Data visualization method and system applied to intelligent building wiring

Abstract

The application discloses a data visualization method and system applied to intelligent building wiring, the method obtains an operation event sequence triggered by an operation and maintenance personnel in a three-dimensional visual operation and maintenance interface, locates a topological node in a building wiring link topology according to an action object identifier and generates an operation walk path; the operation walk path is subjected to path behavior analysis, branch selection tendency characteristics and residence duration characteristics are extracted and combined into an operation and maintenance intention representation vector; the operation and maintenance intention representation vector is associated with the topological node, intention diffusion processing is performed along the topological edge, and residence reinforcement processing is performed on the topological node to generate a topological node visual highlight distribution; the topological node visual highlight distribution is mapped to a wiring asset unit to generate a visual presentation level parameter and configuration information; the configuration information is input into an asset display and concealment control link of a scene rendering pipeline, drawing transparency and wireframe density are adjusted, and adaptive evolution of wiring asset presentation content along with an operation and maintenance cognitive focus is realized.

Description

Technical Field

[0001] This invention relates to the field of big data visualization technology, specifically to a data visualization method and system applied to intelligent building cabling. Background Technology

[0002] In the field of intelligent building operation and maintenance management, 3D visualization technology has been widely used in the daily operation and maintenance management of building cabling assets. Maintenance personnel can use the 3D visualization interface to view the distribution and connection relationships of cabling assets such as network cables, fiber optic cables, patch panels, and switch ports on each floor and in each area of ​​the building, and perform daily inspections, fault location, and link tracing.

[0003] In existing technologies, 3D visualization operation and maintenance interfaces typically use a homogeneous rendering method to present all cabling asset units. This means all asset units have similar rendering transparency and geometric detail, requiring maintenance personnel to rely on their familiarity with the building's cabling topology to locate target asset units one by one within a densely packed 3D model scene. Some existing technologies allow maintenance personnel to manually enter asset numbers or names for retrieval, or to narrow the visible area using preset floor-level filtering mechanisms. Other existing technologies pre-set different display colors or icon styles based on the asset unit's type and attributes to assist maintenance personnel in visual differentiation.

[0004] However, when maintenance personnel perform continuous tasks, the above methods cannot dynamically adjust the content displayed on the interface according to their operation trajectory and cognitive focus. This results in a large number of cabling asset units that are not related to the current maintenance task continuously occupying visual channel resources, increasing the visual search burden of maintenance personnel, reducing the efficiency of maintenance task execution, and failing to perceive the direction selection tendency of maintenance personnel at topology branch nodes and the differences in their attention to different asset units. Therefore, it is difficult to achieve visual guidance at the interface level that matches the cognitive process of maintenance personnel. Summary of the Invention

[0005] The purpose of this invention is to provide a data visualization method and system for intelligent building cabling, so as to solve the problems mentioned in the background art.

[0006] This invention provides a data visualization method for smart building cabling, comprising: The system acquires the sequence of operation events triggered by maintenance personnel in the 3D visualization maintenance interface. Based on the object identifier of each operation event, it locates the corresponding topology node in the building cabling link topology, arranges the topology nodes according to the operation time to generate the topology node access sequence, and records the transfer edge sequence of adjacent topology nodes to generate the operation traversal path. The operation traversal path is analyzed to extract branch selection tendency features and dwell duration features, and combined into an operation and maintenance intention representation vector. The operation and maintenance intent representation vector is associated with the topology nodes in the building cabling link topology. Intent diffusion processing is performed along the topology edges and dwelling enhancement processing is performed on the topology nodes to generate a visually prominent distribution of topology nodes. The topology nodes are visually highlighted and distributed and mapped to the cabling asset units in the three-dimensional visualization operation and maintenance interface to generate visual presentation level parameters for each cabling asset unit and obtain visual presentation level configuration information. The visual presentation level configuration information is input into the asset visibility control stage of the scene rendering pipeline. The drawing transparency and drawing wireframe density of the corresponding wiring asset unit are adjusted according to the visual presentation level parameters to achieve adaptive evolution of the wiring asset presentation content according to the operational and maintenance focus.

[0007] This invention provides a data visualization system, comprising: A processor; a storage device having a computer program stored thereon; a network interface for providing network communication functions; when the computer program is executed by the processor, the processor enables the processor to implement the above-described data visualization method for intelligent building cabling.

[0008] The present invention provides a readable storage medium on which a program or instruction is stored, and when the program or instruction is executed by a processor, it implements the above-described data visualization method for intelligent building cabling.

[0009] Compared with existing technologies, the beneficial effects of this invention are as follows: By acquiring the sequence of operation events performed by maintenance personnel in a 3D visualized maintenance interface and generating operation traversal paths, the implicit cognitive behavior patterns of maintenance personnel are quantified into computable operation trajectory data, providing structured data for intent perception; by performing path behavior analysis on the operation traversal paths, branch selection tendency features and dwell duration features are extracted and combined into maintenance intent representation vectors, achieving a two-dimensional quantitative expression of the cognitive focus and spatial exploration tendency of maintenance personnel, overcoming the deficiency of traditional methods in being unable to perceive the subjective intent of maintenance personnel; by associating the maintenance intent representation vector with the building cabling link topology, intent diffusion processing is performed along the topology edges and dwell time enhancement processing is performed on the topology nodes. The system generates a visually prominent distribution of topology nodes, allowing the impact of a single operation to propagate along the topology to adjacent nodes. Simultaneously, historical attention information is accumulated and retained, enabling estimation of the spatial range and intensity measurement of the focus of operations and maintenance personnel. By mapping the visually prominent distribution of topology nodes to cabling asset units in the 3D visualization operations and maintenance interface, a visual presentation level parameter is generated. This parameter is then input into the asset visibility control of the scene rendering pipeline to adjust the rendering transparency and wireframe density of the corresponding cabling asset units. This achieves an overall adaptive evolution of the cabling asset presentation content in the 3D visualization operations and maintenance interface according to the operational focus, avoiding the low visual search efficiency caused by the homogeneous presentation of asset units in traditional 3D interfaces. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a data visualization method for intelligent building cabling, provided as an embodiment of the present invention.

[0012] Figure 2 This is a schematic diagram of the interface of the intelligent building cabling operation and maintenance platform provided in an embodiment of the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] This invention can be applied to intelligent building operation and maintenance management scenarios. In this scenario, a large number of cabling asset units are deployed within the building, including but not limited to network cables, optical fibers, patch panels, switch ports, cable trays, and terminal information panels. These cabling asset units form a complex building cabling link topology according to their physical connections and spatial layout. Maintenance personnel perform daily inspections, troubleshooting, and link tracing through a 3D visualization operation and maintenance interface, which presents the cabling asset units and their connections in the form of a 3D model. However, as building size and cabling density increase, maintenance personnel face a large number of simultaneously presented cabling asset units in the 3D visualization operation and maintenance interface, leading to excessive cognitive load and difficulty in quickly locating asset units relevant to the current operation and maintenance task, thus affecting operation and maintenance efficiency.

[0015] To address this, this invention monitors the operational behavior of maintenance personnel in a 3D visualized maintenance interface, analyzes their cognitive intent, and adaptively adjusts the visual presentation intensity of cabling asset units based on this intent. This highlights asset units with high cognitive relevance and weakens those with low cognitive relevance, thereby reducing the visual search cost for maintenance personnel and improving the efficiency of maintenance task execution. Specifically, this method constructs operational walkthrough paths, extracts maintenance intent representations, generates a visual salience distribution of topology nodes, maps it to visual presentation level parameters, and ultimately drives the scene rendering pipeline. This achieves the adaptive evolution of cabling asset presentation content in the 3D visualized maintenance interface according to the maintenance personnel's cognitive focus.

[0016] Please see Figure 1 , Figure 1 This is a flowchart of a data visualization method for intelligent building cabling provided by an embodiment of the present invention. The method can be executed by a data visualization system and includes steps 110-150.

[0017] Step 110: Obtain the sequence of operation events triggered by the operation and maintenance personnel in the 3D visualization operation and maintenance interface. Locate the corresponding topology node in the building cabling link topology according to the object identifier of each operation event. Arrange the topology nodes according to the operation time to generate the topology node access sequence, and record the transfer edge sequence of adjacent topology nodes to generate the operation traversal path.

[0018] In intelligent building operation and maintenance scenarios, maintenance personnel interact with the 3D visualization operation and maintenance interface through input devices such as mouse clicks, keyboard shortcuts, touchpad gestures, or touchscreen operations. Each interaction corresponds to a specific interface response behavior, such as selecting any network cable, zooming in to view any patch panel port, rotating the view to observe the cable tray routing, or clicking the information panel to view the port of its corresponding switch. These operational behaviors reflect the current cognitive focus area and task execution direction of the maintenance personnel. In order to transform discrete raw interaction commands into structured operational behavior descriptions, it is necessary to parse and serialize the raw interaction commands to obtain a sequence of operation events containing operation type, target, and occurrence time. Then, combined with the building cabling link topology, a data structure describing the operation path of the maintenance personnel is generated. Specifically, step 110 includes the following sub-steps: Step 111: Monitor the interactive event channel in the 3D visualization operation and maintenance interface, intercept the original interactive commands triggered by the operation and maintenance personnel through the input device, and arrange the intercepted original interactive commands in ascending order according to the trigger time into an original interactive command queue.

[0019] In the underlying interactive framework of the 3D visualization operation and maintenance interface, all signals generated by input devices are transmitted to the event processing module of the interface through the interactive event channel. This channel is registered as a global event listener at the operating system or graphics engine level, capable of capturing raw signals such as click coordinates and key identifiers in mouse click events, key codes in keyboard events, and touch point coordinates and pressure values ​​in touch events. Whenever an operation is performed by an operator, the interactive event channel generates a raw interactive instruction. This instruction includes an operation type identifier, a pickup identifier of the target in the 3D scene, and a clock cycle count value at the trigger time. The captured raw interactive instructions are temporarily stored in an instruction buffer. Upon the arrival of a new instruction, all instructions in the instruction buffer are sorted in ascending order according to their clock cycle count values ​​at the trigger time, thus forming a raw interactive instruction queue with a clear temporal sequence.

[0020] Step 112: Parse the instruction type of each original interaction instruction in the original interaction instruction queue, identify the operation type label corresponding to the original interaction instruction, and associate the operation type label with the original interaction instruction.

[0021] For each original interaction command in the original interaction command queue, the operation type identifier field is first extracted from the command's data structure. This field is an enumeration value or integer code automatically generated by the interface framework based on the signal source and signal parameters when the interaction event channel captures the signal. For example, a left mouse click corresponds to operation type identifier 001, a double mouse click corresponds to operation type identifier 002, mouse wheel scrolling corresponds to operation type identifier 003, and a keyboard key press corresponds to operation type identifier 004. By querying a preset operation type mapping table, the operation type identifier is converted into a semantically clear operation type label. This label describes the category of the operation in string form, such as "click to select," "double-click to view details," "zoom in / out," or "keyboard shortcut." After the conversion, the operation type label is written back to the metadata field of the original interaction command, enabling the command to be identified in subsequent processing based on its operation semantic category.

[0022] Step 113: Perform target parsing on each original interaction instruction in the original interaction instruction queue, extract the target identifier of the building wiring asset object pointed to by the original interaction instruction, and associate the target identifier with the original interaction instruction.

[0023] In the 3D visualization operation and maintenance interface, each interactive building cabling asset unit has a globally unique target identifier in the scene registry. This identifier is typically a universally unique identifier or a numeric primary key, used to uniquely identify the asset unit within the system. The original interaction command usually includes an instance handle or scene node path returned by the pick operation, which points to the clicked or hovered model object in the 3D scene. In step 113, the instance handle carried in the original interaction command is converted into the target identifier of the corresponding building cabling asset object through the instance handle lookup interface of the scene management system. If the target of the original interaction command is not a specific cabling asset unit but rather the interface background or a global control component, the target resolution result is null. The resolved target identifier is associated with the original interaction command, ensuring that each command carries the unique identifier of the cabling asset unit to which its operation points.

[0024] Step 114: Extract the trigger time of each original interaction command as the operation occurrence time, associate the operation occurrence time with the original interaction command, and generate an operation event that carries an operation type label, an object identifier, and the operation occurrence time.

[0025] When a raw interaction command is captured by the interaction event channel, the system clock records a high-precision timestamp for it. This timestamp, in milliseconds or microseconds, represents the absolute moment the command was triggered. This timestamp value is extracted from each raw interaction command as the operation occurrence time. The operation type label associated in step 112, the target object identifier associated in step 113, and the operation occurrence time are then combined into a complete operation event. This operation event is a standardized product of the structured parsing of the raw interaction command, and its data structure contains three fields: an operation type field to store the operation type label, a target object field to store the target object identifier, and a timestamp field to store the operation occurrence time.

[0026] Step 115: Arrange the operation events in ascending order according to the time of occurrence of the operation to generate an operation event sequence.

[0027] All operation events generated in step 114 are compiled into an event list. The operation events in this list are then sorted in ascending order using the time of occurrence carried by each operation event as the sorting key. After sorting, the operation events in the event list are arranged in chronological order, with the earliest occurring operation event at the beginning and the latest occurring operation event at the end, thus forming an operation event sequence. This sequence completely records all operations performed by the operations personnel within the observation time window, providing an ordered raw data foundation for the subsequent generation of operation traversal paths.

[0028] Step 116: Read the pre-built building cabling link topology, obtain the set of topology nodes contained in the building cabling link topology, and each topology node in the topology node set corresponds to a building cabling asset object and carries a node identifier.

[0029] The building cabling link topology is a pre-built graph structure data model used to describe the physical connections and spatial layout relationships between various cabling asset units in a building. This topology uses nodes to represent cabling asset units and edges to represent cabling connections between asset units. The building cabling link topology is stored in the system's topology database in the form of an adjacency list or adjacency matrix. Reading this topology data and extracting all nodes forms a topology node set. Each topology node in this set carries a node identifier, which maintains a one-to-one numerical correspondence with the target identifier of the corresponding building cabling asset object. This allows the same asset unit to be associated and matched in the topology space and the three-dimensional interface space through the identifier.

[0030] Step 117: Traverse each operation event in the operation event sequence, match the target identifier carried by the operation event with the node identifier of the topology node in the topology node set, and determine the topology node corresponding to the operation event.

[0031] For each operation event in the operation event sequence, its target object identifier field is extracted. This target object identifier is used as the query key to search the topology node set for a node whose identifier matches the target object identifier. If a match is found, that topology node is identified as the topology node corresponding to the operation event; if no match is found, it indicates that the target object of the operation event does not belong to an asset unit in the building cabling link topology, and the operation event is considered an invalid location event and marked. After the above matching process, each valid operation event in the operation event sequence is associated with a unique corresponding topology node.

[0032] Step 118: Arrange the matched topology nodes sequentially according to the order of the operation events in the operation event sequence to obtain the topology node access sequence.

[0033] The topology nodes identified in step 117 for each operation event are extracted and arranged according to the order of their corresponding operation events in the operation event sequence. Specifically, the topology node corresponding to the first operation event in the operation event sequence is taken as the first element of the topology node access sequence, the topology node corresponding to the second operation event is taken as the second element, and so on, until all valid operation events have been processed. This yields the topology node access sequence, where each element is a topology node, and the sequence order reflects the time sequence in which maintenance personnel operate on the asset units corresponding to each topology node.

[0034] Step 119: Check the adjacent topology nodes in the topology node access sequence in turn. If the node identifiers of the adjacent topology nodes are different, generate a transfer edge from the earlier topology node to the later topology node. Combine all the generated transfer edges in the order of inspection into a transfer edge sequence. Merge the topology node access sequence and the transfer edge sequence to generate an operation traversal path that describes the operation traversal path of the operation and maintenance personnel.

[0035] For each pair of adjacent topology nodes in the topology node access sequence, the node identifiers of the preceding and subsequent topology nodes are extracted and compared. If they are the same, it indicates that the maintenance personnel acted on the same asset unit in two adjacent operations, and no transfer between topology nodes occurs; therefore, no transfer edge is generated. If they are different, it indicates that the maintenance personnel's focus has shifted from the asset unit corresponding to the preceding topology node to the asset unit corresponding to the subsequent topology node; therefore, a directed transfer edge is generated from the preceding topology node to the subsequent topology node. All generated directed transfer edges are arranged sequentially according to their adjacent order in the topology node access sequence to form a transfer edge sequence. Finally, the topology node access sequence is used as the node sequence part of the operation walk path, and the transfer edge sequence is used as the edge sequence part of the operation walk path. The two are combined to form a complete operation walk path. This path describes the operation trajectory of the maintenance personnel on the building cabling link topology in the form of a walk path in graph theory. The nodes in the path represent the asset units being operated on, and the edges in the path represent the direction of switching of the focus between different asset units.

[0036] Step 120: Analyze the path behavior of the operation traversal path, extract the branch selection tendency features and dwell duration features, and combine them into an operation and maintenance intention representation vector.

[0037] The operation walk path records the access trajectory of maintenance personnel on the building cabling link topology. This trajectory not only includes which topology nodes were visited, but also implicitly reveals the maintenance personnel's selection preferences at topology branch nodes and the length of time spent at each topology node. These two behavioral patterns reflect two different dimensions of the maintenance personnel's intentions: branch selection preference reflects the maintenance personnel's focus on the designated link direction, and dwell time reflects the maintenance personnel's focus on the designated asset unit. To quantify these behavioral patterns into computable feature vectors, the operation walk path needs to be analyzed and its features extracted. Specifically, step 120 includes the following sub-steps: Step 121: Obtain the number of adjacent edges of each topology node in the building cabling link topology, mark the topology nodes with the number of adjacent edges exceeding the preset connection edge threshold as branch nodes, and construct a set of branch nodes.

[0038] In building cabling link topologies, the number of edges connected to different topology nodes varies. Nodes in the middle of a link typically connect to two edges, pointing to their upstream and downstream nodes respectively; while nodes at aggregation or distribution points may connect to three or more edges. For example, a patch panel node may connect to multiple network cables from different information panels. In the topology data structure, the number of adjacent edges for each topology node is counted, i.e., the total number of edges directly connected to that node. This counted number of adjacent edges is compared to a preset threshold for the number of connected edges. This threshold is related to the connectivity characteristics of the topology and can be calculated as the mean of the number of adjacent edges for all nodes in the topology plus one standard deviation. If the number of adjacent edges for any topology node exceeds this threshold, the node is marked as a branch node and added to the branch node set. All nodes in the branch node set represent locations where maintenance personnel face directional choices during operational walks.

[0039] Step 122: Traverse the sequence of transition edges in the operation's traversal path, and determine whether the starting topological node of each transition edge belongs to the branch node set. If it does, record the transition edge as a branch selection transition edge.

[0040] For each transition edge in the sequence of transition edges in the operational traversal path, extract the starting topology node of that transition edge, i.e., the starting node of the transition behavior indicated by that transition edge. Check if this starting topology node exists in the branch node set. If it exists, it indicates that when the operations personnel performed this transition, their current topology node was a branch node with multiple selectable outgoing edge directions, and the operations personnel chose a specific direction for the transition at that location. Mark and record this transition edge as a branch selection transition edge, which records a specific direction selection behavior of the operations personnel at the branch node.

[0041] Step 123: Extract the starting topology node identifier and outgoing edge direction of each branch selection transition edge, and generate a branch selection record containing the starting topology node identifier and outgoing edge direction.

[0042] For each transition edge marked as a branch selection transition edge, extract the node identifier of the starting topology node of the transition edge, and the outgoing direction that the transition edge points to among all outgoing edges of the starting topology node. The outgoing direction can be represented by the node identifier of the successor topology node pointed to by the transition edge, the index position of the transition edge in the adjacent edge list of the starting topology node, or the angle value between the transition edge and a preset reference direction. Combine the starting topology node identifier and the outgoing direction into a branch selection record, which clearly indicates which direction the operations and maintenance personnel chose to continue moving at the designated branch node.

[0043] Step 124: Arrange the branch selection records according to the time sequence of the operation path to form a branch selection record sequence. Perform directional continuity analysis on the branch selection record sequence, identify segments in continuous branch selection records where the outgoing edge direction remains consistent as continuous segments, and identify segments where the outgoing edge direction changes as turning segments.

[0044] All branch selection records generated in step 123 are arranged according to the order of their corresponding transition edges in the operation traversal path transition edge sequence, forming a branch selection record sequence. Each record in this sequence corresponds to a direction selection made by the operations and maintenance personnel at any branch node, and the order of the records reflects the timing of the direction selection behavior. A direction continuity analysis is performed on the branch selection record sequence. Specifically, starting from the first record in the sequence, the outgoing edge directions of adjacent records are compared sequentially. If the outgoing edge directions of adjacent records are the same or determined to be the same direction within a preset angle tolerance range, these two records are grouped into the same continuation segment. If the outgoing edge directions of adjacent records change, the current continuation segment ends at the previous record, and a new continuation segment begins at the next record. A continuation segment represents that the operations and maintenance personnel have selected the same outgoing edge direction multiple times when passing through the branch node, indicating that the operations and maintenance personnel have a continuous focus on the set link direction; a transition segment represents that the outgoing edge direction of the operations and maintenance personnel changes at the branch node, indicating that the focus of the operations and maintenance personnel has shifted directionally.

[0045] Step 124-1: Convert the outgoing directions of adjacent branch selection records in the branch selection record sequence into direction vectors, calculate the angle change between adjacent direction vectors. If the angle change is within the preset direction continuation tolerance range, then the adjacent branch selection records are grouped into the same continuation segment, and the outgoing direction of the next branch selection record is taken as the continuation direction of the continuation segment. If the angle change exceeds the preset direction continuation tolerance range, then the current continuation segment ends at the previous branch selection record, and a new continuation segment begins at the next branch selection record. At the same time, record the direction change method from the end of the continuation direction to the new continuation direction, and classify the recorded direction change method into left deflection, right deflection, or reverse foldback as the transition type of the transition segment.

[0046] The outgoing direction in a branch selection record is represented as a direction vector. This vector has a clear direction and magnitude in a two-dimensional plane or three-dimensional space, where the magnitude is normalized to a unit length to ensure that only directional information is represented. For two adjacent records in a branch selection record sequence, the direction vectors corresponding to their outgoing directions are extracted, and the change in angle between the two direction vectors is calculated. This change in angle is obtained by dividing the dot product of the two direction vectors by the product of their magnitudes and taking the inverse cosine. If the change in angle is less than or equal to a preset direction continuation tolerance threshold, it is determined that the maintenance personnel have maintained consistency in direction between the two adjacent branch selections. These two branch selection records are grouped into the same continuation segment, and the outgoing direction of the latter branch selection record is taken as the continuation direction of this continuation segment. If the change in angle is greater than the preset direction continuation tolerance threshold, it is determined that the maintenance personnel have changed direction between the two adjacent branch selections. The current continuation segment ends at the former branch selection record, and a new continuation segment begins at the latter branch selection record. Simultaneously, the method of direction change from the end continuation direction to the new continuation direction is recorded. Specifically, the rotation direction and rotation angle of the new continuation direction relative to the end continuation direction are calculated. If the rotation angle is within a preset left deflection angle range, it is marked as a left deflection; if it is within a preset right deflection angle range, it is marked as a right deflection; if the rotation angle is close to 180 degrees, it is marked as a reverse reversal. The above method of direction change is stored as the transition type of the transition segment.

[0047] Step 125: Based on the distribution of continuation segments and transition segments in the branch selection record sequence, generate branch selection tendency features to describe the degree of preference of maintenance personnel for the continuation direction at the topology branch node.

[0048] After identifying continuation and transition segments in the branch selection record sequence, the proportion of each continuation segment in the sequence and the frequency distribution of transition types for each transition segment are statistically analyzed. Specifically, the ratio of the number of branch selection records contained in a continuation segment to the total number of records in the branch selection record sequence is calculated as the basic continuation tendency ratio. For each identified continuation segment, the frequency of its continuation direction among all continuation segments is calculated, and the continuation direction with the highest frequency is taken as the primary continuation direction. The ratio of the total length of the continuation segment corresponding to the primary continuation direction to the total length of all continuation segments is taken as the primary continuation direction strength. The basic continuation tendency ratio and the primary continuation direction strength are combined into a two-dimensional vector, which is the branch selection tendency feature. Its first dimension represents the degree to which operations and maintenance personnel generally tend to maintain a consistent direction at branch nodes, and the second dimension represents the strength of the continuation direction most preferred by operations and maintenance personnel.

[0049] Step 126: Obtain the operation occurrence time of the operation event corresponding to each topological node in the topological node access sequence in the operation traversal path, calculate the time difference of the operation occurrence time of adjacent topological nodes as the dwell duration of the subsequent topological node, and generate a dwell duration sequence.

[0050] For each topology node in the topology node access sequence of the operation traversal path, its corresponding operation event carries the operation occurrence time. Starting from the second node in the topology node access sequence, for each topology node, calculate the time difference between the operation occurrence time of the operation event corresponding to that node and the operation occurrence time of the operation event corresponding to its predecessor. This time difference is used as the dwell duration of that topology node for which the operation is focused by the maintenance personnel. The first topology node in the topology node access sequence has no predecessor node, so its dwell duration is set to zero or the default value. Arrange the calculated dwell durations of each topology node according to the order of the topology node access sequence to form a dwell duration sequence. The i-th element in this sequence corresponds to the dwell duration of the (i+1)-th topology node in the topology node access sequence.

[0051] Step 127: Bind the topology node identifier in the topology node access sequence to the corresponding residence duration in the residence duration sequence to obtain the node residence record set.

[0052] The node identifier of each topology node in the topology node access sequence is paired and bound to the corresponding dwell duration. For the first node in the topology node access sequence, its dwell duration uses the default value. For each node starting from the second node, its corresponding dwell duration is taken from the element at the corresponding position in the dwell duration sequence. Each pairing and binding result forms a node dwell record, which contains two fields: topology node identifier and dwell duration. All node dwell records are aggregated into a node dwell record set, which fully describes the length of time that the operation and maintenance personnel spend on each topology node traversed in the operation traversal path.

[0053] Step 128: Encode the duration of residence for each topological node in the node residence record set to generate a duration feature that characterizes the degree of operation focus on the topological node.

[0054] For each node residency record in the node residency record set, its residency duration value is extracted. The residency duration values ​​from all node residency records are then aggregated and normalized. The normalization benchmark is the maximum residency duration in the node residency record set. The residency duration of each node is divided by this maximum value to obtain the normalized residency duration ratio, which is between zero and one. Subsequently, a non-linear mapping is applied to the normalized residency duration ratio of each node. A logarithmic function or square root function is used to transform the normalized ratio to compress the long-tail distribution and highlight the distinguishability of medium-duration residency. The transformed result serves as the residency duration feature of that topology node. This feature is a scalar value whose magnitude is proportional to the time that maintenance personnel spend observing the asset unit corresponding to that topology node, reflecting the degree of attention that asset unit receives from the maintenance personnel's perception.

[0055] Step 129: Concatenate the branch selection tendency feature and the dwell duration feature into feature vectors to generate the operation and maintenance intention representation vector. One dimension of the operation and maintenance intention representation vector corresponds to the branch selection tendency feature, and the other dimension corresponds to the dwell duration feature.

[0056] The branch selection tendency feature is a two-dimensional vector, and the dwell duration feature is a scalar value corresponding to each topology node. However, the dwell duration features of multiple topology nodes need to be aggregated before they can be concatenated with the branch selection tendency feature. Specifically, the dwell duration features of all topology nodes in the node dwell record set are indexed according to the topology node identifier, constructing a dwell duration feature vector with a dimension equal to the total number of topology nodes. The i-th component of this vector is the dwell duration feature of the i-th topology node. This dwell duration feature vector is concatenated with the branch selection tendency feature vector along the dimensional direction. The dimension of the concatenated vector is equal to the sum of the dimension of the branch selection tendency feature and the dimension of the dwell duration feature vector. This concatenation result is the operation and maintenance intention representation vector. The first two dimensions of this vector are the branch selection tendency feature, and the subsequent dimensions are the dwell duration features of each topology node. The operation and maintenance intention representation vector comprehensively describes the direction selection tendency of operation and maintenance personnel at topology branch nodes and the intensity of dwell attention to each topology node in the form of a numerical vector.

[0057] Step 130: Associate the operation and maintenance intent representation vector with the topology nodes in the building cabling link topology, perform intent diffusion processing along the topology edges and residency enhancement processing on the topology nodes to generate a visually prominent distribution of topology nodes.

[0058] The operation and maintenance intent representation vector reflects the historical operational behavior patterns of operation and maintenance personnel, which implies the spatial distribution tendency of their current cognitive focus. However, historical operational behavior only covers the topology nodes that operation and maintenance personnel have actually operated, while their cognitive focus may also include adjacent nodes that have not been directly operated but have topological connections with the operated nodes. In order to expand the discrete operational behavior information into a visual salience distribution covering the entire topology, the information in the operation and maintenance intent representation vector needs to be propagated along the topological edges of the building cabling link topology, while applying dwell reinforcement to the topology nodes that have been directly operated, and finally generating the visual salience value of each topology node. Step 130 includes the following sub-steps: Step 131: Analyze the operation and maintenance intention representation vector to separate the branch selection tendency feature vector and the dwell duration feature vector.

[0059] The operational intent representation vector is a composite vector formed by concatenating the branch selection tendency feature vector and the dwell duration feature vector along the dimensions. In step 131, according to the concatenation order and dimensional division defined in step 129, the first two dimensions are extracted from the operational intent representation vector as the branch selection tendency feature vector, and the remaining dimensions are extracted as the dwell duration feature vector. After separation, the branch selection tendency feature vector retains the directional selection tendency information of the operational personnel at the branch node, and the dwell duration feature vector retains the dwell attention intensity information of the operational personnel on each topology node.

[0060] Step 132: Extract the outgoing edge direction of the maintenance personnel at each branch node from the branch selection tendency feature vector, and determine the intention diffusion direction in the building cabling link topology by combining the outgoing edge direction.

[0061] The first dimension of the branch selection tendency feature vector is the basic ratio of continuation tendency, and the second dimension is the strength of the main continuation direction. Based on this feature vector, the main continuation direction is first determined, which is the outgoing edge direction corresponding to the strength of the main continuation direction in the branch selection tendency feature. This outgoing edge direction is represented in the form of a direction vector. After determining the main continuation direction, this direction vector is used as the intention diffusion direction in the building cabling link topology. This direction indicates the spatial propagation trend of the focus of operation and maintenance personnel's cognition, that is, operation and maintenance personnel are more likely to continue exploring subsequent nodes in the link along this direction.

[0062] Step 133: Take the last visited topology node in the operation traversal path as the diffusion start node and assign an initial diffusion strength value to the diffusion start node.

[0063] The last element in the topology node access sequence of the operational traversal path is the topology node last operated on by the operations personnel. This node represents the spatial location of the operations personnel's current cognitive focus. This node is selected as the diffusion initiation node. A preset initial diffusion intensity value is assigned to the diffusion initiation node. This initial diffusion intensity value is the initial energy of the intended diffusion process, and its magnitude determines the spatial range that the diffusion process can propagate. The initial diffusion intensity value is a fixed constant.

[0064] Step 134: Starting from the diffusion start node, traverse the topological edges of the building cabling link topology along the intended diffusion direction, gradually attenuate the diffusion intensity value along the traversal path, and assign the attenuated diffusion intensity value to the topological nodes traversed until the diffusion intensity value is lower than the preset cutoff limit, and terminate the diffusion to obtain the diffusion contribution component of each topological node.

[0065] Starting from the diffusion initiation node, adjacent topology nodes are visited hop-by-hop along the intended diffusion direction determined in step 132. For each visited topology node, the current diffusion strength value is multiplied by a preset attenuation factor to obtain an attenuated diffusion strength value, which is then assigned to the currently visited topology node as its diffusion contribution component. If the attenuated diffusion strength value is still higher than a preset cutoff threshold, the process continues to visit the next hop topology node along the intended diffusion direction; if the attenuated diffusion strength value is lower than or equal to the preset cutoff threshold, the diffusion process in that direction is terminated. In building cabling link topologies where multiple outgoing edges may align with the intended diffusion direction, the diffusion process preferentially selects the outgoing edge with the smallest angle to the intended diffusion direction for propagation. After the above diffusion process, each topology node traversed by the diffusion path receives a diffusion contribution component, while the diffusion contribution component of topology nodes not traversed by the diffusion path is zero.

[0066] Step 134-1: Set the diffusion initiation node as the current node, assign the initial diffusion intensity value to the current node as its diffusion contribution component, and mark the current node as visited.

[0067] In the initial state of the diffusion process, the diffusion initiation node is set as the current node. The initial diffusion intensity value assigned in step 133 is written into the diffusion contribution component field of the current node. At the same time, an visited flag is written into the access status flag field of the current node to prevent repeated access to the node in subsequent diffusion processes.

[0068] Step 134-2: Query the outgoing edges of the current node in the direction of the intention to spread. If there is an outgoing edge and the neighbor node pointed to by the outgoing edge has not been marked as visited, then the neighbor node is taken as the next hop node.

[0069] In the adjacency table of the building cabling link topology, query all outgoing edges of the current node, i.e., all directed edges originating from the current node. For each outgoing edge, calculate the angle between the outgoing edge's direction and the intended diffusion direction, and select the outgoing edge with the smallest angle as a candidate outgoing edge. Check the access status flag of the neighbor node pointed to by the candidate outgoing edge. If the neighbor node is not marked as visited, then determine the neighbor node as the next hop node.

[0070] Step 134-3: Multiply the diffusion intensity value of the current node by a preset attenuation factor to obtain the attenuated diffusion intensity value, and assign the attenuated diffusion intensity value to the next hop node as its diffusion contribution component.

[0071] The current diffusion strength value is read from the diffusion contribution component field of the current node. This value is then multiplied by a preset attenuation factor, and the product is the attenuated diffusion strength value. The preset attenuation factor is a constant between zero and one, and its specific value determines the rate at which the diffusion strength decays with increasing hop count. The calculated attenuated diffusion strength value is then written into the diffusion contribution component field of the next hop node.

[0072] Step 134-4: If the attenuated diffusion intensity value is lower than the preset cutoff limit, then the diffusion along the path is terminated.

[0073] After calculating the attenuated diffusion intensity value in step 134-3, this value is compared with a preset cutoff threshold. The preset cutoff threshold is a pre-defined intensity threshold whose magnitude determines the spatial propagation limit of the diffusion process. If the attenuated diffusion intensity value is lower than or equal to the preset cutoff threshold, it indicates that the diffusion energy on the current path is insufficient to continue effective propagation. Therefore, further diffusion along this path is terminated, and the next hop node is no longer used as the new current node for iteration.

[0074] Step 134-5: Take the next hop node as the new current node and repeat the decay diffusion process until all reachable paths have been traversed or the diffusion intensity value is lower than the preset cutoff limit.

[0075] If the comparison result in step 134-4 indicates that the attenuated diffusion strength value is higher than the preset cutoff threshold, then the next-hop node is set as the new current node, and the process returns to step 134-2 to continue execution. The outgoing edges of the new current node in the intended diffusion direction are queried, and subsequent steps are repeated. The diffusion process terminates when all reachable paths consistent with the intended diffusion direction have been traversed, or when the diffusion strength values ​​at the ends of all paths are lower than the preset cutoff threshold. At this point, all topology nodes in the building cabling link topology that have been visited by the diffusion process have obtained the corresponding diffusion contribution component.

[0076] Step 135: Extract the dwell duration code corresponding to each topological node from the dwell duration feature vector, and generate dwell reinforcement increment based on the dwell duration code. The higher the focus duration indicated by the dwell duration code, the larger the dwell reinforcement increment.

[0077] Each component in the dwell duration feature vector corresponds to a topology node. For each topology node, a dwell duration encoded value is extracted from its corresponding component; this encoded value is the dwell duration feature scalar value generated in step 128. This encoded value is multiplied by a preset dwell enhancement coefficient, and the product is used as the dwell enhancement increment for that topology node. The dwell enhancement coefficient is a positive real constant used to control the contribution weight of dwell duration to the final visual salience. Since the dwell duration encoded value itself has been normalized and non-linearly mapped, its magnitude reflects the degree of focus persistence of the maintenance personnel on that node; therefore, the dwell enhancement increment is directly proportional to the degree of focus persistence.

[0078] Step 136: The residency enhancement increment of each topological node is superimposed on the diffusion contribution component of that topological node to obtain the comprehensive salience component of that topological node.

[0079] For each topology node in the building cabling link topology, if the node has both a diffusion contribution component and a residency reinforcement increment, the two are added together to obtain the overall salience component of the node. If the node only has a diffusion contribution component and no residency reinforcement increment, the overall salience component takes the value of the diffusion contribution component. If the node only has a residency reinforcement increment and no diffusion contribution component, the overall salience component takes the value of the residency reinforcement increment. The overall salience component is the result of the combined effect of the diffusion contribution component and the residency reinforcement increment, reflecting both the spatial propagation influence of the operational personnel's cognitive focus and the influence of historical residency attention.

[0080] Step 137: Assign a basic salience component to topology nodes in the building cabling link topology that have not received a diffusion contribution component and have not received a residency enhancement increment.

[0081] For topology nodes in the building cabling link topology that have neither been visited during the diffusion process nor appeared in the node dwell record set, their diffusion contribution component and dwell reinforcement increment are zero. To prevent these nodes from being completely ignored in subsequent visual presentation and losing basic recognizability, a basic salience component is assigned to them. The basic salience component is a preset positive real constant, whose value is much smaller than the typical values ​​of the diffusion contribution component and the dwell reinforcement increment, ensuring that these nodes maintain a minimum level of recognizability in visual presentation.

[0082] Step 138: The comprehensive salience component of each topological node is fused with its basic salience component to generate the visual salience value of the topological node.

[0083] For each topology node, if the node has a comprehensive salience component, the visual salience value is taken from the comprehensive salience component; if the node only has a basic salience component, the visual salience value is taken from the basic salience component. In an alternative implementation, for nodes that have both a comprehensive salience component and a basic salience component, the two can be added together as the visual salience value. However, since the basic salience component is only assigned to nodes that do not have a comprehensive salience component, the two usually do not exist simultaneously.

[0084] Step 139: Collect the visual salience values ​​of all topology nodes in the building cabling link topology to generate the visual salience distribution of topology nodes.

[0085] The visual salience value of each topology node calculated in step 138 is indexed and organized according to the topology node identifier to form a mapping table from the topology node identifier to the visual salience value. This mapping table is the topology node visual salience distribution. Each key-value pair represents a topology node and its corresponding visual salience value. The topology node visual salience distribution fully describes the spatial distribution of the cognitive focus of operation and maintenance personnel on the entire building cabling link topology.

[0086] Step 140: Map the visually prominent distribution of topology nodes to cabling asset units in the 3D visualization operation and maintenance interface, generate visual presentation level parameters for each cabling asset unit, and obtain visual presentation level configuration information.

[0087] The visual salience distribution of topology nodes describes the visual salience of each topology node in the building cabling link topology. However, topology nodes are abstract representations at the logical level, while what is actually presented to maintenance personnel in the 3D visualization operation and maintenance interface is a 3D model of the cabling asset unit. Therefore, it is necessary to transfer the visual salience at the topology node level to the corresponding cabling asset unit and discretize the continuous visual salience values ​​into visual presentation level parameters that can be used for rendering control. For example, step 140 includes the following sub-steps: Step 141: Analyze the visual salience distribution of the topology nodes and extract the visual salience value corresponding to each topology node.

[0088] From the topology node visual salience distribution mapping table generated in step 139, all key-value pairs are traversed to extract each topology node identifier and its corresponding visual salience value. This extraction process converts the topology node visual salience distribution from the mapping table structure into a list of visual salience values ​​indexed by the topology node, which facilitates subsequent mapping with cabling asset units.

[0089] Step 142: Retrieve the mapping table of correspondence between each topology node in the building cabling link topology and the cabling asset unit in the 3D visualization operation and maintenance interface. Based on the mapping table, transmit the visual prominence value of the topology node to the corresponding cabling asset unit, and determine the received visual prominence value for each cabling asset unit.

[0090] During system initialization, each topology node in the building cabling link topology is associated with a building cabling asset object during construction. This asset object has a corresponding 3D model instance in the 3D visualization operation and maintenance interface. By traversing the topology nodes and querying the scene asset registry, a mapping table is established between topology nodes and cabling asset units. Each entry in this mapping table contains a topology node identifier and the corresponding asset unit identifier of the cabling asset unit. This mapping table is retrieved, and for each entry, the visual prominence value corresponding to the topology node identifier is extracted from the topology node visual prominence distribution and written to the received visual prominence value field of the cabling asset unit pointed to by the entry. If any cabling asset unit does not have a corresponding topology node in the mapping table, the received visual prominence value of that cabling asset unit is set to zero.

[0091] Step 142-1: Traverse all topology nodes in the building cabling link topology and obtain the node identifier of each topology node.

[0092] Each topology node is retrieved sequentially from the node set of the building cabling link topology, and the node identifier field stored in the node is read to obtain the unique identifier of the topology node.

[0093] Step 142-2: Query the scene asset registry in the 3D visualization operation and maintenance interface. The scene asset registry stores the asset unit identifier of each cabling asset unit in the scene and the corresponding building cabling asset object identifier.

[0094] The Scene Asset Registry is a metadata index structure built during the initialization of the 3D visualization operation and maintenance interface. Each record contains the asset unit identifier of a cabling asset unit in the 3D scene, as well as the building cabling asset object identifier corresponding to that cabling asset unit. The asset unit identifier is a handle or name string used in the 3D rendering engine to uniquely identify a scene model instance, while the building cabling asset object identifier is a number used in the business logic layer to identify asset objects. The Scene Asset Registry provides a bridge between 3D rendering objects and business logic objects.

[0095] Step 142-3: Compare the node identifier of the topology node with the building cabling asset object identifier in the scene asset registry. If they match, establish a mapping relationship from the topology node to the corresponding asset unit identifier.

[0096] For each topology node obtained in step 142-1, the node identifier is used as the query key to retrieve records in the scene asset registry whose building cabling asset object identifier field matches the node identifier. If a match is found, a mapping relationship is established between the topology node and the asset unit identifier in the record, indicating that the topology node and the cabling asset unit logically correspond to the same cabling asset.

[0097] Step 142-4: Gather all established mapping relationships to generate a corresponding mapping table. For each mapping relationship in the corresponding mapping table, extract the visual prominence value corresponding to the topology node identifier from the topology node visual prominence distribution, and assign the visual prominence value to the cabling asset unit pointed to by the mapping relationship.

[0098] The mapping relationships between all topology nodes and cabling asset units are compiled into a mapping table. For each entry in this mapping table, the visual salience value corresponding to the topology node identifier in that entry is retrieved from the topology node visual salience distribution. This value is then assigned to the cabling asset unit corresponding to the asset unit identifier in that entry, serving as the received visual salience value for that cabling asset unit.

[0099] Step 143: Divide the visual prominence value received by each cabling asset unit into segments, and map the visual prominence value to a transparency level label according to the preset mapping rule between prominence value segments and transparency levels.

[0100] The visual salience value is a continuous real number, while transparency control in 3D rendering pipelines typically uses discrete level labels for parameter configuration. The range of visual salience values ​​is pre-divided into multiple continuous and non-overlapping segments, each segment corresponding to a transparency level label. The transparency level labels increment from zero; a larger value indicates higher rendering transparency for the wired asset unit, meaning a weaker visual appearance. Specifically, the interval between the minimum and maximum possible values ​​of the visual salience value is divided into N equally or unequally divided sub-intervals, each assigned a transparency level label. For each wired asset unit's received visual salience value, it is determined which sub-interval it falls into, and the transparency level label corresponding to that sub-interval is used as the transparency level label for that wired asset unit.

[0101] Step 144: Divide the visual prominence value received by each cabling asset unit into segments, and map the visual prominence value to a wireframe density level label according to the preset mapping rule between prominence value segments and wireframe density levels.

[0102] Similar to step 143, the range of visual salience values ​​is pre-divided into multiple continuous and non-overlapping segments, each segment corresponding to a wireframe density level label. The wireframe density level label values ​​increase from zero, with larger values ​​indicating denser wireframe rendering of the 3D model of the wiring asset unit, resulting in richer geometric details. For each wiring asset unit's received visual salience value, it is determined which sub-interval it falls into, and the wireframe density level label corresponding to that sub-interval is used as the wireframe density level label for that wiring asset unit. The segmentation in steps 143 and 144 can use the same method, or independent methods can be used depending on the different sensitivities of transparency control and wireframe density control.

[0103] Step 145: Combine the transparency level label and the wireframe density level label of the same cabling asset unit to generate the visual presentation level parameter of the cabling asset unit.

[0104] For each cabling asset unit, the transparency level label obtained in step 143 and the wireframe density level label obtained in step 144 are combined into a composite parameter, which is the visual presentation level parameter of that cabling asset unit. The data structure of the visual presentation level parameter is a tuple containing two integer fields: the first field stores the transparency level label, and the second field stores the wireframe density level label.

[0105] Step 146: Traverse all cabling asset units in the 3D visualization operation and maintenance interface, obtain the visual presentation level parameters corresponding to each cabling asset unit, and associate and store the asset unit identifier of the cabling asset unit with the visual presentation level parameters.

[0106] For each cabling asset unit registered in the 3D visualization operation and maintenance interface scenario, its asset unit identifier is extracted, and the visual presentation level parameter corresponding to the asset unit identifier is obtained from the calculation result of step 145. The asset unit identifier and the visual presentation level parameter are associated and stored in a temporary configuration table in the form of key-value pairs. This temporary configuration table contains the visual presentation level parameter configurations for all cabling asset units in the scenario.

[0107] Step 147: Combine the asset unit identifiers and corresponding visual presentation level parameters of the cabling asset units within the current operational visibility range into a subset of visible visual presentation level configurations, and combine the asset unit identifiers and corresponding visual presentation level parameters of the cabling asset units within the current operational visibility range into a subset of invisible visual presentation level configurations.

[0108] Obtain the spatial range enclosed by the view frustum of the current virtual camera in the 3D visualization operation and maintenance interface. Use a view frustum clipping algorithm to determine whether the 3D bounding box of each cabling asset unit intersects with the view frustum. If they intersect, the cabling asset unit is within the visible range of the current operation and maintenance view; if they do not intersect, the cabling asset unit is outside the visible range. Based on the determination result, divide the key-value pairs in the temporary configuration table in step 146 into two subsets: the visible portion visual rendering level configuration subset contains the configurations of all visible cabling asset units, and the invisible portion visual rendering level configuration subset contains the configurations of all invisible cabling asset units.

[0109] Step 148: Merge the visible portion visual presentation level configuration subset and the invisible portion visual presentation level configuration subset to obtain visual presentation level configuration information.

[0110] The subset of visible visual presentation level configurations and the subset of invisible visual presentation level configurations obtained in step 147 are merged. The merged complete configuration set is the visual presentation level configuration information. Each entry in this configuration information contains an asset unit identifier and the corresponding visual presentation level parameters, covering the visual presentation level configuration of all cabling asset units in the 3D visualization operation and maintenance interface.

[0111] Step 150: Input the visual presentation level configuration information into the asset visibility control section of the scene rendering pipeline, and adjust the drawing transparency and drawing wireframe density of the corresponding wiring asset unit according to the visual presentation level parameters to achieve adaptive evolution of the wiring asset presentation content with the operational and maintenance cognitive focus.

[0112] The scene rendering pipeline of the 3D visualization operation and maintenance interface includes multiple sequential processing stages, from vertex processing, primitive assembly, rasterization to pixel shading. An asset visibility control stage is inserted after the material calculation stage and before the rasterization stage. This stage modifies the rendering attributes of each wiring asset unit based on its visual presentation level parameters. By passing the visual presentation level configuration information generated in step 148 to this stage, the rendering transparency and wireframe density of each wiring asset unit are adjusted unit-by-unit, thereby presenting a visual highlighting effect in the rendered output that matches the focus of the operation and maintenance personnel's perception. Optionally, step 150 includes the following sub-steps: Step 151: The visual rendering level configuration information is passed to the asset visibility control stage in the scene rendering pipeline. The asset visibility control stage is located after the material calculation stage and before the rasterization stage in the scene rendering pipeline.

[0113] The scene rendering pipeline executes each rendering stage in a predetermined order. In the material calculation stage, the material properties of the 3D model for each wireframe asset unit are calculated, including base color, metallicity, and roughness. After the material calculation stage is complete, the rendering data is passed to the asset visibility control stage. This stage is implemented as a callback function or interceptor within the rendering pipeline, allowing modification of the rendering data before the material calculation output is passed to the rasterization stage. Visual rendering level configuration information is passed to this stage as input parameters.

[0114] Step 152: The asset visibility control process parses the visual presentation level configuration information and extracts the visual presentation level parameters corresponding to each cabling asset unit. The visual presentation level parameters include the transparency level label and the wireframe density level label.

[0115] After receiving the visual rendering level configuration information, the asset visibility control process iterates through each entry in the configuration information, extracting the asset unit identifier and visual rendering level parameters for each entry. From the visual rendering level parameters, it further parses two integer values: the transparency level label and the wireframe density level label, ready for subsequent rendering attribute modification operations.

[0116] Step 153: For each wired asset unit to be rendered, the asset visibility control link reads its transparency level label and modifies the transparency channel attribute value in the material instance corresponding to the wired asset unit according to the transparency level label, so that the drawing transparency matches the transparency level label.

[0117] In a 3D rendering engine, each wireframe asset unit's 3D model is bound to a material instance during rendering. This material instance contains an opacity channel attribute, with values ​​ranging from zero to one, where zero represents complete opacity and one represents complete transparency. The asset visibility control process reads the opacity level label from the visual rendering level parameters of each wireframe asset unit to be rendered. Based on a preset mapping table between opacity level labels and opacity attribute values, the opacity level label is converted into the corresponding opacity attribute value. This value is then written into the material instance's opacity channel attribute, replacing the original attribute value. After modification, the wireframe asset unit will be drawn according to the new opacity attribute value in subsequent rendering.

[0118] Step 154: For each wireframe asset unit to be rendered, the asset visibility control link reads its wireframe density level label and modifies the geometric drawing mode corresponding to the wireframe asset unit according to the wireframe density level label so that the wireframe drawing density matches the wireframe density level label.

[0119] In a 3D rendering engine, the 3D model of a wireframe asset unit can be switched from solid surface rendering mode to wireframe rendering mode, and the subdivision density of the wireframe can be controlled through tessellation level parameters. The asset visibility control process reads the wireframe density level label from the visual rendering level parameters for each wireframe asset unit to be rendered. Based on a preset mapping table between wireframe density level labels and tessellation level parameters, the wireframe density level label is converted into the corresponding tessellation level parameter value. This value is then written to the tessellation level control field of the geometry rendering mode corresponding to that wireframe asset unit, causing the rendering pipeline to use a wireframe of the specified density when rendering that asset unit.

[0120] Step 155: Submit the wired asset unit rendering data, which has been modified by the transparency attribute and the geometry drawing mode, to the rasterization stage of the scene rendering pipeline, perform pixel shading, and output to the display buffer.

[0121] After the asset visibility control phase completes the modification of the transparency attributes and geometric rendering modes of all asset units to be rendered, it submits the modified rendering data, along with other unmodified rendering data in the scene, to the next stage of the scene rendering pipeline, namely the rasterization stage. The rasterization stage converts the 3D geometric data into 2D pixel data, and the pixel shading stage calculates the final color value of each pixel and writes the calculation results to the corresponding frame buffer location in the display buffer.

[0122] Step 156: Generate an updated 3D visualization operation and maintenance interface in the display buffer, continuously monitor new operation events of operation and maintenance personnel in the updated 3D visualization operation and maintenance interface, add new operation events to the operation event sequence and trigger a new round of visual presentation level configuration information generation and scene rendering pipeline update to achieve cognitive focus adaptive evolution cycle.

[0123] The frame buffer data in the display buffer is periodically scanned and output to the display device, presenting the updated screen of the 3D visualization operation and maintenance interface. While the screen is updated, the interaction event channel continues to listen, capturing new operations triggered by operation and maintenance personnel on the updated interface. Whenever a new raw interaction command is captured, the system processes it through steps 111 to 115, transforming it into a new operation event and appending it to the end of the existing operation event sequence, causing the sequence to continuously grow. After appending a new operation event, the system returns to step 116 to re-execute the complete process of operation traversal path generation, operation and maintenance intent representation vector extraction, topology node visual salience distribution generation, visual presentation level configuration information generation, and scene rendering pipeline update. This ensures that the cabling asset presentation content in the 3D visualization operation and maintenance interface continuously evolves adaptively as the focus of operation and maintenance personnel shifts.

[0124] As another optional embodiment, after the above step 150 realizes the adaptive evolution of the cabling asset presentation content with the operation and maintenance cognitive focus, the method provided by the embodiment of the present invention further includes steps 210 to 240, which are used to perform closed-loop evaluation and parameter adjustment on the response sensitivity of the adaptive evolution process, so as to optimize the dynamic adaptation relationship between the evolution rate and the cognitive focus migration speed.

[0125] Step 210: Obtain the continuous multi-frame rendering images output by the scene rendering pipeline, perform inter-frame difference analysis on the continuous multi-frame rendering images, and generate visual evolution fluctuation features by comparing the change range of the drawing transparency attribute and the change range of the drawing wireframe density attribute of the wiring asset unit in adjacent frames.

[0126] During continuous operation, the scene rendering pipeline stores the rendering result of each frame in the frame buffer after rendering. The system reads multiple consecutively output rendered frames from the frame buffer. For each pair of adjacent frames, it extracts the rendering transparency and wireframe density attributes of the same wiring asset unit, calculates the absolute value of the difference between the two, and obtains the transparency and wireframe density variation amplitudes of that wiring asset unit. The transparency and wireframe density variation amplitudes of all wiring asset units between adjacent frames are summed to obtain the overall transparency and wireframe density variation of that adjacent frame pair. The overall transparency and wireframe density variation amplitudes are combined into a two-dimensional vector as the visual evolution fluctuation component of that adjacent frame pair. The visual evolution fluctuation components of all adjacent frame pairs are arranged in frame order to form a visual evolution fluctuation feature sequence.

[0127] Step 220: The visual evolutionary fluctuation features are temporally aligned with the topological node access sequence of the operational walk path, and the cooperative deviation pattern between the change trend curve of the visual evolutionary fluctuation features and the node switching rhythm of the topological node access sequence is extracted along the temporal dimension.

[0128] Obtain the frame timestamps corresponding to each component in the visual evolutionary fluctuation feature sequence, and the operation occurrence times corresponding to each node in the topology node access sequence of the operation walk path. Using the operation occurrence time as the time anchor, perform nearest neighbor matching between the frame timestamps in the visual evolutionary fluctuation feature sequence and the operation occurrence times in the topology node access sequence, so that the visual evolutionary fluctuation feature of each frame is associated with its temporally closest topology node access event. After completing the temporal alignment, extract the trend curves of the overall transparency change and the overall wireframe density change in the visual evolutionary fluctuation feature over time, and simultaneously extract the rhythm curve of the node identifier change over time in the topology node access sequence. Compare the phase difference and amplitude difference of the two curves in the same time interval, calculate the offset of the extreme points of the trend curve and the extreme points of the node switching curve on the time axis, and use the statistical distribution of the above offsets as the cooperative bias pattern.

[0129] Step 230: Identify response hysteresis segments of the adaptive evolution of content presentation of wiring assets from the collaborative deviation pattern, and generate cognitive focus following sensitivity assessment parameters based on the distribution density of response hysteresis segments on the time axis.

[0130] In the cooperative bias model, if the extreme point of the trend curve of visual evolution fluctuation characteristics has a continuous positive offset on the time axis compared to the extreme point of the node switching curve of the topological node access sequence, i.e., the visual presentation change lags behind the operational focus switching, then the continuous frame sequence within this time interval is marked as a response lag segment. The ratio of the total duration of all marked response lag segments to the total observation duration is calculated as the response lag duration percentage. Simultaneously, the frequency of occurrence of response lag segments on the time axis is calculated, i.e., the number of response lag segments per unit time. The weighted sum of the response lag duration percentage and the frequency of occurrence yields a cognitive focus following sensitivity evaluation parameter. A larger value of this parameter indicates a more severe system response lag and a lower cognitive focus following sensitivity.

[0131] Step 240: Feedback the cognitive focus following sensitivity assessment parameter to the attenuation factor adjustment link of the intention diffusion processing. When the cognitive focus following sensitivity assessment parameter indicates that the following lag exceeds the preset sensitivity threshold range, generate an attenuation factor correction instruction to adjust the attenuation rate of the diffusion intensity value in the intention diffusion processing, so that the spatial propagation range of intention diffusion is dynamically adapted to the cognitive focus migration speed of the operation and maintenance personnel.

[0132] The preset sensitivity threshold range includes an upper threshold and a lower threshold. The cognitive focus following sensitivity evaluation parameter generated in step 230 is compared with the preset sensitivity threshold range. If the cognitive focus following sensitivity evaluation parameter is higher than the upper threshold, it indicates that the current system response is too sluggish, meaning the propagation speed of intent diffusion is too slow. An attenuation factor correction instruction is generated to increase the value of the preset attenuation factor, slowing down the attenuation rate of the diffusion intensity value as it propagates along the topological edge, expanding the diffusion space range, and thus accelerating the update speed of the visual salience distribution. If the cognitive focus following sensitivity evaluation parameter is lower than the lower threshold, it indicates that the current system response is too sensitive, and visual presentation changes too frequently. An attenuation factor correction instruction is generated to decrease the value of the preset attenuation factor, accelerating the attenuation rate of the diffusion intensity value, shrinking the diffusion space range, and thus slowing down the update speed of the visual salience distribution. If the cognitive focus following sensitivity evaluation parameter is within the preset sensitivity threshold range, no correction instruction is generated, and the current attenuation factor remains unchanged. The corrected attenuation factor is written into the configuration parameters for intent diffusion processing and takes effect in the diffusion intensity value attenuation calculation in subsequent step 134, thereby achieving dynamic adaptation between the spatial propagation range of intent diffusion and the cognitive focus migration speed of maintenance personnel.

[0133] As another optional embodiment, after the above step 150 realizes the adaptive evolution of the cabling asset presentation content with the focus of operation and maintenance cognition, the method provided by the embodiment of the present invention further includes steps 310 to 340, for identifying cognitive blind spots that operation and maintenance personnel have not paid attention to for a long time, and performing visual compensation for the blind spots to ensure that the cabling asset units in the blind spots maintain the minimum recognizability in the interface.

[0134] Step 310: Obtain the visual prominence distribution of cabling asset units within the visible range of the operation and maintenance field of view in the 3D visualization operation and maintenance interface under different visual presentation level parameters, and generate a historical attention heat distribution pattern by combining the topology node access sequence of the operation traversal path.

[0135] For each cabling asset unit within the visible range of the 3D visualization operation and maintenance interface, the transparency level label and wireframe density level label are extracted from its corresponding visual presentation level parameters. Based on the preset mapping relationship between visual presentation level parameters and visual prominence values, the visual presentation level parameters are converted into the current visual prominence value of the cabling asset unit. Simultaneously, the total number of times each topology node is accessed is counted from the topology node access sequence of the operation traversal path, serving as the original access frequency for the cabling asset unit corresponding to that topology node. The current visual prominence value of each cabling asset unit is weighted and fused with the original access frequency. The fusion weight is controlled by a preset access frequency confidence coefficient, and the fusion result serves as the historical attention heat value for that cabling asset unit. The historical attention heat values ​​of all cabling asset units within the visible range are organized according to their topological location to form a historical attention heat distribution pattern.

[0136] Step 320: Perform topological constraint correlation analysis on the historical attention distribution pattern and the topology of the building cabling link topology. Use the connection relationship between topology nodes as a constraint condition to perform topological structure regularization on the historical attention distribution pattern and generate attention transmission distribution under topological structure constraints.

[0137] The historical attention distribution value of each cabling asset unit in the historical attention distribution pattern is mapped back to its corresponding topology node, forming an initial attention distribution at the topology node level. The initial attention distribution is smoothed using the topology edge connections of the building cabling link topology as constraints. Specifically, for each topology node, its initial attention value is weighted and averaged with the initial attention values ​​of all its neighboring nodes. The weighting coefficients are related to the edge weights between topology nodes, resulting in the normalized attention value of that topology node. This normalization process can be iterated multiple times until the change in the normalized attention value of each topology node is lower than a preset convergence threshold. After topology normalization, the difference in attention values ​​between adjacent topology nodes is reduced, and the attention distribution better conforms to the topology connectivity constraints, forming an attention transmission distribution under topology constraints.

[0138] Step 330: Extract topological connected regions with attention values ​​lower than the preset threshold for determining cold areas of attention from the attention heat conduction distribution under topological constraints, and identify the topological connected regions as blind spots of operation and maintenance cognition.

[0139] A preset threshold for identifying "cold areas" is used to distinguish between areas with normal and low levels of interest. The normalized interest value of each topology node in the interest distribution under topology constraints is compared with the threshold, and topology nodes with normalized interest values ​​below the threshold are marked. In the building cabling link topology, connected regions formed by adjacent marked nodes are extracted; each connected region is a topology connected subgraph. All extracted topology connected regions are identified as blind spots in operation and maintenance awareness.

[0140] Step 340: Using the blind spot of operation and maintenance cognition as a constraint, the visual presentation level configuration information is visually compensated and adjusted. When the visual presentation level parameter of the corresponding cabling asset unit in the visual presentation level configuration information falls into the preset ignored presentation level range, the visual presentation level parameter is offset and adjusted to the preset benchmark presentation level so that the cabling asset unit corresponding to the blind spot of operation and maintenance cognition maintains the minimum recognizable visual presentation intensity in the three-dimensional visualization operation and maintenance interface.

[0141] For each topology node included in the maintenance and operation blind spot identified in step 330, obtain the asset unit identifier of its corresponding cabling asset unit. Search for the visual presentation level parameter corresponding to this asset unit identifier in the visual presentation level configuration information. Read the transparency level label and wireframe density level label in this visual presentation level parameter, and determine whether both fall within the preset ignore presentation level range. The preset ignore presentation level range refers to the range where the transparency level label of the visual presentation level parameter is higher than a certain high transparency threshold and the wireframe density level label is lower than a certain low wireframe density threshold. This parameter combination indicates that the cabling asset unit has extremely low presentation intensity under the current configuration, making it almost indistinguishable. If the visual presentation level parameter falls within this range, replace the entire visual presentation level parameter with the preset baseline presentation level parameter. Set the transparency level label of the baseline presentation level parameter to the preset medium transparency label and the wireframe density level label to the preset medium wireframe density label, so that the cabling asset unit is restored to the lowest identifiable visual presentation intensity in the image, avoiding the inability of maintenance personnel to perceive the existence of the asset unit due to complete weakening. After completing the visual compensation adjustment, the adjusted visual rendering level configuration information is input into the scene rendering pipeline asset visibility control step in step 151 to execute the screen update rendering.

[0142] Please refer to the foregoing content. Figure 2 It provides a schematic diagram of the interface of the intelligent building cabling operation and maintenance platform, by Figure 2 As can be seen, the interface adopts a three-column layout, integrating three major functional modules: real-time intent analysis, 3D building cabling topology view, and operation trajectory and rendering parameter linkage. It fully presents the entire process of operation effect of this embodiment of the invention, from operation behavior capture and intent parsing to visual presentation adaptive adjustment. The left side is the real-time intent analysis module. The upper branch selection tendency card identifies the East Zone - Power Well as the current area of ​​interest, marks the tendency direction and identifies the continuous segment as the main cable, and the corresponding branch selection tendency feature extraction and direction continuity analysis results are shown. The lower dwell time feature card records that the dwell time of switch A-03 is 15.8s, which is marked as an abnormal focus node and exceeds the average by 3.2 times. The output combination vector is [0.82, 0.91, 0.76], which corresponds to the dwell duration feature encoding and the splicing generation of the operation and maintenance intent representation vector. The status bar at the bottom of the module prompts "Operation and maintenance intent representation vector has been associated with topology", indicating that the representation intent data has been bound to the building cabling link topology.

[0143] The central section features a 3D building cabling topology view, showcasing various cabling asset units with differentiated levels of prominence: the core switch (SW-Core-01) is in a high-prominence state, backbone cables-03 and 07, distribution frames-B12 and B08, and fiber optic terminal boxes are in a medium-prominence state, while non-focus assets such as wall sockets C07, horizontal cable areas, information panels D12, and redundant ports are in a low-prominence, noise-reduced state. The bottom of the view displays a hierarchical legend of high, medium, and low prominence (noise reduction), corresponding to the mapping of the topology node visual prominence distribution to cabling asset units. This intuitively demonstrates the adaptive presentation effect of enhancing assets in the cognitive focus area and weakening assets in irrelevant areas. The status bar at the bottom of the view displays "Real-time evolution of visual presentation level · Cognitive focus focused," indicating that the rendering is in a dynamically adaptable state.

[0144] The upper right section is the operation event sequence and traversal path module, which displays the operation and maintenance operation trajectory in ascending order of time. It records the operation nodes in sequence: 10:25:28 power well - cabinet, 10:25:31 switch A-03, 10:25:44 patch panel - B12, and 10:26:02 core switch. The transfer edges between nodes are marked as deep check types, and the current path is summarized as the branch node continuation direction. It corresponds to the process of operation event sequence generation, topology node access sequence construction, and transfer edge sequence extraction, which completely restores the operation and traversal path of the operation and maintenance personnel. The lower right section is the current rendering level parameter module, which displays the rendering configuration of each asset unit in a list format: Core Switch-A01 corresponds to 0% highlight transparency and 100% wireframe density, Patch Panel-B12 corresponds to 40% semi-transparent transparency and 50% wireframe density, Information Outlet-C07 corresponds to 90% weakened transparency and 10% sparse wireframe density, and Redundant Cable-Z3 corresponds to 92% transparency and 8% wireframe density, showing a mapping pattern where the prominence is negatively correlated with transparency and positively correlated with wireframe density; The bottom of the module prompts "Visible configuration has been synchronized. Scene rendering pipeline is updating," which corresponds to the execution process of the visual presentation level parameter input scene rendering pipeline asset visibility control link and adjustment of drawing transparency and wireframe density.

[0145] The overall interface enables real-time linkage between operation and maintenance behavior, intent parsing results, and 3D visual presentation. Operation and maintenance personnel can intuitively perceive the cognitive focus recognition results corresponding to their own operation trajectory, as well as the adaptive evolution effect of the visual presentation of cabling assets, effectively reducing the visual search load in dense cabling scenarios and improving the efficiency of operation and maintenance task execution.

[0146] In the method provided in this embodiment of the invention, the model module involved includes the direction vector angle calculation logic used in step 120 for branch direction continuity analysis. This logic is implemented based on a vector space model, which takes the outgoing direction in the branch selection record as input. The outgoing direction is represented in the form of a three-dimensional unit vector, and the vector components correspond to the three orthogonal coordinate axes in the building cabling link topology space. The model internally uses the vector angle cosine calculation formula to process the angle change between adjacent direction vectors. That is, it calculates the dot product of two unit vectors as the cosine value of the angle, and then obtains the angle value through an inverse cosine transformation. This model has no training step, and its processing logic follows fixed geometric calculation rules. In application, the outgoing direction field of the branch selection record is directly converted into a three-dimensional unit vector, input into the angle calculation logic, and the output is the angle change value expressed in degrees.

[0147] Optionally, another processing step involves calculating the decay of the diffusion intensity value during the intent diffusion processing in step 130. This calculation is based on an exponential decay model. The exponential decay model takes the diffusion intensity value of the current node as input, uses a preset decay factor as the decay rate control parameter, and calculates the diffusion intensity value of the next hop node using a multiplicative decay method. This model is also a deterministic calculation model and does not involve a parameter training process. In application, the diffusion intensity value is read from the diffusion contribution component field of the current node, multiplied by the preset decay factor to obtain the decayed intensity value, and then output and written to the diffusion contribution component field of the next hop node.

[0148] Furthermore, the mapping process from visual salience values ​​to transparency level labels and wireframe density level labels involved in step 140 is implemented using a piecewise linear mapping model. The piecewise linear mapping model takes the visual salience value as input and a set of preset segmented interval endpoint values ​​and corresponding level label mapping values ​​as parameters. The model linearly interpolates the level labels of the interval endpoints into which the input value falls. The segmented interval endpoint values ​​and level label mapping values ​​are preset based on the rendering capabilities of the 3D visualization operation and maintenance interface during system initialization. In application, the visual salience value received by each cabling asset unit is input into this mapping model, and the output is an integer transparency level label and an integer wireframe density level label, which are used for subsequent modifications to the transparency attributes and geometric drawing modes of the rendering pipeline, respectively.

[0149] It is understandable that the cognitive focus following sensitivity assessment parameter feedback adjustment process involved in step 240 uses a proportional-integral (PI) controller as the attenuation factor correction command generation model. The input of the PPI controller is the deviation signal between the cognitive focus following sensitivity assessment parameter and the upper and lower limits of the preset sensitivity threshold range, and the output is the attenuation factor correction amount. The proportional coefficient and integral coefficient of the PPI controller are calibrated through simulation during system initialization. In application, the cognitive focus following sensitivity assessment parameter is compared with the upper and lower limits of the preset sensitivity threshold range to calculate the deviation signal. After the deviation signal is processed by the PPI controller, an attenuation factor correction command is generated. The correction command is incrementally superimposed on the current preset attenuation factor to obtain the updated preset attenuation factor value, which is used for subsequent diffusion intensity value attenuation calculation.

[0150] It is understandable that the process of generating the attention distribution under topological constraints involved in step 320 uses a graph Laplace smoothing model to normalize the initial attention distribution. The graph Laplace smoothing model takes the adjacency matrix of the building cabling link topology and the initial attention distribution vector as input, and uses the graph Laplace matrix as a smoothing operator. It achieves the smooth propagation of attention values ​​between topology nodes by iteratively solving a system of linear equations. This model is a fixed computational model with no training step. In application, the adjacency matrix of the building cabling link topology is constructed and the graph Laplace matrix is ​​calculated. The historical attention distribution pattern is mapped to the initial attention distribution vector, and then the smoothing update equation is iteratively executed until convergence, outputting the normalized attention distribution vector.

[0151] In summary, the above method acquires the sequence of operation events performed by maintenance personnel in the 3D visualized maintenance interface and generates operation traversal paths, quantifying the implicit cognitive behavior patterns of maintenance personnel into computable operation trajectory data, thus providing structured data for intent perception. By analyzing the path behavior of the operation traversal paths, branch selection tendency features and dwell duration features are extracted and combined into a maintenance intent representation vector, achieving a two-dimensional quantitative expression of the maintenance personnel's cognitive focus and spatial exploration tendency, overcoming the deficiency of traditional methods in being unable to perceive the subjective intent of maintenance personnel. By associating the maintenance intent representation vector with the building cabling link topology, performing intent diffusion processing along the topology edges and dwell reinforcement processing on the topology nodes, a topology is generated. The visually prominent distribution of nodes allows the impact of a single operation to propagate along the topology to adjacent nodes, while historical attention information is accumulated and retained, enabling estimation of the spatial range and intensity measurement of the cognitive focus of operations and maintenance personnel. By mapping the visually prominent distribution of topology nodes to cabling asset units in the 3D visualization operations and maintenance interface, visual presentation level parameters are generated. These parameters are then input into the asset visibility control of the scene rendering pipeline to adjust the rendering transparency and wireframe density of the corresponding cabling asset units. Overall, this achieves the adaptive evolution of the cabling asset presentation content in the 3D visualization operations and maintenance interface according to the cognitive focus of operations and maintenance, avoiding the problem of low visual search efficiency caused by the homogeneous presentation of asset units in traditional 3D interfaces.

[0152] This invention also provides a data visualization system: a processor; a storage device storing a computer program thereon; and a network interface for providing network communication functions; when the computer program is executed by the processor, the processor implements any of the data visualization methods described above for intelligent building cabling.

[0153] Based on the above, a readable storage medium is provided, on which a program or instructions are stored, and when the program or instructions are executed by a processor, the steps of the above method are implemented.

[0154] Furthermore, it should be noted that this embodiment of the invention also provides a computer program product, which may include a computer program that can be stored in a computer-readable storage medium. The processor of the data visualization system reads the computer program from the computer-readable storage medium, and the processor can execute the computer program, causing the data visualization system to perform the aforementioned... Figure 1 The methods described in the corresponding embodiments are already known, and therefore will not be repeated here. Furthermore, the beneficial effects of using the same method will also not be repeated. For technical details not disclosed in the computer program product embodiments related to this invention, please refer to the description of the method embodiments of this invention.

[0155] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems or apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and relevant parts can be referred to the method section.

Claims

1. A data visualization method for intelligent building cabling, characterized in that, include: The system acquires the sequence of operation events triggered by maintenance personnel in the 3D visualization maintenance interface. Based on the object identifier of each operation event, it locates the corresponding topology node in the building cabling link topology, arranges the topology nodes according to the operation time to generate the topology node access sequence, and records the transfer edge sequence of adjacent topology nodes to generate the operation traversal path. The operation traversal path is analyzed to extract branch selection tendency features and dwell duration features, and combined into an operation and maintenance intention representation vector. The operation and maintenance intent representation vector is associated with the topology nodes in the building cabling link topology. Intent diffusion processing is performed along the topology edges and dwelling enhancement processing is performed on the topology nodes to generate a visually prominent distribution of topology nodes. The topology nodes are visually highlighted and distributed and mapped to the cabling asset units in the three-dimensional visualization operation and maintenance interface to generate visual presentation level parameters for each cabling asset unit and obtain visual presentation level configuration information. The visual presentation level configuration information is input into the asset visibility control stage of the scene rendering pipeline. The drawing transparency and drawing wireframe density of the corresponding wiring asset unit are adjusted according to the visual presentation level parameters to achieve adaptive evolution of the wiring asset presentation content according to the operational and maintenance focus.

2. The method according to claim 1, characterized in that, The process involves acquiring the sequence of operation events triggered by maintenance personnel in the 3D visualization maintenance interface, locating the corresponding topology node in the building cabling link topology based on the object identifier of each operation event, arranging the topology nodes by operation time to generate a topology node access sequence, and recording the transition edge sequence of adjacent topology nodes to generate an operation traversal path, including: Monitor the interactive event channel in the 3D visualization operation and maintenance interface, intercept the original interactive commands triggered by the operation and maintenance personnel through the input device, and arrange the intercepted original interactive commands in ascending order according to the trigger time into an original interactive command queue; Each original interaction instruction in the original interaction instruction queue is parsed for instruction type, the operation type label corresponding to the original interaction instruction is identified, and the operation type label is associated with the original interaction instruction. For each original interaction instruction in the original interaction instruction queue, the target of the original interaction instruction is parsed, the target identifier of the building wiring asset object pointed to by the original interaction instruction is extracted, and the target identifier is associated with the original interaction instruction. Extract the trigger time of each original interaction command as the operation occurrence time, associate the operation occurrence time with the original interaction command, and generate an operation event that carries an operation type label, an object identifier, and the operation occurrence time. The operation events are arranged in ascending order according to the time of occurrence to generate the operation event sequence; Read the pre-built building cabling link topology, obtain the set of topology nodes contained in the building cabling link topology, and each topology node in the set of topology nodes corresponds to a building cabling asset object and carries a node identifier; Traverse each operation event in the operation event sequence, match the target identifier carried by the operation event with the node identifier of the topology node in the topology node set, and determine the topology node corresponding to the operation event. According to the order of the operation events in the operation event sequence, the matched topology nodes are arranged sequentially to obtain the topology node access sequence; The adjacent topological nodes in the topological node access sequence are checked sequentially. If the node identifiers of the adjacent topological nodes are different, a transfer edge is generated from the earlier topological node to the later topological node. All the generated transfer edges are combined into a transfer edge sequence according to the checking order. The topology node access sequence is merged with the transfer edge sequence to generate an operation traversal path describing the operation traversal path of the operation and maintenance personnel.

3. The method according to claim 1, characterized in that, The process of parsing the operation traversal path, extracting branch selection tendency features and dwell duration features, and combining them into an operation and maintenance intent representation vector includes: Obtain the number of adjacent edges of each topology node in the building cabling link topology, mark the topology nodes with the number of adjacent edges exceeding the preset connection edge threshold as branch nodes, and construct a set of branch nodes; Traverse the sequence of transition edges of the operation's traversal path, and determine whether the starting topological node of each transition edge belongs to the set of branch nodes. If it does, record the transition edge as a branch selection transition edge. Extract the starting topology node identifier and outgoing edge direction of each branch selection transition edge, and generate a branch selection record containing the starting topology node identifier and outgoing edge direction; The branch selection records are arranged in chronological order according to the operation path to form a branch selection record sequence. The branch selection record sequence is analyzed for directional continuity. Segments in consecutive branch selection records with consistent outgoing edge directions are identified as continuous segments, and segments with changing outgoing edge directions are identified as turning segments. Based on the distribution of the continuation segments and the turning segments in the branch selection record sequence, a branch selection tendency feature is generated to describe the degree of preference of maintenance personnel for the continuation direction at the topology branch node; Obtain the operation occurrence time of the operation event corresponding to each topological node in the topological node access sequence in the operation traversal path, calculate the time difference of the operation occurrence time of adjacent topological nodes as the dwell duration of the subsequent topological node, and generate a dwell duration sequence. Bind the topology node identifier in the topology node access sequence to the corresponding residence duration in the residence duration sequence to obtain a node residence record set. The dwell duration of each topological node in the node dwell record set is encoded with a dwell duration feature to generate a dwell duration feature that characterizes the degree of operation focus on the topological node. The branch selection tendency feature and the dwell duration feature are concatenated into feature vectors to generate an operation and maintenance intention representation vector. One dimension of the operation and maintenance intention representation vector corresponds to the branch selection tendency feature, and the other dimension corresponds to the dwell duration feature.

4. The method according to claim 3, characterized in that, The step of performing directional continuity analysis on the branch selection record sequence, identifying segments in consecutive branch selection records where the outgoing edge direction remains consistent as continuous segments, and identifying segments where the outgoing edge direction changes as turning segments, includes: Convert the outgoing directions of adjacent branch selection records in the branch selection record sequence into direction vectors, and calculate the change in the angle between adjacent direction vectors; If the change in the included angle is within the preset direction continuity tolerance range, then the adjacent branch selection records will be grouped into the same continuity segment, and the outgoing direction of the next branch selection record will be taken as the continuity direction of the continuity segment. If the change in the included angle exceeds the preset direction continuation tolerance range, the current continuation segment ends at the previous branch selection record point, and a new continuation segment begins at the next branch selection record point. At the same time, the direction change method from the end continuation direction to the new continuation direction is recorded. The recorded direction change methods are divided into leftward deflection, rightward deflection, or reverse reversal, which are used as the transition types of transition segments.

5. The method according to claim 1, characterized in that, The step of associating the operation and maintenance intent representation vector with the topology nodes in the building cabling link topology, performing intent diffusion processing along the topology edges and dwell enhancement processing on the topology nodes to generate a visually prominent distribution of topology nodes includes: The operation and maintenance intention representation vector is analyzed to separate the branch selection tendency feature vector and the dwell duration feature vector. Extract the outgoing edge direction of the maintenance personnel at each branch node from the branch selection tendency feature vector, and combine the outgoing edge direction to determine the intention diffusion direction in the building cabling link topology; The last topological node visited in the operation traversal path is taken as the diffusion start node, and an initial diffusion intensity value is assigned to the diffusion start node. Starting from the diffusion initiation node, the topological edges of the building cabling link topology are traversed along the intended diffusion direction. The diffusion intensity value is gradually attenuated along the traversal path, and the attenuated diffusion intensity value is assigned to the topological nodes traversed until the diffusion intensity value is lower than the preset cutoff limit, thus terminating the diffusion and obtaining the diffusion contribution component of each topological node. Extract the dwell duration code corresponding to each topological node from the dwell duration feature vector, and generate a dwell enhancement increment based on the dwell duration code. The higher the focus duration indicated by the dwell duration code, the larger the dwell enhancement increment. The residency enhancement increment of each topological node is superimposed on the diffusion contribution component of that topological node to obtain the overall salience component of that topological node. For topology nodes in the building cabling link topology that do not receive a diffusion contribution component and do not receive a residency enhancement increment, a basic salience component is assigned. The overall salience component of each topological node is fused with its basic salience component to generate the visual salience value of that topological node. Collect the visual salience values ​​of all topology nodes in the building cabling link topology to generate the visual salience distribution of topology nodes.

6. The method according to claim 5, characterized in that, Starting from the diffusion initiation node, the topological edges of the building cabling link topology are traversed along the intended diffusion direction. The diffusion intensity value is gradually attenuated along the traversal path, and the attenuated diffusion intensity value is assigned to the topological nodes traversed until the diffusion intensity value is lower than a preset cutoff threshold, at which point the diffusion terminates. This yields the diffusion contribution component of each topological node, including: The diffusion initiation node is set as the current node, the initial diffusion intensity value is assigned to the current node as its diffusion contribution component, and the current node is marked as visited. Query the outgoing edges of the current node in the direction of the intention propagation. If an outgoing edge exists and the neighbor node pointed to by the outgoing edge is not marked as visited, then the neighbor node is taken as the next hop node. Multiply the diffusion intensity value of the current node by a preset attenuation factor to obtain the attenuated diffusion intensity value, and assign the attenuated diffusion intensity value to the next hop node as its diffusion contribution component. If the attenuated diffusion intensity value is lower than the preset cutoff limit, diffusion along that path will be terminated. The next hop node is used as the new current node, and the decay diffusion process is repeated until all reachable paths have been traversed or the diffusion intensity value is lower than the preset cutoff limit.

7. The method according to claim 1, characterized in that, The process involves mapping the visually prominent distribution of the topology nodes to cabling asset units in the 3D visualization operation and maintenance interface, generating visual presentation level parameters for each cabling asset unit, and obtaining visual presentation level configuration information, including: Analyze the visual salience distribution of the topology nodes and extract the visual salience value corresponding to each topology node; Retrieve the mapping table of correspondence between each topology node in the building cabling link topology and the cabling asset unit in the 3D visualization operation and maintenance interface, and transmit the visual prominence value of the topology node to the corresponding cabling asset unit according to the mapping table, and determine the received visual prominence value for each cabling asset unit. The visual prominence value received by each cabling asset unit is divided into segments, and the visual prominence value is mapped to a transparency level label according to the preset mapping rules between prominence value segments and transparency levels. The visual prominence value received by each cabling asset unit is divided into segments, and the visual prominence value is mapped to a wireframe density level label according to the preset mapping rule between the prominence value segments and the wireframe density level. The transparency level label of the same cabling asset unit is combined with the wireframe density level label to generate the visual presentation level parameter of that cabling asset unit. Traverse all cabling asset units in the three-dimensional visualization operation and maintenance interface, obtain the visual presentation level parameters corresponding to each cabling asset unit, and associate and store the asset unit identifier of the cabling asset unit with the visual presentation level parameters; The asset unit identifier and corresponding visual presentation level parameters of the cabling asset units within the current operational and maintenance field of view are combined into a subset of the visible visual presentation level configuration, and the asset unit identifier and corresponding visual presentation level parameters of the cabling asset units within the current operational and maintenance field of view are combined into a subset of the invisible visual presentation level configuration. The visual presentation level configuration subsets of the visible portion and the invisible portion are merged to obtain visual presentation level configuration information.

8. The method according to claim 7, characterized in that, The step of retrieving the mapping table between each topology node in the building cabling link topology and the cabling asset unit in the 3D visualization operation and maintenance interface, and transmitting the visual prominence value of the topology node to the corresponding cabling asset unit according to the mapping table, includes: Traverse all topology nodes in the building cabling link topology and obtain the node identifier of each topology node; Query the scene asset registry in the 3D visualization operation and maintenance interface. The scene asset registry stores the asset unit identifier of each cabling asset unit in the scene and the corresponding building cabling asset object identifier. The node identifier of the topology node is compared with the building cabling asset object identifier in the scene asset registry. If they match, a mapping relationship is established from the topology node to the corresponding asset unit identifier. All established mapping relationships are aggregated to generate a corresponding mapping table. For each mapping relationship in the corresponding mapping table, the visual prominence value corresponding to the topology node identifier is extracted from the topology node visual prominence distribution, and the visual prominence value is assigned to the cabling asset unit pointed to by the mapping relationship.

9. The method according to claim 1, characterized in that, The step of inputting the visual rendering level configuration information into the asset visibility control stage of the scene rendering pipeline, and adjusting the drawing transparency and drawing wireframe density of the corresponding wiring asset unit according to the visual rendering level parameters, to achieve adaptive evolution of the wiring asset presentation content according to the operational and maintenance focus, includes: The visual rendering level configuration information is transmitted to the asset visibility control stage in the scene rendering pipeline. The asset visibility control stage is located after the material calculation stage and before the rasterization stage of the scene rendering pipeline. The visual presentation level configuration information is parsed by the asset visibility control link, and the visual presentation level parameters corresponding to each wiring asset unit are extracted. The visual presentation level parameters include transparency level labels and wireframe density level labels. For each wired asset unit to be rendered, the asset visibility control link reads its transparency level label and modifies the transparency channel attribute value in the material instance corresponding to the wired asset unit according to the transparency level label, so that the drawing transparency matches the transparency level label. For each wireframe asset unit to be rendered, the asset visibility control link reads its wireframe density level label and modifies the geometric drawing mode corresponding to the wireframe asset unit according to the wireframe density level label so that the wireframe drawing density matches the wireframe density level label. The rendering data of the wired asset unit, after modification of transparency attribute and geometric drawing mode, is submitted to the rasterization stage of the scene rendering pipeline, where pixel shading is performed and output to the display buffer. An updated 3D visualization operation and maintenance interface is generated in the display buffer. New operation events of operation and maintenance personnel in the updated 3D visualization operation and maintenance interface are continuously monitored. The new operation events are added to the operation event sequence and a new round of visual presentation level configuration information generation and scene rendering pipeline update is triggered to achieve cognitive focus adaptive evolution cycle.

10. A data visualization system, characterized in that, include: A processor; a storage device having a computer program stored thereon; a network interface for providing network communication functions; when the computer program is executed by the processor, the processor enables the processor to implement the data visualization method for intelligent building cabling as described in any one of claims 1-9.

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