Visual emergency management command system

Abstract

The invention relates to the technical field of emergency management, in particular to a visual emergency management command system which comprises a network channel judgment module, a broadcast circling adjustment module, a material linkage retrieval module, a bidirectional response matching module and an instruction popup prompt module. And judging the fluctuation condition of the signal-to-noise ratio along with time. According to the method, the signal dynamic change and the communication quality sequence are fused, multi-channel use is optimized in real time, the boundary is dynamically linked according to spatial distribution and equipment motion characteristics in the region circling operation, and multi-dimensional association is realized by combining the spatial distance between a team and a warehouse and a material demand type; the supply-demand relationship is automatically graded according to the actual supply difference and visual identification is realized, and the material gap is displayed through popup window information and geographical highlight linkage, so that multi-link data-driven linkage across network, space and resource dimensions is integrally realized, the fine resource allocation and efficient response capabilities are improved, and the collaborative guarantee in an emergency scene is enhanced.

Description

Technical Field

[0001] This invention relates to the field of emergency management technology, and in particular to a visual emergency management command system. Background Technology

[0002] Emergency management primarily involves early warning, monitoring, analysis, command, and resource coordination for public emergencies. This field focuses on the efficient collection and transmission of information, multi-departmental collaboration, and rapid response and decision support in the event of disasters, accidents, or public health emergencies. Traditional visual emergency management command systems provide a platform for commanders to view the situation on-site and support decision-making through geographic information layer display, data report generation, integrated surveillance video, and event status visualization. They typically employ geographic information system data overlay, graphical interface display, real-time information synchronization, and event log management to uniformly display and manage emergency events, resource distribution, and on-site conditions.

[0003] When dealing with emergencies, existing technologies rely heavily on single static parameters for network channel switching, and the selection of on-site maps and the display of equipment locations are often limited to periodic updates. During resource scheduling, team and material data cannot achieve multi-dimensional interactive matching, and there is a lack of visual prompts based on dynamic differences and real-time needs. Information push can only cover basic status. In practical applications, in complex scenarios such as large-scale equipment movement and fluctuations in resource demand, traditional platforms suffer from scheduling delays, insufficient resource allocation, and fragmented rescue response chains, making it difficult to meet the complex needs of collaborative command. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a visual emergency management command system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a visual emergency management command system, the system comprising: The network channel discrimination module is based on terminal equipment, analyzes signal strength changes and signal-to-noise ratio fluctuations, judges the multi-mode gateway switching response, and determines the optimal channel based on communication quality to obtain the optimal communication path sequence; Based on the optimal communication path sequence, the broadcast selection and adjustment module determines the spatial distribution of devices within the selected area, compares the device movement speed and density, adjusts the boundary to match the scene, and obtains the fence dynamic adjustment parameter set. The material linkage retrieval module dynamically adjusts the parameter group based on the fence, filters the icons of rescue teams within the coverage area, analyzes the geographical location of the teams and warehouses, determines the material allocation relationship of the nearest warehouse, and obtains the warehouse-team association distance sequence. Based on the warehouse-team association distance sequence, the two-way response matching module analyzes the correspondence between warehouses and rescue teams, optimizes the spatial distribution of team locations within the service range of warehouses, determines the difference between team supply needs and warehouse supplies, and obtains supply-demand difference matching data. Based on the supply and demand difference matching data, the instruction pop-up prompt module filters rescue teams with demand gaps, analyzes the geographical distribution of team icons, adjusts the pop-up content to display team numbers and details of missing materials, controls the prompt status, and obtains information on team material shortages.

[0006] The present invention improves upon the following: the optimal communication path sequence includes a link type identifier, channel preference order, and switching record information; the fence dynamic adjustment parameter group includes a boundary adjustment method, spatial distribution label, and dynamic delineation identifier; the warehouse-team association distance sequence includes an association index number, distance arrangement result, and pairing group label; the supply-demand difference matching data includes a gap classification type, supply quantity distribution, and difference marking information; and the team material gap display information includes a highlighted prompt element, a material detail list, and a response level identifier.

[0007] The present invention is improved in that the network channel discrimination module includes: The signal feature analysis submodule is based on the terminal device and analyzes the change process of the received wireless signal. By comparing the intensity trend and change amplitude of the signal in a continuous time period, it identifies signal interruption points and abrupt change segments, judges the stability characteristics of each signal state, and obtains a group of signal fluctuation trend indicators. The communication stability comparison submodule compares the communication continuity of multiple network links within the same time period based on the signal fluctuation trend index group, analyzes the bit error response, disconnection performance and reconnection trigger of each link, optimizes the judgment criteria for link communication smoothness, and summarizes the stability performance of each network type during communication interruption and recovery, and obtains multi-link continuity comparison data. The path optimization generation submodule determines the channel switching status of the multi-link continuity comparison data in private and public network environments, analyzes the channel adaptation performance during the switching response process, identifies channels with continuous availability, and obtains the optimal communication path sequence.

[0008] The present invention is improved in that the broadcast selection adjustment module includes: The device distribution determination submodule analyzes the geographic coordinate data of all devices within the selected area based on the optimal communication path sequence, compares the spatial distribution pattern and density between devices, determines the distribution trend of devices in each spatial block, identifies blocks with changes in spatial distribution, and obtains the spatial block distribution status. The dynamic boundary adjustment submodule determines the direction of change of the device movement trend relative to the boundary based on the spatial block distribution status, optimizes the boundary adjustment method, compares the original boundary with the device distribution relationship, adjusts the spatial expansion range of the selected boundary, and obtains the boundary expansion relationship group. The scene parameter matching submodule analyzes the current scheduling scene requirements based on the boundary extension relationship group, optimizes the correspondence between the boundary and the device task category, determines the task distribution of the device within the boundary, identifies the device distribution status that meets the scene requirements, adjusts the boundary rules, and obtains the fence dynamic adjustment parameter group.

[0009] The present invention is improved in that the material linkage retrieval module includes: The team icon filtering submodule dynamically adjusts the parameter group based on the fence, analyzes the boundary set and spatial distribution labels, filters rescue team icons within the selected range, determines the geographical location and spatial affiliation of each team icon, optimizes the filtering process, and obtains the spatial affiliation set of team icons. The geolocation calculation submodule compares the spatial coordinates between each rescue team and the warehouse based on the team icon spatial affiliation set, calculates the spatial interval between each team and the warehouse, determines the correspondence between the team and the warehouse, filters the pairing with the best distance, and obtains the team-warehouse spatial association pairing data. The material allocation and determination submodule analyzes the material demand types of each rescue team and warehouse based on the team-warehouse spatial association pairing data, determines the matching degree of material types in each pairing, optimizes the material allocation combination, compares the supply and demand relationship between team needs and existing warehouse materials, and obtains the warehouse-team association distance sequence.

[0010] The present invention is improved in that the bidirectional response matching module includes: The warehouse-team pairing determination submodule compares the geographical relationship between the coordinates of the rescue team's location and the warehouse service area based on the warehouse-team association distance sequence, determines whether the team's location is within the warehouse's coverage area, filters valid pairing combinations, and counts the coverage of the teams corresponding to each warehouse service to obtain the warehouse's effective service distribution parameters. The supply-demand discrepancy calculation submodule compares the material demand of the rescue team with the warehouse inventory based on the warehouse's effective service distribution parameters, calculates the degree of deviation between the demand quantity and the available quantity of each type of material, and obtains the degree of supply-demand discrepancy. Based on the degree of supply-demand misalignment, the difference screening and evaluation submodule screens key rescue team and material combinations, determines the urgency level of the task and the influencing factors of allocation, optimizes the priority order of combinations, adjusts the combination screening criteria, compares the distribution characteristics of the screening results at the spatial and task levels, and obtains supply-demand misalignment matching data.

[0011] The present invention is improved in that the instruction pop-up prompt module includes: The team screening submodule analyzes the supply and demand difference matching data of the rescue teams, compares the supply and demand differences of each team under the current allocation conditions, screens teams with material shortages, determines the emergency response level and material category of the teams, optimizes the screening process, and obtains the screening results of the differentiated teams. Based on the results of the differential team screening, the icon labeling submodule analyzes the geographical distribution characteristics of the screened teams on the map, optimizes the icon style, combines the distribution density and positional relationship of the teams with the map layer, compares the visualization priority of each team's icon, adjusts the display style, and obtains visual icon labeling data. The pop-up generation submodule analyzes the material needs details of each team based on the visual marker data, determines their display priority, filters the teams that need pop-up prompts, optimizes the pop-up content structure, and adjusts the display order of team numbers and missing materials in the pop-up to obtain the material shortage display information for each team.

[0012] The present invention is improved in that the terminal device refers to various mobile or fixed devices with communication, positioning and data transmission functions; the switching response refers to the dynamic response behavior of the multi-mode gateway device when it detects a decline in the quality of the current connected network channel or an abnormality, and automatically switches to a backup or better network channel; and the coverage area refers to the target geographical area determined and dynamically adjusted by the broadcast selection and adjustment module.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by integrating dynamic changes in signals with the order of communication quality, the use of multiple channels is optimized in real time. In the area selection operation, the boundary is dynamically linked based on spatial distribution and equipment movement characteristics. Multi-dimensional association is achieved by combining the spatial distance between the team and the warehouse and the type of material demand. The supply and demand relationship is automatically classified according to the actual supply difference and visualized. Material gaps are displayed through pop-up information and geographic highlighting. Overall, multi-stage data-driven linkage across network, space and resource dimensions is realized, which improves the ability of fine resource allocation and efficient response and strengthens collaborative support in emergency scenarios. Attached Figure Description

[0014] Figure 1 This is a system flowchart of the present invention; Figure 2 This is a flowchart of the network channel discrimination module in this invention; Figure 3 This is a flowchart of the broadcast selection adjustment module in this invention; Figure 4 This is a flowchart of the material linkage retrieval module in this invention; Figure 5 This is a flowchart of the bidirectional response matching module in this invention; Figure 6 This is a flowchart of the instruction pop-up prompt module in this invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0016] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0017] Example

[0018] Please see Figure 1 This invention provides a technical solution: a visual emergency management command system comprising: The network channel discrimination module is based on the terminal device, analyzes the trend of received signal strength change, judges the signal-to-noise ratio fluctuation over time, optimizes the bit error rate parameter, compares the stability differences of multiple network communications, judges the switching response of multi-mode gateway devices in dedicated and public network environments, and determines the optimal channel based on the communication quality order to obtain the optimal communication path sequence. The broadcast selection adjustment module determines the spatial distribution status of devices within the map selection area based on the optimal communication path sequence, optimizes the dynamic acquisition method of center coordinates and boundary sets, compares the spatial movement speed of devices with the actual distribution density, adjusts the selection boundary range, and matches the current scene requirements to obtain the fence dynamic adjustment parameter set; The material linkage retrieval module dynamically adjusts the parameter group based on the fence, filters all rescue team icons within its coverage area, analyzes the geographical relationship between each rescue team and the warehouse, compares the straight-line distance between the rescue team and the warehouse, determines the material allocation relationship between the nearest warehouse and each rescue team, and obtains the warehouse-team association distance sequence by matching the rescue team's demand information with the warehouse list. The two-way response matching module analyzes the correspondence between warehouses and rescue teams based on the warehouse-team association distance sequence, optimizes the spatial distribution of rescue team bases within the service range of warehouses, determines the difference between the supply needs of rescue teams and the available materials in warehouses, and filters the supply and demand difference matching data in sequence according to the demand gap data. The instruction pop-up notification module uses supply and demand difference matching data to filter rescue teams with demand gaps, analyzes the geographical distribution characteristics of team icons on the map, optimizes the display of highlighted icons, adjusts the pop-up content to display team numbers and details of missing materials, and controls the pop-up notification status according to the urgency level to obtain information on team material shortages.

[0019] The optimal communication path sequence includes link type identifier, channel preference order, and switching record information; the fence dynamic adjustment parameter group includes boundary adjustment method, spatial distribution label, and dynamic delineation identifier; the warehouse-team association distance sequence includes association index number, distance arrangement result, and pairing group label; the supply and demand difference matching data includes gap classification type, supply amount distribution, and difference marking information; and the team material gap display information includes highlighted prompt elements, material details list, and response level identifier.

[0020] In the network channel discrimination module, terminal equipment refers to various mobile or fixed devices with communication, positioning, and data transmission functions, including 4G terminals, vehicle-mounted mobile terminals, portable radios, command terminals, etc., serving as network access points for the emergency management platform; signal strength change trend refers to the trajectory of the received wireless signal strength over time during communication, used to judge signal quality stability and network adaptability; time fluctuation refers to the fluctuation characteristics of wireless parameters such as signal-to-noise ratio at different time points during the establishment and maintenance of the communication link, reflecting the real-time status of signal interference or environmental influences; bit error rate... Rate parameter refers to the ratio of erroneous bits to the total number of bits in a communication link during signal transmission, used to measure the accuracy of data transmission; multi-network communication stability difference refers to the different characteristics of stability, reliability, and continuity exhibited by multiple available network links such as 1.4G private network, 4G public network, and satellite Internet in data transmission; switching response refers to the dynamic response behavior of a multi-mode gateway device when it detects a decline or anomaly in the quality of the currently connected network channel and automatically switches to a backup or better network channel; optimal channel refers to the network link with the highest communication quality evaluation among all currently available networks after a series of parameter comparisons and weighted judgments.

[0021] In the broadcast selection and adjustment module, the map selection area refers to a geometric region (such as a polygon or circle) selected by the dispatcher on the visual map interface using a mouse or other means, used to limit the target range for operations such as broadcast notifications, team statistics, and resource allocation; the device spatial distribution status refers to the geographical coordinate distribution of all online terminal devices within the selected area, including the density, concentration, and positional relationship of the distribution; the dynamic acquisition method refers to the system automatically collecting and refreshing parameters such as the center coordinate point and boundary set when real-time events such as user selection, device movement, or scene changes occur, rather than single static collection; device space Inter-device movement speed refers to the real-time displacement speed of each device within the selected area on the map space, used to determine whether the device is in a high-dynamic scene or needs to expand the broadcast range; actual distribution density refers to statistical characteristics reflecting the spatial density or sparseness, such as the average distance between devices within the selected area and the number of devices per unit area; the selected boundary range refers to the boundary of the area formed by the user's selection on the map, and the system can adaptively adjust its shape or size according to the actual device distribution and needs; current scenario requirements refer to the specific parameter requirements for the selection operation based on the nature of the scheduling task, device distribution, instruction content, broadcast priority, etc.

[0022] In the material linkage retrieval module, the coverage area refers to the target geographical area determined and dynamically adjusted by the broadcast selection and adjustment module, which includes all identified and statistically analyzed rescue team icons, warehouse icons, etc.; the geographical location relationship refers to the spatial orientation, straight-line distance, relative position, geographical distribution, and other relationships between rescue teams and warehouses; the material allocation relationship refers to the business association that determines which warehouse should prioritize allocating materials to which team based on geographical location, warehouse inventory, and team demand data; and the corresponding processing refers to the association, pairing, and scheduling processing between rescue team demand information and warehouse material list data according to standards such as distance, type, and quantity.

[0023] In the two-way response matching module, the correspondence relationship refers to the one-to-one or many-to-many scheduling and supply relationship between the rescue team and the warehouses it can serve, established through the distance sequence of the warehouse team association; the spatial distribution within the service range refers to the geographical distribution of the warehouse to all the rescue team's bases in its surrounding area, a specific radius, or within the reachable area; the difference refers to the inconsistency in value or category between the actual supply demand of the rescue team and the current available supply quantity of the warehouse; the demand gap data sequential filtering refers to filtering out the teams and material categories that need to be prioritized for supply based on the above differences, according to the size of the gap, priority, or urgency.

[0024] In the instruction pop-up notification module, geographical distribution characteristics refer to the actual geographical location of the team icons on the map interface and their spatial distribution patterns, such as clustered, dispersed, and remote; icon presentation refers to the front-end visual display methods such as the display style, color, border, and animation effects of the rescue team or warehouse icons in the visualization interface; urgency level refers to the urgency of the rescue team's supply needs, which is usually determined by a comprehensive judgment based on the size of the gap, the mission level, and on-site feedback, and is used to dynamically adjust the notification priority; pop-up notification status refers to the variable front-end status of the corresponding pop-up after an icon on the map is selected or filtered by the system as a key focus object, including its content, display logic, automatic highlighting, and warning style.

[0025] This visualized emergency management command system is a platform with multi-dimensional signal coverage guarantee through a hybrid network of 1.4G private network, 4G public network and satellite Internet. It includes a dispatch system with functions such as GIS, audio and video transmission, equipment status monitoring, and command and dispatch. Its main purpose is to provide command and dispatch personnel at all levels with global, real-time and intuitive on-site situation awareness capabilities to achieve the purpose of command and dispatch. It enables command and dispatch functions for independent networking of 1.4G private network and hybrid networking of 4G network equipment, and the self-organizing network nodes adopt AES 128-bit hardware encryption. It also includes a selection and broadcast function: the dispatcher can select an area on the map with the mouse (selection), and the online 4G law enforcement recorder, vehicle mobile terminal and other devices that support voice intercom function within the box will form a new temporary group. The dispatcher can then broadcast notifications to the selected group of devices. It also includes trajectory playback: linked with the trajectory button in online command, it allows users to view the historical movement trajectory path of a specified device in the history playback, combined with a map.

[0026] The specific functions for managing material teams include: It is mainly used by emergency rescue command centers to intuitively and quickly view the location distribution and team names of emergency rescue teams at all levels on a map during emergencies. At the same time, it displays the number of people in the rescue team, the duty phone number, and the list of rescue equipment and materials configured online in real time. It also displays the list of rescue material warehouses and reserve materials of governments at all levels online.

[0027] Simply click the "Supply Teams" button in the upper right corner of the screen to open it. Rescue teams and warehouse icons will appear on the map. When the mouse hovers over the "Rescue Teams and Warehouses" icon, the team name, detailed address, number of personnel, and duty phone number will automatically pop up. When the mouse hovers over the supply warehouse icon, the warehouse name, detailed address, and list of reserved supplies will automatically be displayed. The data is updated monthly in advance by the system administrator.

[0028] Please see Figure 2The network channel discrimination module includes: The signal feature analysis submodule is based on the terminal device and analyzes the change process of the received wireless signal. By comparing the intensity trend and change amplitude of the signal in a continuous time period, it identifies signal interruption points and abrupt change segments, judges the stability characteristics of each signal state, and obtains a group of signal fluctuation trend indicators. After the terminal device's communication module is activated, the received wireless signal strength value is periodically collected at a frequency of 5 times per second and a sampling period of 30 seconds. Within this period, 150 sets of signal strength values ​​are recorded. The values ​​are sorted chronologically and subtracted sequentially to calculate the difference between consecutive data points, forming a fluctuation sequence. Furthermore, a three-point sliding window method is used to form a local slope sequence for each group of three adjacent data points. If the slope direction of the current window is opposite to that of the previous window, and the difference between the maximum and minimum values ​​in the difference sequence exceeds 5 dBm, a sudden change is considered to have occurred at that point. Three consecutive sudden changes are considered a sudden change segment. If the signal strength at any given time is below -105 dBm and remains below that level for an extended period... If the interval exceeds 3 seconds, it is marked as a signal interruption segment. For the remaining unclassified segments, fluctuation analysis is performed to calculate their signal strength variance and range. When the variance of a segment is greater than 9, it is considered that the signal fluctuation is too large and is marked as an unstable segment. Segments with a variance of less than 4 are considered stable segments. All data segments in the entire sampling period are classified and marked as stable segments, abrupt segments, or interruption segments according to the above rules. At the same time, parameters such as the average strength, fluctuation trend, and slope change value of adjacent segments are statistically analyzed for subsequent analysis. For example, in a certain sampling, the terminal device signal fluctuates in the range of -85 to -95dBm, with 3 abrupt changes and a fluctuation variance of 11. This segment is classified as an abrupt segment. After summarizing all the markings, a group of signal fluctuation trend indicators is formed.

[0029] The communication stability comparison submodule compares the communication continuity of multiple network links within the same time period based on the signal fluctuation trend index group, analyzes the bit error response, disconnection performance and reconnection trigger of each link, optimizes the judgment criteria for link communication smoothness, and summarizes the stability performance of each network type during communication interruption and recovery, and obtains multi-link continuity comparison data. The system calls multiple communication interface modules of the terminal device to simultaneously evaluate the signal stability of different network links. For each link, three indicators are extracted: the number of stable segments, the proportion of abrupt changes, and the cumulative duration of interruptions. These indicators are then combined into a statistical matrix for horizontal comparison. Further data on the bit error rate and number of dropped connections for each link are read. If the number of dropped connections exceeds 2 and the cumulative interruption duration is greater than 10 seconds, the link is classified as having poor continuity. Based on whether the number of stable segments is greater than 4, the proportion of abrupt changes is less than 0.2%, and the interruption duration is less than 5 seconds, it is determined to be a high continuity link, with 2 to 4 stable segments and a proportion of abrupt changes. Links with a frequency change rate below 0.4 and interruptions between 5 and 10 seconds are classified as having medium continuity. Links with fewer than 2 stable segments, a frequency change rate above 0.4, and an interruption time exceeding 10 seconds are classified as having low continuity. The reconnection frequency of each link under its category is calculated. If the number of reconnections is less than 1, it is further marked as a stable link. For example, link A has 5 stable segments, a frequency change rate of 0.15, an interruption time of 2 seconds, and 0 disconnections, and is marked as a high continuity link. Link B has only 1 stable segment, a frequency change rate of 0.45, an interruption time of 12 seconds, and 3 disconnections, and is marked as a low continuity link. The comparison is used to form multi-link continuity comparison data.

[0030] The path optimization generation submodule determines the channel switching status of multi-link continuity comparison data, analyzes the channel adaptation performance during the switching response process, identifies channels with continuous availability, and obtains the optimal communication path sequence. First, extract the current channel type and channel switching history logs recorded by the gateway device, including parameters such as switching start and end times, channel strength, and signal-to-noise ratio. When a switching action occurs, the duration of the switching process is calculated. If the channel switching time exceeds 1.5 seconds and there are consecutive abrupt changes after the switching, it is recorded as an abnormal switching channel. From this, channels with a switching response time of less than 1 second and whose consecutive data segments after the switching are stable are selected as the candidate channel set. Then, compare the continuity comparison data to find channels with high continuity links and no abnormal switching records, and include them in the continuously available channel set. Then, for each channel in the set, its average signal-to-noise ratio (SNR), average signal strength, and number of stable segments are calculated sequentially. The communication quality score (Q-value) of each channel is calculated using a fixed weighting method, and the channels are sorted from high to low based on their Q-values. For example, channel A has an average SNR of 20dB, an average signal strength of -80dBm, and 5 stable segments, while channel B has an SNR of 18dB, a signal strength of -75dBm, and 6 stable segments. After weighted Q-value calculation, channel B's score is slightly higher than that of channel A. Therefore, channel B is selected first, and the optimal communication path sequence is generated based on the channel score results.

[0031] Please see Figure 3 The broadcast selection adjustment module includes: The device distribution determination submodule analyzes the geographic coordinate data of all devices within the selected area based on the optimal communication path sequence, compares the spatial distribution pattern and density between devices, determines the distribution trend of devices in each spatial block, identifies blocks with changes in spatial distribution, and obtains the spatial block distribution status. The system retrieves the geographic coordinate data of the terminal devices within the selected area. By extracting latitude and longitude coordinates and converting them to relative position coordinates in a planar coordinate system, the coordinates of each device are marked, generating a two-dimensional point distribution map. The entire selected area is then divided into multiple spatial blocks using a 50-meter grid. The number of devices within each block is counted, and the device density per unit area is calculated. Areas with a device density less than 0.01 units / square meter are marked as sparse blocks, those between 0.01 and 0.03 units / square meter as medium-dense blocks, and those greater than 0.03 units / square meter as high-dense blocks. Furthermore, the average distance from each device to the centroid within each block is calculated. If the average distance varies beyond a certain range... If the distance exceeds 5 meters, the block is marked as a distribution fluctuation block. By comparing the changes in equipment coordinates of each block in two adjacent time periods, it is determined whether there is a trend of equipment density shifting to the edge or clustering. For example, if a block originally has 9 devices with a density of 0.036 devices / square meter, and the number drops to 6 devices in the next moment, the density drops to 0.024, and it is marked as a density change block. The average distance between two adjacent devices in each block is calculated. If the distance decreases by more than 3 meters, the block is judged as a clustering change block. Through the above processing method, the equipment density type and distribution change characteristics of all spatial blocks are identified, and corresponding block numbers, coordinate ranges, and distribution status labels are generated, outputting the spatial block distribution status.

[0032] The dynamic boundary adjustment submodule determines the direction of change of the equipment movement trend relative to the boundary based on the spatial block distribution status, optimizes the boundary adjustment method, compares the original boundary with the new equipment distribution relationship, adjusts the spatial expansion range of the selected boundary, and obtains the boundary expansion relationship group. Read the boundary coordinate set of the currently selected area and call the relative direction vector data of each boundary point. Compare the rate of change of the number of devices in each block inside and outside the boundary. If the growth rate of the number of devices in the adjacent external block is higher than 25%, it is judged to be an area with a significant clustering trend outside the boundary. It is necessary to consider expanding the current boundary in this direction. Set the maximum expandable distance threshold of 200 meters for each direction of the boundary. Try expanding in the corresponding direction step by step by 50 meters, 100 meters, 150 meters, and 200 meters, and record the number of new devices in the boundary after each expansion. If the number of new devices reaches more than 8 after expanding by 100 meters, and the density reaches more than 0.03 devices / square meter, it is judged that the expansion in this direction is reasonable, and the original boundary is updated by 10 in this direction. When multiple directions meet the conditions simultaneously, the expansion data for each direction is recorded and combined to form a boundary adjustment matrix. The distance between each side boundary and the edge of the densely populated area is compared before and after expansion. If the distance is shortened from more than 50 meters to less than 20 meters, it is considered a valid fit adjustment. Conversely, if the dense area is still more than 80 meters away from the boundary after adjustment, it is determined that the adjustment is invalid and the boundary is reverted. For example, there is a dense area outside the north side of the original boundary, where the number of devices has increased from 8 to 13, a growth rate of 62.5%. After expanding by 100 meters, 10 new devices are added, with an average density of 0.04 devices / square meter. In this case, it is determined that the north boundary needs to be expanded by 100 meters and updated to the new boundary coordinates, generating a boundary expansion relationship group.

[0033] The scene parameter matching submodule analyzes the current scheduling scene requirements based on the boundary extension relationship group, optimizes the correspondence between the boundary and the device task category, determines the task distribution of the device within the boundary, identifies the device distribution status that meets the scene requirements, adjusts the boundary rules, and obtains the fence dynamic adjustment parameter group. The system invokes the parameter configurations for the current task scenario in the scheduling platform, including task type, priority requirements, and resource allocation mode. For example, in a scenario of centralized material distribution, priority is given to covering equipment transportation equipment. Subsequently, task tags are compared for all equipment within the selected boundary area. The task type field is extracted from the equipment information, and equipment marked with the task type "equipment transportation" is screened out. Their quantity and distribution within the boundary are counted, and their proportion in each block is calculated. If the proportion of target task equipment in a certain block exceeds 60%, it is marked as a target task concentration block. Further comparison is made to see if this block is within the adjusted boundary area. If a target task concentration block is found to be located in the area near the outer edge of the boundary and can be covered after the boundary is extended, the boundary is finely adjusted and expanded. The boundary is refitted to a minimum bounding polygon covering all target task devices when there are significant differences in the distribution of device task categories. During boundary fitting, the minimum area and maximum axis length are constrained to not exceed 50% of the original boundary expansion. The minimum coverage requirement for devices in the task scenario is compared with the current coverage status. If the requirement is met, the current boundary is fixed. If not, the boundary is extended by 10 meters to a maximum of 50 meters towards the edge of each target block. The number of extensions shall not exceed 5. For example, if the current task requires at least 20 transportation devices to be covered, 17 devices are covered within the original boundary, and 5 devices are clustered in the area outside the southeast direction of the boundary, after extending by 20 meters, 4 more devices are added to cover a total of 21 devices. Once the conditions are met, the boundary is fixed, forming a fence with dynamically adjusted parameter groups.

[0034] Please see Figure 4 The material linkage retrieval module includes: The team icon filtering submodule dynamically adjusts the parameter group based on the fence, analyzes the boundary set and spatial distribution label, filters the rescue team icons within the selected range, determines the geographical location and spatial affiliation of each team icon, optimizes the filtering process, and obtains the spatial affiliation set of team icons. The adjusted boundary coordinates are used as the two-dimensional spatial boundary region. Then, the current geographic coordinates of all registered rescue team icons are extracted from the map visualization system. The latitude and longitude coordinates of each team icon are converted and mapped to coordinate values ​​in the same planar projection system as the boundary coordinates. Next, it is determined whether each icon is within the boundary range. This is done by performing a point inclusion check between each icon's coordinates and the boundary polygon. If the point is inside the boundary polygon, it is marked as a "team within the boundary"; otherwise, it is marked as a "team outside the boundary". Finally, the spatial distribution labels of all team icons within the boundary are extracted, including their grid number, distance from adjacent icons, and distance from the boundary edge. The shortest distance and other spatial information are used to further associate the marking results with the spatial annotation structure to determine the block to which each icon belongs in the grid. If multiple team icons exist in a block and the distance between the icons is less than 30 meters, the block is considered a "centralized belonging area". Otherwise, it is a "discrete belonging area". The judgment results are summarized and data records with fields such as team icon number, spatial coordinates, block, and relationship with the boundary are formed. For example, if the team icon number is R03, its coordinates are (468, 322), it is located inside the boundary polygon, the grid number is C14, and the distance between the icons is less than 30 meters, then R03 is classified as a centralized belonging block, forming a spatial belonging set of team icons.

[0035] The geolocation calculation submodule compares the spatial coordinates between each rescue team and the warehouse based on the spatial affiliation set of team icons, calculates the spatial interval between each team and the warehouse, determines the correspondence between teams and warehouses, filters the pairing with the best distance, and obtains the team-warehouse spatial association pairing data. Extract the spatial coordinates of each rescue team icon and perform a one-to-many combination calculation with the warehouse icon coordinates to generate coordinate pairs between teams and warehouses for each group. Use the spatial coordinate calculation formula to calculate the Euclidean distance between each team and all warehouses, construct a distance matrix, and store each distance value as a floating-point number with two decimal places in a structure table. Sort all distance values ​​and determine the closest pairing relationship between each team and all warehouses. If the distance between a warehouse and a team is the shortest and the distance value is less than 1500 meters, it is recorded as a "valid pairing"; otherwise, it is marked as a "pairing to be supplemented". Further, call the warehouse service capacity parameters to determine if a warehouse is... If a warehouse is already associated with more than three teams, it is marked as a "saturated warehouse." All teams will remove priority from pointing to this warehouse and instead select the next warehouse with the shortest distance and that is not saturated for re-pairing. In all pairing relationships, the team number, warehouse number, shortest distance value, whether it is the first pairing, and whether it is a substitute pairing are recorded. For example, if the distance between team number R08 and warehouse number W02 is 978 meters and W02 is not saturated, then R08 will be paired with W02. If W02 is already bound to three teams, then R08 will be paired with the next closest warehouse, W03, which is 1102 meters away, forming team-warehouse spatial association pairing data.

[0036] The material allocation and determination submodule analyzes the material demand types of each rescue team and warehouse based on the spatial association and pairing data of the teams and warehouses, determines the degree of matching of material types in each pairing, optimizes the material allocation combination, compares the supply and demand relationship between the team's needs and the existing materials in the warehouse, and obtains the warehouse-team association distance sequence. Read the material requirement list of the paired teams, record the required category number, required quantity, and urgency level for each material type, and simultaneously read the inventory list information of the paired warehouse. For each material number, check if the corresponding category item exists in the warehouse list. If it exists, read the current inventory quantity. If the inventory is greater than or equal to the required quantity, record it as "sufficient pairing"; if the inventory is less than the required quantity but still greater than zero, record it as "partial shortage"; if the inventory item does not exist or the inventory is zero, record it as "complete shortage". For the needs of multiple teams paired with the same warehouse, construct a supply and demand matrix sequentially. The matrix columns are team numbers, the rows are material numbers, and the cells are marked with the supply and demand relationship status. Then, mark and summarize the records of partial and complete shortages in all paired teams under each warehouse. The system calculates the quantity and rate of material shortages. If the shortage rate of a team under a warehouse exceeds 60%, the material allocation status of that warehouse is marked as a "high-pressure warehouse," requiring a replenishment prompt. The total material demand is weighted, with the weight value set according to the urgency level: 1.0 for level 1, 0.75 for level 2, and 0.5 for level 3. The weighted shortage quantity is calculated and sorted for all demanded materials under each pairing relationship. Fields such as warehouse number, team number, corresponding material number, demand quantity, available inventory, shortage status, and weighted score are generated for each pairing. For example, if team R05 requests 50 boxes of "drinking water" from warehouse W01, but W01 only has 20 boxes, it is set as a partial shortage with an urgency level of level 1. The weighted shortage is 30, and this item is recorded as a key material for allocation. A warehouse-team association distance sequence is generated.

[0037] Please see Figure 5 The bidirectional response matching module includes: The warehouse-team pairing determination submodule compares the geographical relationship between the coordinates of the rescue team's location and the warehouse service area based on the warehouse-team association distance sequence, determines whether the team's location is within the warehouse's coverage area, filters valid pairing combinations, and counts the coverage of the teams corresponding to each warehouse service to obtain the effective service distribution parameters of the warehouse. The system retrieves the coordinates of the rescue teams' bases, reads their corresponding latitude and longitude data, and converts them into absolute positions in a unified plane coordinate system. It then extracts the service coverage radius value set for each warehouse as the radius boundary; for example, the service radius of warehouse W01 is set to 2000 meters. The distance between the warehouse coordinates and the rescue team's base coordinates is then calculated. If the Euclidean distance from the team's base to the warehouse is less than or equal to the corresponding service radius value, the team is considered to be within the warehouse's service coverage area; otherwise, it is considered to be outside the coverage area. After comparing all rescue teams item by item, the team numbers of all teams within the effective service radius are marked, and this group of warehouses and team numbers is set as a "valid pairing combination." The number of valid paired teams for each warehouse is then calculated. The system performs statistical analysis, calculates the total number of teams that a warehouse can currently serve, and compares it with its maximum service capacity. If the number of teams served exceeds the maximum capacity, the excess teams are removed from the valid pairing set. The system then selects the second closest warehouse to re-evaluate the service, regenerates the pairing relationships, and updates the pairing records. For example, if warehouse W03 has a maximum service capacity of 4 teams and 6 teams within its service radius meet the criteria, the two furthest teams are removed and marked as "awaiting reallocation." The system summarizes all valid pairings between warehouses and their service ranges and outputs each warehouse number, a list of service team numbers, a pairing validity flag, and a coverage quantity field to obtain the warehouse's valid service distribution parameters.

[0038] The supply-demand discrepancy calculation submodule, based on warehouse effective service distribution parameters, compares the material needs of rescue teams with warehouse inventory, calculates the deviation between the required quantity and the available quantity for each type of material, using the following formula: ; The degree of supply and demand offset is obtained, among which, Indicates the first The rescue team and the first The warehouse in the first The degree of supply and demand imbalance in similar goods Indicates the first The rescue team for the first The quantity requirements of such materials Indicates the first The warehouse can supply the first The quantity of Category j supplies allocated by the rescue team. Indicates the first The urgency level factor for supplying the rescue teams. Indicates the first The supply response coefficient of this type of material. Indicates the first The rescue team in the The proportion of shortages in this type of material Indicates the first Category of materials and the first Functional compatibility coefficient of similar materials Indicates the total number of material categories. Indicates the index number of the rescue team. Indicates the material category index number, Indicates the relationship with the first The warehouse index number associated with the rescue team. Indicates the summation index number of the material category; The degree of supply-demand imbalance measures the overall strength of the difference between supply and demand in terms of both absolute quantity and category structure for a specific rescue team in the supply of a certain type of materials. It is a quantitative reflection of the "balance state of material allocation". The higher the value, the more prominent the supply-demand contradiction of the combination of materials and the higher the allocation priority. The quantities of supplies needed by the rescue teams are compared with the corresponding quantities available in the warehouses. The quantity offsets for the same type of supplies are calculated, and the data is normalized according to the urgency level of the mission and the response characteristics of the supply allocation to unify the calculation benchmark under different dimensions. The normalization method adopts standard deviation normalization. First, the first... The rescue team is numbered The matched warehouse number is Its impact on the first Quantity required for such supplies (e.g., drinking water) Original value Items, corresponding warehouse available quantity Original value The items, after standard deviation normalization, are as follows: , The team's supply urgency level factor The original level was set to medium level. After normalization , No. Response coefficient for the allocation of similar materials The original response period is Hours, after normalization Regarding complementary supplies, the team provided the first... Quantity required for such supplies (e.g., dry rations) Original value Items, Shortage Ratio The original ratio is After normalization, they are respectively , , No. Class and the Compatibility coefficient of different types of materials Originally set to Even after normalization, it remains as Based on the above parameters, substitute them into the formula: The denominator for the first term is: ; The first numerator is: ; The first result is: ; The second calculation is as follows: ; The result is: ; Based on historical allocation data and task-level response mechanisms, the degree of supply-demand imbalance is preset. The reference intervals are divided as follows: when This indicates that the supply and demand relationship between the team and the warehouse for this type of material is basically matched, and it falls within the range of balanced allocation; when When this occurs, it indicates a slight difference between supply and demand, but it does not affect the basic allocation arrangements and falls within a slightly offset range. when When the time is right, it indicates that there is a difference in quantity or an imbalance in the complementary structure of the allocation, and the allocation strategy should be given priority. This is in the moderate deviation range. when At this time, it indicates that the team is currently experiencing a significant shortage of supplies, posing a risk of mission interruption, and is considered to be in a severely off-target range.

[0039] get The results indicate that the current combination (the supply and demand matching of the first rescue team and Warehouse A in the first category of materials) is in a moderate deviation range, indicating a structural deviation between the team's material needs and the warehouse's allocation capacity. Further quantitative evaluation is needed by introducing dimensions such as task level and spatial deployment influence factors in the subsequent difference screening and evaluation steps. This value not only reflects the current imbalance in material allocation but also constitutes a key supporting quantity for decision ranking and screening mechanisms in the system's allocation logic. The formula, through a dual-channel calculation path of quantitative difference and complementary structure, can accurately quantify the imbalance in allocation and express it uniformly in a normalized numerical framework, providing a quantitative reference for subsequent selection of priority combinations.

[0040] The difference screening and assessment submodule screens key rescue team and material combinations based on the degree of supply and demand offset, determines the urgency level of the task and the influencing factors of allocation, optimizes the priority order of combinations, adjusts the combination screening criteria, compares the distribution characteristics of the screening results at the spatial and task levels, and obtains supply and demand difference matching data. Extract all rescue team numbers and material shortage lists from the supply-demand discrepancy table. Record the required quantity, available quantity, and corresponding difference range for each material. Mark records with an absolute difference greater than 50 as key supply-demand offset items. Further read the task urgency level field for all key items. If the task level is Level 1 or 2, its urgency weight is set to 1.0 or 0.75; if it is Level 3, it is 0.5. Multiply the urgency weight by the material shortage value to obtain an urgency score. Sort all material shortage records according to the score from high to low, and select the top 30% of records as the priority supply-demand matching combination. Record the team number, material type, and score value for each combination. Then read the allocation impact factor, which consists of the complexity of material type allocation and the length of replenishment cycle. Set the impact factor for materials with a replenishment cycle exceeding 48 hours as high (0.8), and also set complex allocation types such as cold chain materials as high impact factors (0.9). After combining the urgency score and impact factor weights, sort the groups again. Prioritize the combinations. If a combination's score, multiplied by the influence factor, still ranks in the top 10%, it is identified as a key allocation item. Then, perform spatial feature statistics on all selected combinations, calculating the team geographical distribution density of each resource shortage combination in the map area. If they are concentrated in 3 or fewer spatial grids, they are classified as "spatial clustered"; if they are distributed in more than 5 areas, they are marked as "spatial discrete". At the same time, analyze the task type distribution. If most teams' task type is "basic support", it is marked as "support-type concentrated shortage"; if the task types are diverse, it is marked as "mixed task difference". For example, rescue team R09 has a shortage of 200 boxes of drinking water, but only the warehouse can provide 100 boxes, the difference is 100, the task level is level one, the replenishment cycle is 72 hours, the score is 100, the influence factor is 0.8, the comprehensive score is 80, and it is in the high-priority matching group. Output each team number, resource type, shortage quantity, task level, score value, and spatial distribution characteristics to obtain supply and demand difference matching data.

[0041] Please see Figure 6 The instruction pop-up prompt module includes: The team selection submodule analyzes the supply and demand matching data of rescue teams, compares the supply and demand differences of each team under the current allocation conditions, selects teams with material shortages, determines the emergency response level and material category of the teams, optimizes the selection process, and obtains the selection results of teams with differences. Extract all rescue team numbers and their corresponding shortage material types and quantities from the supply and demand difference data. Then, simultaneously read the corresponding material numbers and remaining inventory from the real-time warehouse inventory table. Calculate the shortage value for each team under a specific material item. The shortage value is the team's demand minus the warehouse allocation. If the result is positive, it is recorded as a material shortage item; if it is zero or negative, it is recorded as a supply and demand balance item. Statistically analyze the material shortage items for all teams, and filter out teams with one or more shortage records, designating them as "shortage teams." Next, read the task level identifier and the emergency response level parameter mapped to the task level for each team. For example, a level 1 task level corresponds to response level A. Response level A has a weight of 1.0 in the priority filtering, level B has a weight of 0.8, and level C has a weight of 0.6. The shortage teams are sequentially assessed based on their emergency level and the total number of missing materials. The shortage severity index is calculated as the ratio of the number of missing materials to the total number of required materials. If the ratio is greater than 0.5 and the response level is A or B, the team is designated as a "key shortage team." Subsequently, all selected teams are sorted by weighted response level and shortage severity. If the weighted value exceeds 0.7, it is prioritized for the first round of output. For example, team R12 needs 70 cases of drinking water, with 40 cases available, resulting in a shortage of 30 cases. It also needs 20 boxes of medicine, with only 5 boxes remaining, resulting in a shortage of 15 boxes. With a response level of A and a shortage rate of 100%, the weighted score is 1.0, making it a key team. The team numbers, material types, shortage values, response levels, and priority groups of all teams meeting the criteria are summarized to obtain the results of the differential team selection.

[0042] The icon labeling submodule analyzes the geographical distribution characteristics of the selected teams on the map based on the results of the differential team screening, optimizes the icon style, combines the distribution density and location relationship of the teams with the map layer, compares the visualization priority of each team's icon, adjusts the display style, and obtains visual icon labeling data. Extract the map icon IDs and geographic coordinates of all teams marked as having different roles, load the corresponding map layer configuration file, and map all team icons onto the current map display view. Then, calculate the relative position of each icon within the current visible range and the minimum distance to surrounding icons. If the minimum distance is less than 40 meters and there are more than three different team icons in the same area, mark that area as an icon clustering area and mark all icons in that area as "overlap risk." Prioritize enlarging the size and adding a red outline to icons within the overlap risk area. Further, for icons in non-overlapping areas, set a visual hierarchy based on information priority; for example, icons with priority 1 are enlarged to 120% of their original size, and so on. When the priority is 2, the size is magnified to 110%; when the priority is 3, the original size is maintained. At the same time, each icon is assigned a color code: red for first-level response, orange for second-level response, and yellow for third-level response. Then, the existing label elements and rescue markers on the map layer are extracted to determine if there is any occlusion. If there is an occlusion area, the icon position is moved to a relatively empty area, and a transparent connecting line is added to maintain the positional relationship. For example, the team icon R07 is located at the center point of the layer (450, 380), and there are 4 other icons within a 30-meter radius. It is determined to be a gathering icon, and a red frame highlight style is set. R07 is a first-level response and is marked as a red icon. The annotation information, style type, and relative priority of all icons on the map are output to obtain the visual icon marking data.

[0043] The pop-up generation submodule analyzes the material needs details of each team based on the visual icon data, determines their display priority, filters the teams that need to be prompted by pop-ups, optimizes the content structure of the pop-ups, and adjusts the display order of team numbers and missing materials in the pop-ups to obtain the material shortage display information of the teams. Extract the team number and its missing resource details for each icon. Record the resource type, required quantity, shortage value, and response level for each resource detail. Set the pop-up display size range based on the total amount of information; for example, if there are more than 5 resource items, set the pop-up width to 320 pixels, and if there are fewer than 5, set it to 280 pixels. Set the initial pop-up state for all icons to "inactive." Then, sort the icons according to their visual priority, setting the top 10 priority teams as the objects to be automatically displayed in the pop-up upon initial loading. Next, optimize the structure of the content within each pop-up, setting the team number as the first-line title, and arranging all resource items below it according to the shortage value from largest to smallest. Set the shortage value for each resource. The system uses a value labeling system. A shortage value higher than 50 is marked as a red warning, higher than 20 but less than 50 as an orange alert, and less than 20 as yellow text. Each record includes unit information to avoid ambiguity in content identification. If the same type of resource appears in the shortages of multiple teams, the text "This resource is a resource in short supply across the region" is added below the pop-up window to enhance the linkage of identification. For example, if team R14's pop-up window shows a shortage of 30 boxes of drinking water, 10 tents, and 55 first-aid kits, then the background of the drinking water entry is set to orange, and the first-aid kit entry to red. Each pop-up window displays the following information in sequence: number, type of resource in short supply, required quantity, shortage value, and level prompt, thus providing the team's resource shortage information.

[0044] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A visual emergency management command system, characterized in that, The system includes: The network channel discrimination module is based on terminal equipment, analyzes signal strength changes and signal-to-noise ratio fluctuations, judges the multi-mode gateway switching response, and determines the optimal channel based on communication quality to obtain the optimal communication path sequence; Based on the optimal communication path sequence, the broadcast selection and adjustment module determines the spatial distribution of devices within the selected area, compares the device movement speed and density, adjusts the boundary to match the scene, and obtains the fence dynamic adjustment parameter set. The material linkage retrieval module dynamically adjusts the parameter group based on the fence, filters the icons of rescue teams within the coverage area, analyzes the geographical location of the teams and warehouses, determines the material allocation relationship of the nearest warehouse, and obtains the warehouse-team association distance sequence. Based on the warehouse-team association distance sequence, the two-way response matching module analyzes the correspondence between warehouses and rescue teams, optimizes the spatial distribution of team locations within the service range of warehouses, determines the difference between team supply needs and warehouse supplies, and obtains supply-demand difference matching data. Based on the supply and demand difference matching data, the instruction pop-up prompt module filters rescue teams with demand gaps, analyzes the geographical distribution of team icons, adjusts the pop-up content to display team numbers and details of missing materials, controls the prompt status, and obtains information on team material shortages.

2. The visual emergency management command system according to claim 1, characterized in that, The optimal communication path sequence includes link type identifier, channel preference order, and switching record information; the fence dynamic adjustment parameter group includes boundary adjustment method, spatial distribution label, and dynamic delineation identifier; the warehouse-team association distance sequence includes association index number, distance arrangement result, and pairing group label; the supply and demand difference matching data includes gap classification type, supply amount distribution, and difference marking information; and the team material gap display information includes highlighted prompt elements, material detail list, and response level identifier.

3. The visual emergency management command system according to claim 1, characterized in that, The network channel discrimination module includes: The signal feature analysis submodule is based on the terminal device and analyzes the change process of the received wireless signal. By comparing the intensity trend and change amplitude of the signal in a continuous time period, it identifies signal interruption points and abrupt change segments, judges the stability characteristics of each signal state, and obtains a group of signal fluctuation trend indicators. The communication stability comparison submodule compares the communication continuity of multiple network links within the same time period based on the signal fluctuation trend index group, analyzes the bit error response, disconnection performance and reconnection trigger of each link, optimizes the judgment criteria for link communication smoothness, and summarizes the stability performance of each network type during communication interruption and recovery, and obtains multi-link continuity comparison data. The path optimization generation submodule determines the channel switching status of the multi-link continuity comparison data in private and public network environments, analyzes the channel adaptation performance during the switching response process, identifies channels with continuous availability, and obtains the optimal communication path sequence.

4. The visual emergency management command system according to claim 1, characterized in that, The broadcast selection adjustment module includes: The device distribution determination submodule analyzes the geographic coordinate data of all devices within the selected area based on the optimal communication path sequence, compares the spatial distribution pattern and density between devices, determines the distribution trend of devices in each spatial block, identifies blocks with changes in spatial distribution, and obtains the spatial block distribution status. The dynamic boundary adjustment submodule determines the direction of change of the device movement trend relative to the boundary based on the spatial block distribution status, optimizes the boundary adjustment method, compares the original boundary with the device distribution relationship, adjusts the spatial expansion range of the selected boundary, and obtains the boundary expansion relationship group. The scene parameter matching submodule analyzes the current scheduling scene requirements based on the boundary extension relationship group, optimizes the correspondence between the boundary and the device task category, determines the task distribution of the device within the boundary, identifies the device distribution status that meets the scene requirements, adjusts the boundary rules, and obtains the fence dynamic adjustment parameter group.

5. The visual emergency management command system according to claim 1, characterized in that, The material linkage retrieval module includes: The team icon filtering submodule dynamically adjusts the parameter group based on the fence, analyzes the boundary set and spatial distribution labels, filters rescue team icons within the selected range, determines the geographical location and spatial affiliation of each team icon, optimizes the filtering process, and obtains the spatial affiliation set of team icons. The geolocation calculation submodule compares the spatial coordinates between each rescue team and the warehouse based on the team icon spatial affiliation set, calculates the spatial interval between each team and the warehouse, determines the correspondence between the team and the warehouse, filters the pairing with the best distance, and obtains the team-warehouse spatial association pairing data. The material allocation and determination submodule analyzes the material demand types of each rescue team and warehouse based on the team-warehouse spatial association pairing data, determines the matching degree of material types in each pairing, optimizes the material allocation combination, compares the supply and demand relationship between team needs and existing warehouse materials, and obtains the warehouse-team association distance sequence.

6. The visual emergency management command system according to claim 1, characterized in that, The bidirectional response matching module includes: The warehouse-team pairing determination submodule compares the geographical relationship between the coordinates of the rescue team's location and the warehouse service area based on the warehouse-team association distance sequence, determines whether the team's location is within the warehouse's coverage area, filters valid pairing combinations, and counts the coverage of the teams corresponding to each warehouse service to obtain the warehouse's effective service distribution parameters. The supply-demand discrepancy calculation submodule compares the material demand of the rescue team with the warehouse inventory based on the warehouse's effective service distribution parameters, calculates the degree of deviation between the demand quantity and the available quantity of each type of material, and obtains the degree of supply-demand discrepancy. Based on the degree of supply-demand misalignment, the difference screening and evaluation submodule screens key rescue team and material combinations, determines the urgency level of the task and the influencing factors of allocation, optimizes the priority order of combinations, adjusts the combination screening criteria, compares the distribution characteristics of the screening results at the spatial and task levels, and obtains supply-demand misalignment matching data.

7. The visual emergency management command system according to claim 1, characterized in that, The instruction pop-up prompt module includes: The team screening submodule analyzes the supply and demand difference matching data of the rescue teams, compares the supply and demand differences of each team under the current allocation conditions, screens teams with material shortages, determines the emergency response level and material category of the teams, optimizes the screening process, and obtains the screening results of the differentiated teams. Based on the results of the differential team screening, the icon labeling submodule analyzes the geographical distribution characteristics of the screened teams on the map, optimizes the icon style, combines the distribution density and positional relationship of the teams with the map layer, compares the visualization priority of each team's icon, adjusts the display style, and obtains visual icon labeling data. The pop-up generation submodule analyzes the material needs details of each team based on the visual marker data, determines their display priority, filters the teams that need pop-up prompts, optimizes the pop-up content structure, and adjusts the display order of team numbers and missing materials in the pop-up to obtain the material shortage display information for each team.

8. The visual emergency management command system according to claim 1, characterized in that, The terminal device refers to various mobile or fixed devices with communication, positioning and data transmission functions. The switching response refers to the dynamic response behavior of the multi-mode gateway device when it detects a decline in the quality of the current connected network channel or an anomaly, and automatically switches to a backup or better network channel. The coverage area refers to the target geographical area determined and dynamically adjusted by the broadcast selection and adjustment module.

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