Visual fire rescue man-vehicle statistical analysis display system

Abstract

The invention relates to the technical field of electric digital data processing, in particular to a visual fire rescue man-vehicle statistical analysis display system, which comprises a basic data acquisition module, an initial resource allocation module, a field resource allocation module, an equipment responsibility analysis module and a statistical analysis display module, firstly, vehicle state data and on-duty fireman data of a fire station are obtained; then data processing is carried out to construct a dynamic rescue force demand model, meanwhile, the comprehensive matching degree is calculated, and a rescue force distribution scheme is constructed; secondly, acquiring regional actual rescue strength data and regional standard rescue strength data of each rescue region, and distributing rescue strength among the regions through regional strength deviation; constructing an equipment circulation directed graph and calculating an edge weight and a node responsibility degree; and finally, carrying out statistics on data of each module and carrying out visual display, and carrying out field resource allocation and result traceability. According to the invention, real-time data processing and scientific decision support in a dynamic rescue scene can be provided.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and specifically to a visual fire rescue vehicle and personnel statistical analysis and display system. Background Art

[0002] With the continuous development of computer technology and data processing technology, the fire rescue field is gradually transforming towards the intelligent direction. Currently, fire rescue work faces an increasingly complex fire situation and diverse types of disaster accidents, such as high-rise building fires, hazardous chemical explosions, and large commercial complex fires. These accidents are characterized by strong suddenness, high casualty risks, and great difficulty in handling, and the complex data generated has the characteristics of spatio-temporal dynamic changes. Traditional fire rescue command and decision-making mainly rely on the experience and intuitive judgment of commanders, lacking scientific and data-based support. In a changing rescue environment, it is difficult to achieve reasonable allocation of rescue forces and balanced distribution of resources.

[0003] In recent years, significant progress has been made in Internet of Things technology, big data analysis, and visualization technology, providing technical support for data processing in fire rescue work. However, the current application of these technologies in fire rescue mainly focuses on static data recording and simple statistical analysis, lacking effective dynamic data analysis, resulting in inefficient resource allocation and insufficient support for collaborative decision-making in complex and changing rescue scenarios, affecting rescue efficiency and success rate.

[0004] Therefore, a visual fire rescue vehicle and personnel statistical analysis and display system is proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a visual fire rescue vehicle and personnel statistical analysis and display system, including: a basic data acquisition module, an initial resource allocation module, a on-site resource allocation module, an equipment responsibility analysis module, and a statistical analysis and display module. First, obtain the vehicle status data and on-duty firefighter data of the fire station; then perform data processing to construct a dynamic rescue force demand model, and at the same time, calculate the comprehensive matching degree and construct a rescue force allocation plan; then obtain the actual on-site rescue force data and regional standard rescue force data of each rescue area, and allocate the rescue forces between regions through regional force deviation; then construct a directed graph of equipment transfer and calculate the edge weight and node responsibility degree; finally, statistically analyze the data of each module and visually display it, perform on-site resource allocation and result traceability. The present invention can provide real-time data analysis and scientific decision-making support in a dynamic rescue scenario.

[0006] To achieve the above object, the present invention provides the following technical solutions: A visual fire rescue vehicle and personnel statistical analysis and display system, including: A basic data acquisition module, which obtains the vehicle status data and on-duty firefighter data of the fire station; An initial resource allocation module constructs a dynamic rescue force demand model based on a historical rescue database, extracts the data features of fire alarm information to calculate the initial rescue force demand data, calculates the comprehensive matching degree according to the on-duty firefighter data, and constructs a rescue force allocation plan; A on-site resource allocation module obtains the actual rescue force data of each area in real time, calculates the standard rescue force data of the area, and allocates the rescue force between areas through the regional force deviation; An equipment responsibility analysis module records the equipment handover data, constructs a directed graph of equipment transfer, and calculates the edge weight and node responsibility degree; A statistical analysis and display module statistically analyzes the data of the basic data acquisition module, the initial resource allocation module, the on-site resource allocation module and the equipment responsibility analysis module, renders a visual interface based on the real-time data stream, and conducts on-site resource allocation and result traceability through data analysis.

[0007] Preferably, constructing the dynamic rescue force demand model based on the historical rescue database includes: based on the historical rescue database, calculating the case feature similarity through data processing, selecting similar historical cases according to a preset similarity threshold; constructing the dynamic rescue force demand model according to the case feature similarity of the similar historical cases; before dispatch, calculating the initial rescue force demand data according to the data features of the fire alarm information and the dynamic rescue force demand model; the expression of the dynamic rescue force demand model is: ; Wherein, is the dynamic rescue force demand data at time t, is the number of cumulative time windows, is the weight coefficient, is the number of similar historical cases in the k-th time window, is the data feature of the fire alarm information at time t, is the data feature of the fire alarm information of the i-th similar historical case among similar historical cases, is the case feature similarity between and

[0008] Preferably, constructing the rescue force allocation plan includes: obtaining the on-duty firefighter data, constructing the personal ability vector of each firefighter, constructing the rescue team ability matrix based on the personal ability vector, and calculating the team professional complementarity according to the rescue team ability matrix; extracting the rescue team information features and the fire alarm information data features to calculate the task fitness, and calculating the comprehensive matching degree according to the team professional complementarity and the task fitness; selecting m rescue teams through the integer programming algorithm according to the comprehensive matching degree.

[0009] Preferably, the initial resource allocation module further includes a reinforcement judgment unit for judging whether reinforcement is needed. Specifically, after arriving at the scene, calculate the dynamic rescue force demand data at the current moment according to the fire alarm information data features at the current moment and the dynamic rescue force demand model; calculate the overall force deviation between the dynamic rescue force demand data and the actual rescue force data on the scene. If the overall force deviation exceeds the first deviation threshold, reinforcement is needed.

[0010] Preferably, the inter-regional rescue force allocation includes: counting the regional actual rescue force data of each region; calculating the real-time situation score of each region according to the on-site situation; calculating the regional standard rescue force data according to the real-time situation score; calculating the regional force deviation according to the regional standard rescue force data and the regional actual rescue force data; forming a set of recipient regions for the regions where the regional force deviation is greater than the second deviation threshold; for the regions where the regional force deviation is less than or equal to the second deviation threshold, if it satisfies that the regional force deviation is less than or equal to the third deviation threshold, form a set of support regions, otherwise do not act as support regions.

[0011] Preferably, constructing the equipment transfer directed graph includes: collecting equipment handover data and performing data preprocessing; the equipment handover data includes equipment data, handing-over firefighter data, receiving firefighter data, handover time data, and handover location coordinate data; constructing the equipment transfer directed graph according to the equipment handover data , is the node set, representing the firefighters holding the equipment, is the edge set, representing the equipment handover records; after the rescue is over, conduct the responsibility traceability of each equipment according to the equipment transfer directed graph; the edge weight and node responsibility degree calculation formulas are: ; ; Among them, is the edge weight from node i to j, , and are respectively the holding duration, handover frequency, and responsibility level of node i, is the weight coefficient, , and are the maximum reference values for the holding duration, handover frequency, and responsibility level, respectively; is the responsibility degree of node i for the equipment ; is the directed graph of equipment transfer for the equipment ; is the edge in where node i is the equipment handing - over party, is the edge weight of the edge ; is the number of edges in ;

[0012] Preferably, the statistical analysis and display module includes a rescue data display unit and an equipment responsibility tracing unit; the rescue data display unit is used to visually display the data of the basic data acquisition module, the initial resource allocation module, and the on - site resource allocation module in real time; the equipment responsibility tracing unit is used to visually display the directed graph of equipment transfer and conduct equipment responsibility tracing.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention establishes a dynamic rescue force demand model based on the historical rescue database. By calculating the similarity of case characteristics, historical cases similar to the current fire situation are screened out, and according to the rescue force input of these similar historical cases, a rescue force demand model suitable for the current situation is constructed. Its dynamic nature and self - adaptability enable the allocation of rescue forces to be dynamically adjusted over time, more in line with the uncertainty of the fire situation development in the actual rescue process. At the same time, it can quickly calculate the initial rescue force demand data before dispatch, providing a scientific basis for the first - time rescue force allocation. During the rescue process, it can calculate the dynamic rescue force demand data in real time according to the fire information data at the current moment, and timely judge whether reinforcement is needed. It effectively solves the problem of inaccurate resource allocation caused by the lack of real - time data analysis in dynamic rescue scenarios, and significantly improves the utilization efficiency of rescue resources.

[0014] 2. The present invention proposes an optimized formation mechanism for rescue teams. By constructing the personal ability vectors of each firefighter, a rescue team ability matrix is formed, and the professional complementarity degree of the team is calculated. At the same time, based on the rescue team information and fire alarm information data, the task fitness is calculated to evaluate the comprehensive matching degree of the team. Through an optimization algorithm, the optimal rescue team combination is selected to ensure that the selected team has the highest comprehensive matching degree under the constraint conditions of meeting the initial rescue force requirement data. This makes the formation of the rescue force no longer limited to the simple matching of the number of people and vehicles, but takes into account the matching relationship between the professional skills of rescue firefighters and specific rescue tasks, improving the professionalism and effectiveness of rescue operations, providing a scientific means for precise firefighter deployment in dynamic rescue scenarios, and effectively improving the quality of rescue decisions.

[0015] 3. The present invention constructs a dynamic collaborative resource allocation mechanism for rescue forces between regions. Through the real-time evaluation of multi-dimensional on-site information, the sum of the real-time situation scores of each rescue region is calculated. Based on the situation scores, the standard rescue force data of the region is calculated, and the regional force deviation is calculated to identify the regions in need of assistance and the regions that can provide support. In addition, through the equipment handover data, a directed graph of equipment transfer is constructed to achieve precise traceability of equipment responsibilities, quantify the degree of responsibility of each firefighter for specific equipment, and provide an objective basis for post-event equipment management and liability investigation. Through real-time data analysis and visual display, cross-regional optimized scheduling of rescue forces and precise traceability of equipment responsibilities are achieved, effectively solving the problems of unbalanced resource allocation and unclear responsibility definition in dynamic rescue scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic structural diagram of a visual fire rescue vehicle and personnel statistical analysis and display system of the present invention; Figure 2 It is a schematic diagram of the inter-regional rescue force scheduling process of the present invention; Figure 3 It is a schematic structural diagram of the statistical analysis and display module of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0018] Please refer to Figures 1 to 3 , the present invention provides a visual fire rescue vehicle and personnel statistical analysis and display system, and the technical solutions are as follows: Embodiment 1: A visual fire rescue vehicle and personnel statistical analysis and display system, comprising: A basic data acquisition module, which acquires vehicle status data and on-duty firefighter data of a fire station; An initial resource allocation module, which constructs a dynamic rescue force demand model based on a historical rescue database, extracts the data characteristics of fire alarm information to calculate the initial rescue force demand data, calculates the comprehensive matching degree according to the on-duty firefighter data, and constructs a rescue force allocation plan; A on-site resource allocation module, which acquires the actual rescue force data of each area in real time, calculates the standard rescue force data of the area, and allocates the rescue force between areas through the area force deviation; An equipment responsibility analysis module, which records equipment handover data, constructs a directed graph of equipment flow, and calculates the edge weight and node responsibility degree; A statistical analysis and display module, which statistically analyzes the data of the basic data acquisition module, the initial resource allocation module, the on-site resource allocation module and the equipment responsibility analysis module, renders a visual interface based on the real-time data stream, and conducts on-site resource allocation and result traceability through data analysis.

[0019] Specifically, the vehicle status data includes vehicle RFID tag data, vehicle positioning data, in-vehicle equipment list, equipment RFID tag data and equipment positioning data; the on-duty firefighter data includes firefighter RFID tag data, firefighter positioning data and work data; The present invention adopts the active RFID technology with a 2.4G frequency, embeds active tags into the firefighter's combat uniform, inside the vehicle and on the shell of key equipment respectively, and installs active base stations inside the vehicle and at the camp access control; obtains vehicle positioning data through in-vehicle GPS, obtains equipment positioning data and firefighter positioning data through ultra-wideband positioning devices, and reads tag data through the active RFID technology at the same time; the identification range of the active base station can reach 30 meters and can penetrate walls, ensuring accurate identification in complex environments; when a firefighter gets on the vehicle or enters and exits the camp access control, the corresponding base station can read the tag information in real time and automatically count the personnel and vehicle information; Based on the real-time monitoring function of the active RFID base station, when it is detected that the RFID tag of a certain piece of equipment and the RFID tag of a certain firefighter continuously maintain a close contact state within a specific time, and the equipment was previously associated with the tag of another firefighter, the system automatically generates equipment handover data, including equipment ID, equipment type, handing-over firefighter ID, receiving firefighter ID and handover time; in addition, the ultra-wideband positioning device can provide the position coordinate data of the equipment and record the specific location of the equipment handover; When the combatants arrive at the rescue site, real-time data is collected through RFID tags, active base stations, and positioning devices and transmitted to the central server of the system via wireless communication. A communication protocol with a 2.4G frequency is used to achieve stable signal transmission, with strong anti-interference ability and suitability for complex radio network environments. The server eliminates positioning noise through Kalman filtering, aligns multi-source data through the time synchronization protocol, and analyzes and calculates the preprocessed data through the initial resource allocation module, on-site resource allocation module, and equipment responsibility analysis module, and inputs it into the statistical analysis and display module.

[0020] The visual fire rescue vehicle and personnel statistical analysis and display system proposed by the present invention constructs a dynamic rescue force demand model based on historical data, optimizes the formation of rescue teams according to the matching relationship between firefighters' professional skills and rescue tasks, realizes the dynamic allocation of forces in the on-site rescue area, and traces the responsibility by recording the equipment transfer path through equipment tags. Finally, all analysis results are visually displayed to provide comprehensive support for command and decision-making. The present invention realizes the intelligent allocation of rescue forces throughout the whole process from pre-departure preparation to on-site rescue and post-event evaluation, helps to improve the scientificity and accuracy of rescue force deployment, enhance the coordination and efficiency of on-site rescue, strengthen the traceability of resource allocation, thereby significantly improving the overall level of fire rescue and providing strong technical support for ensuring public safety.

[0021] Further, constructing the dynamic rescue force demand model based on the historical rescue database includes: based on the historical rescue database, calculating the similarity of case features through data processing, selecting similar historical cases according to a preset similarity threshold; constructing the dynamic rescue force demand model according to the case feature similarity of the similar historical cases; before departure, calculating the initial rescue force demand data according to the fire alarm information data features and the dynamic rescue force demand model; the expression of the dynamic rescue force demand model is: ; Among them, is the dynamic rescue force demand data at time t, is the cumulative number of time windows, is the weight coefficient, is the number of similar historical cases within the kth time window, is the fire alarm information data feature at time t, is the fire alarm information data feature of the ith similar historical case among is the case feature similarity between and calculated using cosine similarity,

[0022] Specifically, classify the fire alarm information data in the historical rescue database. Under each type of fire alarm information data, include the required types of fire trucks and rescue equipment. When calculating the dynamic rescue force demand data, calculate the number of firefighters, the number of each type of fire truck, and the number of each type of equipment respectively.

[0023] Calculate the required force for the current rescue based on historical experience, avoid shortages or surpluses of rescue force, and improve resource utilization efficiency. At the same time, the dynamics of the dynamic rescue force demand model enable the rescue command firefighters to adjust the rescue strategy during the development of the fire, achieve the optimal allocation of resources, and provide data support for scientific decision-making.

[0024] Furthermore, constructing a rescue force allocation plan includes: obtaining the on-duty firefighter data, constructing the personal ability vector of each firefighter, constructing the rescue team ability matrix based on the personal ability vector, and calculating the group professional complementarity degree according to the rescue team ability matrix; extracting the rescue team information characteristics and the fire alarm information data characteristics to calculate the task fitness degree, and calculating the comprehensive matching degree according to the group professional complementarity degree and the task fitness degree; selecting m rescue teams through the integer programming algorithm according to the comprehensive matching degree.

[0025] Specifically, perform a weighted sum of the group professional complementarity degree and the task fitness degree to obtain the comprehensive matching degree. Take the maximization of the sum of the comprehensive matching degrees of the selected teams as the objective function, and take the number of firefighters, the number of each type of fire truck, and the number of each type of equipment all meeting the initial rescue force demand data as the constraint conditions, and select m rescue teams through the optimization algorithm of integer programming; the calculation formulas for the group professional complementarity degree and the task fitness degree are: ; ; Among them, is the group professional complementarity degree, is the length of the personal ability vector, and each component in the personal ability vector represents a professional skill evaluation value. is the variance of the i-th professional skill evaluation value within the group, is the mean of the i-th professional skill evaluation value within the group; is the group task fitness degree, is the collective ability vector of the group, defined as the maximum evaluation value of all team members in each professional skill. is the ability demand vector generated according to the fire alarm information data, is the modulus of the vector.

[0026] A method for calculating the professional complementarity degree of a rescue team based on the rescue team ability matrix and selecting the optimal rescue team in combination with the task fitness is beneficial to forming a rescue team with strong complementarity and high professionalism, and avoids the extensive deployment mode that simply takes the number of people and vehicles as the standard in traditional rescue. By using the integer programming optimization algorithm to select the rescue team combination with the highest comprehensive matching degree, it not only ensures that the rescue force meets the requirements, but also maximizes the professional ability matching degree of the rescue team, improving the rescue efficiency and success rate.

[0027] Furthermore, the initial resource allocation module further includes a reinforcement judgment unit for judging whether reinforcement is needed. Specifically, after arriving at the scene, calculate the dynamic rescue force demand data at the current moment according to the fire alarm information data characteristics at the current moment and the dynamic rescue force demand model; calculate the overall force deviation between the dynamic rescue force demand data and the actual on-site rescue force data. If the overall force deviation exceeds the first deviation threshold, reinforcement is needed.

[0028] The overall force deviation The calculation method is , where is the dynamic rescue force demand data, is the actual on-site rescue force data. Specifically, for the number of firefighters, the number of each type of fire truck, and the number of each type of equipment, calculate respectively through and then take the mean value of all results as the overall force deviation.

[0029] Calculating the overall force deviation between the dynamic rescue force demand data at the current moment and the actual on-site rescue force, scientifically judging whether reinforcement is needed, avoiding the subjectivity and lag of the reinforcement decision, making the reinforcement decision based on real-time data analysis, which can not only timely supplement the insufficient rescue force, but also avoid unnecessary resource waste, improving the accuracy and timeliness of emergency response.

[0030] Furthermore, referring to Figure 2 , the inter-regional rescue force allocation includes: counting the regional actual rescue force data of each region; calculating the real-time situation score of each region according to the on-site situation; calculating the regional standard rescue force data according to the real-time situation score; calculating the regional force deviation according to the regional standard rescue force data and the regional actual rescue force data; forming a set of recipient regions for the regions where the regional force deviation is greater than the second deviation threshold; for the regions where the regional force deviation is less than or equal to the second deviation threshold, if it meets that the regional force deviation is less than or equal to the third deviation threshold, form a set of supporting regions, otherwise do not act as a supporting region.

[0031] Specifically, every other time window, the firefighters designated on-site conduct the fire spread situation and the situation of trapped firefighters Degree of building damage Threat of dangerous goods and rescue progress Score (from 0 to 10) respectively and transmit through voice input of the mobile terminal to the platform system to calculate the real-time situation score; the calculation formulas for the real-time situation score and the regional standard rescue force data are: ; ; ; Among them, is the real-time situation score, and are weight coefficients, is the degree of urgency, is the scoring result of the fire spread situation, the situation of trapped firefighters, the degree of building damage and the threat of dangerous goods, is the weight coefficient; is the regional standard rescue force data, is the weight coefficient, is the benchmark configuration force; the calculation of the regional standard rescue force data is based on the number categories of fire trucks and the categories of fire fighting equipment in the initial rescue force demand data, and the number of firefighters, the number of each type of fire truck and the number of each type of equipment are calculated respectively.

[0032] Regional force deviation The calculation method is , among which, is the regional standard rescue force data, is the regional actual rescue force data. Specifically, for the number of firefighters, the number of each type of fire truck and the number of each type of equipment, calculate respectively through and then take the mean value of all results as the regional force deviation.

[0033] Statistically analyze the regional actual rescue force data through tags, calculate the real-time situation score and the regional standard rescue force data in combination with the on-site situation, and then judge the recipient and support status of each region. The regional inter-force coordination and allocation mechanism based on real-time data is beneficial to optimizing the on-site rescue resource allocation, ensuring that each region has a rescue force matching its degree of urgency, avoiding the situation of excessive force in some regions and insufficient force in other regions, and improving the overall rescue efficiency and collaborative combat ability.

[0034] Furthermore, constructing the directed graph of equipment transfer includes: collecting equipment handover data and performing data preprocessing; the equipment handover data includes equipment data, handing-over firefighter data, receiving firefighter data, handover time data and handover location coordinate data; constructing the directed graph of equipment transfer according to the equipment handover data , is a set of nodes, representing firefighters holding equipment, is a set of edges, representing equipment handover records; after the rescue ends, the responsibility traceability of each piece of equipment is carried out according to the described equipment transfer directed graph; the edge weight and node responsibility degree calculation formulas are: ; ; Among them, is the edge weight from node i to j, , and are respectively the holding duration, handover frequency and responsibility level of node i, and the responsibility level is determined according to the position of the firefighter, is the weight coefficient, , and are respectively the maximum reference values of the holding duration, handover frequency and responsibility level; is the responsibility degree of node i for the equipment , is the equipment transfer directed graph of the equipment , is the edge in which node i is the equipment handing - out party, is the edge , is the number of edges in, is the attenuation coefficient.

[0035] Construct an equipment transfer directed graph based on equipment handover data to achieve equipment responsibility traceability. It is beneficial to clarify the transfer path and responsibility attribution of equipment during the rescue, and solves the problems of chaotic equipment management and unclear responsibilities in the rescue. By quantifying the responsibility degree, it provides an objective basis for equipment management and post - incident responsibility investigation, and promotes the standardization of equipment management and the implementation of the responsibility system.

[0036] Furthermore, referring to Figure 3 , the statistical analysis and display module includes a rescue data display unit and an equipment responsibility traceability unit; the rescue data display unit is used to visually display the data of the basic data acquisition module, the initial resource allocation module and the on - site resource allocation module in real time; the equipment responsibility traceability unit is used to visually display the equipment transfer directed graph and conduct equipment responsibility traceability.

[0037] Specifically, the statistical analysis and display module receives the data streams from each module in real time through the message middleware of the central server. The rescue data display unit includes: based on the positioning data, generating a dynamic heat distribution using the Gaussian kernel density estimation algorithm, obtaining a visual real-time rescue force heat map by using HSV color gamut mapping, and updating the heat intensity value every 500 ms; using a data visualization library to draw a double-axis line chart, with the left axis showing the real-time rescue force demand (rescue force demand data or regional standard rescue force data), and the right axis showing the force deviation (overall force deviation or regional force deviation), the data window length is 15 minutes, and it is smoothed and refreshed every 3 seconds; the equipment responsibility traceability unit includes: dynamically arranging the topological structure of the equipment transfer directed graph, the node radius is positively correlated with the firefighter's responsibility degree, and the edge width is logarithmically scaled according to the handover frequency, supporting clicking on the node to view the holding duration and the details of the handover data, which is beneficial to the traceability of equipment responsibility after the rescue ends.

[0038] The statistical analysis and display module is beneficial to improving the intuitiveness and convenience of command and decision-making, enabling the command firefighters to quickly obtain key information and make scientific decisions. At the same time, the visual equipment responsibility traceability provides an intuitive basis for post-event evaluation and improvement, promotes the continuous improvement and optimization of rescue work, and enhances the overall level of fire rescue.

[0039] Embodiment 2: In order to realize the force allocation and collaborative management for high-rise residential building fire rescue, this embodiment applies a visual fire rescue vehicle and personnel statistical analysis and display system, including: The basic data acquisition module, which acquires the vehicle status data and on-duty firefighter data of the fire station; The initial resource allocation module, which constructs a dynamic rescue force demand model based on the historical rescue database, extracts the data characteristics of the fire alarm information to calculate the initial rescue force demand data, calculates the comprehensive matching degree according to the on-duty firefighter data, and constructs a rescue force allocation plan; The on-site resource allocation module, which acquires the actual on-site rescue force data of each area in real time, calculates the regional standard rescue force data, and allocates the rescue force between regions through the regional force deviation; The equipment responsibility analysis module, which records the equipment handover data, constructs an equipment transfer directed graph, and calculates the edge weight and node responsibility degree; The statistical analysis and display module, which statistically analyzes the data of the basic data acquisition module, the initial resource allocation module, the on-site resource allocation module and the equipment responsibility analysis module, renders a visual interface based on the real-time data stream, and conducts on-site resource allocation and result traceability through data analysis.

[0040] Further, constructing the dynamic rescue force demand model based on the historical rescue database includes: based on the historical rescue database, calculating the similarity of case features through data processing, selecting similar historical cases according to a preset similarity threshold; constructing the dynamic rescue force demand model according to the case feature similarity of the similar historical cases; before dispatch, calculating the initial rescue force demand data according to the fire alarm information data features and the dynamic rescue force demand model; the expression of the dynamic rescue force demand model is: ; where, is the dynamic rescue force demand data at time t, is the number of cumulative time windows, is the weight coefficient, is the number of similar historical cases within the k-th time window, is the fire alarm information data feature at time t, is the fire alarm information data feature of the i-th similar historical case among is and is the case feature similarity between calculated using cosine similarity, and

[0041] Table 1 shows the fire alarm information data of current high-rise residential building fires and similar historical cases; Table 2 shows an example of the initial rescue force demand data.

[0042] Table 1. Fire Alarm Information Data of Similar Historical Cases

[0043] Table 2. Example of Initial Rescue Force Demand Data

[0044] Further, constructing the rescue force allocation plan includes: obtaining the on-duty firefighter data, constructing the personal ability vector of each firefighter, constructing the rescue team ability matrix based on the personal ability vector, and calculating the group professional complementarity according to the rescue team ability matrix; extracting the rescue team information features and the fire alarm information data features to calculate the task fitness, and calculating the comprehensive matching degree according to the group professional complementarity and the task fitness; selecting m rescue teams through an integer programming algorithm according to the comprehensive matching degree.

[0045] Table 3. Group Professional Complementarity and Task Fitness

[0046] Table 4. Example of Personal Ability Vectors of Firefighters

[0047] Table 3 shows the data of professional complementarity and task adaptability of different rescue teams; Table 4 gives examples of personal ability vectors of firefighters in each team.

[0048] Furthermore, the initial resource allocation module further includes a reinforcement judgment unit for judging whether reinforcement is needed, specifically: after arriving at the scene, calculate the dynamic rescue force demand data at the current moment according to the fire alarm information data characteristics at the current moment and the dynamic rescue force demand model; calculate the overall force deviation between the dynamic rescue force demand data and the actual rescue force data on the scene. If the overall force deviation exceeds the first deviation threshold, reinforcement is needed.

[0049] Furthermore, the allocation of rescue forces between regions includes: counting the actual rescue force data of each region; calculating the real-time situation score of each region according to the on-site situation; calculating the standard rescue force data of the region according to the real-time situation score; calculating the regional force deviation according to the regional standard rescue force data and the actual rescue force data of the region; forming a set of recipient regions for the regions where the regional force deviation is greater than the second deviation threshold; for the regions where the regional force deviation is less than or equal to the second deviation threshold, if it satisfies that the regional force deviation is less than or equal to the third deviation threshold, form a set of support regions, otherwise do not act as support regions.

[0050] Furthermore, constructing the equipment transfer directed graph includes: collecting equipment handover data and performing data preprocessing; the equipment handover data includes equipment data, handing-over firefighter data, receiving firefighter data, handover time data, and handover position coordinate data; constructing an equipment transfer directed graph according to the equipment handover data , is the node set, representing the firefighters holding the equipment, is the edge set, representing the equipment handover records; after the rescue is over, conduct responsibility tracing for each piece of equipment according to the equipment transfer directed graph; the edge weight and node responsibility degree calculation formulas are: ; ; Among them, is the edge weight from node i to j, , and are the holding duration, handover frequency, and responsibility level of node i respectively, is the weight coefficient, , and They are the maximum reference values of the holding duration, handover frequency, and responsibility level respectively; is the responsibility degree of node i for the equipment ; is the directed graph of equipment transfer of the equipment ; is the edge in which node i is the equipment handing - over party in ; is the edge weight of the edge ; is the number of edges in ;

[0051] Furthermore, the statistical analysis and display module includes a rescue data display unit and an equipment responsibility tracing unit; the rescue data display unit is used to visually display the data of the basic data acquisition module, the initial resource allocation module, and the on - site resource allocation module in real time; the equipment responsibility tracing unit is used to visually display the directed graph of equipment transfer and conduct equipment responsibility tracing.

[0052] Although the embodiments of the present invention have been shown and described, for those ordinary - skilled firefighters in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A visual statistical analysis and display system for fire rescue vehicles and personnel, characterized in that, Including: A basic data acquisition module, which acquires the vehicle status data and on-duty firefighter data of the fire station; An initial resource allocation module, which constructs a dynamic rescue force demand model based on the historical rescue database, extracts the data features of the fire alarm information to calculate the initial rescue force demand data, calculates the comprehensive matching degree according to the on-duty firefighter data, and constructs a rescue force allocation plan; A on-site resource allocation module, which acquires the actual rescue force data of each region in real time, calculates the standard rescue force data of the region, and allocates the rescue force between regions through the regional force deviation; An equipment responsibility analysis module, which records the equipment handover data, constructs a directed graph of equipment flow, and calculates the edge weight and node responsibility degree; A statistical analysis and display module, which statistically analyzes the data of the basic data acquisition module, the initial resource allocation module, the on-site resource allocation module and the equipment responsibility analysis module, renders a visual interface based on the real-time data stream, and conducts on-site resource allocation and result traceability through data analysis.

2. The visual fire rescue vehicle and personnel statistical analysis and display system according to claim 1, wherein, Constructing the dynamic rescue force demand model based on the historical rescue database includes: based on the historical rescue database, calculating the case feature similarity through data processing, selecting similar historical cases according to a preset similarity threshold; constructing the dynamic rescue force demand model according to the case feature similarity of the similar historical cases; before dispatch, calculating the initial rescue force demand data according to the data features of the fire alarm information and the dynamic rescue force demand model; the expression of the dynamic rescue force demand model is: ； Among them, is the dynamic rescue force demand data at time t, is the number of cumulative time windows, is the weight coefficient, is the number of similar historical cases within the k-th time window, is the fire alarm information data feature at time t, is the fire alarm information data feature of the i-th similar historical case among is and the case feature similarity, calculated using cosine similarity, is the rescue force invested in the i-th similar historical case.

3. A visualized fire rescue vehicle and personnel statistical analysis and display system according to claim 1, characterized in that, Constructing a rescue force allocation plan includes: acquiring the on-duty firefighter data, constructing the personal ability vector of each firefighter, constructing a rescue team ability matrix based on the personal ability vector, and calculating the team professional complementarity according to the rescue team ability matrix; extracting the information features of the rescue team and the data features of the fire alarm information to calculate the task fitness, and calculating the comprehensive matching degree according to the team professional complementarity and the task fitness; selecting m rescue teams through an integer programming algorithm according to the comprehensive matching degree.

4. A visualized fire rescue vehicle and personnel statistical analysis and display system according to claim 1, characterized in that, The initial resource allocation module further includes a reinforcement judgment unit, which is used to judge whether reinforcement is needed. Specifically: after arriving at the scene, calculate the dynamic rescue force demand data at the current moment according to the data features of the fire alarm information at the current moment and the dynamic rescue force demand model; calculate the overall force deviation between the dynamic rescue force demand data and the actual rescue force data on the scene. If the overall force deviation exceeds the first deviation threshold, reinforcement is needed.

5. A visual fire rescue vehicle and personnel statistical analysis and display system according to claim 1, characterized in that The rescue force allocation between regions includes: statistically analyzing the actual rescue force data of each region; calculating the real-time situation score of each region according to the on-site situation; calculating the standard rescue force data of the region according to the real-time situation score; calculating the regional force deviation according to the standard rescue force data of the region and the actual rescue force data of the region; forming a set of recipient regions for the regions where the regional force deviation is greater than the second deviation threshold; for the regions where the regional force deviation is less than or equal to the second deviation threshold, if it meets the condition that the regional force deviation is less than or equal to the third deviation threshold, form a set of support regions, otherwise do not act as support regions.

6. The visualized fire rescue vehicle and personnel statistical analysis and display system according to claim 1, characterized in that, Constructing the equipment transfer directed graph includes: collecting equipment handover data and performing data preprocessing; the equipment handover data includes equipment data, handing-over firefighter data, receiving firefighter data, handover time data, and handover location coordinate data; constructing an equipment transfer directed graph according to the equipment handover data , is a set of nodes, representing the firefighters holding the equipment, is a set of edges, representing the equipment handover records; after the rescue is over, conduct liability tracing for each piece of equipment according to the equipment transfer directed graph; the edge weight and node liability degree calculation formulas are as follows: ； ； Among them, is the edge weight from node i to j, , and are the holding duration, handover frequency and responsibility level of node i respectively, is the weight coefficient, , and are the maximum reference values of the holding duration, handover frequency and responsibility level respectively; is the responsibility degree of node i for the equipment , is the directed graph of equipment transfer of the equipment , is the edge in which node i is the equipment handing - over party, is the edge of the edge weight, is the number of edges in, is the attenuation coefficient.

7. A visual fire rescue vehicle and personnel statistical analysis and display system according to claim 1, characterized in that, The statistical analysis and display module includes a rescue data display unit and an equipment responsibility tracing unit; the rescue data display unit is used to visually display the data of the basic data acquisition module, the initial resource allocation module, and the on-site resource allocation module in real time; The equipment responsibility tracing unit is used to visualize the equipment transfer directed graph and trace the equipment responsibility.

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