data interface module;
the network data extraction module is used for acquiring news and events published on the Internet so as to extract risk factors forming risks to communities; the street safety module is a street safety camera module which is arranged in a government administration department and is set so as to provide risk factors for the social streets; the community safety monitoring network module is a safety monitoring video system arranged in a community, and provides a risk factor for forming a risk to the community through a monitoring image acquired by the safety monitoring video system of the community; the road safety monitoring network module is a video monitoring system which is arranged on a road and is used for detecting road vehicles, so that data of the vehicles and road conditions on the road are provided, and risk factors on the road are formed; the household data interface module is used for acquiring household data of population so as to provide household risk factors of the resident population;
the data storage module is used for storing the multidimensional risk factors acquired by the monitoring data acquisition module; the risk early warning and displaying module is used for displaying the risk analyzed by the comprehensive evaluation and evaluation platform and sending a risk early warning to a management department; the information issuing module is used for issuing risk early warning on the risk analyzed by the comprehensive evaluation and evaluation platform;
when the risk early warning system operates to carry out risk early warning, the network data extraction module, the street safety module, the cell safety monitoring network module, the road safety monitoring network module and the household data interface module respectively acquire various risk factors and store the risk factors in the data storage module;
the real-time risk early warning module, the multi-factor intelligent analysis module and the AI intelligent analysis detection module of the comprehensive evaluation and evaluation platform perform big data analysis based on data stored in the data storage module to obtain real-time risk early warning data and social security data, and send the obtained risk early warning data to the information publishing module, the information publishing module sends the risk early warning data to supervision responsibility departments and community living personnel in corresponding areas so as to respond in time, and the risk early warning and displaying module is used for displaying for supervision and scheduling departments so as to arrange risk processing work with the supervision departments and departments in the corresponding areas and adjust the number of working personnel of the corresponding risk supervision responsibility departments and the corresponding community living personnel.
Preferably, the risk early warning system further comprises a crowd user side, the crowd user side can be in an APP form or a WeChat applet form, the crowd user side is in data communication connection with the monitoring data acquisition module, so that a crowd can report risk data to the monitoring data acquisition module through the crowd user side and store the risk data in the data storage module, and the comprehensive evaluation platform performs big data analysis based on the data stored in the data storage module to obtain real-time risk and social security data.
Preferably, the official user side is configured with an official account number of an official party, and the official account number is configured for use by members of the group and community staff.
Preferably, the monitoring data acquiring module further comprises a medical treatment data acquiring module, the medical treatment data acquiring module acquires medical treatment data of a community hospital and stores the medical treatment data in the data storage module, the AI intelligent analysis and detection module analyzes a disease treatment model of the area based on the acquired medical treatment data by using historical medical treatment data stored in the data storage module, the disease treatment model is a disease treatment model including a treatment hospital, a disease type, the number of patients and the age of the patients, and provides the disease treatment model to the real-time risk early warning module, so that the real-time risk early warning module performs data comparison based on the treatment hospital, the disease type, the number of patients and the age of the patients obtained in real time and the disease treatment model, thereby analyzing abnormal treatment hospitals, abnormal treatment types, abnormal patients, abnormal treatment types, disease type, increasing speed of disease personnel and age of disease personnel, and providing the disease type, increasing speed of disease personnel and age of disease personnel to experts in the field of responding to disease treatment so as to judge the spreading characteristics of diseases and the outbreak place of diseases in time, so as to block the development of diseases in time and provide early warning of disease risk.
Preferably, each city responsible management department is provided with a corresponding risk early warning receiving and scheduling module, and when receiving a risk early warning and a risk type sent by the comprehensive evaluation and evaluation platform, the city responsible management department completes corresponding risk troubleshooting work based on the responsibility of the city responsible management department or receives a scheduling instruction of risk processing sent by the comprehensive evaluation and evaluation platform for progress risk processing.
Preferably, the risk early warning and display module further comprises a risk processing and scheduling module, when the comprehensive evaluation and evaluation platform monitors a risk, the risk early warning module sends a risk early warning to the risk early warning and display module, and when a plurality of city responsible management departments need to jointly process and eliminate the risk, the risk processing and scheduling module coordinates each city responsible management department to reduce and eliminate the risk; and the city responsible management department which is responsible for eliminating or reducing the risk can not finish the risk reduction or elimination work independently, and the risk processing and scheduling module sends out a risk elimination or reduction assistance request to other city responsible management departments, thereby realizing the risk command and scheduling work.
Preferably, the risk early warning system further includes a process of setting a key monitoring event, a key monitoring area and a key monitoring person, and the corresponding monitoring data acquisition modules are set in the areas where the key monitoring event, the key monitoring area and the key monitoring person are located through the predetermined key monitoring event, the key monitoring area and the key monitoring person, so as to acquire the multidimensional risk factors, thereby monitoring the key area and finding the risk more quickly.
Preferably, the risk early warning and display module comprises risk processing scheduling modules respectively arranged in a central scheduling department and each basic level management department, the central scheduling department realizes data communication connection and command scheduling with each basic level management department, and communication connection and command scheduling are realized among the basic level management departments, so that a comprehensive command scheduling system with longitudinal communication and transverse communication is established.
In addition, on the other hand, the application also provides a risk early warning method based on multi-factor model construction, which comprises a risk early warning system based on multi-factor model construction, and is characterized by comprising the following steps:
step S1, when the risk early warning system is in operation, the network data extraction module, the street safety module, the cell safety monitoring network module, the road safety monitoring network module and the household data interface module respectively acquire risk behaviors and potential risk parameters of monitoring personnel and monitoring areas, and the acquired risk parameters and risk behaviors form multi-dimensional risk factors and are stored in the data storage module;
step S2, the comprehensive evaluation and evaluation platform carries out risk evaluation, risk early 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 fuses AI intelligent application, and a risk early warning model and a risk area are formed based on the detected risk factors and the existing risk corresponding relation stored in the data storage module, so as to obtain an intelligent analysis model; so as to carry out monitoring and adjust the arrangement of the corresponding monitoring data acquisition module;
step S3, the multi-factor intelligent analysis module finds accurate key persons and key units in the whole market based on the constructed multi-factor intelligent analysis model, screens out potential hidden danger events and realizes the change from manual scheduling to comprehensive perception;
step S4, the real-time risk early warning module is based on the risk sensing data acquired by the monitoring data acquisition module in real time, and sends the risk sensing data to the multi-factor intelligent analysis module to perform data query and analysis in combination with the multi-factor intelligent analysis model constructed by the multi-factor intelligent analysis module, so as to obtain the risk types and risk grade parameters which may occur, and sends the risk types and risk grade parameters to the risk early warning and display module and the information release module;
step S5, the risk early warning and display module displays the risk analyzed by the comprehensive evaluation and evaluation platform and sends out risk early warning to a management department; the information issuing module performs issuing risk early warning on the risk analyzed by the comprehensive evaluation and evaluation platform;
and step S6, the risk early warning and display module is used for displaying to a supervision and scheduling department so as to arrange risk processing work with the supervision department and the responsibility department in the corresponding area and adjust the number of staff of the corresponding risk supervision responsibility department and the corresponding responsibility department.
Preferably, the risk early warning and display module comprises risk processing scheduling modules respectively arranged in a central scheduling department and each basic level management department, the central scheduling department realizes data communication connection and command scheduling with each basic level management department, and communication connection and command scheduling are realized among the basic level management departments, so that a comprehensive command scheduling system with longitudinal communication and transverse communication is established.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the risk early warning system and the risk early warning method based on multi-factor model construction, a multi-disciplinary comprehensive model construction principle is adopted, and the acquired risk early warning systems of multiple management departments of risk factors are subjected to comprehensive sharing management, so that risks are analyzed from data of multiple dimensions, and risk analysis and risk early warning are more accurate.
The risk early warning system and the risk early warning method which are constructed based on the multi-factor model realize the longitudinal communication and the transverse communication for eliminating and reducing the risk of the comprehensive coordination department and each basic department, thereby realizing the direct issuing of the management command by the comprehensive coordination department for eliminating and reducing the risk, the coordination between different departments, the reduction of the hierarchy and the simple flow, the improvement of the daily management efficiency, the unified linkage of emergency command and the optimization of the social management mode.
The invention relates to a risk early warning system and a risk early warning method constructed based on a multi-factor model, which utilize a medical treatment data acquisition module to acquire the types of diseases to be treated, the number of disease personnel and the ages of the disease personnel in each treatment hospital, acquire a disease treatment model through intelligent analysis, acquire corresponding treatment data in real time, and provide the treatment data to experts responding to the disease treatment field in time when the treatment hospitals, the types of diseases, the number of disease personnel and the ages of the disease personnel are abnormal, so as to judge the propagation characteristics of the diseases and the outbreak places of the diseases in time, so as to block the development of the diseases in time and provide disease risk early warning.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a schematic diagram of a data flow structure of the comprehensive evaluation platform according to the present invention;
FIG. 3 is a schematic diagram of a data flow structure of a monitoring data acquisition module according to the present invention.
In the figure: 1. a comprehensive evaluation platform; 2. a monitoring data acquisition module; 3. a data storage module; 4. a risk early warning and display module; 5. an information release module; 6. a multi-factor intelligent analysis module; 7. a real-time risk early warning module; 8. an AI intelligent analysis detection module; 9. a network data extraction module; 10. a street security module; 11. a cell safety monitoring network module; 12. a road safety monitoring network module; 13. a household data interface module; 14. a medical treatment data acquisition module; 15. an official user side; 16. a public user side; 17. and a risk processing scheduling module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
1. a risk early warning system constructed based on a multi-factor model comprises a comprehensive evaluation 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 evaluation platform 1 is respectively in data communication connection 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;
the monitoring data acquisition module 2 is used for acquiring risk behaviors and potential risk parameters of monitoring personnel and a monitoring area, and the acquired risk parameters and risk behaviors of various types form a multi-dimensional risk factor;
the comprehensive evaluation and evaluation platform 1 carries out risk evaluation, risk early warning and risk control on the basis of risk sensing data acquired by the monitoring data acquisition module 2, and the comprehensive evaluation and evaluation platform 1 comprises a multi-factor intelligent analysis module 6, a real-time risk early warning module 7 and an AI intelligent analysis detection module 8;
the multi-factor intelligent analysis module 6 finds key people and key units in the whole city based on the constructed multi-factor intelligent analysis model, screens out potential hidden danger events and realizes the change from manual scheduling to comprehensive perception;
the real-time risk early warning module 7 is used for sending risk sensing data acquired in real time by the monitoring data acquisition module 2 to the multi-factor intelligent analysis module 6 to perform data query and analysis by combining the multi-factor intelligent analysis model constructed by the multi-factor intelligent analysis module, obtaining possible risk types and risk grade parameters and sending the risk types and the risk grade parameters to the risk early warning and display module 4 and the information release module 5;
the AI intelligent analysis and detection module 8 integrates AI intelligent application, and forms a risk early warning model and a risk area based on the detected risk factors and the existing risk corresponding relation stored in the data storage module 3 to obtain an intelligent analysis model; so as to carry out monitoring and adjust the arrangement of the corresponding monitoring data acquisition module 2;
the monitoring data acquisition module 2 comprises a network data extraction module 9, a street safety module 10, a cell safety monitoring network module 11, a road safety monitoring network module 12 and an interface module 13 of household data;
the network data extraction module 9 is configured to acquire news and events published on the internet, so as to extract risk factors constituting risks to communities; the street safety module 10 is a street safety camera module which is arranged in a government administration department and is set so as to provide risk factors for social streets; the cell security monitoring network module 11 is a security monitoring video system arranged in a cell, and provides a risk factor for forming a risk to a community through a monitoring image obtained by the security monitoring video system of the cell; the road safety monitoring network module 12 is a video monitoring system arranged on a road and used for detecting vehicles on the road, so as to provide data of the vehicles and road conditions on the road and form risk factors on the road; the household data interface module 13 is used for acquiring household data of population so as to provide household risk factors of the resident population;
the data storage module 3 is used for storing the multidimensional risk factors acquired by the monitoring data acquisition module 2; the risk early warning and displaying module 4 is used for displaying the risk analyzed by the comprehensive evaluation and evaluation platform 1 and sending a risk early warning to a management department; the information release module 5 is used for performing release risk early warning on the risk analyzed by the comprehensive evaluation and evaluation platform 1;
when the risk early warning system operates to carry out risk early warning, the network data extraction module 9, the street safety module 10, the cell safety monitoring network module 11, the road safety monitoring network module 12 and the household data interface module 13 respectively acquire various risk factors and store the risk factors in the data storage module 3;
the real-time risk early warning module 7, the multi-factor intelligent analysis module 6 and the AI intelligent analysis detection module 8 of the comprehensive evaluation and evaluation platform 1 perform big data analysis based on the data stored in the data storage module 3 to obtain real-time risk early warning data and social security data, and send the obtained risk early warning data to the information publishing module 5, the information publishing module 5 sends the risk early warning data to supervision responsibilities and community life personnel in corresponding areas so as to respond in time, and the risk early warning and displaying module 4 is used for displaying the risk early warning and displaying data to a supervision and scheduling department so as to arrange risk processing work with the supervision departments and the responsibilities in the corresponding areas and adjust the number of the staff of the corresponding risk supervision responsibilities and the corresponding risk supervision departments.
Preferably, the risk early warning system further comprises a crowd user side 16, the crowd user side 16 can be in an APP form or a micro message applet form, the crowd user side 16 is in data communication connection with the monitoring data acquisition module 2, so that the crowd can report risk data to the monitoring data acquisition module 2 through the crowd user side 16 and store the risk data in the data storage module 3, and the comprehensive evaluation and evaluation platform 1 performs big data analysis based on the storage in the data storage module 3 to obtain real-time risk and social security data.
Preferably, the official user terminal 15 is configured with an official account number, is in communication connection with the risk early warning system, is configured for use by a party organization and community staff, and sends the official information and the risk information of the government to all users to transmit the sound to all the users by selecting a broadcast mode when the official information needs to be sent out in time.
Preferably, the monitoring data obtaining module 2 further comprises a medical treatment data obtaining module 14, the medical treatment data obtaining module 14 obtains medical treatment data of a community hospital and stores the medical treatment data in the data storage module 3, the AI intelligent analysis and detection module 8 analyzes a disease treatment model of the area by using historical medical treatment data stored in the data storage module 3 based on the obtained medical treatment data, the disease treatment model is a disease treatment model including a treatment hospital, a disease type, the number of disease staff and the age of the disease staff and provides the disease treatment model to the real-time risk early warning module 7, so that the real-time risk early warning module 7 performs data comparison based on the treatment hospital, the disease type, the number of disease staff and the age of the disease staff of the treatment patient and the disease treatment model obtained in real time, therefore, abnormal treatment hospitals, disease types, disease person increasing speeds and the ages of the disease persons are analyzed and provided for experts in the field of responding to disease treatment, so that the propagation characteristics of diseases and the disease outbreak places can be judged in time, the development of the diseases can be blocked in time, and disease risk early warning is provided.
Preferably, each city responsible management department is provided with a corresponding risk early warning receiving and scheduling module 17, and when the risk early warning receiving and scheduling module 17 receives a risk early warning and a risk type sent by the comprehensive evaluation and evaluation platform 1, the city responsible management department completes corresponding risk investigation work based on its own responsibility or performs risk processing when receiving a scheduling instruction of risk processing sent by the comprehensive evaluation and evaluation platform 1.
Preferably, the risk early warning and display module 4 further includes a risk processing scheduling module 17, when the comprehensive evaluation and evaluation platform 1 monitors a risk, the risk early warning module sends a risk early warning to the risk early warning and display module 4, and when a plurality of city responsible management departments need to jointly process and eliminate the risk, the risk processing scheduling module 17 coordinates each city responsible management department to reduce and eliminate the risk; moreover, the city responsible management department responsible for eliminating or reducing the risk cannot independently complete the risk reduction or elimination work, and the risk processing and scheduling module 17 sends out a risk elimination or reduction assistance request to other city responsible management departments, so that the risk commanding and scheduling work is realized.
Preferably, the risk early warning system further includes a process of setting a key monitoring event, a key monitoring area and a key monitoring person, and the corresponding monitoring data acquisition module 2 is set in the area where the key monitoring event, the key monitoring area and the key monitoring person are located through the predetermined key monitoring event, the key monitoring area and the key monitoring person, so as to acquire the multidimensional risk factors, thereby monitoring the key area and finding the risk more quickly.
Preferably, the risk early warning and display module 4 includes a risk processing scheduling module 17 respectively disposed in the central scheduling department and each basic level management department, the central scheduling department realizes data communication connection and command scheduling with each basic level management department, and communication connection and command scheduling are realized between each basic level management department, so as to establish a comprehensive command scheduling system with longitudinal communication and transverse communication.
The second embodiment is as follows:
a risk early warning method based on multi-factor model construction comprises a risk early warning system based on multi-factor model construction, and is characterized by comprising the following steps:
step S1, when the risk early warning system is in operation, the network data extraction module 9, the street safety module 10, the cell safety monitoring network module 11, the road safety monitoring network module 12, and the household data interface module 13 respectively obtain risk behaviors and potential risk parameters of monitoring personnel and monitoring areas, and the obtained risk parameters and risk behaviors of various types form a multidimensional risk factor and are stored in the data storage module 3;
step S2, the comprehensive evaluation platform 1 performs risk evaluation, risk pre-warning and risk control based on the risk sensing data acquired by the monitoring data acquisition module 2, specifically, the AI intelligent analysis detection module 8 integrates AI intelligent application, and forms a risk pre-warning model and a risk area based on the detected risk factors and the existing risk corresponding relationship stored in the data storage module 3 to obtain an intelligent analysis model; so as to carry out monitoring and adjust the arrangement of the corresponding monitoring data acquisition module 2;
step S3, the multi-factor intelligent analysis module 6 finds accurate key persons and key units in the whole market based on the constructed multi-factor intelligent analysis model, screens out potential hidden danger events, and realizes the change from manual mode to comprehensive perception;
step S4, the real-time risk early warning module 7 sends risk sensing data acquired in real time by the monitoring data acquisition module 2 to the multi-factor intelligent analysis module 6 for data query and analysis in combination with the multi-factor intelligent analysis model constructed by the multi-factor intelligent analysis module, obtains risk types and risk level parameters that may occur, and sends the risk types and risk level parameters to the risk early warning and display module 4 and the information issuing module 5;
step S5, the risk early warning and display module 4 displays the risk analyzed by the comprehensive evaluation platform 1 and sends a risk early warning to a management department; the information release module 5 performs release risk early warning on the risk analyzed by the comprehensive evaluation and evaluation platform 1;
and step S6, the risk early warning and display module 4 is used for displaying to the supervision and scheduling department so as to arrange risk processing work with the supervision department and the responsibility department in the corresponding area and adjust the number of staff of the corresponding risk supervision responsibility department and the corresponding responsibility department.
Preferably, the risk early warning and display module 4 includes a risk processing scheduling module 17 respectively disposed in the central scheduling department and each basic level management department, the central scheduling department realizes data communication connection and command scheduling with each basic level management department, and communication connection and command scheduling are realized between each basic level management department, so as to establish a comprehensive command scheduling system with longitudinal communication and transverse communication.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A risk early warning system constructed based on a multi-factor model comprises a comprehensive evaluation and evaluation 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 evaluation platform (1) is respectively in data communication connection 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);
the monitoring data acquisition module (2) is used for acquiring risk behaviors and potential risk parameters of monitoring personnel and monitoring areas, and the acquired risk parameters and risk behaviors of various types form multi-dimensional risk factors;
the comprehensive evaluation and evaluation platform (1) carries out risk evaluation, risk early warning and risk control on the basis of risk sensing data acquired by the monitoring data acquisition module (2), and the comprehensive evaluation and evaluation platform (1) comprises a multi-factor intelligent analysis module (6), a real-time risk early warning module (7) and an AI intelligent analysis and detection module (8);
the multi-factor intelligent analysis module (6) finds key people and key units in the whole market accurately based on the constructed multi-factor intelligent analysis model, screens out potential hidden danger events and realizes that the artificial touch is changed into comprehensive perception;
the real-time risk early warning module (7) is used for carrying out data query analysis on risk sensing data acquired in real time by the monitoring data acquisition module (2) and sending the risk sensing data to the multi-factor intelligent analysis module (6) in combination with the multi-factor intelligent analysis model constructed by the multi-factor intelligent analysis module to obtain possible risk types and risk grade parameters, and sending the risk types and risk grade parameters to the risk early warning and display module (4) and the information release module (5);
the AI intelligent analysis and detection module (8) is fused with AI intelligent application, and a risk early warning model and a risk area are formed based on the detected risk factors and the existing risk corresponding relation stored in the data storage module (3) to obtain an intelligent analysis model; so as to carry out the monitoring and to adjust the arrangement of the corresponding monitoring data acquisition modules (2);
the monitoring data acquisition module (2) comprises a network data extraction module (9), a street safety module (10), a cell safety monitoring network module (11), a road safety monitoring network module (12) and an housekeeping data interface module (13);
the network data extraction module (9) is used for acquiring news and events published on the Internet so as to extract risk factors forming risks to communities; the street safety module (10) is a street safety camera module which is arranged in a government administration department and is set so as to provide risk factors for the social streets; the community safety monitoring network module (11) is a safety monitoring video system arranged in a community, and provides a risk factor for forming a risk to the community through a monitoring image obtained by the safety monitoring video system of the community; the road safety monitoring network module (12) is a video monitoring system which is arranged on a road and is used for detecting road vehicles, so that data of the vehicles and road conditions on the road are provided, and risk factors on the road are formed; the household data interface module (13) is used for acquiring household data of population so as to provide household risk factors of the resident population;
the data storage module (3) is used for storing the multidimensional risk factors acquired by the monitoring data acquisition module (2); the risk early warning and displaying module (4) is used for displaying the risk analyzed by the comprehensive evaluation and evaluation platform (1) and sending a risk early warning to a management department; the information release module (5) is used for carrying out release risk early warning on the risk analyzed by the comprehensive evaluation and evaluation platform (1);
the method is characterized in that:
when the risk early warning system operates to carry out risk early warning, the network data extraction module (9), the street safety module (10), the cell safety monitoring network module (11), the road safety monitoring network module (12) and the household data interface module (13) respectively acquire various risk factors and store the risk factors in the data storage module (3);
the real-time risk early warning module (7), the multi-factor intelligent analysis module (6) and the AI intelligent analysis detection module (8) of the comprehensive evaluation and evaluation platform (1) perform big data analysis based on the data stored in the data storage module (3) to obtain real-time risk early warning data and social security data, and send the obtained risk early warning data to the information publishing module (5), the information publishing module (5) sends the risk early warning data to supervision authorities and community living personnel in corresponding areas so as to respond in time, and the risk early warning and display module (4) is used for displaying the risk early warning data to supervision and scheduling authorities so as to arrange risk processing work with the supervision authorities and responsibility authorities in the corresponding areas and adjust the number of working personnel of the corresponding risk responsibility supervision authorities and working personnel.
2. The risk early warning system constructed based on the multi-factor model according to claim 1, wherein: the risk early warning system further comprises a crowd user side (16) which is in communication connection with the risk early warning system, the crowd user side (16) can be in the form of APP or in the form of WeChat small program, the crowd user side (16) is in data communication connection with the monitoring data acquisition module (2), so that the crowd can report risk data to the monitoring data acquisition module (2) through the crowd user side (16) and store the risk data in the data storage module (3), and the comprehensive evaluation platform (1) performs big data analysis on the basis of the storage in the data storage module (3) to obtain real-time risk and social security data.
3. The risk early warning system constructed based on the multi-factor model according to claim 2, wherein: the official user side (15) is provided with an official account number, is in communication connection with the risk early warning system, is provided for a party organization and community workers to use, and sends the official information and the risk information of the government to all users to transmit the sound to the thousands of households by selecting a broadcast mode when the official information needs to be sent out in time.
4. The risk early warning system constructed based on the multi-factor model according to claim 1, wherein: the monitoring data acquisition module (2) further comprises a medical treatment data acquisition module (14), the medical treatment data acquisition module (14) acquires medical treatment data of a community hospital and stores the medical treatment data in the data storage module (3), the AI intelligent analysis detection module (8) analyzes a disease treatment model of the area by using historical medical treatment data stored in the data storage module (3) based on the acquired medical treatment data, the disease treatment model is a disease treatment model comprising a treatment hospital, a disease type, the number of disease staff and the age of the disease staff and provides the disease treatment model to the real-time risk early warning module (7), so that the real-time risk early warning module (7) performs data comparison based on the treatment hospital, the disease type, the number of disease staff and the age of the disease staff of the treatment patient and the disease treatment model obtained in real time, therefore, abnormal treatment hospitals, disease types, disease person increasing speeds and the ages of the disease persons are analyzed and provided for experts in the field of responding to disease treatment, so that the propagation characteristics of diseases and the disease outbreak places can be judged in time, the development of the diseases can be blocked in time, and disease risk early warning is provided.
5. The risk early warning system constructed based on the multi-factor model according to claim 1, wherein: each city responsible management department is provided with a corresponding risk early warning receiving and scheduling module (16), and when the risk early warning receiving and scheduling module (16) receives the risk early warning and the risk type sent by the comprehensive evaluation and evaluation platform (1), the city responsible management department completes corresponding risk investigation work based on the responsibility of the city responsible management department or receives the scheduling instruction of risk processing sent by the comprehensive evaluation and evaluation platform (1), and then carries out the risk processing.
6. The risk early warning system constructed based on the multi-factor model according to claim 5, wherein: the risk early warning and display module (4) further comprises a risk processing and scheduling module (17), when the comprehensive evaluation and evaluation platform (1) monitors risks, risk early warning is sent to the risk early warning and display module (4), and when a plurality of city responsible management departments need to jointly process and eliminate the risks, the risk processing and scheduling module (17) coordinates each city responsible management department to reduce and eliminate the risks; and the city responsible management department which is responsible for eliminating or reducing the risk can not finish the risk reduction or elimination work independently, and the risk processing and scheduling module (17) sends out a risk elimination or reduction assistance request to other city responsible management departments, thereby realizing the risk commanding and scheduling work.
7. The risk early warning system constructed based on the multi-factor model according to claim 6, wherein: the risk early warning system also comprises a process for setting key monitoring events, key monitoring areas and key monitoring personnel, and corresponding monitoring data acquisition modules (2) are arranged in the areas where the key monitoring events, the key monitoring areas and the key monitoring personnel are located through the predetermined key monitoring events, the predetermined key monitoring areas and the predetermined key monitoring personnel so as to acquire the multi-dimensional risk factors, so that the key areas are monitored and risks are found more quickly.
8. The risk early warning system constructed based on the multi-factor model according to claim 6, wherein: the risk early warning and display module (4) comprises risk processing scheduling modules (17) respectively arranged in a central scheduling department and each basic level management department, the central scheduling department realizes data communication connection and command scheduling with each basic level management department, and communication connection and command scheduling are realized among the basic level management departments, so that a comprehensive command scheduling system with longitudinal communication and transverse communication is established.
9. A risk early warning method based on multi-factor model construction, comprising the risk early warning system based on multi-factor model construction as claimed in any one of claims 1-8, characterized by comprising the following steps:
step S1, when the risk early warning system is in operation, the network data extraction module (9), the street safety module (10), the cell safety monitoring network module (11), the road safety monitoring network module (12) and the household data interface module (13) respectively acquire risk behaviors and potential risk parameters of monitoring personnel and monitoring areas, and the acquired risk parameters and risk behaviors form multi-dimensional risk factors and are stored in the data storage module (3);
step S2, the comprehensive evaluation and evaluation platform (1) carries out risk evaluation, risk early warning and risk control based on risk sensing data acquired by the monitoring data acquisition module (2), specifically, the AI intelligent analysis and detection module (8) integrates AI intelligent application, and a risk early warning model and a risk area are formed based on the detected risk factors and the existing risk corresponding relation stored in the data storage module (3) to obtain an intelligent analysis model; so as to carry out the monitoring and to adjust the arrangement of the corresponding monitoring data acquisition modules (2);
step S3, the multi-factor intelligent analysis module (6) finds and aims at key persons and key units in the whole market based on the constructed multi-factor intelligent analysis model, screens out potential hidden danger events and realizes that the artificial touch is changed into comprehensive perception;
step S4, the real-time risk early warning module (7) is based on risk sensing data acquired by the monitoring data acquisition module (2) in real time, and sends the risk sensing data to the multi-factor intelligent analysis module (6) to perform data query and analysis by combining with the multi-factor intelligent analysis model constructed by the multi-factor intelligent analysis module, so as to obtain risk types and risk grade parameters which are possibly generated, and sends the risk types and the risk grade parameters to the risk early warning and display module (4) and the information release module (5);
step S5, the risk early warning and display module (4) displays the risk analyzed by the comprehensive evaluation and evaluation platform (1) and sends a risk early warning to a management department; the information release module (5) carries out release risk early warning on the risk analyzed by the comprehensive evaluation and evaluation platform (1);
and step S6, the risk early warning and display module (4) is used for displaying for the supervision and scheduling department so as to arrange risk processing work with the supervision department and the responsibility department in the corresponding area and adjust the number of staff of the corresponding risk supervision and responsibility department.
10. The risk early warning method based on multi-factor model construction according to claim 9, wherein: the risk early warning and display module (4) comprises risk processing scheduling modules (17) respectively arranged in a central scheduling department and each basic level management department, the central scheduling department realizes data communication connection and command scheduling with each basic level management department, and communication connection and command scheduling are realized among the basic level management departments, so that a comprehensive command scheduling system with longitudinal communication and transverse communication is established.
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| CN115050160A (en) * | 2022-05-31 | 2022-09-13 | 中冶华天南京工程技术有限公司 | Intelligent safety supervision device for industrial unmanned production field |
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| CN115050160A (en) * | 2022-05-31 | 2022-09-13 | 中冶华天南京工程技术有限公司 | Intelligent safety supervision device for industrial unmanned production field |
| CN115050160B (en) * | 2022-05-31 | 2024-02-23 | 中冶华天南京工程技术有限公司 | Intelligent safety supervision device for industrial unmanned production site |
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