Risk assessment and risk warning system and method based on AI intelligent analysis and detection

Abstract

The present invention discloses a risk assessment and risk prediction system and prediction method based on AI intelligent analysis and detection, comprising an AI intelligent analysis and evaluation platform (1), a risk factor data acquisition module (2), a risk processing and scheduling module (3), a risk data storage module (4), a risk warning and alarm module (5) and an information release module (6); the AI ​​intelligent analysis and evaluation platform (1) is respectively connected to the risk factor data acquisition module (2), the risk processing and scheduling module (3), the risk data storage module (4), the risk warning and alarm module (5) and the information release module (6) for data communication. The risk assessment and risk warning system and prediction method based on AI intelligent analysis and detection of the present invention utilizes a comprehensive risk management system to comprehensively obtain various risk parameter sensor data, and performs comprehensive data management and comprehensive analysis on the risk parameter sensor data, thereby realizing the sharing of various risk parameter sensor data, bringing more management and efficiency to urban management and risk forecasting and warning.

Description

Technical Field

[0001] The present invention relates to the field of intelligent risk warning technology, and specifically to a risk assessment and risk prediction system and prediction method based on AI intelligent analysis and detection. Background Art

[0002] With the comprehensive development of automation technology and intelligent technology, all aspects of life have been greatly facilitated. By using automation and intelligent technology, we can realize the safe operation monitoring and illegal behavior of roads, ensure the safety of vehicle driving, and realize power saving and lighting through intelligent street lamp technology, which plays an important role in the diversion of road congestion. At the same time, on the streets, in order to ensure the safety of the streets and timely discover public security incidents, and deal with public security incidents in a timely manner, equipment such as Skynet is set up to timely discover public security incidents and subsequent case tracking; in the community, the property company usually sets up a community video surveillance system to ensure the monitoring of safety risks in the community; at the same time, in the living community, it is inevitable to use electricity, natural gas and water, but electricity, natural gas and water pass through the residential area, and in the event of leakage, it will inevitably lead to extremely serious incidents, such as electrical short circuits are easy to cause fires, fires caused by electricity occur from time to time every year, and gas leaks caused by natural gas cause explosions occasionally. Therefore, how to monitor and timely warn of such incidents is particularly important, but now, these emergencies are usually managed by each department, but usually when dealing with emergencies, it will involve multiple management departments and responsible departments at the same time, and coordination of the responsible departments is required. Therefore, corresponding sensor modules and management departments are usually set up to assist in detection and management;

[0003] For example, patent application CN110378824A discloses a traffic management data brain, which can realize the integration and data integration of traffic management systems in various places, enhance the ability to deeply apply data information, and make the traffic management system more collaborative; at the same time, the present invention also discloses a construction method based on the traffic management data brain. It includes: facility layer, platform layer, and application layer. The facility layer includes a dedicated cloud infrastructure for traffic management and a cloud resource management system. The platform layer is used to access, integrate, store and process various types of traffic management information resources, and provide resource services to the outside world. It includes a unified data exchange system, a video AI application platform, and a big data resource pool; the application layer provides application functions and services for various types of traffic management users, including a digital traffic geographic information system and an intelligent collaborative management and control application platform.

[0004] Patent application CN112261384A discloses an artificial intelligence violation behavior recognition system, including a system module assembly, the system module assembly includes a data source integration platform, a big data platform, an artificial intelligence automatic analysis platform, and an application system platform, and the data source integration platform sensor access terminal includes an intelligent gateway module; the present invention also proposes an artificial intelligence violation behavior recognition method, including the following steps: S1: the platform and the existing camera access the video stream through an interface; S2: the platform adopts a big data and AI analysis platform architecture. The present invention is conducive to strengthening the management of the unit's security; it can improve the efficiency of security prevention and reach the management level of modern networks. Through functions such as face recognition, tracking of movement trajectories of people and objects, and monitoring of the working environment, it can realize electronic fence isolation of the workplace, automatic identification of violations, and automatic warning of risks and hidden dangers.

[0005] Patent application CN 113053514A discloses a smart city medical alliance system based on 5G communication technology, which is used to intelligently coordinate the central hospital system of regional medical care and the grassroots medical alliance system, including the grassroots medical consultation system, the grassroots medical emergency remote diagnosis system, the pre-hospital emergency monitoring and diagnosis system and the grassroots medical clinical decision-making support system. The invention combines the grassroots medical consultation system, the grassroots medical emergency remote diagnosis system, the pre-hospital emergency monitoring and diagnosis system and the grassroots medical clinical decision-making support system to intelligently coordinate the central hospital system of regional medical care and the grassroots medical alliance system, and to link the consultation, emergency diagnosis, pre-hospital emergency monitoring and diagnosis and clinical decision-making support.

[0006] Patent application CN113176748A discloses a computer room fire information comprehensive linkage dispatching system and method. The present invention aims at the bottleneck of traditional fire protection technology, and is designed through three aspects: intelligent collection of environmental data, intelligent data analysis, and intelligent control of power equipment. It collects information about the temperature and humidity of the computer room, smoke, flames, far-infrared heat release signals, power load and AI images, performs calculations and analysis, and identifies abnormal data through comprehensive analysis of multi-dimensional information, and controls the air conditioner, ventilation system, fire door extinguisher and power switch control module according to data linkage. It solves the problems of inaccurate and untimely alarm data caused by many factors such as single environmental collection data, no algorithm for data analysis, and uncontrollable power equipment in traditional fire protection equipment. At the same time, through artificial intelligence analysis, the prediction and alarm of potential risks are realized, and the power equipment is regulated to avoid the occurrence of fire accidents.

[0007] Patent application CN111556294A discloses a security monitoring method, device, server, terminal and readable storage medium, which belongs to the field of computer technology. The method includes: inputting multiple first video images of the first target place into at least two first image recognition models respectively, determining the target image recognition model based on at least two crowd density information output, inputting multiple second video images into the target image recognition model, and determining the first security monitoring information according to the crowd density information of the at least one second video image. The present application processes the video images acquired at the initial stage of monitoring according to at least two first image recognition models to obtain crowd density information determined by multiple models, and selects the target image recognition model based on the crowd density information determined above, so as to select a model that is more suitable for the first target place for the subsequent monitoring process, thereby adaptively improving the accuracy of the crowd density information and improving safety.

[0008] Patent application CN112488398A discloses that the present invention discloses a power management method and system based on MEC edge intelligent gateway, including using cloud center to globally manage basic configuration information, using intelligent meters to classify and collect historical power consumption data, and transmitting it to MEC edge intelligent gateway through base station, using end module to pre-process raw data; analyzing and training user power consumption data according to AI module to form user power consumption business demand model, and encrypting and uploading the trained model gradient parameter data; parsing the encrypted model gradient of edge gateway and aggregating and training multiple models to form a joint model, backing up and sending gateway model gradient parameters; updating the model parameters and other data retained information, and sending power management decision information back to the corresponding user end according to actual situation. The present invention improves the computing power on the edge computing side, and in the contemporary society of massive data interaction, satisfies users' protection of their own power privacy data.

[0009] It can be seen that at present, although there are still the following technical defects in the monitoring and prediction of social security and risks in life on the market;

[0010] 1. In the prior art, in order to cope with the safe operation of the city, it is necessary to ensure that all aspects of the city are maintained in a safe operation state, which requires joint management by various departments and people in charge of the city. For this purpose, corresponding risk parameter sensing and acquisition equipment are set up. However, the sensing and acquisition equipment for acquiring urban risk parameters usually belongs to different regulatory departments or owner units, and the risk parameter sensing data are not shared between the regulatory departments or owner units. Therefore, the various risk parameter sensing data of the safe operation of the city are not shared, so that each management department acts independently, which is not conducive to the comprehensive management of the city and the comprehensive supervision and dispatch of risks;

[0011] 2. In the prior art, when risks occur or relevant management departments monitor data through various risk parameters and conduct risk assessments, risk data sharing among departments is not achieved, resulting in difficulties in risk response.

[0012] 3. In existing technologies, in order to ensure effective prevention and control of certain emergencies, it is necessary to manage some areas.

[0013] In the face of the above technical problems, people hope to provide a technical means that can quickly locate risks and classify risk levels. However, so far, there is no effective way to solve the above technical problems in the existing technology. Summary of the invention

[0014] The purpose of the present invention is to provide a risk assessment and risk prediction system and prediction method based on AI intelligent analysis and detection 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 assessment and risk warning system based on AI intelligent analysis and detection, comprising an AI intelligent analysis and assessment platform, a risk factor data acquisition module, a risk processing and scheduling module, a risk data storage module, a risk warning and alarm module, and an information release module; the AI ​​intelligent analysis and assessment platform is respectively connected to the risk factor data acquisition module, the risk processing and scheduling module, the risk data storage module, the risk warning and alarm module, and the information release module for data communication;

[0017] It is characterized in that: the AI ​​intelligent analysis and evaluation platform is based on the multi-dimensional risk factors obtained by the risk factor data acquisition module stored in the risk data storage module, and is evaluated and analyzed based on the stored risk warning model to obtain risk warning information and risk handling methods; when the AI ​​intelligent analysis and evaluation platform analyzes the risk warning information, it is sent to the risk warning and alarm module for risk warning and alarm, and the risk warning and risk warning broadcast are issued to users and management departments through the information release module, and sent to the risk handling scheduling module for risk reduction and clearance processing;

[0018] The AI ​​intelligent sub-platform includes an AI risk intelligent assessment module, a risk level setting module and a risk assessment and early warning model construction module; the AI ​​risk intelligent assessment module analyzes the risk level and risk response method based on the risk assessment and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module, using a neural network analysis method; the risk level setting module sets the risk level and risk response method according to the risk response requirements of the management department, and sets key monitoring personnel, key events and key locations to facilitate the layout of the risk factor data collection module; the risk assessment and early warning model construction module constructs a risk early warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and formulated risk response methods collected by the risk factor data collection module, and stores it in the risk data storage module;

[0019] The risk factor data collection module is used to collect various risk factor data, and form a daily work log of risk factors, and store it in the risk data storage module; the risk factor data collection module includes an Internet data capture module, a Skynet module, a community safety monitoring network module, a community fire risk monitoring module, a road operation monitoring module, a household registration data interface module and a personnel data monitoring module;

[0020] The Internet data capture module is used to obtain events and messages published on the Internet in order to extract risk factors that pose risks to urban management; the Skynet module is a street safety Skynet image acquisition module that has been set up by the management department to ensure urban cases, so as to obtain risk factors on urban roads and streets; the community safety monitoring network module is a security monitoring video system set up in the community, and the monitoring images obtained by the community security monitoring video system are used to provide risk factors that pose risks to the community;

[0021] The community fire risk monitoring module is a monitoring module set up in the community corridor, which is used to detect the gas leakage concentration and smoke concentration, and the monitored gas leakage concentration and smoke concentration constitute the fire risk factor; the road operation monitoring module is a video monitoring system set up in the road to detect the vehicle operation on the road, so as to provide vehicle driving and road condition data on the road, and form the risk factor on the road; the household registration data interface module is used to obtain the household registration data of the current urban population, so as to provide the household registration risk factor of the resident population; the personnel data monitoring module uses the mobile phone to obtain the movement trajectory of the personnel through the communication department, and forms the risk factor caused by the movement of the personnel;

[0022] The risk data storage module is used to store the multi-dimensional risk factors acquired by the risk factor data acquisition module, the processing methods for eliminating and reducing various risk factors, and the risk assessment and early warning models;

[0023] When the risk assessment and risk warning system is running, the risk factor data collection module collects various risk factors, and the management department specifies the risk level and risk response method, and stores them in the risk data storage module. The risk assessment and warning model construction module constructs a risk warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and risk response methods collected by the risk factor data collection module.

[0024] The AI ​​risk intelligent assessment module analyzes the risk level and risk response method based on the risk assessment and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module, using the neural network analysis method, and sends them to the risk processing scheduling module, thereby scheduling the corresponding department to carry out risk processing.

[0025] Preferably, the risk level is graded according to the management requirements of the urban management department and the urgency of the risk, and is divided into five different levels. At the same time, different numbers of personnel for risk elimination or reduction and priority levels of risk response are specified for different risk levels.

[0026] Preferably, the risk handling scheduling module directs the corresponding risk management department to handle the risk based on the risk level and risk response method analyzed by the AI ​​risk intelligent assessment module, and dispatches other departments to assist in risk handling when the risk reduction cannot be reduced or eliminated in time.

[0027] Preferably, the risk level setting module also counts the number of personnel posing risks, the frequency weights of various risk factors and the risk level weights of various locations, wherein the frequency weights of various risk factors are the frequencies of each risk factor exceeding a certain risk level, and the risk level weights of various locations are assigned to the risk level of various locations, and the risk level weights of various locations are obtained based on the number of monitoring days.

[0028] That is, risk level weight = ∑ / number of days of monitoring time, so the risk level setting module adjusts the personnel in the department responsible for the corresponding risk factors and the risk handling personnel at each location based on the number of people at risk, the frequency weights of various risk factors and the risk level weights of each location.

[0029] Preferably, when monitoring the person of concern, the personnel data monitoring module identifies the person of concern by mobile phone number, and locates and tracks the whereabouts of the person of concern based on the base station of the communication operator; when the person of concern walks out of the corresponding person of concern monitoring area, the risk factor is sent to the risk processing scheduling module, so that the risk processing scheduling module schedules the corresponding risk processing department to reduce or eliminate the risk; at the same time, risk alarms and alarms to the person of concern are issued through the risk warning and alarm module, so as to remind the person of concern.

[0030] Preferably, the information release module and the risk warning and alarm module are connected in data communication, so that when the risk warning and alarm module receives a need for risk warning and alarm, it releases the risk information to the corresponding risk management department and users through the information release module to facilitate risk warning and risk elimination, or sends the government's official information and risk information to all users to provide risk prevention.

[0031] Preferably, the risk factor data collection module also includes a risk reporting module, which is arranged in each management department and user, so that each management department can report risks through the risk reporting module based on the detected risks, and the user reports risks through the risk reporting module when discovering risks, so that the AI ​​risk intelligent assessment module analyzes the reported risks, derives the risk level, risk management department and risk handling method, and sends them to the risk responsible department for risk elimination or risk reduction.

[0032] Preferably, when the risk is a risk that needs to be handled jointly across departments, the risk handling scheduling module coordinates the responsible management departments of each city to reduce and eliminate the risk; if the responsible management department of the city 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 the responsible management departments of other cities through the risk handling scheduling module, thereby realizing risk command and scheduling work.

[0033] On the other hand, the present application also provides a prediction method of a risk assessment and risk warning system based on AI intelligent analysis and detection, including a risk assessment and risk warning system based on AI intelligent analysis and detection, and the specific risk assessment and risk warning methods are as follows;

[0034] Step S1, the risk level setting module sets the risk level and risk response method according to the risk response requirements of the management personnel, sets the key monitoring personnel, key events and key locations, so as to carry out the layout of the risk factor data collection module;

[0035] Step S2, the Internet data capture module is used to obtain events and messages published on the Internet, so as to extract risk factors that pose risks to urban management; the Skynet module is a street safety Skynet image acquisition module that the management department has set up to ensure urban cases, so as to obtain risk factors on urban roads and streets; the community safety monitoring network module is a security monitoring video system set up in the community, and the monitoring images obtained by the community security monitoring video system are used to provide risk factors that pose risks to the community;

[0036] Step S3, the community fire risk monitoring module is a monitoring module set in the community corridor, which is used to detect the gas leakage concentration and smoke concentration, and the monitored gas leakage concentration and smoke concentration constitute the fire risk factor; the road operation monitoring module is a video monitoring system set in the road for detecting the vehicle operation on the road, so as to provide vehicle driving and road condition data on the road, and form the risk factor on the road; the household registration data interface module is used to obtain the household registration data of the current urban population, so as to provide the household registration risk factor of the resident population; the personnel data monitoring module obtains the movement trajectory of personnel through the communication department using the mobile phone, and forms the risk factor caused by the movement of personnel;

[0037] Step S4, the risk assessment and early warning model building module constructs a risk early warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and risk response methods collected by the risk factor data collection module, and stores it in the risk data storage module;

[0038] Step S5, the AI ​​risk intelligent assessment module analyzes the risk level and risk response method based on the risk assessment and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module using a neural network analysis method;

[0039] Step S6, sending to the risk warning and alarm module for risk warning and alarm, and issuing risk warning and risk warning broadcast to users and management departments through the information release module, and sending to the risk processing scheduling module for risk reduction and clearing.

[0040] Preferably, when the risk is a risk that needs to be handled jointly across departments, the risk handling scheduling module coordinates the responsible management departments of each city to reduce and eliminate the risk; if the responsible management department of the city 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 the responsible management departments of other cities through the risk handling scheduling module, thereby realizing risk command and scheduling work.

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

[0042] 1. The risk assessment and risk warning system and prediction method based on AI intelligent analysis and detection of the present invention utilizes a comprehensive risk management system to comprehensively acquire various risk parameter sensor data, and conducts comprehensive data management and comprehensive analysis on the risk parameter sensor data, thereby realizing the sharing of various risk parameter sensor data, bringing more management and efficiency to urban management and risk forecasting and warning.

[0043] 2. The risk assessment and risk warning system and prediction method based on AI intelligent analysis and detection of the present invention can achieve all-round risk response through Skynet, road monitoring, and community personnel monitoring, and can coordinate the risk response and elimination of various departments, so as to quickly deal with risks.

[0044] 3. The risk assessment and risk warning system and prediction method based on AI intelligent analysis and detection of the present invention identifies the person of concern by mobile phone number, and locates and tracks the whereabouts of the person of concern based on the base station of the communication operator. When the person of concern walks out of the corresponding person of concern monitoring area, the risk factor is sent to the risk processing scheduling module, so that the risk processing scheduling module dispatches the corresponding risk processing department to reduce or eliminate the risk; at the same time, risk alarms and alarms to the person of concern are issued through the risk warning and alarm module to remind the person of concern. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0046] Figure 2 This is a schematic diagram of the structure of the AI ​​intelligent analysis and evaluation platform of the present invention;

[0047] Figure 3 It is a schematic diagram of the structure of the risk factor data acquisition module of the present invention.

[0048] In the figure: 1. AI intelligent analysis and evaluation platform; 2. Risk factor data collection module; 3. Risk processing and scheduling module; 4. Risk data storage module; 5. Risk warning and alarm module; 6. Information release module; 7. AI risk intelligent assessment module; 8. Risk level setting module; 9. Risk assessment and warning model construction module; 10. Internet data capture module; 11. Skynet module; 12. Community safety monitoring network module; 13. Community fire risk monitoring module; 14. Road operation monitoring module; 15. Household registration data interface module; 16. Personnel data monitoring module; 17 Risk reporting 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] See also Figure 1-3 , the present invention provides a technical solution:

[0052] 1. A risk assessment and risk warning system based on AI intelligent analysis and detection, comprising an AI intelligent analysis and assessment platform 1, a risk factor data acquisition module 2, a risk processing and scheduling module 3, a risk data storage module 4, a risk warning and alarm module 5 and an information release module 6; the AI ​​intelligent analysis and assessment platform 1 is respectively connected to the risk factor data acquisition module 2, the risk processing and scheduling module 3, the risk data storage module 4, the risk warning and alarm module 5 and the information release module 6 for data communication;

[0053] It is characterized in that: the AI ​​intelligent analysis and evaluation platform 1 is based on the multi-dimensional risk factors obtained by the risk factor data acquisition module 2 stored in the risk data storage module 4, and is evaluated and analyzed based on the stored risk warning model to obtain risk warning information and risk handling methods; when the AI ​​intelligent analysis and evaluation platform 1 analyzes the risk warning information, it is sent to the risk warning and alarm module 5 for risk warning and alarm, and the risk warning and risk warning broadcast are issued to users and management departments through the information release module 6, and sent to the risk handling scheduling module 3 for risk reduction and clearance processing;

[0054] The AI ​​intelligent analysis and evaluation platform 1 includes an AI risk intelligent evaluation module 7, a risk level setting module 8 and a risk evaluation and early warning model construction module 9; the AI ​​risk intelligent evaluation module 7 analyzes the risk level and risk response method based on the risk evaluation and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module 2, using a neural network analysis method; the risk level setting module 8 sets the risk level and risk response method according to the risk response requirements of the management department, and sets key monitoring personnel, key events and key locations in order to layout the risk factor data collection module 2; the risk evaluation and early warning model construction module 9 constructs a risk early warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and formulated risk response methods collected by the risk factor data collection module 2, and stores it in the risk data storage module 4;

[0055] The risk factor data collection module 2 is used to collect various risk factor data, and form a daily work log of risk factors, and store it in the risk data storage module 4; the risk factor data collection module 2 includes an Internet data capture module 10, a Skynet module 11, a community safety monitoring network module 12, a community fire risk monitoring module 13, a road operation monitoring module 14, a household registration data interface module 15 and a personnel data monitoring module 16;

[0056] The Internet data capture module 10 is used to obtain events and messages published on the Internet in order to extract risk factors that pose risks to urban management; the Skynet module 11 is a street safety Skynet image acquisition module that the management department has set up to ensure urban cases, so as to obtain risk factors on urban roads and streets; the community safety monitoring network module 12 is a security monitoring video system set up in the community, and the monitoring images obtained by the community security monitoring video system are used to provide risk factors that pose risks to the community;

[0057] The community fire risk monitoring module 13 is a monitoring module set in the community corridor, which is used to detect the gas leakage concentration and smoke concentration, and the monitored gas leakage concentration and smoke concentration constitute the fire risk factor; the road operation monitoring module 14 is a video monitoring system set in the road for detecting the vehicle operation on the road, thereby providing vehicle driving and road condition data on the road to form a risk factor on the road; the household registration data interface module 15 is used to obtain the household registration data of the current urban population, so as to provide the household registration risk factor of the resident population; the personnel data monitoring module 16 obtains the movement trajectory of personnel through the communication department using mobile phones to form a risk factor caused by personnel movement;

[0058] The risk data storage module 4 is used to store the multi-dimensional risk factors acquired by the risk factor data acquisition module 2, the processing methods for eliminating and reducing various risk factors, and the risk assessment and early warning models;

[0059] When the risk assessment and risk warning system is running, the risk factor data collection module 2 collects various risk factors, and the management department specifies the risk level and risk response method, and stores them in the risk data storage module 4. The risk assessment and warning model construction module 9 constructs a risk warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and risk response methods collected by the risk factor data collection module 2.

[0060] The AI ​​risk intelligent assessment module 7 analyzes the risk level and risk response method based on the risk assessment and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module 2, using the neural network analysis method, and sends them to the risk processing scheduling module 3, thereby scheduling the corresponding department to carry out risk processing.

[0061] Preferably, the risk level is graded according to the management requirements of the urban management department and the urgency of the risk, and is divided into five different levels. At the same time, different numbers of personnel for risk elimination or reduction and priority levels of risk response are specified for different risk levels.

[0062] Preferably, the risk handling scheduling module 3 directs the corresponding risk management department to handle the risk based on the risk level and risk response method analyzed by the AI ​​risk intelligent assessment module 7, and dispatches other departments to assist in risk handling when the risk reduction cannot be reduced or eliminated in time.

[0063] Preferably, the risk level setting module 8 also counts the number of personnel posing risks, the frequency weights of various risk factors and the risk level weights of various locations, wherein the frequency weights of various risk factors are the frequencies of each risk factor exceeding a certain risk level, and the risk level weights of various locations are assigned to the risk level of each location, and the risk level weights of various locations are obtained based on the number of monitoring days.

[0064] That is, risk level weight = ∑ risk level assignment for each day during the monitoring period / number of days during the monitoring period, so that the risk level setting module 8 adjusts the personnel of the department responsible for the corresponding risk factors and the risk handling personnel at each location according to the number of people at risk, the frequency weights of various risk factors and the risk level weights of each location.

[0065] Preferably, when monitoring the person of concern, the personnel data monitoring module 16 identifies the person of concern by mobile phone number, and locates and tracks the whereabouts of the person of concern based on the base station of the communication operator; when the person of concern walks out of the corresponding monitoring area of ​​the person of concern, the risk factor is sent to the risk processing scheduling module 3, so that the risk processing scheduling module 3 dispatches the corresponding risk processing department to reduce or eliminate the risk; at the same time, the risk alarm is issued and the person of concern is alarmed through the risk warning and alarm module 5, so as to remind the person of concern.

[0066] Preferably, the information release module 6 and the risk warning and alarm module 5 are connected in data communication, so that when the risk warning and alarm module 5 receives a need for risk warning and alarm, it releases the risk information to the corresponding risk management department and users through the information release module 6 to facilitate risk warning and risk elimination, or sends the government's official information and risk information to all users to provide risk prevention.

[0067] Preferably, the risk factor data collection module 2 also includes a risk reporting module 17, which is arranged in each management department and user, so that each management department can report risks through the risk reporting module 17 according to the detected risks, and the user reports risks through the risk reporting module 17 when discovering risks, so that the AI ​​risk intelligent assessment module 7 analyzes the reported risks, derives the risk level, risk management department and risk handling method, and sends them to the risk responsible department for risk elimination or risk reduction.

[0068] Preferably, when the risk is a risk that needs to be handled jointly across departments, the risk handling and scheduling module 3 coordinates the responsible management departments of each city to reduce and eliminate the risk; if the responsible management department of the city responsible for eliminating or reducing the risk cannot complete the risk reduction or elimination work alone, a request for assistance in risk elimination or reduction is issued to the responsible management departments of other cities through the risk handling and scheduling module 3, thereby realizing risk command and scheduling work. Specific embodiment 2:

[0070] On the other hand, the present application also provides a prediction method of a risk assessment and risk warning system based on AI intelligent analysis and detection, including a risk assessment and risk warning system based on AI intelligent analysis and detection according to any one of claims 2 to 8, and the specific risk assessment and risk warning method is as follows;

[0071] Step S1, the risk level setting module 8 sets the risk level and risk response method according to the risk response requirements of the management personnel, sets the key monitoring personnel, key events and key locations, so as to carry out the layout of the risk factor data collection module 2;

[0072] Step S2, the Internet data capture module 10 is used to obtain events and messages published on the Internet, so as to extract risk factors that pose risks to urban management; the Skynet module 11 is a street safety Skynet image acquisition module that the management department has set up to ensure urban cases, so as to obtain risk factors on urban roads and streets; the community safety monitoring network module 12 is a security monitoring video system set up 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;

[0073] Step S3, the community fire risk monitoring module 13 is a monitoring module set in the community corridor, which is used to detect the gas leakage concentration and smoke concentration, and the monitored gas leakage concentration and smoke concentration constitute the fire risk factor; the road operation monitoring module 14 is a video monitoring system set in the road for detecting the vehicle operation on the road, so as to provide vehicle driving and road condition data on the road, and form the risk factor on the road; the household registration data interface module 15 is used to obtain the household registration data of the current urban population, so as to provide the household registration risk factor of the resident population; the personnel data monitoring module 16 obtains the movement trajectory of personnel through the communication department using the mobile phone, and forms the risk factor caused by the movement of personnel;

[0074] Step S4, the risk assessment and early warning model building module 9 constructs a risk early warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and risk response methods collected by the risk factor data collection module 2, and stores it in the risk data storage module 4;

[0075] Step S5, the AI ​​risk intelligent assessment module 7 analyzes the risk level and risk response method based on the risk assessment and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module 2 using a neural network analysis method;

[0076] Step S6, sending to the risk warning and alarm module 5 for risk warning and alarm, and issuing risk warning and risk warning broadcast to users and management departments through the information release module 6, and sending to the risk processing scheduling module 3 for risk reduction and clearing.

[0077] Preferably, when the risk is a risk that needs to be handled jointly across departments, the risk handling and scheduling module 3 coordinates the responsible management departments of each city to reduce and eliminate the risk; if the responsible management department of the city responsible for eliminating or reducing the risk cannot complete the risk reduction or elimination work alone, a request for assistance in risk elimination or reduction is issued to the responsible management departments of other cities through the risk handling and scheduling module 3, thereby realizing risk command and scheduling work.

[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 "comprise", "include" 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 assessment and risk warning system based on AI intelligent analysis and detection, characterized by: It includes an AI intelligent analysis and evaluation platform (1), a risk factor data collection module (2), a risk processing and scheduling module (3), a risk data storage module (4), a risk early warning and alarm module (5) and an information release module (6); The AI ​​intelligent analysis and evaluation platform (1) is respectively connected to the risk factor data acquisition module (2), the risk processing and scheduling module (3), the risk data storage module (4), the risk warning and alarm module (5) and the information release module (6) for data communication; The AI ​​intelligent analysis and evaluation platform (1) is based on the multi-dimensional risk factors acquired by the risk factor data acquisition module (2) stored in the risk data storage module (4), and is evaluated and analyzed based on the stored risk warning model to obtain risk warning information and risk handling methods; when the AI ​​intelligent analysis and evaluation platform (1) analyzes the risk warning information, it is sent to the risk warning and alarm module (5) for risk warning and alarm, and the risk warning is issued and broadcast to users and management departments through the information release module (6), and is sent to the risk handling scheduling module (3) for risk reduction and clearance processing; The AI ​​intelligent analysis and evaluation platform (1) comprises an AI risk intelligent evaluation module (7), a risk level setting module (8) and a risk evaluation and early warning model construction module (9); the AI ​​risk intelligent evaluation module (7) uses a neural network analysis method to analyze the risk level and risk response method based on the risk evaluation and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module (2); the risk level setting module (8) sets the risk level and risk response method according to the risk response requirements of the management department, sets key monitoring personnel, key events and key locations, so as to arrange the risk factor data collection module (2); the risk evaluation and early warning model construction module (9) constructs a risk early warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and formulated risk response methods collected by the risk factor data collection module (2), and stores it in the risk data storage module (4); The risk factor data collection module (2) is used to collect various risk factor data, and form a daily work log of risk factors, and store it in the risk data storage module (4); the risk factor data collection module (2) includes an Internet data capture module (10), a Skynet module (11), a community safety monitoring network module (12), a community fire risk monitoring module (13), a road operation monitoring module (14), a household registration data interface module (15) and a personnel data monitoring module (16); The Internet data capture module (10) is used to obtain events and messages published on the Internet so as to extract risk factors that pose risks to urban management; the Skynet module (11) is a street safety Skynet image acquisition module that has been set up by the management department to ensure urban cases, so as to obtain risk factors on urban roads and streets; the community safety monitoring network module (12) is a security monitoring video system set up in the community, and the monitoring images obtained by the community security monitoring video system are used to provide risk factors that pose risks to the community; The community fire risk monitoring module (13) is a monitoring module set in the community corridor, which is used to detect the gas leakage concentration and smoke concentration, and the monitored gas leakage concentration and smoke concentration constitute the fire risk factor; the road operation monitoring module (14) is a video monitoring system set in the road for detecting the vehicle operation on the road, thereby providing vehicle driving and road condition data on the road, forming a risk factor on the road; the household registration data interface module (15) is used to obtain the household registration data of the current urban population, so as to provide the household registration risk factor of the resident population; The personnel data monitoring module (16) uses a mobile phone to obtain the movement trajectory of personnel through the communication department to form risk factors caused by the movement of personnel; the risk data storage module (4) is used to store the multi-dimensional risk factors, the processing methods for eliminating and reducing various risk factors, and the risk assessment and early warning models obtained by the risk factor data acquisition module (2); When the risk assessment and risk warning system is in operation, the risk factor data collection module (2) collects various risk factors, and the management department specifies the risk level and risk response method, and stores them in the risk data storage module (4). The risk assessment and warning model construction module (9) constructs a risk warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and risk response methods collected by the risk factor data collection module (2). The AI ​​risk intelligent assessment module (7) is based on the risk assessment and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module (2), and uses a neural network analysis method to analyze the risk level and risk response method, and sends them to the risk processing scheduling module (3), thereby scheduling the corresponding department to handle the risk; the risk level is graded according to the management requirements of the urban management department and the urgency of the risk, and is divided into five different levels. At the same time, different risk levels are assigned different numbers of people to eliminate or reduce the risk and the priority level of the risk response.

2. According to claim 1, a risk assessment and risk warning system based on AI intelligent analysis and detection is characterized in that: The risk handling scheduling module (3) directs the corresponding risk management department to handle the risk based on the risk level and risk response method analyzed by the AI ​​risk intelligent assessment module (7), and dispatches other departments to assist in risk handling when the risk cannot be reduced or eliminated in time.

3. The risk assessment and risk warning system based on AI intelligent analysis and detection according to claim 1 is characterized in that: The risk level setting module (8) further counts the number of personnel posing risks, the frequency weights of various risk factors and the risk level weights of various locations, wherein the frequency weights of various risk factors are the frequencies of each risk factor exceeding a certain risk level, and the risk level weights of various locations are the values ​​assigned to the risk levels of various locations, and the risk level weights of various locations are obtained based on the number of monitoring days. That is, risk level weight = ∑ (risk level assigned for each day during the monitoring period) / number of days during the monitoring period, so that the risk level setting module (8) adjusts the personnel of the department responsible for the corresponding risk factor and the risk handling personnel at each location according to the number of personnel at risk, the frequency weights of various risk factors and the risk level weights of each location.

4. The risk assessment and risk warning system based on AI intelligent analysis and detection according to claim 1 is characterized in that: When monitoring a person of concern, the personnel data monitoring module (16) identifies the person of concern by mobile phone number, and locates and tracks the whereabouts of the person of concern based on the base station of the communication operator. When the person of concern walks out of the corresponding monitoring area of ​​the person of concern, the risk factor is sent to the risk processing scheduling module (3), so that the risk processing scheduling module (3) schedules the corresponding risk processing department to reduce or eliminate the risk; at the same time, the risk warning and the person of concern are alarmed through the risk warning and alarm module (5) to remind the person of concern.

5. The risk assessment and risk warning system based on AI intelligent analysis and detection according to claim 1 is characterized in that: The information release module (6) and the risk warning and alarm module (5) are connected in data communication, so that when the risk warning and alarm module (5) receives a need for risk warning and alarm, it releases the risk information to the corresponding risk management department and users through the information release module (6) to facilitate risk warning and risk elimination, or sends the government's official information and risk information to all users to provide risk prevention.

6. The risk assessment and risk warning system based on AI intelligent analysis and detection according to claim 1 is characterized in that: The risk factor data collection module (2) also includes a risk reporting module (17), which is arranged in each management department and user, so that each management department can report risks through the risk reporting module (17) according to the detected risks, and the user can report risks through the risk reporting module (17) when discovering risks, so that the AI ​​risk intelligent assessment module (7) analyzes the reported risks, obtains the risk level, risk management department and risk handling method, and sends them to the risk responsible department for risk elimination or risk reduction.

7. The risk assessment and risk warning system based on AI intelligent analysis and detection according to claim 1 is characterized in that: When the risk is a risk that is jointly handled by multiple departments, the risk handling and scheduling module (3) coordinates the responsible management departments of each city to reduce and eliminate the risk; if the responsible management department of the city responsible for eliminating or reducing the risk is unable to complete the risk reduction or elimination work alone, it will send a request for assistance in risk elimination or reduction to the responsible management departments of other cities through the risk handling and scheduling module (3), thereby realizing risk command and scheduling work.

8. A prediction method for a risk assessment and risk warning system based on AI intelligent analysis and detection, comprising a risk assessment and risk warning system based on AI intelligent analysis and detection according to any one of claims 1 to 7, wherein the specific risk assessment and risk warning method is as follows; Step S1, the risk level setting module (8) sets the risk level and risk response method according to the risk response requirements of the management personnel, sets the key monitoring personnel, key events and key locations, so as to arrange the risk factor data collection module (2); Step S2, the Internet data capture module (10) is used to obtain events and messages published on the Internet, so as to extract risk factors that pose risks to urban management; the Skynet module (11) is a street safety Skynet image acquisition module that has been set up by the management department to ensure urban cases, so as to obtain risk factors on urban roads and streets; the community safety monitoring network module (12) is a security monitoring video system set up in the community, and the monitoring images obtained by the community security monitoring video system are used to provide risk factors that pose risks to the community; Step S3, the community fire risk monitoring module (13) is a monitoring module set in the community corridor, which is used to detect the gas leakage concentration and smoke concentration, and the monitored gas leakage concentration and smoke concentration constitute the fire risk factor; The road operation monitoring module (14) is a video monitoring system arranged on the road for detecting vehicle operation on the road, thereby providing vehicle travel and road condition data on the road and forming risk factors on the road; The household registration data interface module (15) is used to obtain the household registration data of the current urban population so as to provide the household registration risk factor of the resident population; The personnel data monitoring module (16) obtains the movement trajectory of personnel through the mobile phone of the communication department to form the risk factors caused by the movement of personnel; Step S4, the risk assessment and early warning model building module (9) constructs a risk early warning model of risk factor-risk level-risk response method based on the multi-dimensional risk factors, risk levels and risk response methods collected by the risk factor data collection module (2), and stores it in the risk data storage module (4); Step S5, the AI ​​risk intelligent assessment module (7) analyzes the risk level and risk response method based on the risk assessment and early warning model and the real-time multi-dimensional risk factors collected by the risk factor data collection module (2) using a neural network analysis method; Step S6, sending to the risk warning and alarm module (5) for risk warning and alarm, and issuing risk warning and risk warning broadcast to users and management departments through the information release module (6), and sending to the risk processing scheduling module (3) for risk reduction and clearing.

9. The prediction method of the risk assessment and risk early warning system based on AI intelligent analysis and detection according to claim 8 is characterized by: When the risk is a risk that is jointly handled by multiple departments, the risk handling and scheduling module (3) coordinates the responsible management departments of each city to reduce and eliminate the risk; if the responsible management department of the city responsible for eliminating or reducing the risk is unable to complete the risk reduction or elimination work alone, it will send a request for assistance in risk elimination or reduction to the responsible management departments of other cities through the risk handling and scheduling module (3), thereby realizing risk command and scheduling work.

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