An exhibition hall layout security checking method, system, medium and product

Abstract

A method, system, medium, and product for exhibition hall layout security verification are disclosed. The method includes: acquiring a building information model of the target exhibition hall and equipment deployment data of the deployed equipment; constructing an equipment-facilities security domain diagram of the target exhibition hall based on the equipment deployment data and the structural features of the exhibition hall; calculating a spatial risk coefficient between each deployed equipment node and a target security facility node in the equipment-facilities security domain diagram; calculating a risk transmission coefficient from multiple deployed equipment nodes to the same security facility node in the equipment-facilities security domain diagram based on a first preset risk model; calculating a comprehensive risk level of the security facility node based on the spatial risk coefficient and the risk transmission coefficient using a second preset risk model; and generating equipment-facilities collaborative optimization suggestions when the comprehensive risk level exceeds a preset risk threshold. This application can improve the accuracy of exhibition hall layout security verification.

Description

Technical Field

[0001] This application relates to the field of security verification technology, specifically to a method, system, medium, and product for security verification of exhibition hall layout. Background Technology

[0002] Building Information Modeling (BIM) technology has been widely applied in the design and operation of modern large-scale public spaces such as exhibition halls, conference centers, and museums. By constructing a unified, multi-dimensional digital model of the building's physical and functional characteristics, BIM technology provides a reliable data foundation for various decisions throughout the building's entire lifecycle. In particular, utilizing BIM technology for spatial layout planning and safety verification is crucial and necessary for ensuring the safety of temporary and complex environments such as exhibition halls with high pedestrian traffic and variable layouts.

[0003] Existing technologies typically rely on BIM's clash detection technology for safety verification. Specifically, a building information model (BIM) containing the layout of fixed safety facilities such as fire hydrants, sprinkler heads, and emergency exit signs is loaded into the exhibition hall. Then, based on the exhibition layout plan to be reviewed, digital models of deployed equipment such as booths, displays, and lighting fixtures are imported into the BIM. Subsequently, the system automatically performs spatial interference analysis, checking for direct spatial conflicts between deployed equipment and safety facilities by calculating overlaps between geometric models or intrusions within preset safety distances. For example, this method can identify whether a booth structure is too close to a fire hydrant, hindering its use, or whether a large suspended device directly obstructs the view to emergency exits. After verification, the system generates a conflict report listing all equipment and facility locations that do not meet spatial avoidance requirements.

[0004] However, in a highly integrated exhibition hall environment, the operating status of different deployed devices often affects each other, resulting in a complex security hazard that traditional spatial intervention analysis cannot foresee, affecting the accuracy of exhibition hall layout security verification. Summary of the Invention

[0005] This application provides a method, system, medium, and product for exhibition hall layout security verification, which is used to identify security risks between deployed equipment and security facilities and improve the accuracy of exhibition hall layout security verification.

[0006] The first aspect of this application provides a method for verifying the security of exhibition hall layout, the method comprising: Obtain the building information model of the target exhibition hall and the equipment deployment data of the deployed equipment. The building information model includes the exhibition hall structural features and safety facility layout data of the target exhibition hall. Based on the equipment deployment data and the structural features of the exhibition hall, a security domain diagram of the equipment-facilities of the target exhibition hall is constructed. The security domain diagram of the equipment-facilities includes conventional coupling links and non-adjacent coupling links. One deployed device corresponds to one deployed device node, and one security facility corresponds to one security facility node. Calculate the spatial risk coefficient between each deployed device node and the target security facility node in the device-facility security domain graph, wherein the target security facility node is a security facility node connected to the deployed device node through the conventional coupling link or the non-adjacent coupling link; Based on the first preset risk model, calculate the risk transmission coefficient of multiple deployed device nodes to the same security facility node in the device-facility security domain diagram; The comprehensive risk level of the safety facility node is calculated based on the spatial risk coefficient and the risk transmission coefficient using a second preset risk model. When the overall risk level is greater than a preset risk threshold, a collaborative optimization suggestion for equipment and facilities is generated.

[0007] Optionally, based on the equipment deployment data and the structural characteristics of the exhibition hall, a security domain diagram of the equipment and facilities of the target exhibition hall is constructed, specifically including: Analyze the structural features of the exhibition hall in the building information model, identify the structural medium components that serve as physical supports or spatial barriers for deployed equipment in the target exhibition hall, and obtain the conduction properties of the structural medium components; Taking the deployed device node as the starting point of the risk source, and based on the preset inherent risk of the deployed device node and the conduction properties of the structural medium component, a penetrating influence path is traced to determine the penetrating influence path of the deployed device node. The penetrating influence path includes the starting point of the risk source, the endpoint of the influence, and the degree of risk attenuation between the starting point of the risk source and the endpoint of the influence. Determine whether the affected endpoint falls within the preset sensing range of any of the security facility nodes; If so, a non-adjacent coupling link characterizing cross-media impact is established between the deployed device node and the security facility node, and the degree of risk attenuation is used as the weight attribute of the non-adjacent coupling link; Obtain the regular coupling links between the deployed device nodes and the security facility nodes, whereby the regular coupling links are used to characterize the coupling influence relationships directly transmitted through the environmental space; The device-facility security domain graph is obtained based on the non-adjacent coupling links and the conventional coupling links.

[0008] Optionally, taking the deployed device node as the starting point of the risk source, and based on the pre-defined inherent risks of the deployed device node and the conduction properties of the structural medium components, a penetrating influence path tracing is performed, specifically including: Identify the contact surfaces between the deployment device and the structural media component, generate a tracking branch for each contact surface, and use the deployment device node as the starting point of the risk source for all tracking branches; For any of the tracking branches, based on the conduction properties of the first structural medium component corresponding to any of the tracking branches, it is determined whether the preset inherent risk corresponding to the deployment device node can penetrate the first structural medium component, and one preset inherent risk corresponds to one initial influence intensity. If the preset inherent risk can penetrate the first structural medium component, then based on the barrier coefficient in the conduction property, the initial influence intensity of the tracking branch is attenuated to obtain the first residual influence intensity, and based on the structural characteristics of the first structural medium component, the current tracking position and the next tracking direction after penetrating the first structural medium component are determined. Using the first residual influence intensity as the current influence intensity, the next hop tracing is performed based on the current tracing position and the next tracing direction until the preset tracing termination condition is met. The influence path result of the tracing branch is then determined, and the influence path results corresponding to all the contact surfaces are set together to obtain the penetrating influence path. The influence path result includes the influence endpoint and the risk attenuation degree.

[0009] Optionally, based on the current tracking position and the next tracking direction, perform the next hop tracking until a preset tracking termination condition is met, and then determine the influence path result of the tracking branch, specifically including: From the current tracking position, track along the next tracking direction to determine whether a target structural medium component is encountered. The target structural medium component is any structural medium component other than the first structural medium component in the current tracking process. If the target structural medium component is encountered, it is determined whether the current influence intensity can penetrate the target structural medium component based on the conduction properties of the target structural medium component; If penetration is possible, the second residual influence intensity is calculated based on the blocking coefficient of the target structure medium component, the current tracking position and the next tracking direction are updated, and the next hop tracking is continued. If penetration is not possible, the contact surface of the target structural medium component is determined as the endpoint of the influence, and the degree of risk attenuation is calculated based on the initial influence intensity and the current influence intensity. If the target structural medium component is not encountered, calculate the minimum distance from the current tracking position to the exhibition hall boundary; If the minimum distance is less than a preset distance threshold, the exhibition hall boundary is determined as the endpoint of the impact, and the first impact intensity after spatial attenuation is calculated based on the minimum distance. The initial impact intensity and the first impact intensity are used to calculate the degree of risk attenuation. If the minimum distance is greater than or equal to the preset distance threshold, the current tracking position is determined as the impact endpoint, and the risk attenuation degree is calculated based on the initial impact intensity and the residual impact intensity corresponding to the current tracking position. When the current influence intensity is less than a preset intensity threshold, or the current tracking hop count reaches a preset maximum hop count, or the influence endpoint is determined, the preset tracking termination condition is satisfied.

[0010] Optionally, the spatial risk coefficient between each deployed device node and the target security facility node in the device-facility security domain graph is calculated, specifically including: Calculate the conventional spatial risk coefficient of the conventional coupling links in the equipment-facility security domain diagram, and calculate the penetration spatial risk coefficient of the non-adjacent coupling links in the equipment-facility security domain diagram; The space risk coefficient is obtained by weighted summing of the conventional space risk coefficient and the penetrating space risk coefficient.

[0011] Optionally, the conventional spatial risk coefficient of the conventional coupling links in the equipment-facility security domain diagram is calculated, and the penetration spatial risk coefficient of the non-adjacent coupling links in the equipment-facility security domain diagram is calculated, specifically including: For each of the aforementioned conventional coupling links, calculate the straight-line distance from the deployed device node to the target security facility node; Calculate the spatial attenuation factor based on the straight-line distance; The conventional spatial risk coefficient corresponding to the conventional coupling link is obtained by multiplying the spatial attenuation factor with the preset risk level coefficient of the deployed device node. For each of the non-adjacent coupled links, the weight attribute of the non-adjacent coupled link is obtained as a penetration attenuation factor; The penetration attenuation factor is multiplied by the preset risk level coefficient of the deployed device node to obtain the penetration space risk coefficient corresponding to the non-adjacent coupling link.

[0012] Optionally, after calculating the comprehensive risk level of each deployed device to the security facility based on the spatial risk coefficient and the risk transmission coefficient using a preset risk model, the method includes: Obtain the runtime sequence table of the deployed device, which includes the startup order, running duration, and maintenance time window of the deployed device; Based on the runtime sequence table, determine the time-overlapping device group; When any of the time-overlapping device groups has a coupling link with the same security facility node in the device-facility security domain diagram, calculate the time-coordination risk factor of the time-overlapping device group; The overall risk level is corrected based on the aforementioned time-series collaborative risk factors.

[0013] Secondly, embodiments of this application provide an exhibition hall layout security verification system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, which includes computer instructions, and the one or more processors call the computer instructions to cause the exhibition hall layout security verification system to perform the method described in the first aspect and any possible implementation thereof.

[0014] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on an exhibition hall layout security verification system, cause the exhibition hall layout security verification system to perform the method described in the first aspect and any possible implementation thereof.

[0015] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on an exhibition hall layout security verification system, cause the exhibition hall layout security verification system to perform the method described in the first aspect and any possible implementation thereof.

[0016] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: 1. By characterizing the direct spatial impact and cross-media penetration impact between equipment and safety facilities through conventional coupling links and non-adjacent coupling links, a comprehensive multi-dimensional impact path of deployed equipment on safety facilities is captured. Based on this, a spatial risk coefficient is further calculated to quantify the direct impact of individual equipment. Simultaneously, a risk transmission coefficient is introduced to characterize the coupling effect between multiple devices. These two types of risk factors are comprehensively evaluated through a pre-set risk model, thereby accurately identifying potential safety hazards in the exhibition hall layout. This risk assessment method based on multi-dimensional impact paths overcomes the limitations of traditional methods relying solely on geometric collision detection. It can effectively predict and prevent complex safety risks caused by the interaction of equipment operating states, improving the accuracy of exhibition hall layout safety verification.

[0017] 2. By analyzing the conduction properties of structural media components, a physical correlation model between equipment risks and building structures was established. Based on this, the solution starts from the deployed equipment nodes, identifies the contact surfaces between the equipment and structural media components, and generates independent tracing branches for each contact surface, achieving comprehensive tracking of the risk propagation path. During the tracing process, the system dynamically calculates the risk penetration capability and attenuation degree based on the conduction properties of the structural media components, and accurately characterizes the diffusion law of risk in complex structures through the step-by-step transmission and accumulation of residual influence intensity. When the endpoint of the risk impact falls within the perception range of the safety facility node, the system establishes a non-adjacent coupling link with weighted attributes, which, together with the conventional coupling link representing direct spatial impact, constitutes a complete equipment-facility safety domain graph. This provides a comprehensive analytical basis for subsequent risk assessment, encompassing both direct impacts and indirect penetration effects. This refined risk propagation modeling method based on physical characteristics overcomes the limitations of traditional methods that only consider spatial geometric relationships, enabling more accurate prediction and assessment of potential safety hazards in complex exhibition hall environments.

[0018] 3. By dynamically determining the existence and transmission characteristics of the target structural medium component during each hop of the tracking process, the system achieves precise tracking of the risk propagation path. When encountering a penetrable target structural medium component, the system calculates the second residual influence intensity based on its barrier coefficient and continuously updates the tracking position and direction, thus accurately reflecting the cumulative attenuation effect of risk in multiple media. For impenetrable cases, the solution directly determines the contact surface as the influence endpoint and quantifies the degree of risk attenuation along the complete propagation path by comparing the initial influence intensity with the current influence intensity. In particular, when no target structural medium component is encountered, the system adopts different termination strategies and attenuation calculation methods based on the distance relationship with the exhibition hall boundary, considering both natural spatial attenuation and avoiding invalid path extensions. By setting multi-dimensional termination conditions such as preset intensity thresholds and maximum number of hops, the solution ensures both the convergence of the tracking process and the timeliness and accuracy of risk assessment. This intelligent risk propagation path tracking method breaks through the limitations of traditional fixed-distance judgment and can adaptively determine the scope and degree of influence according to actual environmental characteristics, providing a more accurate decision-making basis for optimizing the safety layout of the exhibition hall.

[0019] 4. A complete spatial risk assessment model was established by calculating the risk coefficients for conventional and non-adjacent coupled links. For conventional coupled links, the scheme calculates the spatial attenuation factor based on the straight-line distance from the deployed equipment node to the target security facility node, and multiplies it by the equipment's preset risk level coefficient, accurately reflecting the degree of impact of the equipment on the security facility through direct spatial transmission. Simultaneously, for non-adjacent coupled links, the system uses the weighted attributes obtained from previous penetrating influence path tracing as the penetration attenuation factor, and similarly combines it with the preset risk level coefficient to quantify the intensity of the equipment's indirect impact on the security facility through the structural medium. By weighted summing of these two types of spatial risk coefficients, the scheme achieves a comprehensive assessment of both direct spatial impact and indirect penetration impact, considering the diversity of risk propagation while maintaining the comparability of assessment results. This dual-channel risk quantification method overcomes the limitations of traditional single-distance assessment, comprehensively and accurately depicting the multi-dimensional impact relationship between equipment and security facilities in complex exhibition hall environments, providing a reliable computational foundation for subsequent comprehensive risk assessment. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a method for verifying the security of an exhibition hall layout, as described in an embodiment of this application. Figure 2 This is a schematic diagram of the process for constructing a device-facility security domain diagram in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of the electronic device in the embodiments of this application.

[0021] Explanation of reference numerals in the attached drawings: 301, Central Processing Unit; 302, Read-Only Memory; 303, Random Access Memory; 304, Bus; 305, Input / Output Interface; 306, Input Section; 307, Output Section; 308, Storage Section; 309, Communication Section; 310, Driver; 311, Removable Media. Detailed Implementation

[0022] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0023] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. In the description of the embodiments of this application, the term "multiple" means two or more. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0024] Figure 1 This is a flowchart illustrating a method for verifying the security of an exhibition hall layout, as described in an embodiment of this application.

[0025] Please see Figure 1 This application provides an embodiment of a method for verifying the security of an exhibition hall layout, the method comprising: S101. Obtain the building information model of the target exhibition hall and the equipment deployment data of the deployed equipment. The building information model includes the exhibition hall structural features and safety facility layout data of the target exhibition hall. To effectively verify the safety layout of the target exhibition hall, it is first necessary to obtain the building information model (BIM) of the target exhibition hall and the equipment deployment data of the deployed equipment. Building Information Modeling (BIM) is a data model based on three-dimensional digital technology that integrates multi-dimensional information such as building geometry, spatial layout, material properties, and construction process. In this embodiment, the BIM mainly includes structural feature information describing the exhibition hall's spatial structure, and safety facility layout data representing the location, type, and layout logic of safety equipment.

[0026] The process of acquiring a Building Information Model (BIM) typically relies on the BIM file created during the architectural design phase. This file can be in IFC (Industry Foundation Classes) format. A BIM parsing engine reads this file, extracting and reconstructing the spatial structural units of the exhibition hall, including structural feature parameters such as walls, doors and windows, floors, height, passageways, and partitions. Simultaneously, the location, function type, coverage area, and spatial relationship between deployed safety facilities (such as fire extinguishers, smoke detectors, emergency indicator lights, and safety exits) and structural units are extracted from the model, forming complete safety facility layout data. This process can be accomplished by constructing a spatial semantic parsing module. This module, based on a spatial topology algorithm, identifies the interaction areas between each safety facility and the exhibition hall structure, providing an accurate spatial foundation for subsequent safety domain map construction.

[0027] Simultaneously, to further refine the spatial distribution relationship between equipment and safety facilities within the exhibition hall, it is also necessary to obtain equipment deployment data. Equipment deployment data refers to the collection of data including the spatial location, equipment type, operating status, power rating, and heat generation of various types of equipment actually in operation or planned for deployment in the exhibition hall (such as exhibit display devices, lighting systems, intelligent monitoring terminals, interactive projection equipment, etc.). This data can be exported from the exhibition hall management system or generated through the equipment installation record system during on-site deployment. The data format can be JSON, XML, or database record format. By constructing a data extraction module, the equipment deployment data is aligned with the building information model in terms of spatial coordinates, enabling precise positioning of various deployed equipment within the exhibition hall space.

[0028] Through the above acquisition steps, a complete three-dimensional digital model can be formed, containing the structural features of the exhibition hall, the layout data of safety facilities, and the spatial information of deployed equipment. This model serves as the basic data source for the subsequent construction of the equipment-facility safety domain map, not only improving the accuracy of spatial analysis but also providing spatial semantic support for risk assessment.

[0029] S102. Based on the equipment deployment data and the structural features of the exhibition hall, construct the equipment-facilities security domain diagram of the target exhibition hall. The equipment-facilities security domain diagram includes conventional coupled links and non-adjacent coupled links. One deployed device corresponds to one deployed device node, and one security facility corresponds to one security facility node. After acquiring the building information model and equipment deployment data for the target exhibition hall, to comprehensively reflect the potential impact of equipment on safety facilities, it is necessary not only to establish conventional coupling links representing direct influence relationships in the physical space, but also to introduce non-adjacent coupling links representing indirect effects through structural media. To this end, it is necessary to further analyze the characteristics of structural media components in the exhibition hall structure, identify spatial paths with potential transmission risks, and perform penetrating influence path tracing in conjunction with the inherent risk types of deployed equipment. This will systematically construct a multi-dimensional relationship between equipment and facilities, forming a safety domain graph with spatial physical reference and risk transmission semantics, serving as the basis for subsequent spatial risk assessment and optimization recommendations. In the graph, we abstract each deployed device as a deployed device node and each safety facility as a safety facility node. Figure 2 This is a schematic diagram of the process for constructing a device-facility security domain diagram in an embodiment of this application. The following is a summary of the process. Figure 2 Step S102 will be further explained.

[0030] S201. Analyze the structural features of the exhibition hall in the building information model, identify the structural medium components that serve as physical supports or spatial barriers for deployed equipment in the target exhibition hall, and obtain the conduction properties of the structural medium components. In this embodiment, to accurately establish potential non-adjacent coupling links between deployed equipment nodes and security facility nodes, it is first necessary to conduct an in-depth analysis of the building information model of the target exhibition hall, identify structural media components that constitute physical support or act as spatial barriers in the exhibition hall space, and obtain the material types and conduction properties of these structural media components. Structural media components refer to various building components that constitute the interior space of the exhibition hall, such as load-bearing walls, partitions, beams, columns, ceilings, and floors. These components not only bear the structural function of supporting equipment installation, but may also constitute the medium for the conduction of risk energy (such as heat, electromagnetic radiation, and vibration) in the space when deployed equipment generates risk energy.

[0031] In the specific implementation process, by analyzing the configuration, location, and attribute identifiers of various components in the Building Information Model (BIM), the set of components that have spatial contact or proximity with the deployed equipment in the target exhibition hall is identified. This process relies on the component classification standards and spatial coordinate system of BIM data, and determines whether there is a physical support relationship or a spatial occlusion relationship between the deployed equipment and specific components through three-dimensional spatial relationships. A physical support relationship refers to the deployed equipment being directly installed on the surface of a structural component, such as display equipment being fixed to a wall or embedded in the ground; a spatial occlusion relationship indicates that there is a structural component separating the two, which may attenuate or guide the propagation of risk energy.

[0032] After identifying the relevant structural media components, the material type information for each type of structural component is further extracted based on the material property fields recorded in the Building Information Model (BIM), such as reinforced concrete, gypsum board, glass curtain wall, and composite wood. Each material has specific conductivity properties, including thermal conductivity, electromagnetic shielding coefficient, and acoustic wave transmission coefficient. These parameters determine the attenuation and path deformation characteristics of the risk energy generated by deployed equipment as it propagates through the medium. To support the subsequent penetrating influence path tracing process, a material-conduction property mapping model needs to be constructed. This model can be established using a material physics database or measured parameters to quantify the conductivity of each medium for different types of risk energy.

[0033] By analyzing the structural features of the exhibition hall, structural media components are identified and their conduction properties are obtained. This not only clarifies whether the risks of deployed equipment may penetrate building components and indirectly affect safety facilities at a distance, but also provides physical basis and quantitative parameter support for establishing non-adjacent coupling links across media, enabling accurate modeling of complex risk transmission paths in the equipment-facility safety domain diagram.

[0034] S202. Taking the deployed device node as the starting point of the risk source, based on the preset inherent risk of the deployed device node and the conduction properties of the structural medium component, a penetrating influence path tracing is performed to determine the penetrating influence path of the deployed device node. The penetrating influence path includes the starting point of the risk source, the endpoint of the influence, and the degree of risk attenuation between the starting point of the risk source and the endpoint of the influence. After identifying the structural media components and extracting their transmission properties, to further construct non-adjacent coupling links between the deployed equipment and safety facilities, it is necessary to take the deployed equipment node as the starting point of the risk source, and combine its preset inherent risk type with the transmission properties of the structural media components to perform a penetrating impact path tracing operation. Penetrating impact path tracing aims to simulate the propagation behavior of risks carried by the deployed equipment as they traverse the exhibition hall's structural media. By analyzing whether the risk can penetrate a specific structural medium, the risk intensity attenuation process along the propagation path, and the final impact range, the path trajectory and risk attenuation degree from the risk source starting point to the potential impact endpoint are determined. To achieve the above path tracing, it needs to be further refined into multiple tracing branches, and iterative tracing calculations are performed based on the contact surface information between the deployed equipment and the structural medium, the blocking capacity of the structural components, and the multiple attenuations of risk intensity, thereby forming a complete penetrating impact path, providing path basis and quantitative parameters for the subsequent establishment of non-adjacent coupling links. Specifically, this may include steps S2021-S2024.

[0035] S2021. Identify the contact surface between the deployment device and the structural media component, generate a tracking branch for each contact surface, and use the deployment device node as the risk source starting point for all tracking branches; In this embodiment, to achieve penetrating influence path identification of potential security facility nodes in the external space from deployed device nodes, it is necessary to first determine the starting direction and path branches of the potential transmission of risk energy. Therefore, it is necessary to identify the contact surfaces between the deployed device and the structural media components that directly contact it, and generate independent tracing branches starting from each contact surface. The core of this step is to transform the single risk source location of the deployed device node into multiple risk propagation starting points with directionality and structural dependence, thereby establishing a branch topology basis for subsequent path calculation.

[0036] Based on the parsed Building Information Model (BIM) and equipment deployment data, a 3D spatial positioning algorithm is used to perform spatial intersection detection between the spatial geometric model of the deployed equipment and the spatial model of the structural media components. Spatial intersection detection employs component bounding box overlap judgment and surface normal vector projection algorithms to identify areas where the deployed equipment geometry and the surfaces of surrounding structural components are in direct contact or contact. Specifically, this involves two steps: First, component bounding box overlap judgment is used, generating a minimum 3D bounding box for each geometry and determining whether there is an overlap area in 3D space, serving as an initial screening for contact probability. Second, given the bounding box overlap, a surface normal vector projection algorithm is further used to calculate the angle between the normal vectors of the deployed equipment and the surface of the structural media, as well as the distance error at the contact point, to accurately determine whether there is an actual contact or contact area. This method effectively filters out non-contact but spatially close components and ensures that the identified contact surfaces have genuine physical contact attributes, providing an accurate starting position for subsequent penetration path tracing. Each identified contact area constitutes a contact surface, corresponding to a potential risk transmission direction.

[0037] After identifying all contact surfaces, a tracking branch is generated for each contact surface, and the deployed device node serves as the shared risk source starting point for all tracking branches. Each tracking branch acts as an independent channel for the outward propagation of risk energy, and in subsequent steps, path expansion and impact intensity attenuation calculations will be performed based on the conduction properties, barrier capabilities, and geometric directionality of the structural medium components. By modeling risk propagation as parallel tracking branches originating from multiple contact surfaces, not only can the directional coverage of path identification be improved, but the multi-path superposition behavior of risk propagation in different structural media can also be simulated more accurately.

[0038] S2022. For any of the tracking branches, based on the conduction properties of the first structural medium component corresponding to any of the tracking branches, determine whether the preset inherent risk corresponding to the deployment device node can penetrate the first structural medium component, and one preset inherent risk corresponds to one initial influence intensity. To accurately simulate the potential penetration behavior of the inherent risks carried by the deployed equipment within the exhibition hall structure, a risk penetration feasibility assessment is required for each tracing branch. The core of this assessment lies in determining whether the inherent risk corresponding to the deployed equipment node can penetrate the first structural medium component contacted by the tracing branch. This serves as a prerequisite for deciding whether to continue path expansion and impact attenuation calculations. If the risk type itself does not possess the ability to penetrate the structural medium, then the tracing branch can be considered a closed path, and further resource-intensive propagation simulations are unnecessary.

[0039] In the specific implementation process, the inherent risk type is determined based on the equipment type and functional attributes of the deployed equipment nodes. For example, the preset inherent risk of a certain type of laser projection equipment is "high-frequency electromagnetic radiation," while the preset inherent risk of a certain type of high-power audio system may be "low-frequency noise vibration" or "heat dissipation." Each risk type has a corresponding propagation model and initial influence intensity preset in the system. The initial influence intensity is a physical quantity defined by the system, used to characterize the theoretical strength of the risk at the source point before any attenuation occurs. For example, for a certain high-power audio equipment, the heat dissipation during its operation constitutes a "heat dissipation" risk. The initial influence intensity in the system is measured in terms of the temperature rise rate (K / min). When the equipment is running at full load, the heat release rate of its rear contact surface is: initial influence intensity = 1.6 K / min, that is, the surface temperature of the equipment is conducted to the contact structure at a rate of 1.6 Kelvin per minute, which serves as the starting value for the thermal risk propagation model. This initial influence intensity is modeled and set by the system based on the equipment type, operating parameters, and preset risk type, combined with industry standards, manufacturer data, or experimental measurement results.

[0040] The system calls the conduction properties of the first structural medium component corresponding to this tracing branch. Conduction properties are a set of parameters describing the medium's ability to shield or conduct different types of risk energy, typically including the barrier coefficient, critical penetration threshold, and anisotropy coefficient. The barrier coefficient measures the degree of attenuation of risk energy when penetrating a certain type of material; a higher value indicates stronger shielding capability. The system matches the pre-defined inherent risks of the deployed equipment with the conduction properties of the structural medium to check if a corresponding penetration path model exists for that type of risk. If no matching model exists or the barrier coefficient is infinitely large, the risk is determined to be unable to penetrate this structural medium, and the tracing branch terminates directly. If a corresponding model exists and the penetration conditions are met, the initial impact intensity of that risk type is recorded, providing input for subsequent risk attenuation calculations and path jumping.

[0041] For example, in a typical scenario, if a device emits a risk type of "electromagnetic interference" and the device is in contact with a reinforced concrete wall, the system will check the conduction properties of the reinforced concrete in the electromagnetic frequency band. If its shielding coefficient far exceeds the critical penetration threshold of the electromagnetic interference, it can be presumed that this risk type cannot penetrate the wall, and this branch tracing does not need to continue. Conversely, if the device is behind a glass curtain wall, and the preset risk is still electromagnetic interference, the system may determine that it has the possibility of penetration and calculate the initial attenuation process of the risk energy based on the shielding coefficient of the glass material.

[0042] Through the above processing, the system can effectively filter the path-following branches in the early stage, preventing paths without a physical propagation basis from entering the subsequent calculation process, thereby improving the efficiency and physical rationality of the entire penetrating influence path modeling.

[0043] S2023. If the preset inherent risk can penetrate the first structural medium component, then based on the barrier coefficient in the conduction property, the initial influence intensity of the tracking branch is attenuated to obtain the first residual influence intensity, and based on the structural characteristics of the first structural medium component, the current tracking position and the next tracking direction after penetrating the first structural medium component are determined. To realistically simulate the propagation of pre-defined inherent risks emitted by deployed device nodes within the structural medium, it is necessary to quantify and attenuate the initial impact intensity of the risk after confirming its ability to penetrate the first structural medium component, and to accurately determine the propagation location and direction after penetration. This process can not only be used to dynamically construct penetration paths but also to continuously calculate the spatial attenuation process of risk energy during subsequent path jumps, ensuring the physical rationality and directional consistency of the entire impact path.

[0044] In the specific implementation process, the system first calculates the energy attenuation of the initial impact intensity based on the barrier coefficient in the conductivity properties of the first structural medium component. The barrier coefficient is a pre-set risk type and material type matching parameter in the material database, used to characterize the energy transmittance of a certain type of structural medium to a specific risk type, and its value range is usually between 0 and 1. The attenuation calculation adopts an exponential attenuation model or a linear attenuation model, which is specifically defined by the risk type. For example, if the initial impact intensity of the deployed equipment node is 5.0 W / m² and the barrier coefficient is 0.4, then the system calculates the effective energy retained by the risk after penetrating the first structural medium component using the formula: First residual impact intensity = Initial impact intensity × Barrier coefficient, that is: 5.0 × 0.4 = 2.0 W / m², which is the first residual impact intensity.

[0045] After intensity attenuation is complete, the system needs to determine the propagation position and direction of the current tracing branch after penetrating the first structural medium component, based on its structural characteristics. Structural characteristics include the component's geometric thickness, internal hierarchical relationships, normal vector direction, and connection relationships with other components. The system uses the exit surface of the structural medium as the current position of risk propagation and determines the propagation direction of the next hop based on the normal vector direction of the contact surface before penetration. If the structural medium is a heterogeneous composite material, the system also needs to adjust the propagation path angle according to its internal layered structure to ensure the spatial continuity of the risk propagation path.

[0046] In this embodiment, if the first structural medium component is a heterogeneous composite material, that is, it is composed of two or more different materials and each material layer has different physical properties, such as material density, refractive index, and barrier capability, then when the system executes the penetration and extension of the risk propagation path, it needs to consider not only the surface normal direction of the overall medium, but also its internal layered structure to further adjust the risk propagation direction, so as to ensure the geometric continuity and physical consistency of the penetration path in the heterogeneous material's internal and external space.

[0047] Specifically, the system retrieves construction description data of the structural media components from the Building Information Model (BIM) to analyze information such as the layering order, thickness of each layer, material type, and interface normal direction of the composite material. For each layer, the system reads its transmission properties for the current risk type to further determine whether directional deflection or energy scattering has occurred. If a layer exhibits strong anisotropy (i.e., the material displays different response characteristics to risk propagation in different directions), the system will adjust the direction of the current propagation path based on the anisotropy coefficient of that material layer.

[0048] The adjustment method can employ propagation and refraction rules based on physical models. For example, if the risk type is electromagnetic radiation, the system will analogize the phenomenon of electromagnetic waves refracting in different media, employing a propagation direction adjustment model similar to **Snell's Law (law of refraction)**: n1·sinθ1 = n2·sinθ2; where n1 and n2 are the relative "material refractive indices" of the two layers of material for this risk type, θ1 is the incident angle, and θ2 is the propagation direction angle after penetration. By solving for such angular relationships, the system calculates the change in the direction of risk propagation between each layer of material, and provides an accurate exit position and propagation direction vector when finally penetrating the boundary of the composite material.

[0049] For example, consider a composite partition wall composed of a fiberglass layer, a hollow aluminum honeycomb layer, and a PVC coating layer. A laser device's back contacts this wall, and the system identifies it as a three-layer heterogeneous composite material. The inherent risk of the laser device is "high-frequency electromagnetic radiation," with an incident angle of 45°. The system first identifies the relative refractive index of the fiberglass layer as 1.5, the aluminum honeycomb layer as 2.0, and the PVC layer as 1.3. Using a layered refraction model, the propagation path angle is adjusted sequentially, calculating the deflection angle of the propagation direction in each layer, and determining the propagation displacement based on the layer thickness. Finally, the three propagation paths of the electromagnetic wave within the composite wall and the exit point are obtained. The exit direction angle is determined to be 38°, which is used as the current tracking position and the next tracking direction for calculating the next hop path.

[0050] During path tracing, the system accumulates and records the propagation trajectory of the risk path within each layer as sub-path segments, and calculates the residual impact intensity after penetration of each layer. The final current tracking position is the center point of the surface from which the risk path exits the composite material component, and the next tracking direction is the unit vector direction that continues to propagate from that point along the aforementioned refraction direction.

[0051] Through the above processing, the system realizes the energy attenuation and path advancement of risk propagation in the structural medium through physical modeling, exhibiting good interpretability and engineering adaptability. This step not only provides input parameters for subsequent path expansion but also provides a dynamic basis for risk intensity and spatial location for the final construction of non-adjacent coupling relationships between equipment and facilities.

[0052] For example, consider a laser projection device with its back against a glass curtain wall. The inherent risk is pre-defined as "high-frequency electromagnetic radiation," with an initial impact intensity of 6.0 W / m². The system reads that the glass material's blocking coefficient for this frequency band is 0.35, calculating the first residual impact intensity as 2.1 W / m². Subsequently, based on the glass curtain wall's thickness of 20 mm and its outward-facing normal vector, the system determines the risk propagation path to continue along the normal direction from the outer surface of the glass, using this position and remaining energy as the current tracking state to provide a basis for the next hop propagation.

[0053] S2024. Using the first residual influence intensity as the current influence intensity, perform the next hop tracing based on the current tracing position and the next tracing direction until the preset tracing termination condition is met. Determine the influence path result of the tracing branch, and collect the influence path results corresponding to all the contact surfaces to obtain the penetrating influence path. The influence path result includes the influence endpoint and the risk attenuation degree.

[0054] To accurately simulate the multi-hop propagation process of inherent risks of deployed equipment in structural media, after penetrating the first structural media component, the system uses the first residual influence intensity as the new current influence intensity. Based on determining the current tracking position and the next tracking direction, it continuously executes the next-hop tracking operation for the risk path. In each hop, the system dynamically determines whether the risk encounters a new target structural media component and, based on its transmission properties, decides whether to continue propagating or terminate tracking until a preset tracking termination condition is met, thereby determining the complete influence path result of that tracking branch. After performing this type of tracking on multiple contact surfaces, the path results of all tracking branches are summarized to construct the penetration influence path corresponding to the deployed equipment node. This path includes the influence endpoint of each branch and the corresponding risk attenuation degree, providing a basis for further refinement of the path jump judgment logic and termination conditions. Specifically, it may include the following steps: The tracing process begins from the current tracing position along the next tracing direction to determine if a target structural medium component has been encountered. The target structural medium component is any structural medium component other than the first structural medium component during the current tracing process. If the target structural medium component is encountered, the current influence intensity is determined based on the conductive properties of the target structural medium component to determine if it can penetrate the target structural medium component. If it can penetrate, a second residual influence intensity is calculated based on the blocking coefficient of the target structural medium component, the current tracing position and the next tracing direction are updated, and the next hop tracing continues. If it cannot penetrate, the contact surface of the target structural medium component is determined as the influence endpoint, and the risk attenuation is calculated based on the initial influence intensity and the current influence intensity. If the target structural medium component is not encountered, the minimum distance from the current tracking position to the exhibition hall boundary is calculated. If the minimum distance is less than a preset distance threshold, the exhibition hall boundary is determined as the impact endpoint, and the first impact intensity after spatial attenuation is calculated based on the minimum distance. The initial impact intensity and the first impact intensity are used to calculate the risk attenuation degree. If the minimum distance is greater than or equal to the preset distance threshold, the current tracking position is determined as the impact endpoint, and the risk attenuation degree is calculated based on the initial impact intensity and the residual impact intensity corresponding to the current tracking position. When the current impact intensity is less than a preset intensity threshold, or the current tracking hop count reaches a preset maximum hop count, or the impact endpoint is determined, the preset tracking termination condition is satisfied.

[0055] In the specific implementation process, in order to achieve complete propagation modeling of the inherent risks emitted by the deployed equipment nodes in the exhibition hall structural medium, after completing the penetration of the first structural medium component, the system takes the current tracking position and the next tracking direction as the new propagation starting point to move forward, and determines whether there are other structural medium components on the path.

[0056] Once the target structural medium component is identified, the system determines whether the current impact intensity is sufficient to penetrate it based on its conduction properties. Conduction properties include parameters such as the component's barrier coefficient for the current risk type, thickness, and density. The barrier coefficient is a numerical indicator used to quantify the risk's transmission capability within the material. The system uses a risk type matching table to look up the corresponding penetration threshold and compares the current impact intensity with this threshold to determine penetration capability. If the current impact intensity is greater than the threshold, the system determines that penetration is possible and proceeds to the next stage of intensity update and direction adjustment. This judgment mechanism ensures the physical rationality of the risk propagation path and avoids false paths when energy is insufficient. The penetration threshold is a reference value pre-set and stored in the risk type matching table based on the minimum penetrable energy requirements for different risk types in various structural materials, obtained through experimental data or material physics model simulations.

[0057] If the current impact intensity is sufficient to penetrate the target structural medium component, the system calculates the attenuation of the current impact intensity based on the barrier coefficient of the target component to obtain the second residual impact intensity. This calculation process typically employs a linear or exponential attenuation model. For example, the system directly obtains the energy level after penetration using the formula: Second Residual Impact Intensity = Current Impact Intensity × Barrier Coefficient. Subsequently, the system updates the current tracking position and the next tracking direction based on the center point of the exit surface and the normal vector direction of the target structural medium component, constituting the initial state for the next hop propagation. By continuously executing this process, the system can dynamically construct multi-hop risk paths in complex multi-structure exhibition hall environments, achieving high-precision spatial propagation modeling. For example, if the current impact intensity is 3.0 W / m² and the barrier coefficient of the target structural medium is 0.4, then the second residual impact intensity is 1.2 W / m², and the system updates the path state accordingly.

[0058] If the current impact intensity cannot penetrate the target structural medium component (i.e., the current impact intensity is below the penetration threshold set by the structural material for the risk type), the system determines that propagation cannot continue, terminates the risk propagation path at the contact surface of the structural component, and uses the coordinates of that contact surface as the impact endpoint. To accurately characterize the energy evolution process of the path, the system calculates the degree of risk attenuation based on the initial impact intensity at the path starting point and the impact intensity under the current propagation state, according to a relative attenuation rate: Risk Attenuation = (Initial Impact Intensity - Current Impact Intensity) ÷ Initial Impact Intensity. This percentage-based attenuation rate more intuitively reflects the relative loss of risk energy, facilitating standardized risk comparison and assessment across multiple paths and devices.

[0059] If no structural media components are encountered along the next tracking direction from the current tracking position, the system further determines whether that direction is close to the exhibition hall boundary. Specifically, the system first constructs a spatial ray based on the current tracking position and propagation direction, and extracts all exhibition hall boundary surface data from the building information model, including key enclosed surfaces such as walls, ceilings, and floors. Then, it performs geometric intersection calculations on the ray with each boundary surface to obtain a set of all possible intersection points. The system calculates the spatial distance from the current tracking position to each intersection point and selects the minimum value as the minimum boundary distance in the current direction. If this minimum distance is less than a preset distance threshold (this threshold is set according to the minimum safe buffer distance between the risk source and the boundary in the exhibition hall safety specifications, for example, 1.0 meter), the system determines that the propagation path is about to cross the exhibition hall spatial boundary, posing a risk of outward leakage. Therefore, the coordinates of the corresponding intersection point on the exhibition hall boundary surface are set as the impact endpoint of this tracking. Subsequently, the system calculates the first impact intensity at this point based on the propagation path length and a spatial attenuation model. The spatial attenuation model typically uses the inverse square formula or a free space propagation loss model to simulate the degree of attenuation of risk energy with path distance. Finally, the system combines the first impact intensity with the initial impact intensity and calculates the degree of risk attenuation according to the relative attenuation rate. This is used to quantify the energy attenuation effect of the risk when crossing open space and to provide input for the risk assessment of subsequent boundary-sensitive equipment.

[0060] If the minimum distance from the current tracking position to the exhibition hall boundary is greater than or equal to a preset distance threshold, the system determines that the propagation path has not encountered structural obstruction in the current direction and has not approached the spatial boundary, indicating that the risk propagation has tended to attenuate and stabilize. In this case, the system takes the current tracking position as the impact endpoint and calculates the degree of risk attenuation based on the relative attenuation rate between the initial impact intensity and the current residual impact intensity. The specific calculation method is: Risk attenuation degree = (Initial impact intensity - Current residual impact intensity) ÷ Initial impact intensity, thus forming the energy assessment result of the path endpoint. This processing logic is applicable to scenarios where the propagation path gradually dissipates in open spaces, ensuring that risk modeling covers propagation termination modes under all spatial states.

[0061] Throughout the pathfinding process, the system continuously monitors whether the current impact intensity is below a preset intensity threshold (e.g., 0.1 W / m²) and whether the number of pathfinding hops has reached a preset maximum number of hops (e.g., 10 hops). Once either condition is met, or the impact endpoint is clearly identified in the aforementioned steps, the system determines that the current pathfinding branch has met the termination condition and stops propagating hops. The preset intensity threshold is a lower limit value used to determine whether the risk energy is sufficient to continue propagating. It is typically set based on the minimum effective impact intensity that different risk types may have on the structural medium and safety facilities, derived from experimental data, industry standards, or simulation analysis results, to avoid meaningless propagation even when energy has significantly decayed. The preset maximum number of hops limits the upper limit of the number of consecutive hops in a penetrating propagation path, preventing the path from getting stuck in excessive iteration or infinite loop calculations in complex structures. This parameter is usually set based on system simulation stability tests or structural complexity experience, for example, set to 10 or 15 hops, to ensure that the system completes the path termination judgment within reasonable computational resources. The impact endpoint refers to the termination position of the risk propagation path on the current branch. The system triggers path termination logic based on conditions such as encountering impenetrable structural media, approaching exhibition hall boundaries, energy falling below the intensity threshold, or exceeding the hop count limit during propagation. The coordinates of the propagation stop point are recorded as the impact endpoint of this tracing branch, used for subsequent risk path mapping and attenuation assessment. Ultimately, the system records the complete path of this branch, the impact endpoint, and the risk attenuation level as a valid impact path result for this deployed device node, providing a path foundation for subsequent non-adjacent coupling mapping of equipment and facilities and comprehensive safety assessment. By setting path termination rules, the system effectively prevents excessive computational overhead or ineffective extensions in risk propagation paths, improving algorithm efficiency and model convergence speed.

[0062] After completing the multi-hop risk propagation modeling of each tracing branch in the exhibition hall's structural medium, to comprehensively reflect the risk impact range and path characteristics of deployed equipment nodes in the structural space, the system aggregates the impact path results corresponding to all contact surfaces to construct a complete penetrating impact path. This path aggregate not only includes the spatial trajectory information of multiple branch paths but also the coordinates of their respective impact endpoints and the corresponding risk attenuation levels, ultimately forming a multi-path risk transmission map that propagates from a single deployed equipment node along different structural medium directions. The system chooses to aggregate paths based on "contact surfaces" because each contact surface represents a potential coupling entry point between the deployed equipment and the structural medium. Different entry points may lead to completely different risk propagation directions and structural paths, and their impact endpoints may also fall on different security facility nodes. Therefore, it is necessary to record and integrate these branch information one by one to obtain a complete and realistic penetrating risk representation model.

[0063] In practical implementation, the system first extracts all contact surface information between the deployed equipment nodes and the structural media components they contact from the equipment deployment data, typically based on the surface contact relationships in a three-dimensional geometric model. Subsequently, the system performs the aforementioned penetrating multi-hop tracing process for each contact surface to obtain the corresponding impact path results. Each path result contains three core components: first, the start and end points of the path, i.e., the spatial trajectory endpoints from the risk source to the propagation termination; second, the propagation path, including all structural components traversed, the residual impact intensity value of each hop, and the propagation direction; and third, the overall risk attenuation degree of the path, used to quantify the risk energy loss rate along the path.

[0064] After tracing and recording all contact surface branch paths, the system aggregates these path results into a unified set of penetrating influence paths for the deployed device node. This set is typically stored in a graphical structure or as a path list, where each element represents a valid influence branch, and its endpoint may be used to determine whether it hits the perception range of a security facility node. If it does, the system establishes a non-adjacent coupling link between the device node and the facility node, using the risk attenuation level recorded in the path as the link's weight attribute to reflect the risk transmission strength of the path. For example, if a device node has three contact surfaces, generating three paths, and the first path penetrates two walls and terminates behind a security camera with a risk attenuation level of 0.75, the system establishes a non-adjacent coupling link between the device node and the camera facility node, setting its weight to 0.25 (i.e., retaining the risk intensity percentage).

[0065] Through this path aggregation mechanism, the system not only achieves multi-directional and multi-path risk propagation modeling of deployed equipment in the structural space, but also provides basic data support for the calculation of spatial risk coefficients and overall safety assessment in subsequent steps. This method effectively enhances the model's ability to express the risk propagation characteristics in complex structural environments, ensuring that even with multi-media coupled paths, the system can still accurately identify high-risk areas and potential hazard links, thus providing more targeted decision-making basis for exhibition hall safety optimization.

[0066] S203. Determine whether the affected endpoint falls within the preset sensing range of any of the security facility nodes; In step S203, the system needs to determine whether the endpoint of a penetrating influence path falls within the preset sensing range of any safety facility node. The purpose is to identify the potential actual impact of risk paths on safety facilities to determine whether to establish a non-adjacent coupling relationship. Specifically, the system first acquires the sensing range data of all safety facility nodes in the equipment-facility safety domain diagram. This range is typically given by the technical specifications or deployment requirements of the safety facility, such as the field of view of a surveillance camera or the detection radius of a smoke detector. This data is then spatially modeled in the Building Information Modeling (BIM) as spherical, conical, or polygonal sensing areas. The system then performs a spatial inclusion relationship determination between the coordinates of the endpoint of each penetrating influence path and the sensing areas of all safety facility nodes. This involves determining whether the endpoint is located within a certain sensing area, using a point-in-region geometric algorithm (such as based on bounding boxes or ray casting). If an inclusion relationship exists, the system considers the endpoint of the path to have a potential effective impact on the facility, thus confirming the existence of a cross-media risk association. For example, if the endpoint of a path is located within a smoke detector sensing sphere with a radius of 3 meters, the system determines that the smoke detector is affected by the penetrating risk of the deployed equipment. If the system determines that the endpoint of the penetrating impact path does not fall within the preset sensing range of any safety facility node, i.e., the endpoint coordinates do not belong to the spatial sensing area of ​​any safety facility, the system considers that the path does not pose a substantial risk impact to any facility node, and therefore does not establish a non-adjacent coupling link. This determination is based on the spatial geometric inclusion calculation results. If the sensing geometric area of ​​all safety facilities does not include the endpoint of the path, it means that although the path has achieved medium penetration in structure, its risk energy has not effectively acted on any sensing facility node. In this case, the system will mark the path as an invalid penetrating path and use it only for subsequent path statistics and structural analysis, without participating in the construction of the coupling relationship of the equipment-facility safety domain graph.

[0067] S204. If so, a non-adjacent coupling link characterizing cross-media impact is established between the deployment device node and the security facility node, and the degree of risk attenuation is used as the weight attribute of the non-adjacent coupling link. Assuming the path endpoint falls within the perception range of a security facility node, the system establishes a non-adjacent coupling link representing cross-media impact in S204, using the risk attenuation level as the weight attribute of this link. The key to this step is to structurally incorporate the risk propagation relationship formed by the penetrating path into the equipment-facility security domain graph, enabling modeling of potential coupling between indirect spatially adjacent equipment and facilities. Specifically, the system adds a directed edge between the deployed equipment node and the security facility node, marking it as a "non-adjacent coupling link." The semantic representation of this link is: the facility may be indirectly affected by the risk source of the equipment through the structural medium. To quantify this impact, the system calls the risk attenuation level data recorded in the path tracing module, calculated as: Attenuation rate = (Initial impact strength - Current propagation endpoint strength) ÷ Initial impact strength. The resulting percentage value serves as the weight attribute of the link, reflecting the degree of energy attenuation of the risk along the path. This mechanism not only preserves the topological relationship of risk accessibility but also reflects the intensity of risk action through numerical weights, facilitating subsequent hierarchical processing in the evaluation model. For example, if a deployed device node penetrates multiple structural media and its impact endpoint falls within the sensing range of a fire controller, and the risk attenuation rate is 75%, then the weight of this non-adjacent coupled link is 0.75, indicating that the path retains 25% of the risk energy acting on the facility node.

[0068] S205. Obtain the regular coupling link between the deployed device node and the security facility node, wherein the regular coupling link is used to characterize the coupling influence relationship directly transmitted through the environmental space; While forming non-adjacent coupling links, the system further obtains information in S205 regarding whether conventional coupling links exist between deployed equipment nodes and security facility nodes to capture risk impact relationships from direct spatial action paths. Conventional coupling links describe perceptible impact links formed between deployed equipment and facilities in a shared open space due to proximity and the absence of structural obstructions, such as thermal radiation, sound wave propagation, or electromagnetic interference. In practice, the system calculates the straight-line spatial distance between deployed equipment nodes and security facility nodes based on a building information model and checks for structural media barriers between them. If there are no barriers and the distance is less than the facility's direct perception range threshold, such as within 5 meters of a temperature sensor's sensing area, the system determines that a conventional coupling link can be formed and adds this link to the security domain graph. This determination is typically achieved using an intersection detection algorithm of spatial line segments and obstacle sets to ensure that the established link truly represents the actual propagation probability in open space. By introducing conventional coupling links, the system can simultaneously cover both "direct impact" and "penetrating impact" risk mechanisms, thus providing a reliable structural foundation for subsequent risk superposition modeling.

[0069] S206. The device-facility security domain diagram is obtained based on the non-adjacent coupling links and the conventional coupling links.

[0070] After constructing both non-adjacent and regular coupling links, the system integrates these two types of links in S206 to form a device-facility security domain graph, representing the comprehensive coupling relationship between deployed device nodes and all potentially affected facility nodes. In practice, the system maintains the organizational relationship between nodes and links in the form of a graph structure, using all deployed device nodes and security facility nodes as vertices in the graph, and adding non-adjacent and regular coupling links as directed edges, assigning them type labels and weight attributes respectively. The system achieves panoramic modeling of the device-facility coupling topology through the graph structure, enabling subsequent path traversal, risk aggregation, shortest path analysis, and other graph algorithm operations based on this graph. The resulting device-facility security domain graph can simultaneously express multi-dimensional information such as spatial location, structural medium, risk paths, and energy attenuation, constructing a complete risk transmission link from deployed devices to facility nodes. For example, in an exhibition hall, if an electromagnetic device simultaneously affects a surveillance camera (regular link) through an open space and indirectly affects a fire alarm (non-adjacent link) through a wall, then the graph will contain two edges corresponding to different path mechanisms, which will be used to support the generation of subsequent comprehensive risk calculations and layout optimization suggestions.

[0071] S103. Calculate the spatial risk coefficient between each deployed device node and the target security facility node in the device-facility security domain diagram, wherein the target security facility node is a security facility node connected to the deployed device node through the conventional coupling link or the non-adjacent coupling link; After constructing the equipment-facility security domain diagram, the system needs to further assess the potential spatial risk impact of each deployed equipment node on its connected target security facility nodes, providing a foundational input for subsequent comprehensive risk calculation. To this end, in step S103, the system calculates the corresponding spatial risk coefficient between each deployed equipment node in the diagram and its connected security facility nodes via conventional or non-adjacent coupling links. This coefficient quantifies the extent to which risk propagates in space and affects the facility nodes. In practical implementation, to more accurately reflect the risk transmission characteristics under different coupling paths, the system treats conventional and non-adjacent coupling links as two different path mechanisms, calculating their corresponding conventional spatial risk coefficient and penetrating spatial risk coefficient respectively. These are then weighted and synthesized to obtain a unified spatial risk coefficient. This approach ensures that the risk assessment model can consider the risk transmission characteristics under both open space and structural media paths, achieving comprehensive perception and quantification of the impact of multi-source heterogeneous risks in the spatial layout. Specifically, this may include the following steps: calculating the conventional spatial risk coefficient of the conventional coupling links in the equipment-facility security domain diagram, calculating the penetration spatial risk coefficient of the non-adjacent coupling links in the equipment-facility security domain diagram; and weighted summing the conventional spatial risk coefficient and the penetration spatial risk coefficient to obtain the spatial risk coefficient.

[0072] In the specific implementation process, after completing the overall calculation framework for the spatial risk coefficient between deployed equipment nodes and safety facility nodes in the equipment-facility safety domain diagram, the system needs to further refine the specific calculation methods for the spatial risk impact corresponding to different types of coupling links to improve the accuracy and differentiated expression capability of risk assessment. To this end, the system independently models conventional coupling links and non-adjacent coupling links, calculating their corresponding conventional spatial risk coefficients and penetration spatial risk coefficients respectively. Conventional coupling links mainly reflect the direct interaction between deployed equipment and safety facilities in open space; therefore, their risk assessment usually depends on the straight-line distance between them and the risk level attributes of the equipment itself. Non-adjacent coupling links, on the other hand, indicate that risk is indirectly transmitted to facility nodes through structural media, and their spatial risk is mainly determined by the energy attenuation during path penetration. To take into account the different characteristics of these two coupling mechanisms, the system introduces spatial attenuation factors and penetration attenuation factors in the calculation process, and weights them with the preset risk level coefficients of the deployed equipment to ensure that the spatial risk coefficients can comprehensively reflect the risk transmission intensity under different path mechanisms. Specifically, the process may include the following steps: for each conventional coupling link, calculate the straight-line distance from the deployed device node to the target security facility node; calculate a spatial attenuation factor based on the straight-line distance; calculate the product of the spatial attenuation factor and the preset risk level coefficient of the deployed device node to obtain the conventional spatial risk coefficient corresponding to the conventional coupling link; for each non-adjacent coupling link, obtain the weight attribute of the non-adjacent coupling link as a penetration attenuation factor; multiply the penetration attenuation factor by the preset risk level coefficient of the deployed device node to obtain the penetration spatial risk coefficient corresponding to the non-adjacent coupling link.

[0073] In constructing the spatial risk coefficient, to comprehensively reflect the potential impact of deployed equipment on target safety facilities, the system needs to establish quantitative models for both conventional and non-adjacent coupled links. For conventional coupled links, the system first calculates the straight-line distance between the deployed equipment node and the target safety facility node. This aims to assess their physical proximity in the three-dimensional open space, as closer spatial distances result in weaker natural risk attenuation during transmission, and vice versa. The system extracts the spatial coordinates of the deployed equipment node and the safety facility node based on location coordinate data from the Building Information Model (BIM). For each pair of nodes connected by a conventional coupled link, the Euclidean distance formula is applied to calculate the spatial distance, specifically: For example, if a deployed device is located at (10, 5, 3) and a security facility is located at (13, 9, 3), the straight-line distance is 5 meters. This distance result will serve as the input basis for the subsequent spatial attenuation factor.

[0074] After obtaining the straight-line distance, the system calculates the corresponding spatial attenuation factor based on this distance value to simulate the natural attenuation trend of risk energy during its propagation in free space. The spatial attenuation factor is a coefficient constructed based on the laws of physical propagation; its value decreases as distance increases. Common models include the inverse proportional model and the exponential attenuation model. In this embodiment, to ensure a sensitive response to short-to-medium distance propagation effects, the system adopts an exponential attenuation model, with the formula: Spatial attenuation factor = e^(–αd), where d is the previously calculated straight-line distance, and α is an attenuation coefficient that can be set according to environmental characteristics, typically ranging from 0.1 to 0.5. This model can effectively simulate the rapid attenuation trend of risk factors (such as heat, electromagnetic waves, and smoke) as they propagate through the air. For example, when α is 0.2 and the distance is 5 meters, the spatial attenuation factor is approximately e^(–1) ≈ 0.3679, indicating that the original risk source retains only about 36.79% of its intensity when it reaches the facility node.

[0075] To further reflect the differences in risk levels among different deployed devices, the system multiplies the aforementioned spatial attenuation factor with the preset risk level coefficient of the deployed device node to obtain the conventional spatial risk coefficient corresponding to the conventional coupling link. The preset risk level coefficient is a basic risk value set by the system based on factors such as equipment type, process characteristics, and energy level, and is usually predefined in the equipment deployment data. For example, high-voltage electrical equipment might be set to 0.9, while ordinary lighting equipment might be set to 0.2. The significance of this multiplication operation lies in comprehensively considering the inherent risks of the equipment and the spatial propagation impact, forming a quantitative indicator that reflects the overall risk transmission capability. For example, if the risk level coefficient of a certain device is 0.8 and the spatial attenuation factor is 0.3679, then the conventional spatial risk coefficient is 0.2943, representing the actual spatial risk effect under this path.

[0076] When dealing with non-adjacent coupled links, since the risk does not propagate directly through open space but indirectly affects facility nodes by penetrating the structural medium, the system no longer models based on spatial distance. Instead, it directly obtains the weight attributes recorded by the non-adjacent coupled links and uses them as a penetration attenuation factor. This weight attribute is dynamically generated by the system during the tracing of the penetrating influence path and represents the attenuation ratio of the risk intensity from the risk source, through the structural medium, to the influence endpoint. It is typically calculated as: Penetration Attenuation Factor = Residual Intensity ÷ Initial Intensity. For example, if the initial influence intensity is 1.0 and the residual influence intensity is 0.25, then the penetration attenuation factor is 0.25, indicating that only one-quarter of the energy is retained after the risk is transmitted along the path. This factor is determined by the material type and barrier coefficient of each structural component in the penetration path.

[0077] Finally, to standardize the risk transmission measurement method, the system multiplies the aforementioned penetration attenuation factor with the preset risk level coefficient of the corresponding deployed equipment node to obtain the penetration space risk coefficient corresponding to the non-adjacent coupling link. This product value comprehensively considers the source risk level of the equipment and the degree of loss on the penetration path, effectively quantifying the intensity of risk indirectly affecting facility nodes through the structure. For example, if the equipment's risk level coefficient is 0.7 and the penetration attenuation factor is 0.25, then the penetration space risk coefficient is 0.175, indicating that the effective risk transmission capacity on this path is 17.5% of the overall level. Through this method, the system achieves unified modeling and quantitative output of the risk impact under two different propagation mechanisms, providing a scientific basis for subsequent risk superposition analysis and optimization suggestion generation.

[0078] When calculating the spatial risk coefficient between each deployed device node and the target security facility node, in order to achieve a comprehensive assessment of different risk propagation paths, the system ultimately needs to perform a weighted summation of the conventional spatial risk coefficient calculated through regular coupling links and the penetrating spatial risk coefficient calculated through non-adjacent coupling links, forming a unified spatial risk coefficient value. The core purpose of this operation is to integrate the risk impact of the same deployed device under two propagation paths to comprehensively express its risk coverage to a specific security facility. Because the risk transmission characteristics of different path mechanisms differ—for example, the conventional path reflects direct impact in open space, while the penetrating path reflects indirect coupling under structural partitions—direct summation may lead to an imbalance or distortion of influence. Therefore, the system introduces a set of adjustable weighting coefficients, assigning different levels of evaluation weight to the influence of the conventional path and the penetrating path.

[0079] In practical implementation, the system first obtains the conventional space risk coefficient and the penetration space risk coefficient based on each link type. For example, in the aforementioned steps, if the conventional space risk coefficient between a deployed device and a security facility is 0.28 and the penetration space risk coefficient is 0.15, the system uses these two values ​​as basic inputs. Subsequently, the system sets the weighting coefficient for the conventional path as α and the weighting coefficient for the penetration path as β, based on scenario characteristics or expert presets, where α + β = 1. This weighting ratio can be flexibly adjusted according to factors such as the transparency of the exhibition hall's spatial structure, the protection requirements of security facilities, and the density of equipment deployment. For example, in an exhibition hall with a complex structure and dense walls, the penetration path may pose a greater risk to security facilities, so it can be configured as α = 0.4 and β = 0.6; conversely, in an open exhibition hall with good transparency, it can be set as α = 0.7 and β = 0.3.

[0080] The system uses the following formula to calculate the spatial risk coefficient: Spatial Risk Coefficient = α × Conventional Spatial Risk Coefficient + β × Penetration Spatial Risk Coefficient. Continuing the example above, if α = 0.6 and β = 0.4, the final spatial risk coefficient is 0.6 × 0.28 + 0.4 × 0.15 = 0.224 + 0.06 = 0.284. This value will be used as the comprehensive risk contribution of the current equipment to the specified safety facility in the spatial dimension in subsequent risk transmission modeling and comprehensive risk assessment.

[0081] Through this weighted fusion method, the system achieves a reasonable normalization of the impact of multi-path risks. This ensures that the spatial risk coefficient not only retains the differences in risk characteristics across different paths but also allows for flexible adjustment based on actual application scenarios, enhancing the method's adaptability and accuracy. For example, in a real exhibition hall scenario, there are both air convection paths and wall heat conduction paths between a high-heat source device and a fire extinguishing device. The spatial risk coefficient calculated using the aforementioned weighted fusion method can more accurately reflect the comprehensive thermal risks faced by the fire extinguishing device, thus providing a reliable basis for subsequent risk threshold judgment and optimization suggestions.

[0082] S104. Calculate the risk transmission coefficient from multiple deployed device nodes to the same security facility node in the device-facility security domain diagram based on the first preset risk model; After the device-facility security domain graph is constructed and the spatial risk coefficients between each deployed device node and the security facility node are calculated, the system needs to further evaluate the aggregated and superimposed risk effects that multiple deployed devices may have on the same security facility. Therefore, a first preset risk model is introduced to calculate the risk transmission coefficient. The model is designed to capture the differences in the transmission capabilities of the same security facility node's location across multiple deployed device nodes. The core idea of ​​the model comes from the multi-source influence accumulation rate calculation method in network contagion mechanisms, which can be simplified as follows: when multiple risk sources exist simultaneously, a single target node (security facility) will bear different degrees of comprehensive transmission risk due to factors such as its stress point, connection density, and structural obstruction in the structural network. Therefore, the system constructs a risk transmission factor weight matrix based on parameters such as the spatial distribution of device nodes to the security facility node, the number of coupled links, and the degree of path superposition. A node importance scoring mechanism similar to PageRank is introduced to calculate the path weight distribution of the risk path from each device node to the security facility node, thereby deriving the risk transmission coefficient of each deployed device node to the security facility node. The system calculates a transmission coefficient by weighting path overlap, path length, and coupling link type (regular / non-adjacent). For example, if a security facility node is surrounded by three deployed device nodes, where node A has a dual-path link to the facility (1 regular + 1 penetrating), node B has only a penetrating link, and node C has a long-distance regular link, the system assigns a higher transmission coefficient (e.g., 0.45) to A and lower transmission coefficients (e.g., 0.35 and 0.20) to B and C, reflecting the spatial differences in their transmission capabilities.

[0083] S105. Calculate the comprehensive risk level of the safety facility node based on the spatial risk coefficient and the risk transmission coefficient using the second preset risk model; After obtaining the risk transmission coefficient between each pair of deployed device nodes and the target security facility node, the system further introduces a second preset risk model to aggregate the spatial risk coefficient and risk transmission coefficient of each deployed device node, calculating the comprehensive risk level of each device node to the security facility. The design logic of this model is based on the Path-Impact Product Model in risk systems engineering. Its core principle is that in a structured space, the influence of a risk source on a target node depends not only on its spatial intensity (defined by the spatial risk coefficient) but also on the transmission effect of its propagation path in the graph structure (defined by the risk transmission coefficient). Only the product of these two factors can truly reflect the actual transfer efficiency of risk energy from the source to the destination. Therefore, the system performs a one-to-one product operation on the spatial risk coefficient and the risk transmission coefficient to obtain the single-source comprehensive risk level of each deployed device to the target security facility. Subsequently, if a security facility node has risk contributions from multiple device nodes, the system sums the comprehensive risk levels of all related device nodes to form the final total risk level index for the facility node. This metric is used to assess the risk exposure of a facility under its current layout. If it exceeds a preset risk threshold (such as 0.6 or a user-defined value), the system determines that the facility has potential security risks and generates device-facility collaborative optimization suggestions accordingly. For example, if device A has a spatial risk coefficient of 0.35 and a risk transmission coefficient of 0.5 for a certain camera facility node, its overall risk level is 0.175. If device B has an overall risk level of 0.12 for the same facility node, the total overall risk level of that facility node is 0.295, which is still within the safe range. If this value exceeds the set 0.6, the system determines that the risk is too high and initiates the optimization suggestion push process.

[0084] Optional, in Figure 1 After step S105 in the illustrated embodiment, the following steps can be performed: Obtain the runtime sequence table of the deployed devices, which includes the startup order, running duration, and maintenance time window of the deployed devices; determine the time-overlapping device groups based on the runtime sequence table; when any of the time-overlapping device groups has a coupling link with the same security facility node in the device-facility security domain diagram, calculate the time-coordination risk factor of the time-overlapping device group; and correct the comprehensive risk level based on the time-coordination risk factor.

[0085] After obtaining the comprehensive risk level for each facility and equipment node, to further improve the time adaptability and operational reliability of the risk assessment, the system optionally introduces runtime sequence table data of the deployed equipment to dynamically adjust the comprehensive risk level. The runtime sequence table refers to a data structure that records the specific activation, operation, and maintenance time status information of each deployed device in the exhibition hall scenario. It includes fields such as startup sequence, operation duration, and maintenance time window, and is usually provided by the operation and maintenance system or equipment configuration system. By parsing this runtime sequence table, the system identifies sets of devices with overlapping operating states within the same time interval, called time-overlapping device groups. These device groups may have a synergistic impact on the same facility node in both physical space and time dimensions. To quantify this synergistic risk, the system calculates a correction parameter called the time-coordinated risk factor based on the coupling link between these device groups and the target facility node. The calculation of this factor is based on the following: if multiple devices operate simultaneously within similar or overlapping time periods and have direct or penetrating coupling paths with the same facility node, their risk impact on that facility is simultaneous and synergistic. The risks cannot be simply linearly superimposed; therefore, a nonlinear correction needs to be introduced. For example, an exponential growth function or an empirical synergistic weighting model can be used to increase the original comprehensive risk level by a certain proportion to reflect the actual risk concentration effect. The system uses this time-series synergistic risk factor as a weighting function, multiplying it by the original comprehensive risk level to obtain the corrected comprehensive risk level, which is used to more realistically characterize the dynamic volatility of risk in actual usage scenarios. For example, if devices A, B, and C form a time-overlapping device group operating in the same time window and are all connected to a certain safety facility node, the original total comprehensive risk level is 0.55. If the system calculates a time-coordination risk factor of 1.2 based on the degree of device overlap, the corrected comprehensive risk level is 0.55 × 1.2 = 0.66, which exceeds the original threshold. Based on this, the system determines that the facility has a potential overload risk and generates a collaborative optimization prompt that includes runtime adjustment and device replacement suggestions.

[0086] S106. When the overall risk level is greater than the preset risk threshold, generate equipment-facility collaborative optimization suggestions.

[0087] After calculating the overall risk level between each deployed device node and any security facility node, the system enters the subsequent security response phase, which determines whether to trigger the layout optimization mechanism based on the overall risk level. When the overall risk level exceeds the system's set risk threshold, it indicates that the current device, in its physical spatial structure and operating state, constitutes an unacceptable security exposure to a certain security facility, posing potential risks such as interference, obstruction, false triggering, or signal attenuation. To address this, the system introduces a device-facility collaborative optimization suggestion generation module. This module aims to automatically or semi-automatically output risk avoidance suggestions while maintaining the integrity of the exhibition hall's functionality, assisting managers in adjusting deployment plans. The preset risk threshold is set based on a comprehensive analysis of historical exhibition hall security event data, facility sensitivity levels, and equipment risk levels, through simulation modeling and expert experience assessment, and is used to define the maximum acceptable risk exposure level for the facility.

[0088] The optimization recommendations are generated based on the established spatial coupling relationships and runtime sequence information in the equipment-facility safety domain graph, and are derived using a collaborative optimization algorithm based on graph traversal and constraint reconstruction. First, the system identifies critical path nodes that contribute to the increase in overall risk, i.e., deployed equipment nodes with risk contribution values ​​higher than the average level. Combining the coupling link type and path structure between these nodes and the target safety facility nodes, the spatial transmission characteristics of the influencing paths are derived. Then, based on the pre-reserved deployable area data in the Building Information Model (BIM), the system constructs a set of candidate deployment locations and selects locations that meet the following three constraints: (1) locations with higher risk attenuation of the coupling path compared to the original location; (2) locations with temporal peak-shifting relationships with other high-risk equipment nodes in terms of runtime sequence; and (3) locations that will not introduce new non-adjacent coupling paths or obstruct the sensing range of critical safety facilities. After the candidate deployment points are selected, the system simulates and evaluates multiple candidate deployment schemes based on the objective function of minimizing the total risk, and finally outputs several optimal or suboptimal adjustment recommendations.

[0089] The optimization recommendations are output in the form of a graphical deployment suggestion diagram, a risk indicator comparison table, and adjustment explanation text. The recommendations include: adjusting specific equipment to designated coordinate areas, adjusting runtime sequences to avoid high-risk overlapping areas, or introducing additional structural media components to shield non-adjacent coupling paths. This optimization module not only has automated evaluation capabilities but also supports linkage with manual intervention mechanisms, allowing managers to tailor and adjust the recommended solutions based on the actual showroom environment.

[0090] For example, if the overall risk level of camera facility node F1 is 0.72, exceeding the set threshold of 0.6, and device node D3 contributes a risk level of 0.42, the path contains a penetrating coupling link, and the runtime of device D3 overlaps with that of D5, the system will identify D3 as a high-risk node and select three low-coupling candidate points P1, P2, and P3 in its surrounding deployment space for simulated deployment. After evaluation, it is found that moving D3 to P2 can reduce the overall risk level of F1 to 0.51, and at the same time reduce the collaborative risk factors with D5. Based on this, the system generates deployment adjustment suggestions and highlights the risk difference between the original location and the optimized location on the interface to provide decision-making reference for managers.

[0091] Through the implementation of the above-mentioned optimization suggestion generation mechanism, the system not only realizes the automatic identification and response to layout risks, but also improves the intelligence level of exhibition hall security strategies, thereby effectively avoiding problems such as the failure of security facility functions, false alarms or interference caused by improper equipment deployment.

[0092] Please see Figure 3 This is a schematic diagram of the structure of an exhibition hall layout security verification system in an embodiment of this application.

[0093] It should be noted that, Figure 3 The structure of the exhibition hall layout security verification system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0094] like Figure 3 As shown, a showroom layout security verification system includes a central processing unit 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory 302 or a program loaded from a storage section 308 into a random access memory 303, such as executing the methods described in the above embodiments. The random access memory 303 also stores various programs and data required for system operation. The central processing unit 301, the read-only memory 302, and the random access memory 303 are interconnected via a bus 304. An input / output interface 305 is also connected to the bus 304.

[0095] The following components are connected to the input / output interface 305: an input section 306 including audio input devices, push-button switches, etc.; an output section 307 including an LCD display, audio output devices, indicator lights, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the input / output interface 305 as needed. A removable medium 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 310 as needed so that computer programs read from it can be installed into the storage section 308 as needed.

[0096] It should be noted that specific examples of computer-readable storage media may include, but are not limited to, electrical connections having one or more wires, portable computer disks, optical storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used in conjunction with an instruction execution system, apparatus, or otherwise. The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the invention. Specifically, an exhibition hall layout security verification system according to this embodiment includes a processor and a memory. The memory stores a computer program, which, when executed by the processor, implements an exhibition hall layout security verification method provided in the above embodiments. As another aspect, the present invention also provides a computer-readable storage medium, which may be included in an exhibition hall layout security verification system described in the above embodiments; or it may exist independently and not assembled into such an exhibition hall layout security verification system. The storage medium carries one or more computer programs, which, when executed by a processor of the exhibition hall layout security verification system, cause the exhibition hall layout security verification system to implement the exhibition hall layout security verification method provided in the above embodiments.

Claims

1. A method for verifying the security of exhibition hall layout, characterized in that, The method includes: Obtain the building information model of the target exhibition hall and the equipment deployment data of the deployed equipment. The building information model includes the exhibition hall structural features and safety facility layout data of the target exhibition hall. Based on the equipment deployment data and the structural features of the exhibition hall, a security domain diagram of the equipment-facilities of the target exhibition hall is constructed. The security domain diagram of the equipment-facilities includes conventional coupled links and non-adjacent coupled links. One deployed device corresponds to one deployed device node, and one security facility corresponds to one security facility node. Calculate the spatial risk coefficient between each deployed device node and the target security facility node in the device-facility security domain graph, wherein the target security facility node is a security facility node connected to the deployed device node through the conventional coupling link or the non-adjacent coupling link; Based on the first preset risk model, calculate the risk transmission coefficient of multiple deployed device nodes to the same security facility node in the device-facility security domain diagram; The comprehensive risk level of the safety facility node is calculated based on the spatial risk coefficient and the risk transmission coefficient using a second preset risk model. When the overall risk level is greater than a preset risk threshold, a collaborative optimization suggestion for equipment and facilities is generated.

2. The method according to claim 1, characterized in that, The construction of the equipment-facility security domain diagram of the target exhibition hall based on the equipment deployment data and the exhibition hall structural features specifically includes: Analyze the structural features of the exhibition hall in the building information model, identify the structural medium components that serve as physical supports or spatial barriers for deployed equipment in the target exhibition hall, and obtain the conduction properties of the structural medium components; Taking the deployed device node as the starting point of the risk source, and based on the preset inherent risk of the deployed device node and the conduction properties of the structural medium component, a penetrating influence path is traced to determine the penetrating influence path of the deployed device node. The penetrating influence path includes the starting point of the risk source, the endpoint of the influence, and the degree of risk attenuation between the starting point of the risk source and the endpoint of the influence. Determine whether the affected endpoint falls within the preset sensing range of any of the security facility nodes; If so, a non-adjacent coupling link characterizing cross-media impact is established between the deployed device node and the security facility node, and the degree of risk attenuation is used as the weight attribute of the non-adjacent coupling link; Obtain the regular coupling links between the deployed device nodes and the security facility nodes, whereby the regular coupling links are used to characterize the coupling influence relationships directly transmitted through the environmental space; The device-facility security domain graph is obtained based on the non-adjacent coupling links and the conventional coupling links.

3. The method according to claim 2, characterized in that, The step of using the deployed device node as the starting point of the risk source, and based on the inherent risks of the deployed device node and the conduction properties of the structural media components, to perform penetrating influence path tracing, specifically includes: Identify the contact surfaces between the deployment device and the structural media component, generate a tracking branch for each contact surface, and use the deployment device node as the starting point of the risk source for all tracking branches; For any of the tracking branches, based on the conduction properties of the first structural medium component corresponding to any of the tracking branches, it is determined whether the preset inherent risk corresponding to the deployment device node can penetrate the first structural medium component, and one preset inherent risk corresponds to one initial influence intensity. If the preset inherent risk can penetrate the first structural medium component, then based on the barrier coefficient in the conduction property, the initial influence intensity of the tracking branch is attenuated to obtain the first residual influence intensity, and based on the structural characteristics of the first structural medium component, the current tracking position and the next tracking direction after penetrating the first structural medium component are determined. Using the first residual influence intensity as the current influence intensity, the next hop tracing is performed based on the current tracing position and the next tracing direction until the preset tracing termination condition is met. The influence path result of the tracing branch is then determined, and the influence path results corresponding to all the contact surfaces are set together to obtain the penetrating influence path. The influence path result includes the influence endpoint and the risk attenuation degree.

4. The method according to claim 3, characterized in that, The process of performing the next hop tracking based on the current tracking position and the next tracking direction until a preset tracking termination condition is met, and then determining the influence path result of the tracking branch, specifically includes: From the current tracking position, track along the next tracking direction to determine whether a target structural medium component is encountered. The target structural medium component is any structural medium component other than the first structural medium component in the current tracking process. If the target structural medium component is encountered, it is determined whether the current influence intensity can penetrate the target structural medium component based on the conduction properties of the target structural medium component; If penetration is possible, the second residual influence intensity is calculated based on the blocking coefficient of the target structure medium component, the current tracking position and the next tracking direction are updated, and the next hop tracking is continued. If penetration is not possible, the contact surface of the target structural medium component is determined as the endpoint of the influence, and the degree of risk attenuation is calculated based on the initial influence intensity and the current influence intensity. If the target structural medium component is not encountered, calculate the minimum distance from the current tracking position to the exhibition hall boundary; If the minimum distance is less than a preset distance threshold, the exhibition hall boundary is determined as the endpoint of the impact, and the first impact intensity after spatial attenuation is calculated based on the minimum distance. The initial impact intensity and the first impact intensity are used to calculate the degree of risk attenuation. If the minimum distance is greater than or equal to the preset distance threshold, the current tracking position is determined as the impact endpoint, and the risk attenuation degree is calculated based on the initial impact intensity and the residual impact intensity corresponding to the current tracking position. When the current influence intensity is less than a preset intensity threshold, or the current tracking hop count reaches a preset maximum hop count, or the influence endpoint is determined, the preset tracking termination condition is satisfied.

5. The method according to claim 1, characterized in that, The calculation of the spatial risk coefficient between each deployed device node and the target security facility node in the device-facility security domain graph specifically includes: Calculate the conventional spatial risk coefficient of the conventional coupling links in the equipment-facility security domain diagram, and calculate the penetration spatial risk coefficient of the non-adjacent coupling links in the equipment-facility security domain diagram; The space risk coefficient is obtained by weighted summing of the conventional space risk coefficient and the penetrating space risk coefficient.

6. The method according to claim 5, characterized in that, The calculation of the conventional spatial risk coefficient of the conventional coupling links in the equipment-facility security domain diagram and the calculation of the penetration spatial risk coefficient of the non-adjacent coupling links in the equipment-facility security domain diagram specifically include: For each of the aforementioned conventional coupling links, calculate the straight-line distance from the deployed device node to the target security facility node; Calculate the spatial attenuation factor based on the straight-line distance; The conventional spatial risk coefficient corresponding to the conventional coupling link is obtained by multiplying the spatial attenuation factor with the preset risk level coefficient of the deployed device node. For each of the non-adjacent coupled links, the weight attribute of the non-adjacent coupled link is obtained as a penetration attenuation factor; The penetration attenuation factor is multiplied by the preset risk level coefficient of the deployed device node to obtain the penetration space risk coefficient corresponding to the non-adjacent coupling link.

7. The method according to claim 1, characterized in that, After calculating the comprehensive risk level of each deployed device to the security facility based on the spatial risk coefficient and the risk transmission coefficient using a preset risk model, the method includes: Obtain the runtime sequence table of the deployed device, which includes the startup order, running duration, and maintenance time window of the deployed device; Based on the runtime sequence table, determine the time-overlapping device group; When any of the time-overlapping device groups has a coupling link with the same security facility node in the device-facility security domain diagram, calculate the time-coordination risk factor of the time-overlapping device group; The overall risk level is corrected based on the aforementioned time-series collaborative risk factors.

8. A security verification system for exhibition hall layout, characterized in that, The exhibition hall layout security verification system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the exhibition hall layout security verification system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the exhibition hall layout security verification system, the exhibition hall layout security verification system performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the exhibition hall layout security verification system, the exhibition hall layout security verification system performs the method as described in any one of claims 1-7.

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