Fire-fighting management system based on smart city

Abstract

The invention discloses a fire-fighting management system based on a smart city, and relates to the field of fire-fighting management, and the system comprises a fire-fighting management platform which comprises a fire-fighting data collection module, a data twinning processing module, a fire-fighting data analysis module, a fire-fighting decision auxiliary module, a fire-fighting data coordination module and a fire-fighting data management module. The fire-fighting data acquisition module is used for acquiring fire-fighting equipment data, fire-fighting inventory data, historical fire-fighting data and fire-fighting monitoring data; the data twinning processing module generates a fire-fighting twinning image according to the historical fire-fighting data; the fire-fighting data analysis module generates a real-time fire-fighting monitoring image; the fire-fighting decision-making auxiliary module is used for generating fire-fighting auxiliary early warning information; the fire-fighting data coordination module is used for the fire-fighting data coordination module; the fire-fighting data management module is used for generating an intelligent contract according to the fire-fighting auxiliary coordination information for fire-fighting resource management; according to the invention, the coordination in the fire-fighting resource management process is improved to a certain extent.

Description

Technical Field

[0001] The present invention relates to the technical field of fire management, and in particular to a fire management system based on a smart city. Background Art

[0002] With the continuous acceleration of urbanization and the continuous expansion of urban scale, traditional fire management and monitoring methods can no longer meet the requirements of modern society for fire safety. Especially after an accident, the traditional manual intervention fire management model often consumes a lot of manpower, material resources and time costs. The emergence of smart cities provides us with a new solution.

[0003] After searching, the invention patent with Chinese patent number CN116597633A discloses a smart fire management system. The system includes: an equipment data acquisition unit, configured to obtain the operating data information of each fire-fighting device stored in each fire-fighting equipment point; a hierarchical fire-fighting topology network construction unit, configured to construct a multi-layer fire-fighting topology network, specifically including: forming the fire-fighting equipment points of N physical locations with a set M-edge topology structure into a first-layer topology unit, and connecting all the first-layer topology units to form a first-layer topology network. It establishes a three-layer topology network of fire-fighting equipment points, and then uses a recursive algorithm to determine the predicted weak positions from top to bottom, so that the weak positions of the equipment can be updated in time to prevent safety hazards caused by excessive aging of fire-fighting equipment. At the same time, the present invention uses various data collection and data analysis to determine possible weak positions, further improving the accuracy of the results.

[0004] Compared with the existing technology, the invention patent with Chinese patent number CN116597633A improves the efficiency of fire equipment management by setting the fire equipment points corresponding to the fire resources to a three-layer network topology structure, and managing the fire equipment points corresponding to each fire resource through the three-layer network topology structure.

[0005] However, in actual use, the above system does not take into account the dispatch and management of firefighting resources at various locations during the occurrence of corresponding firefighting accidents. It only manages and analyzes the aging degree of firefighting equipment corresponding to each firefighting resource and the location of safety hazards through a three-layer network topology structure. Therefore, how to improve the coordination between various firefighting resources at corresponding locations during the occurrence of corresponding firefighting accidents is a problem we need to solve. Summary of the Invention

[0006] The purpose of the present invention is to solve the problem of poor coordination of fire protection resources in the prior art and to propose a fire protection management system based on smart cities.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions: A fire management system based on a smart city, comprising a fire management platform, wherein the fire management platform includes a fire data acquisition module, a data twin processing module, a fire data analysis module, a fire decision support module, a fire data coordination module, and a fire data management module; The fire data acquisition module is used to collect fire equipment data, fire inventory data, historical fire data and fire monitoring data at corresponding locations; The data twin processing module is used to set the fire twin image corresponding to the corresponding area according to the corresponding historical fire data, and construct the fire analysis model corresponding to the corresponding management area and between adjacent areas in the fire twin image; The fire data analysis module is used to analyze and process the collected fire monitoring data according to the fire twin image to generate a real-time fire monitoring image; The firefighting decision-making assistance module is used to analyze and process the firefighting monitoring data in the real-time firefighting monitoring image through the corresponding firefighting analysis model, obtain the firefighting twin data at the corresponding position, and generate firefighting auxiliary warning information based on the firefighting twin data; The fire data coordination module is provided with an auxiliary warning cycle, and obtains the corresponding position coverage area and the corresponding change rate value within the auxiliary warning cycle according to the fire auxiliary warning information, splits and coordinates the fire inventory information of other locations according to the position coverage area and the corresponding change rate value, obtains the coordinated inventory information, comprehensively analyzes and sorts the various coordinated inventory information, and generates fire auxiliary coordination information; The fire data management module is used to send the corresponding fire auxiliary coordination information to the management department in the corresponding area, and the fire management personnel in the area generate smart contracts based on the fire auxiliary coordination information to manage fire resources.

[0008] Furthermore, the process of the fire data collection module collecting fire equipment data, fire inventory data, historical fire data, and fire monitoring data includes: Obtaining geographic spatial data, building site data, and fire management data corresponding to the corresponding city, and building a smart city model for fire management based on the geographic spatial data, building site data, and fire management data; Set up fire management nodes corresponding to the management area based on the smart city model, and input fire equipment data, fire inventory data, and historical fire data at the corresponding location in the management area through the corresponding fire management nodes; Communication network terminals and data sensor terminals are set at corresponding positions in the management area; corresponding fire monitoring data are collected through the data sensor terminals, and the collected fire monitoring data are transmitted in real time through the communication network terminals.

[0009] Furthermore, the process of setting up the fire twin image includes: Obtain the fire management node corresponding to the corresponding management area, and set the regional twin image within the corresponding management area based on the fire management node; obtain the corresponding geographic space data and building site data in the smart city model corresponding to the fire management node; According to the spatial frame image corresponding to the corresponding fire management node in the smart city model, the fire equipment data is mapped into the corresponding spatial frame image, the corresponding historical fire data is obtained, the historical fire data is set as a historical monitoring data set, and the historical monitoring data set is divided into the corresponding fire status data set and the fire impact data set; Analyze and process the fire status dataset and the fire impact dataset based on the fire dynamics model within the corresponding spatial frame image, construct a fire twin visualization model corresponding to the spatial frame model, and integrate the constructed fire twin visualization model with the corresponding spatial frame model to generate the corresponding regional twin image; Obtain the regional twin images corresponding to each fire management node in the smart city model and integrate them, and obtain the fire twin images in the corresponding city based on the integration results.

[0010] Furthermore, the process of building the corresponding fire analysis model includes: Obtain historical fire data, fire twin images, and corresponding fire equipment data corresponding to corresponding positions in the fire twin image; obtain the fire equipment data at the corresponding position in the fire twin image; set a fire action dataset based on the fire twin visualization model at the corresponding position in the fire twin image, and set a mapping range spatial area corresponding to the fire equipment data at the corresponding position in the fire twin image with respect to the historical fire data according to the fire action dataset; Set the intra-region correlation radius and the inter-region correlation radius respectively, obtain the mapping range spatial area at the corresponding position in the twin image of the corresponding region according to the intra-region correlation radius, and obtain the fire range spatial area at the corresponding position in the fire twin image according to the inter-region correlation radius. Set the associated data set according to the data information corresponding to the corresponding unit time in the obtained mapping range spatial area, analyze and process the associated data set based on the deep learning algorithm, and construct a corresponding fire analysis model. The fire analysis model is used to analyze and process the fire monitoring data and fire equipment data at the corresponding position and the fire impact data and fire action data at the positions associated with them; The fire analysis models that are related to each other at each position are stored in the fire twin image.

[0011] Furthermore, the process of generating real-time fire monitoring images includes: Obtain fire twin images and fire monitoring data, input the fire monitoring data into the fire twin visualization model at the corresponding position in the fire twin image, and the fire twin visualization model outputs the visualization image corresponding to the fire monitoring data at the corresponding position, and generates a real-time fire monitoring image based on the visualization image at each position.

[0012] Furthermore, the process of generating fire auxiliary warning information includes: Analyze and process the visual images at various locations within the real-time fire monitoring image, preset fire warning images, compare and analyze the corresponding pixel values ​​of the visual images at the corresponding locations with those of the fire warning images, determine whether the corresponding fire warning images meet the fire warning indicators, and perform auxiliary warning analysis on the fire monitoring data corresponding to the visual images that do not meet the fire warning indicators; Obtain the location information of the fire twin image where the fire monitoring data is located, input the fire monitoring data into the mutually related fire analysis models in sequence, obtain the fire impact data and fire action data output by each fire analysis model in sequence, and mark them according to the corresponding location information, generate the corresponding fire twin data according to the marking results, generate a twin visualization image according to the fire twin data, and generate the corresponding fire auxiliary warning information in the fire twin image according to the twin visualization image. The fire auxiliary warning information is used to perform early warning processing on areas where fire threats may exist.

[0013] Furthermore, the process of generating fire auxiliary coordination information includes: Obtain the fire monitoring data and fire twin data in the auxiliary fire warning information that do not meet the location information corresponding to the fire warning indicators, obtain the location information within the fire twin image to which the fire twin data belongs, and obtain the location coverage area corresponding to the fire monitoring data corresponding to the fire twin data and the visualization image that does not meet the fire warning indicators; Set an auxiliary warning cycle, obtain the change rate value of the position coverage area according to the auxiliary warning cycle, and set the fire influence coefficient and fire action coefficient corresponding to the corresponding path distance information according to the change rate value; Set a coordination radius based on the location coverage area, obtain the path distance information and corresponding fire inventory information corresponding to each fire equipment data within the coordination radius; split the fire inventory information of the corresponding location to obtain the coordinated inventory information; According to the path distance information and the coordinated inventory information of the corresponding locations, the corresponding fire influence coefficient and fire action coefficient are analyzed to obtain the comprehensive coordination information; The comprehensive coordination information at each location within the coordination radius is sorted and analyzed, and fire-fighting auxiliary coordination information is generated based on the sorting analysis results.

[0014] Furthermore, the process of fire management personnel in the region generating smart contracts based on fire auxiliary coordination information to manage fire resources includes: The corresponding fire auxiliary coordination information is sent to the management department within the corresponding management area based on the location information corresponding to the fire equipment data. The management department generates a corresponding smart contract based on the path distance information corresponding to the fire auxiliary coordination information, and dispatches and manages the fire resources corresponding to the fire inventory information at the corresponding location through the smart contract.

[0015] The present invention has the following beneficial effects: 0. In the present invention, by setting regional twin images, the regional twin images are integrated to construct a corresponding fire twin visualization model, and the corresponding fire monitoring data is analyzed and processed through the fire twin visualization model to construct a corresponding fire twin image. The fire twin image is used to perform early warning analysis on areas where fire threats may exist during the occurrence of fire accidents. According to the early warning results and the possible coverage area, the fire resources at the corresponding location are retrieved through the fire twin image, thereby improving the visualization of the fire data monitoring process to a certain extent, providing convenience for current fire treatment and subsequent fire management, and thus improving the efficiency of the fire management process.

[0016] 1. In the present invention, by analyzing and processing the historical fire data at the corresponding position and other positions in the fire twin image, a corresponding fire analysis model is constructed, the fire analysis model is stored according to the associated location information, and the corresponding fire twin data is obtained. The fire resources in the corresponding city are coordinated and processed through the fire twin data, which improves the response efficiency of fire accidents to a certain extent and indirectly reduces the losses caused by fire accidents to a certain extent.

[0017] 2. In the present invention, firefighting resources at different locations are coordinated by setting up smart contracts, so that the source or destination of each firefighting resource can be traced, which improves the utilization rate of firefighting resources to a certain extent. It also improves the efficiency of the firefighting management process through resource coordination and avoids the subsequent consumption of more manpower and material resources for the management of firefighting resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a structural diagram of a fire management system based on a smart city proposed by the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0020] Example 1 like Figure 1 As shown, the fire management system based on smart city proposed in the present invention includes a fire management platform, in which a fire data acquisition module, a data twin processing module, a fire data analysis module, a fire decision support module, a fire data coordination module and a fire data management module are provided; In this embodiment, the fire management platform is used to analyze and process firefighting equipment within a corresponding urban area and assist in firefighting management of corresponding firefighting incidents based on the location of the firefighting equipment, thereby improving the efficiency of firefighting incident handling and reducing the manpower and material losses caused by firefighting incidents. The specific implementation process includes: The fire data acquisition module is used to collect fire equipment data, fire inventory data, and fire monitoring data, and send the collected data information to the data twin processing module. Its specific implementation process includes: Obtain the geospatial data, building site data, and fire management data corresponding to the corresponding city, set up a city building model based on the geospatial data and building site data, analyze and process the city building model based on the corresponding fire management data, and set up a corresponding smart city model based on the fire management data; The specific implementation process of collecting corresponding fire equipment data, fire inventory data, and fire monitoring data based on the smart city model includes: Set up fire management nodes according to the corresponding urban building equipment in the smart city model, and obtain corresponding fire equipment data, fire inventory data, and fire monitoring data through the fire management nodes; Set up a fire entry window for each building in the corresponding area according to the fire management node, and enter the corresponding fire equipment data, fire inventory data, and historical fire data through the fire entry window, including: The firefighting equipment data includes basic equipment information, installation and deployment information, and operational performance parameter information. Basic equipment information includes equipment number, equipment type, manufacturer, and production date; installation and deployment information includes installation location and area; operational performance parameter information includes corresponding pressure range, response time, and maintenance information; The firefighting inventory data includes inventory data corresponding to corresponding firefighting equipment data; The historical fire protection data includes historical fire protection monitoring data, historical fire protection impact data, historical fire protection effect data corresponding to fire protection equipment data, etc. of corresponding fire protection accidents in different building locations; Setting up the communication network terminal and the data sensor terminal according to the location installation information corresponding to the fire-fighting equipment data; Obtain corresponding fire monitoring data through the data sensor terminal. The fire monitoring data is the data information monitored by the corresponding fire equipment and marked with the corresponding collection time; The obtained fire monitoring data is transmitted in real time through the corresponding communication network terminal.

[0021] The data twin processing module is used to set the fire twin image corresponding to the corresponding area based on the corresponding historical fire data, and construct the fire analysis model corresponding to the corresponding management area and adjacent areas in the fire twin image. The specific implementation process includes: Set up twin processing units and model processing units; The twin processing unit is used to set a corresponding fire twin image according to the corresponding historical fire data. The specific implementation process includes: Obtain the smart city model and the corresponding historical fire data. Perform twin processing on the historical fire data in each fire management node according to the fire management node to which the historical fire data belongs, obtain regional twin images, and splice and integrate the corresponding positions of the smart city model to which each fire management node belongs. The process of generating a fire twin image based on the integration results includes: Obtain the corresponding geospatial data and building site data in the smart city model corresponding to the fire management node; According to the spatial frame image corresponding to the corresponding fire management node in the smart city model, the fire equipment data is mapped into the corresponding spatial frame image, the corresponding historical fire data is obtained, the historical fire data is set as a historical monitoring data set, and the historical monitoring data set is divided into the corresponding fire status data set and the fire impact data set; The fire impact data set is the hazard impact data of the fire monitoring data corresponding to the corresponding historical monitoring data on the corresponding fire incident; Analyze and process the fire status dataset and the fire impact dataset based on the fire dynamics model within the corresponding spatial frame image, construct a fire twin visualization model corresponding to the spatial frame model, and integrate the constructed fire twin visualization model with the corresponding spatial frame model to generate the corresponding regional twin image; It should be further explained that, in the specific implementation process, the fire power model includes the corresponding heat release rate algorithm, the fire spread algorithm and the fire equipment performance algorithm. The fire power model is used to analyze and process the corresponding fire status data set and the fire impact data set in turn, and the model parameters corresponding to the fire status data and the fire impact data are obtained. The model parameters corresponding to the corresponding fire power model are associated with the spatial frame model and marked, and the corresponding fire power model is generated according to the associated marking results.

[0022] The regional twin images corresponding to each fire management node in the smart city model are obtained and integrated. That is, the model parameters corresponding to the fire power model corresponding to the edge position in each regional twin image are associated and marked with the spatial framework model, and the fire twin image in the corresponding city is obtained according to the integration result.

[0023] The model analysis module is used to set a corresponding fire analysis model according to the constructed fire twin image, and analyze and process the fire equipment data and fire monitoring data through the corresponding fire analysis model; Obtain historical fire data, fire twin images, and corresponding fire equipment data corresponding to corresponding positions in the fire twin image; obtain the fire equipment data at the corresponding position in the fire twin image; set a fire action dataset based on the fire twin visualization model at the corresponding position in the fire twin image, and set a mapping range spatial area corresponding to the fire equipment data at the corresponding position in the fire twin image with respect to the historical fire data according to the fire action dataset; Obtain the coverage range corresponding to the corresponding firefighting equipment data in the firefighting twin image, mark the firefighting equipment models corresponding to the firefighting equipment data in the area within the corresponding coverage range, and set the firefighting equipment distribution data based on the marking results; Obtain the corresponding building materials and layout information in the corresponding fire twin image, extract the corresponding historical fire data, map the obtained historical fire data into the fire dynamics model, obtain the corresponding model parameters, analyze and process the historical fire data based on the fire dynamics model according to the corresponding model parameters, obtain fire impact data, and extract the corresponding fire spread characteristic data from the fire impact data; Set regional weight coefficients based on fire equipment distribution data and fire spread characteristic data; According to the fire equipment distribution data, fire spread characteristics data and regional weight coefficient, the intra-regional correlation radius and inter-regional correlation radius are set respectively; Obtain the mapping range spatial area at the corresponding position in the twin image of the corresponding area according to the intra-region correlation radius; obtain the fire range spatial area at the corresponding position in the fire twin image according to the inter-region correlation radius; set a related data set based on the data information corresponding to the corresponding unit time in the obtained mapping range spatial area; analyze and process the related data set based on the deep learning algorithm to construct a corresponding fire analysis model, which is used to analyze and process the fire monitoring data and fire equipment data at the corresponding position and the fire impact data and fire action data at the positions associated with them; The fire analysis models that are related to each other at each position are stored in the fire twin image.

[0024] The fire data analysis module is used to analyze and process the collected fire monitoring data based on the fire twin image to generate a real-time fire monitoring image. The specific implementation process includes: Obtain fire twin images and fire monitoring data, input the fire monitoring data into the fire twin visualization model at the corresponding position in the fire twin image, and the fire twin visualization model outputs the visualization image corresponding to the fire monitoring data at the corresponding position, and generates a real-time fire monitoring image based on the visualization image at each position.

[0025] The firefighting decision-making assistance module is used to analyze and process the firefighting monitoring data in the real-time firefighting monitoring image using the corresponding firefighting analysis model, obtain the firefighting twin data at the corresponding location, and generate firefighting auxiliary warning information based on the firefighting twin data. The specific implementation process includes: Analyze and process the visual images at various locations within the real-time fire monitoring image, preset fire warning images, compare and analyze the corresponding pixel values ​​of the visual images at the corresponding locations with those of the fire warning images, determine whether the corresponding fire warning images meet the fire warning indicators, and perform auxiliary warning analysis on the fire monitoring data corresponding to the visual images that do not meet the fire warning indicators; Obtain the location information of the fire twin image where the fire monitoring data is located, input the fire monitoring data into the mutually related fire analysis models in sequence, obtain the fire impact data and fire action data output by each fire analysis model in sequence, mark them according to the corresponding location information, generate the corresponding fire twin data based on the marking results, generate a twin visualization image based on the fire twin data, the twin visualization image includes the fire status corresponding to the corresponding position, and visualize the corresponding fire status; Obtaining a fire critical safety visualization image corresponding to a corresponding regional position in the fire twin image, wherein the fire critical safety visualization image corresponds to a corresponding fire warning image, and the fire critical safety visualization image is a visualization processing result corresponding to when the fire status corresponding to the corresponding position is about to become a dangerous state; Compare and analyze the obtained fire visualization image with the fire critical safety visualization image at the corresponding area position, and obtain the comparison results of the pixel values ​​corresponding to the corresponding pixel points in turn. If the fire twin data corresponding to the pixel value corresponding to the corresponding pixel point in the corresponding fire visualization image is greater than the fire twin data corresponding to the pixel value corresponding to the corresponding pixel point in the corresponding fire critical safety visualization image, the corresponding pixel point is marked as abnormal; Obtain the abnormality rate of pixels in the corresponding fire visualization image and preset the abnormality rate threshold; If the corresponding abnormality rate is greater than or equal to the abnormality rate threshold, the fire auxiliary warning information corresponding to the corresponding area in the fire twin image is generated. Otherwise, the corresponding fire auxiliary warning information is not generated. The fire auxiliary warning information is used to provide early warning for areas where fire threats may exist.

[0026] The fire data coordination module is provided with an auxiliary warning cycle. The module obtains the corresponding position coverage area and the corresponding change rate value within the auxiliary warning cycle according to the fire auxiliary warning information. The module splits and coordinates the fire inventory information of other locations according to the position coverage area and the corresponding change rate value, obtains the coordinated inventory information, comprehensively analyzes and sorts the various coordinated inventory information, and generates the fire auxiliary coordination information. The specific implementation process includes: Obtain the fire monitoring data and fire twin data corresponding to the pixel points marked as abnormal in the fire auxiliary warning information, obtain the position information within the fire twin image to which the fire twin data belongs based on the corresponding position within the fire twin image to which the pixel points corresponding to the fire auxiliary warning information belong, and obtain the position coverage area corresponding to the fire twin data and the fire monitoring data corresponding to the visualization image that does not meet the fire warning indicators; Set an auxiliary warning cycle, obtain the change rate value of the position coverage area according to the auxiliary warning cycle, and set the fire influence coefficient and fire action coefficient corresponding to the corresponding path distance information according to the change rate value; Set a coordination radius based on the location coverage area, obtain the path distance information and corresponding fire inventory information corresponding to each fire equipment data within the coordination radius; split the fire inventory information of the corresponding location to obtain the coordinated inventory information; Obtain the number of samples of each firefighting equipment data within the coordination radius, and record the corresponding sample number as m, i=1, 2, 3, ..., m, and record each sample as i. Obtain the path distance information and firefighting inventory information corresponding to each firefighting equipment data, and record them as ; Obtain the positive indicator data corresponding to each fire-fighting equipment data and negative indicator data ,in: ; ; Obtain the proportion data of the fire protection influence coefficient and fire protection action coefficient corresponding to the fire protection equipment data of the corresponding sample ,in: ; Set the corresponding entropy value according to the corresponding weight data ,in: ; , ; Get the fire impact coefficient respectively and fire action coefficient ,in: ; ; According to the path distance information and coordinated inventory information of the corresponding locations, the corresponding fire influence coefficient and fire action coefficient are analyzed respectively to obtain comprehensive coordination information; the comprehensive coordination information at each location within the coordination radius is sorted and analyzed, and fire auxiliary coordination information is generated according to the sorting analysis results.

[0027] The fire data management module is used to send the corresponding fire auxiliary coordination information to the management department in the corresponding area. The fire management personnel in the area generate smart contracts based on the fire auxiliary coordination information to manage fire resources. The specific implementation process includes: The corresponding fire auxiliary coordination information is sent to the management department within the corresponding management area based on the location information corresponding to the fire equipment data. The management department generates the corresponding smart contract based on the path distance information corresponding to the fire auxiliary coordination information. The specific implementation process includes: Obtain basic equipment information, installation and deployment information, and operating performance parameter information corresponding to the corresponding fire protection equipment data; According to the basic equipment information, installation and deployment information, and operation performance parameter information corresponding to the corresponding fire-fighting equipment data, the equipment identifier, equipment name, feasibility data, regional management department, coordination and dispatch regional management department, and equipment location information corresponding to the corresponding fire-fighting equipment are set; The obtained device identifier, device name, feasibility data, regional management department, coordination and scheduling regional management department, and device location regional management department information are respectively set to corresponding coding types to encode each data information to obtain corresponding coding information; Set up a device array according to the coding information corresponding to the coding type, and store and manage the fire equipment data corresponding to the coordinated processing in the fire auxiliary coordination information through the device array; The corresponding device array is encrypted according to the coding information corresponding to the regional management department and the coordination and dispatching regional management department. The specific implementation process includes: Set the encoding information corresponding to other data information in the device array as the encoding extraction library; The coding information corresponding to the regional management department and the regional management department of the coordination and dispatch is set as the scrambled character according to the coding information; the character string corresponding to each digit of the scrambled character is obtained, and the corresponding character in the code extraction library is extracted according to the corresponding character string; Set the extracted characters as the smart contract key and encrypt and store the corresponding device array; According to the fire auxiliary coordination information, the encrypted device array is recorded and stored in the fire management node corresponding to the regional management department to which it belongs and the regional management department to which the coordination and dispatch belongs, and the corresponding smart contract is generated; The firefighting resources corresponding to the firefighting inventory information at the corresponding location are dispatched and managed through smart contracts.

[0028] While 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 these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A fire management system based on smart city, including a fire management platform, characterized in that: The fire management platform includes a fire data acquisition module, a data twin processing module, a fire data analysis module, a fire decision support module, a fire data coordination module and a fire data management module; The fire data acquisition module is used to collect fire equipment data, fire inventory data, historical fire data and fire monitoring data at corresponding locations; The data twin processing module is used to set the fire twin image corresponding to the corresponding area according to the corresponding historical fire data, and construct the fire analysis model corresponding to the corresponding management area and between adjacent management areas in the fire twin image; The fire data analysis module is used to analyze and process the collected fire monitoring data according to the fire twin image to generate a real-time fire monitoring image; The firefighting decision-making assistance module is used to analyze and process the firefighting monitoring data in the real-time firefighting monitoring image through the corresponding firefighting analysis model, obtain the firefighting twin data at the corresponding position, and generate firefighting auxiliary warning information based on the firefighting twin data; The fire data coordination module is provided with an auxiliary warning cycle, and obtains the corresponding position coverage area and the corresponding change rate value within the auxiliary warning cycle according to the fire auxiliary warning information, splits and coordinates the fire inventory information of other locations according to the position coverage area and the corresponding change rate value, obtains the coordinated inventory information, comprehensively analyzes and sorts the various coordinated inventory information, and generates fire auxiliary coordination information; The fire data management module is used to send the corresponding fire auxiliary coordination information to the management department within the corresponding management area, and the fire management personnel within the management area generate smart contracts based on the fire auxiliary coordination information to manage fire resources.

2. A fire management system based on smart city according to claim 1, characterized in that: The fire data collection module collects fire equipment data, fire inventory data, historical fire data, and fire monitoring data in the following process: Obtaining geographic spatial data, building site data, and fire management data corresponding to the corresponding city, and building a smart city model for fire management based on the geographic spatial data, building site data, and fire management data; Set up fire management nodes corresponding to the management area based on the smart city model, and input fire equipment data, fire inventory data, and historical fire data at the corresponding location in the management area through the corresponding fire management nodes; Communication network terminals and data sensor terminals are set at corresponding positions in the management area; corresponding fire monitoring data are collected through the data sensor terminals, and the collected fire monitoring data are transmitted in real time through the communication network terminals.

3. A fire management system based on smart city according to claim 2, characterized in that: The process of setting up a fire twin image includes: Obtain the fire management node corresponding to the corresponding management area, and set the regional twin image within the corresponding management area based on the fire management node; obtain the corresponding geographic space data and building site data in the smart city model corresponding to the fire management node; According to the spatial frame image corresponding to the corresponding fire management node in the smart city model, the fire equipment data is mapped into the corresponding spatial frame image, the corresponding historical fire data is obtained, the historical fire data is set as a historical monitoring data set, and the historical monitoring data set is divided into the corresponding fire status data set and the fire impact data set; Analyze and process the fire status dataset and the fire impact dataset based on the fire dynamics model within the corresponding spatial frame image, construct a fire twin visualization model corresponding to the spatial frame model, and integrate the constructed fire twin visualization model with the corresponding spatial frame model to generate the corresponding regional twin image; Obtain the regional twin images corresponding to each fire management node in the smart city model and integrate them, and respond to the fire twin images in the city based on the integration results.

4. A fire management system based on smart city according to claim 3, characterized in that: The process of building the corresponding fire analysis model includes: Obtain historical fire data, fire twin images, and corresponding fire equipment data corresponding to corresponding positions in the fire twin image, obtain the fire equipment data at the corresponding position in the fire twin image, set a fire action dataset based on the fire twin visualization model at the corresponding position in the fire twin image, and set a mapping range space area corresponding to the fire equipment data at the corresponding position in the corresponding fire twin image with respect to the historical fire data based on the fire action dataset; Set the intra-region correlation radius and the inter-region correlation radius respectively, obtain the mapping range spatial area at the corresponding position in the twin image of the corresponding region according to the intra-region correlation radius, and obtain the fire range spatial area at the corresponding position in the fire twin image according to the inter-region correlation radius. Set the associated data set according to the data information corresponding to the corresponding unit time in the obtained mapping range spatial area, analyze and process the associated data set based on the deep learning algorithm, and construct a corresponding fire analysis model. The fire analysis model is used to analyze and process the fire monitoring data and fire equipment data at the corresponding position and the fire impact data and fire action data at the positions associated with them; The fire analysis models that are correlated with each other at various locations are stored in the fire twin image.

5. A fire management system based on smart city according to claim 4, characterized in that: The process of generating real-time fire monitoring images includes: Obtain fire twin images and fire monitoring data, input the fire monitoring data into the fire twin visualization model at the corresponding position in the fire twin image, and the fire twin visualization model outputs the visualization image corresponding to the fire monitoring data at the corresponding position, and generates a real-time fire monitoring image based on the visualization image at each position.

6. The fire protection management system based on smart city according to claim 5, characterized in that: The process of generating fire auxiliary warning information includes: Analyze and process the visual images at various locations within the real-time fire monitoring image, preset fire warning images, compare and analyze the corresponding pixel values ​​of the visual images at the corresponding locations with those of the fire warning images, determine whether the corresponding fire warning images meet the fire warning indicators, and perform auxiliary warning analysis on the fire monitoring data corresponding to the visual images that do not meet the fire warning indicators; Obtain the location information of the fire twin image where the fire monitoring data is located, input the fire monitoring data into the mutually related fire analysis models in sequence, obtain the fire impact data and fire action data output by each fire analysis model in sequence, and mark them according to the corresponding location information, generate the corresponding fire twin data according to the marking results, generate a twin visualization image according to the fire twin data, and generate the corresponding fire auxiliary warning information in the fire twin image according to the twin visualization image. The fire auxiliary warning information is used to perform early warning processing on areas where fire threats may exist.

7. The fire protection management system based on smart city according to claim 6 is characterized in that: The process for generating fire auxiliary coordination information includes: Obtain the fire monitoring data and fire twin data in the auxiliary fire warning information that do not meet the location information corresponding to the fire warning indicators, obtain the location information within the fire twin image to which the fire twin data belongs, and obtain the location coverage area corresponding to the fire monitoring data corresponding to the fire twin data and the visualization image that does not meet the fire warning indicators; Set an auxiliary warning cycle, obtain the change rate value of the position coverage area according to the auxiliary warning cycle, and set the fire influence coefficient and fire action coefficient corresponding to the corresponding path distance information according to the change rate value; Set a coordination radius based on the location coverage area, obtain the path distance information and corresponding fire inventory information corresponding to each fire equipment data within the coordination radius; split the fire inventory information of the corresponding location to obtain the coordinated inventory information; According to the path distance information and the coordinated inventory information of the corresponding location, the corresponding fire influence coefficient and fire action coefficient are analyzed to obtain the comprehensive coordination information; The comprehensive coordination information at each location within the coordination radius is sorted and analyzed, and fire auxiliary coordination information is generated based on the sorting analysis results.

8. The fire protection management system based on smart city according to claim 7 is characterized in that: The process of fire management personnel in the region generating smart contracts based on fire auxiliary coordination information to manage fire resources includes: The corresponding fire auxiliary coordination information is sent to the management department within the corresponding management area based on the location information corresponding to the fire equipment data. The management department generates a corresponding smart contract based on the path distance information corresponding to the fire auxiliary coordination information, and dispatches and manages the fire resources corresponding to the fire inventory information at the corresponding location through the smart contract.

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