Method and system for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm

Abstract

The present invention relates to the field of optical fiber cabling technology, and discloses a method and system for implementing efficient optical fiber cabling planning based on an intelligent path planning algorithm, comprising: constructing a spatial topology model corresponding to a cabling area; gridding the spatial topology model to obtain a spatial topology grid, and calculating the optical fiber installation cost between a starting installation node and a subsequent installation node; planning an optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, and adapting and modeling the optical fiber in the optical fiber installation route to the spatial topology model to obtain an optical fiber adaptation virtual model; evaluating the optical fiber interference between the optical fibers in the optical fiber adaptation virtual model, calculating the route complexity corresponding to the optical fiber installation route, and calculating the environmental coupling degree corresponding to the optical fiber in the optical fiber installation route; and performing route optimization processing on the optical fiber installation route to obtain an optimized installation route for the optical fiber in the area to be installed. The present invention primarily aims to solve the problem of low optical fiber cabling efficiency.

Description

Technical Field

[0001] The present invention relates to a method and system for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, and belongs to the technical field of optical fiber wiring. Background Art

[0002] Fiber optic cabling plays a vital role in modern communications and data transmission. With the rapid development of information technology, the demand for efficient and accurate fiber optic cabling is increasing.

[0003] Existing fiber optic cabling planning primarily relies on manual experience and simple rules. After determining the starting and ending points of the cabling, engineers rely on their experience to select possible paths, taking into account factors such as minimizing cabling length and avoiding collisions with obstacles. However, this approach has many limitations. First, manual planning relies on experience, and the plans of different engineers may vary greatly, lacking consistency and optimality. Second, for complex building structures or large-scale cabling scenarios, manual planning cannot fully consider various factors, such as space limitations, electromagnetic interference, and future expansion needs. Moreover, during the actual cabling process, unexpected situations may arise, resulting in the need for frequent plan adjustments, which in turn reduces the efficiency of fiber optic cabling. Summary of the Invention

[0004] The present invention provides a method and system for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, the main purpose of which is to solve the problem of low optical fiber wiring efficiency.

[0005] To achieve the above objectives, the present invention provides a method for implementing efficient optical fiber cabling planning based on an intelligent path planning algorithm, comprising:

[0006] Obtaining an area to be installed for optical fibers and its corresponding regional wiring requirements, locating a wiring area in the area to be installed based on the regional wiring requirements, collecting regional building information and regional spatial data corresponding to the wiring area, and constructing a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information;

[0007] Gridding the spatial topology model to obtain a spatial topology grid, identifying grid nodes in the spatial topology grid and their corresponding node metadata, the grid nodes including: a starting installation node and a subsequent installation node; and calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata;

[0008] In combination with the optical fiber installation cost and the preset installation expenditure, a preset intelligent path planning algorithm is used to plan an optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, optical fiber installation equipment and installation optical fiber information in the optical fiber installation route are queried, and in combination with the optical fiber installation equipment and the installation optical fiber information, optical fibers in the optical fiber installation route are adaptively modeled with the spatial topology model to obtain an optical fiber adaptation virtual model;

[0009] Evaluating the fiber interference between optical fibers in the optical fiber adaptation virtual model, drawing an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculating the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collecting corresponding node environmental attributes corresponding to the grid nodes, and calculating the environmental coupling degree corresponding to the optical fibers in the optical fiber installation line based on the node environmental attributes;

[0010] The optical fiber installation line is optimized based on the optical fiber interference, the line complexity and the environmental coupling degree to obtain an optimized installation line of the optical fiber in the area to be installed.

[0011] Optionally, locating the wiring area in the area to be installed according to the area wiring requirement includes:

[0012] Performing text recognition on the wiring requirements of the area to obtain a wiring requirement text;

[0013] Analyzing the semantics of the requirement text corresponding to the wiring requirement text, and performing requirement classification processing on the wiring requirement text based on the semantics of the requirement text to obtain a requirement category;

[0014] Extracting key requirement information from the wiring requirement text based on the requirement category;

[0015] Based on the key requirement information, a wiring area in the area to be installed is located.

[0016] Optionally, combining the regional spatial data and the regional building information to construct a spatial topology model corresponding to the wiring area includes:

[0017] Calculating a spatial distance value between each data in the regional spatial data, and calculating a distance variance between each data in the regional spatial data based on the spatial distance value;

[0018] Combining the distance variance and the spatial distance value, removing discrete data in the regional spatial data to obtain target spatial data;

[0019] Identifying building entity elements in the regional building information, marking data corresponding to the building entity elements in the target spatial data, and obtaining physical spatial data;

[0020] Analyzing the positional relationship between the entity spatial data, and determining the element topological relationship between the building entity elements based on the positional relationship;

[0021] The spatial topology model corresponding to the wiring area is constructed by combining the physical space data and the element topological relationship.

[0022] Optionally, the calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata includes:

[0023] Analyzing the spatial geometric features corresponding to the subsequent installation node, and extracting geometric metadata corresponding to the spatial geometric features from the node metadata;

[0024] Calculating the installation complexity corresponding to the subsequent installation node by combining the geometric metadata and the spatial geometric features;

[0025] Identifying node obstacles between the initial installation node and the subsequent installation node, and calculating the optical fiber wiring length between the initial installation node and the subsequent installation node;

[0026] The optical fiber installation cost between the initial installation node and the subsequent installation node is calculated based on the node obstacles, the installation complexity, and the optical fiber wiring length.

[0027] Optionally, the combining the geometric metadata and the spatial geometric features to calculate the installation complexity corresponding to the subsequent installation node includes:

[0028] Determining, based on the geometric metadata, a feature metric value corresponding to the spatial geometric feature;

[0029] Querying a standard metric value corresponding to the spatial geometric feature, and calculating a complex contribution corresponding to the spatial geometric feature by combining the feature metric value and the standard metric value;

[0030] The geometric weight corresponding to the spatial geometric feature is calculated, and the installation complexity corresponding to the subsequent installation node is calculated by combining the geometric weight and the complexity contribution using the following formula:

[0031]

[0032] Among them, A represents the installation complexity corresponding to the subsequent installation node, B arepresents the geometric weight corresponding to the ath feature in the spatial geometric feature, a represents the feature sequence number corresponding to the spatial geometric feature, q represents the number of features of the spatial geometric feature, D a Indicates the complex contribution corresponding to the ath feature in the spatial geometric features.

[0033] Optionally, the combining the optical fiber installation cost and the preset installation expenditure and planning the optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid using a preset intelligent path planning algorithm includes:

[0034] Identifying an installation backup node corresponding to the successor installation node, and evaluating a node priority corresponding to the successor installation node based on the installation backup node;

[0035] In combination with the node priorities, a preset intelligent path planning algorithm is used to perform path planning for the starting installation node and the subsequent installation nodes in the spatial topology grid to obtain a node planning path;

[0036] Calculating a planned path cost corresponding to the node planned path according to the optical fiber installation cost;

[0037] In combination with the optical fiber installation cost and the preset installation expenditure, the optical fiber installation route between the starting installation node and the subsequent installation node is screened out from the node planning path.

[0038] Optionally, evaluating the optical fiber interference between optical fibers in the optical fiber adaptation virtual model includes:

[0039] Dynamically discretizing the optical fiber model in the optical fiber adaptation virtual model to obtain a discrete optical fiber model;

[0040] Traversing the model discrete points of the discrete optical fiber model to obtain spatial coordinate information corresponding to the model discrete points;

[0041] Calculating the discrete point distances between the discrete points of the model based on the spatial coordinate information;

[0042] The fiber radius corresponding to the discrete fiber model is determined. Combining the fiber radius and the discrete point distance, the relative distance coefficient between optical fibers in the fiber adaptation virtual model can be calculated using the following formula:

[0043]

[0044] Where E represents the relative distance coefficient between optical fibers in the optical fiber adaptation virtual model, L d，d+1 Indicates the discrete point distance between the dth model and the d+1th model in the discrete fiber model, R dIndicates the fiber radius corresponding to the dth model in the discrete fiber model, R d+1 Indicates the fiber radius corresponding to the d+1th model in the discrete fiber model, d and d+1 respectively represent the serial numbers corresponding to the discrete fiber models;

[0045] The fiber interference between the optical fibers in the optical fiber adaptation virtual model is evaluated according to the relative distance coefficient.

[0046] Optionally, the calculating, based on the adaptation model diagram, the line complexity corresponding to the optical fiber installation line includes:

[0047] Performing line extraction processing on the adaptation model graph to obtain a model line, and performing smoothing processing on the model line to obtain a smoothed model line;

[0048] Counting the line crossing frequency in the smooth model line and measuring the line curvature in the smooth model line;

[0049] Combined with the line crossing frequency and the line curvature, the line complexity corresponding to the optical fiber installation line is calculated using the following formula:

[0050]

[0051] Among them, F represents the line complexity corresponding to the optical fiber installation line, G represents the line cross frequency, G0 represents the reference cross frequency, H e represents the line curvature corresponding to the e-th line in the smooth model line, r represents the number of smooth model lines, M0 represents the reference curvature, and I0 represents the cross-curvature correlation factor.

[0052] Optionally, the calculating, based on the node environment attribute, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line includes:

[0053] Analyzing environmental attribute factors corresponding to the node environmental attributes, and identifying optical fiber influencing factors from the environmental attribute factors;

[0054] Based on the optical fiber influencing factors, filtering the node environment attributes to obtain target environment attributes;

[0055] Standardizing the target environment attributes to obtain standard environment attributes;

[0056] According to the standard environmental attributes, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line is calculated using a preset geometric mean method.

[0057] An efficient optical fiber cabling planning system is implemented based on an intelligent path planning algorithm, wherein the system comprises:

[0058] A spatial model construction module is used to obtain the area to be installed of the optical fiber and the corresponding regional wiring requirements, locate the wiring area in the area to be installed according to the regional wiring requirements, collect regional building information and regional spatial data corresponding to the wiring area, and construct a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information;

[0059] An installation cost calculation module is configured to perform gridding processing on the spatial topology model to obtain a spatial topology grid, identify grid nodes in the spatial topology grid and their corresponding node metadata, wherein the grid nodes include: a starting installation node and a subsequent installation node, and calculate the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata;

[0060] a fiber adaptation modeling module for planning a fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid using a preset intelligent path planning algorithm based on the fiber installation cost and the preset installation expenditure, querying information about fiber installation equipment and installed fibers in the fiber installation route, and adapting and modeling the fibers in the fiber installation route to the spatial topology model based on the fiber installation equipment and the installed fibers to obtain a fiber adaptation virtual model;

[0061] an environmental coupling degree calculation module, configured to evaluate the optical fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environmental attributes corresponding to the grid nodes, and calculate the environmental coupling degree corresponding to the optical fibers in the optical fiber installation line based on the node environmental attributes;

[0062] The line optimization module is used to optimize the optical fiber installation line based on the optical fiber interference, the line complexity and the environmental coupling degree to obtain an optimized installation line of the optical fiber in the area to be installed.

[0063] Compared with the problem described in the background technology, the present invention locates the wiring area in the area to be installed according to the wiring requirements of the area, and can clarify the specific range for wiring in the area to be installed, providing an accurate layout space basis for subsequent optical fiber wiring planning, and collecting regional building information and regional spatial data corresponding to the wiring area, and can obtain relevant details of the building structure in the wiring area (such as walls, beams and columns, etc.) and space size, shape, channel and other data, which provides a basis for the subsequent construction of the spatial topology model corresponding to the wiring area. The present invention facilitates the spatial quantification of the spatial topology model by gridding the spatial topology model, and then converts the spatial topology model into a simpler visualization method, identifies the grid nodes in the spatial topology grid and their corresponding node metadata, and provides a basis for the subsequent starting installation node and the subsequent The present invention provides a basis for calculating the cost of optical fiber installation between installation nodes. By combining the optical fiber installation cost and the preset installation expenditure, the present invention uses a preset intelligent path planning algorithm to plan the optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, which can efficiently determine the optimal installation path within the cost control range. By evaluating the optical fiber interference between optical fibers in the optical fiber adaptation virtual model, the present invention can accurately understand the degree of mutual influence between optical fibers, and then analyze the rationality of the optical fiber layout, providing a basis for the subsequent line optimization processing of the optical fiber installation line. The present invention optimizes the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling degree, and then obtains the optimal installation route of the optical fiber in the area to be installed, thereby improving the installation efficiency of the optical fiber. Therefore, the present invention proposes a method and system for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, thereby improving the efficiency of optical fiber wiring planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A flowchart of a method for implementing efficient optical fiber cabling planning based on an intelligent path planning algorithm provided by one embodiment of the present invention;

[0065] Figure 2 A functional module diagram of an embodiment of the present invention for implementing an efficient optical fiber cabling planning system based on an intelligent path planning algorithm.

[0066] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0067] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0068] The embodiments of the present application provide a method for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm. The method can be implemented by at least one of a server, a terminal, or other electronic device capable of executing the method provided by the embodiments of the present application. In other words, the method can be implemented by software or hardware installed on a terminal device or a server device. The server device includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0069] Example 1:

[0070] Reference Figure 1 FIG. 1 is a flow chart of a method for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm according to an embodiment of the present invention. In this embodiment, the method for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm includes:

[0071] S1. Obtain the area to be installed of the optical fiber and its corresponding regional wiring requirements, locate the wiring area in the area to be installed based on the regional wiring requirements, collect regional building information and regional spatial data corresponding to the wiring area, and construct a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information.

[0072] The present invention locates the wiring area in the area to be installed based on the regional wiring requirements, and can clarify the specific scope of wiring in the area to be installed, providing an accurate layout space basis for subsequent optical fiber wiring planning. By collecting regional building information and regional spatial data corresponding to the wiring area, relevant details of the building structure in the wiring area (such as the position of walls, beams and columns, etc.) and data such as space size, shape, and channels can be obtained, providing a basis for the subsequent construction of a spatial topology model corresponding to the wiring area.

[0073] It should be explained that the optical fiber is a communication cable that needs to be installed; the area to be installed is the overall area where the optical fiber is planned to be installed; the regional wiring requirements are the conditions and requirements that the optical fiber should meet for installation in the area to be installed; the wiring area is the specific installation range specifically determined for the optical fiber in the area to be installed; the regional building information is related information such as the building structure corresponding to the wiring area; the regional spatial data is the spatial point cloud data corresponding to the wiring area; further, the collection of regional building information and regional spatial data corresponding to the wiring area can be achieved through collection tools, such as a three-dimensional laser scanner, which can quickly and accurately obtain the three-dimensional coordinate information of the building structure in the wiring area, including the position, shape and size of walls, beams, ceilings and floors, so as to fully present the physical outline of the building.

[0074] Specifically, locating the wiring area in the area to be installed according to the area wiring requirements includes:

[0075] Performing text recognition on the wiring requirements of the area to obtain a wiring requirement text;

[0076] Analyzing the semantics of the requirement text corresponding to the wiring requirement text, and performing requirement classification processing on the wiring requirement text based on the semantics of the requirement text to obtain a requirement category;

[0077] Extracting key requirement information from the wiring requirement text based on the requirement category;

[0078] Based on the key requirement information, a wiring area in the area to be installed is located.

[0079] It should be explained that the wiring requirement text is the specific textual expression of the regional wiring requirement; the requirement text semantics is the meaning expressed by the wiring requirement text; the requirement category is the type of wiring requirement text divided according to different characteristics; the key requirement information is the important information in the wiring requirement text that plays a key role in locating the wiring area, such as key location points.

[0080] Furthermore, text recognition of the regional wiring requirements can be achieved using optical character recognition (OCR) technology; semantic analysis can be used to analyze the semantics of the wiring requirement text corresponding to the wiring requirement text; based on the semantics of the requirement text, the wiring requirement text can be classified using a classification algorithm in machine learning (such as a decision tree, support vector machine, etc.) to obtain a requirement category; based on the requirement category, key requirement information in the wiring requirement text can be extracted using an information extraction algorithm (such as a method based on pattern matching or statistical learning); based on the key requirement information, the wiring area in the area to be installed is located. Assuming that the key locations in the key requirement information are the communication room A and various information points in the office area of ​​the building, and the constraints are that the wiring cannot pass through the high-temperature pipeline area and must be arranged along the wall as much as possible, the locations of the communication room A and various information points are first marked on the building plan of the area to be installed. Then, based on the constraints, the area where the high-temperature pipeline is located is avoided, and possible paths are planned along the direction of the wall. The area covered by these qualified paths is the preliminary wiring area. After further optimization, such as considering avoiding narrow passages, the final wiring area is determined.

[0081] The present invention constructs a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information, and can obtain a three-dimensional spatial structure model of the wiring area, clearly presenting the building layout, spatial relationships and obstacle distribution in the wiring area, and providing an accurate spatial reference for optical fiber wiring planning. It should be explained that the spatial topology model is a three-dimensional spatial structure model corresponding to the wiring area.

[0082] Specifically, the combining of the regional spatial data and the regional building information to construct a spatial topology model corresponding to the wiring area includes:

[0083] Calculating a spatial distance value between each data in the regional spatial data, and calculating a distance variance between each data in the regional spatial data based on the spatial distance value;

[0084] Combining the distance variance and the spatial distance value, removing discrete data in the regional spatial data to obtain target spatial data;

[0085] Identifying building entity elements in the regional building information, marking data corresponding to the building entity elements in the target spatial data, and obtaining physical spatial data;

[0086] Analyzing the positional relationship between the entity spatial data, and determining the element topological relationship between the building entity elements based on the positional relationship;

[0087] The spatial topology model corresponding to the wiring area is constructed by combining the physical space data and the element topological relationship.

[0088] It should be explained that the spatial distance value is a measure of the distance between each data in the regional spatial data, the distance variance represents the degree of discreteness between each data in the regional spatial data, the target spatial data is the data obtained after removing the discrete data in the regional spatial data, the building entity elements are structural elements in the regional building information, such as walls, columns, ceilings, etc., the entity spatial data is the data in the target spatial data corresponding to the building entity elements, the positional relationship is the corresponding relationship between the entity spatial data, and the element topological relationship is the connection relationship between the building entity elements.

[0089] Furthermore, the calculation of the spatial distance value between each data in the regional spatial data can be achieved through the Euclidean distance algorithm; the calculation of the distance variance between each data in the regional spatial data can be achieved through the variance formula; when the distance variance is less than the spatial distance value, the corresponding discrete data in the regional spatial data is eliminated to obtain the target spatial data; the identification of the building entity elements in the regional building information can be achieved through natural language processing; marking the data corresponding to the building entity elements in the target spatial data can be achieved through manual marking; the analysis of the positional relationship between the entity spatial data can be achieved through a spatial clustering algorithm; based on the positional relationship, the element topological relationship between the building entity elements is determined. Assuming that there are walls and columns in the building entity elements, if the columns partially overlap with the walls, this is an intersecting positional relationship, then their topological relationship is an intersection, which means that the columns may be the supporting structure of the wall or a design element embedded in the wall; the construction of the spatial topological model corresponding to the wiring area can be achieved through three-dimensional mapping tools, such as CAD mapping tools.

[0090] S2. Gridding the spatial topology model to obtain a spatial topology grid, identifying grid nodes in the spatial topology grid and their corresponding node metadata, wherein the grid nodes include: a starting installation node and a subsequent installation node; and calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata.

[0091] The present invention facilitates spatial quantification of the spatial topology model by gridding the spatial topology model, and then converts the spatial topology model into a simpler visualization method, identifies the grid nodes in the spatial topology grid and their corresponding node metadata, and provides a basis for the subsequent calculation of the optical fiber installation cost between the starting installation node and the subsequent installation node. It should be explained that the spatial topology grid is a grid structure formed after the spatial topology model is gridded; the grid node is the basic unit point in the spatial topology grid, which is used to construct the connection and topological relationship of the grid; the node metadata is the relevant attribute information attached to the grid node; the starting installation node is a specific node in the grid node where the optical fiber wiring starts; the subsequent installation node is a node in the grid node that is located after the starting installation node in the optical fiber wiring sequence. Furthermore, the gridding processing of the spatial topology model can be achieved through the grid division module in the finite element analysis (FEA) software; the identification of the grid nodes in the spatial topology grid and their corresponding node metadata can be achieved through visualization tools. Many professional three-dimensional modeling and visualization software provide interactive functions to identify grid nodes and metadata. In these software, you can select a grid node on the visualized spatial topology grid by clicking the mouse, selecting a box, etc. The software will automatically display the relevant metadata of the node, which may be displayed in the form of a property list, information panel, etc.

[0092] The present invention calculates the optical fiber installation cost between the starting installation node and the subsequent installation node by combining the node metadata, and can calculate the cost of laying optical fiber between the starting installation node and the subsequent installation node to avoid budget overruns. It should be explained that the optical fiber installation cost is the installation cost between the starting installation node and the subsequent installation node.

[0093] Specifically, the calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata includes:

[0094] Analyzing the spatial geometric features corresponding to the subsequent installation node, and extracting geometric metadata corresponding to the spatial geometric features from the node metadata;

[0095] Calculating the installation complexity corresponding to the subsequent installation node by combining the geometric metadata and the spatial geometric features;

[0096] Identifying node obstacles between the initial installation node and the subsequent installation node, and calculating the optical fiber wiring length between the initial installation node and the subsequent installation node;

[0097] The optical fiber installation cost between the initial installation node and the subsequent installation node is calculated based on the node obstacles, the installation complexity, and the optical fiber wiring length.

[0098] It should be explained that the spatial geometric features are the spatial morphological characteristics corresponding to the subsequent installation nodes, such as curvature, spatial altimeter multi-layer structure, etc.; the geometric metadata are the specific data descriptions corresponding to the spatial geometric features in the node metadata; the installation complexity indicates the difficulty of installing the optical fiber corresponding to the subsequent installation node; the node obstacle is the object that hinders the laying of optical fiber between the starting installation node and the subsequent installation node; the optical fiber wiring length is the actual length of the optical fiber laid between the starting installation node and the subsequent installation node.

[0099] Furthermore, the analysis of the spatial geometric features corresponding to the subsequent installation nodes can be achieved through a spatial analysis algorithm; the extraction of geometric metadata corresponding to the spatial geometric features from the node metadata can be achieved through an SQL query method; the identification of node obstacles between the starting installation node and the subsequent installation node can be achieved through millimeter wave radar detection, and the node distance between the starting installation node and the subsequent installation node can be calculated, and the node distance is the optical fiber wiring length; the costs corresponding to the node obstacles and the optical fiber wiring length are determined respectively to obtain the obstacle cost and the optical fiber cost, and the total installation cost = obstacle cost + optical fiber cost × optical fiber wiring length × installation complexity, and then the optical fiber installation cost between the starting installation node and the subsequent installation node is obtained.

[0100] Furthermore, as an optional embodiment of the present invention, the combining of the geometric metadata and the spatial geometric features to calculate the installation complexity corresponding to the subsequent installation node includes:

[0101] Determining, based on the geometric metadata, a feature metric value corresponding to the spatial geometric feature;

[0102] Querying a standard metric value corresponding to the spatial geometric feature, and calculating a complex contribution corresponding to the spatial geometric feature by combining the feature metric value and the standard metric value;

[0103] The geometric weight corresponding to the spatial geometric feature is calculated, and the installation complexity corresponding to the subsequent installation node is calculated by combining the geometric weight and the complexity contribution using the following formula:

[0104]

[0105] Among them, A represents the installation complexity corresponding to the subsequent installation node, B arepresents the geometric weight corresponding to the ath feature in the spatial geometric feature, a represents the feature sequence number corresponding to the spatial geometric feature, q represents the number of features of the spatial geometric feature, D a Indicates the complex contribution corresponding to the ath feature in the spatial geometric features.

[0106] It should be explained that the feature measurement value is the specific expression value corresponding to the spatial combination feature, the standard measurement value is the standard reference value corresponding to the spatial geometric feature, the complexity contribution degree indicates the degree of influence of the subsequent installation node on the overall installation complexity, and the geometric weight indicates the importance corresponding to the spatial geometric feature. Furthermore, the feature measurement value corresponding to the spatial geometric feature can be determined by identifying the data value corresponding to the geometric metadata; the standard measurement value corresponding to the spatial geometric feature can be queried from the Internet through human-computer interaction, the measurement difference between the feature measurement value and the standard measurement value is calculated, and the measurement difference is divided by the standard measurement value to obtain the complexity contribution degree corresponding to the spatial geometric feature; the calculation of the geometric weight corresponding to the spatial geometric feature can be achieved through hierarchical analysis.

[0107] S3. In combination with the optical fiber installation cost and the preset installation expenditure, a preset intelligent path planning algorithm is used to plan the optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, the optical fiber installation equipment and the installed optical fiber information in the optical fiber installation route are queried, and in combination with the optical fiber installation equipment and the installed optical fiber information, the optical fiber in the optical fiber installation route is adaptively modeled with the spatial topology model to obtain an optical fiber adaptation virtual model.

[0108] The present invention combines the optical fiber installation cost and the preset installation expenditure, and utilizes a preset intelligent path planning algorithm to plan the optical fiber installation line between the starting installation node and the subsequent installation node in the spatial topology grid, so as to efficiently determine the optimal installation path within the cost control range. It should be explained that the preset installation expenditure is the amount of funds used for optical fiber installation pre-set according to the overall planning, budget allocation and expected cost control goals before the optical fiber is installed. The preset intelligent path planning algorithm is a computer algorithm designed to determine the optical fiber installation line in a given spatial topology grid, such as algorithm A. The optical fiber installation line is the line used for optical fiber installation in the spatial topology grid.

[0109] Specifically, the method of planning a fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid using a preset intelligent path planning algorithm in combination with the fiber installation cost and the preset installation expenditure includes:

[0110] Identifying an installation backup node corresponding to the successor installation node, and evaluating a node priority corresponding to the successor installation node based on the installation backup node;

[0111] In combination with the node priorities, a preset intelligent path planning algorithm is used to perform path planning for the starting installation node and the subsequent installation nodes in the spatial topology grid to obtain a node planning path;

[0112] Calculating a planned path cost corresponding to the node planned path according to the optical fiber installation cost;

[0113] In combination with the optical fiber installation cost and the preset installation expenditure, the optical fiber installation route between the starting installation node and the subsequent installation node is screened out from the node planning path.

[0114] It should be explained that the installation backup node is the corresponding standby node when the subsequent installation node fails and cannot be used. The node priority represents the importance ranking of the subsequent installation node. The node planning path is the optimal connection route between the starting installation node and the subsequent installation node in the spatial topology grid. The planning path cost is the cost or resource consumption measure corresponding to the node planning path.

[0115] Furthermore, the identification of the installation backup node corresponding to the successor installation node can be achieved through functional equivalence judgment, analyzing the network topology structure to find nodes that are functionally equivalent to the successor installation node; evaluating the node priority corresponding to the successor installation node based on the number of the installation backup nodes, the greater the number, the higher the priority; connecting the successor installation node with a high node priority with the starting installation node to obtain a node planning path; summing the optical fiber installation costs corresponding to the node planning path to obtain a planning path cost; when the optical fiber installation cost is lower than the preset installation expenditure, filtering out the optical fiber installation line between the starting installation node and the successor installation node from the node planning path.

[0116] The present invention combines the optical fiber installation equipment and the installed optical fiber information to adapt and model the optical fiber to the spatial topology model in the optical fiber installation line to obtain an optical fiber adaptation virtual model, thereby facilitating the subsequent calculation and processing of the optical fiber interference between optical fibers. It should be explained that the optical fiber installation equipment is an equipment for installing optical fibers, the installed optical fiber information is the introduction information corresponding to the optical fiber, and the optical fiber adaptation virtual model is a model obtained by adapting the virtual model corresponding to the optical fiber to the spatial topology model. Furthermore, the optical fiber installation equipment and the installed optical fiber information in the optical fiber installation line can be obtained by querying the network management system; the adaptation and modeling of the optical fiber to the spatial topology model in the optical fiber installation line can be achieved through 3D modeling software, such as 3ds Max.

[0117] S4. Evaluate the fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environmental attributes of the grid nodes, and calculate the environmental coupling degree corresponding to the optical fibers in the optical fiber installation line based on the node environmental attributes.

[0118] By evaluating the fiber interference between optical fibers in the fiber adaptation virtual model, the present invention can accurately understand the degree of mutual influence between optical fibers, and then analyze the rationality of the fiber layout, providing a basis for the subsequent line optimization processing of the fiber installation line. It should be explained that the fiber interference represents the degree of mutual influence of the layout between optical fibers in the fiber adaptation virtual model.

[0119] In detail, the evaluating the optical fiber interference between optical fibers in the optical fiber adaptation virtual model includes:

[0120] Dynamically discretizing the optical fiber model in the optical fiber adaptation virtual model to obtain a discrete optical fiber model;

[0121] Traversing the model discrete points of the discrete optical fiber model to obtain spatial coordinate information corresponding to the model discrete points;

[0122] Calculating the discrete point distances between the discrete points of the model based on the spatial coordinate information;

[0123] The fiber radius corresponding to the discrete fiber model is determined. Combining the fiber radius and the discrete point distance, the relative distance coefficient between optical fibers in the fiber adaptation virtual model can be calculated using the following formula:

[0124]

[0125] Where E represents the relative distance coefficient between optical fibers in the optical fiber adaptation virtual model, L d，d+1 Indicates the discrete point distance between the dth model and the d+1th model in the discrete fiber model, R d Indicates the fiber radius corresponding to the dth model in the discrete fiber model, R d+1 Indicates the fiber radius corresponding to the d+1th model in the discrete fiber model, d and d+1 respectively represent the serial numbers corresponding to the discrete fiber models;

[0126] The fiber interference between the optical fibers in the optical fiber adaptation virtual model is evaluated according to the relative distance coefficient.

[0127] It should be explained that the discrete fiber model is a discrete representation of the fiber model in the fiber adaptation virtual model, the model discrete points are the basic elements of the discrete fiber model, the discrete point distance represents the distance value between the model discrete points, and the relative distance coefficient represents the relative spacing between the optical fibers in the fiber adaptation virtual model.

[0128] Furthermore, the dynamic discrete processing of the optical fiber model in the optical fiber adaptation virtual model can be achieved through a discrete algorithm, such as a uniform grid discretization method; the traversal of the model discrete points of the discrete optical fiber model can be achieved through a loop structure in programming; the spatial coordinate information corresponding to the model discrete points can be obtained through a spatial coordinate tool, and the spatial coordinate tool is compiled by a script language, such as a JS script language; the discrete point distance between the model discrete points can be achieved through the above-mentioned Euclidean distance algorithm; according to the relative distance coefficient, the optical fiber interference between the optical fibers in the optical fiber adaptation virtual model is evaluated. If the relative distance coefficient is greater than 1, it means that the distance between the optical fibers in the optical fiber adaptation virtual model is relatively far, and the corresponding optical fiber interference is low. If the relative distance coefficient is less than 1, it means that the distance between the optical fibers in the optical fiber adaptation virtual model is relatively close, and the corresponding optical fiber interference is high.

[0129] The present invention calculates the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, and can understand the line complexity corresponding to each line in the optical fiber installation line through the line complexity, thereby laying the foundation for the subsequent line optimization processing of the optical fiber installation line. It should be explained that the adaptation model diagram is a visualization image corresponding to the optical fiber adaptation virtual model, and the line complexity represents the overall line complexity corresponding to the optical fiber installation line. Furthermore, the drawing of the adaptation model diagram corresponding to the optical fiber adaptation virtual model can be achieved through a drawing tool, and the drawing tool is compiled by a programming language.

[0130] Specifically, the calculating of the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram includes:

[0131] Performing line extraction processing on the adaptation model graph to obtain a model line, and performing smoothing processing on the model line to obtain a smoothed model line;

[0132] Counting the line crossing frequency in the smooth model line and measuring the line curvature in the smooth model line;

[0133] Combined with the line crossing frequency and the line curvature, the line complexity corresponding to the optical fiber installation line is calculated using the following formula:

[0134]

[0135] Among them, F represents the line complexity corresponding to the optical fiber installation line, G represents the line cross frequency, G0 represents the reference cross frequency, H e represents the line curvature corresponding to the e-th line in the smooth model line, r represents the number of smooth model lines, M0 represents the reference curvature, and I0 represents the cross-curvature correlation factor.

[0136] It should be explained that the model line is the corresponding installation line in the adaptation model diagram, the smooth model line is the line obtained by smoothing the jagged or discontinuous line in the model line, the line crossing frequency is the number of crossings in the smooth model line, and the line curvature is the degree of curvature in the smooth model line.

[0137] Furthermore, the line extraction processing of the adaptation model graph can be implemented by an edge detection algorithm; the smoothing processing of the model line can be implemented by a curve fitting algorithm; the statistics of the line crossing frequency in the smoothed model line can be implemented by a geometric intersection judgment algorithm, which traverses the line segments on the line, judges the intersection situation and counts it; the measurement of the line curvature in the smoothed model line can be implemented by calculating the curve curvature, such as taking the second-order derivative of the line segment by segment to obtain the curvature of each segment to measure the curvature; the reference crossing frequency and the reference curvature can be obtained from an existing professional library, which is a database of standard reference values ​​obtained by professional engineers through analysis tools; a large amount of optical fiber installation project case data can be collected, which should include line crossing frequency, curvature, and engineers' subjective assessment of installation complexity, and these data can be classified and statistically analyzed. For example, the complexity level is quantified (such as simple = 1, medium = 2, complex = 3, very complex = 4), and then an attempt is made to find a functional relationship between the crossing frequency and curvature and the complexity level, so as to calculate the crossing-bending correlation factor.

[0138] The present invention calculates the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attributes, and can understand the degree of adaptation between the optical fiber and the corresponding installation environment through the environmental coupling degree, thereby improving the accuracy of subsequent line optimization processing of the optical fiber installation line. It should be explained that the node environmental attributes are the environmental characteristics corresponding to the grid nodes, and the environmental coupling degree represents the degree of adaptation between the optical fiber and the environment in the optical fiber installation line. Furthermore, the collection of the corresponding node environmental attributes corresponding to the grid nodes can be achieved through sensors, such as temperature sensors and humidity sensors.

[0139] Specifically, the calculating of the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attribute includes:

[0140] Analyzing environmental attribute factors corresponding to the node environmental attributes, and identifying optical fiber influencing factors from the environmental attribute factors;

[0141] Based on the optical fiber influencing factors, filtering the node environment attributes to obtain target environment attributes;

[0142] Standardizing the target environment attributes to obtain standard environment attributes;

[0143] According to the standard environmental attributes, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line is calculated using a preset geometric mean method.

[0144] It should be explained that the environmental attribute factors are the environmental factors corresponding to the node environmental attributes, such as temperature and humidity, etc., the optical fiber influencing factors are the environmental factors among the environmental attribute factors that affect the optical fiber, and the standard environmental attributes are the environmental attributes obtained after eliminating the differentiated effects between the target environmental attributes.

[0145] Furthermore, the analysis of the environmental attribute factors corresponding to the node environmental attributes can be achieved through the principal component analysis (PCA) method; the optical fiber influencing factors can be identified from the environmental attribute factors according to a preset influencing factor table, and the influencing factor table can be constructed through an experimental design method, such as installing the same type of optical fiber in each simulated environment and testing the performance indicators of the optical fiber. The performance indicators may include the attenuation degree of the optical signal, the transmission bandwidth, the mechanical strength of the optical fiber (such as tensile strength), etc., so as to determine the corresponding environmental influencing factors; the standardization of the target environmental attributes can be achieved through the Z-Score standardization method; according to the standard environmental attributes, the preset geometric mean method is used to calculate the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line. For example, if the standard environmental attributes are: temperature, humidity, and electromagnetic interference, the corresponding geometric mean method calculation formula is: The environmental coupling degree is calculated based on this.

[0146] S5. Optimize the optical fiber installation line based on the optical fiber interference, the line complexity, and the environmental coupling degree to obtain an optimized installation line for the optical fiber in the area to be installed.

[0147] The present invention optimizes the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling, thereby obtaining the optimal installation line of the optical fiber in the area to be installed, thereby improving the installation efficiency of the optical fiber. Furthermore, the line optimization of the optical fiber installation line can be achieved by combining the optical fiber interference, the line complexity and the corresponding values ​​of the environmental coupling. Assuming that the optical fiber interference is high, the line complexity is large and the environmental coupling is strong, the interference can be reduced by adjusting the direction of the optical fiber, such as avoiding interference sources. For complex lines, the intersection and bending parts are simplified. For harsh environments, more suitable protective materials and installation positions are selected. These measures are combined to obtain an optimized installation line.

[0148] Compared with the problem described in the background technology, the present invention locates the wiring area in the area to be installed according to the wiring requirements of the area, and can clarify the specific range for wiring in the area to be installed, providing an accurate layout space basis for subsequent optical fiber wiring planning, and collecting regional building information and regional spatial data corresponding to the wiring area, and can obtain relevant details of the building structure in the wiring area (such as walls, beams and columns, etc.) and space size, shape, channel and other data, which provides a basis for the subsequent construction of the spatial topology model corresponding to the wiring area. The present invention facilitates the spatial quantification of the spatial topology model by gridding the spatial topology model, and then converts the spatial topology model into a simpler visualization method, identifies the grid nodes in the spatial topology grid and their corresponding node metadata, and provides a basis for the subsequent starting installation node and the subsequent The present invention provides a basis for calculating the cost of optical fiber installation between installation nodes. By combining the optical fiber installation cost and the preset installation expenditure, the present invention uses a preset intelligent path planning algorithm to plan the optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, which can efficiently determine the optimal installation path within the cost control range. By evaluating the optical fiber interference between optical fibers in the optical fiber adaptation virtual model, the present invention can accurately understand the degree of mutual influence between optical fibers, and then analyze the rationality of the optical fiber layout, providing a basis for the subsequent line optimization processing of the optical fiber installation line. The present invention optimizes the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling degree, and then obtains the optimal installation route of the optical fiber in the area to be installed, thereby improving the installation efficiency of the optical fiber. Therefore, the present invention proposes a method for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, thereby improving the efficiency of optical fiber wiring planning.

[0149] Example 2:

[0150] like Figure 2FIG. 1 is a functional module diagram of a system for realizing efficient optical fiber cabling planning based on an intelligent path planning algorithm provided by an embodiment of the present invention.

[0151] The system 100 for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the system 100 can include a spatial modeling module 101, an installation cost calculation module 102, a fiber adaptation modeling module 103, an environmental coupling calculation module 104, and a line optimization module 105. A module, also referred to as a unit, refers to a series of computer program segments that can be executed by an electronic device processor and perform a fixed function. These modules are stored in the electronic device's memory.

[0152] In this embodiment, the functions of each module / unit are as follows:

[0153] The spatial model construction module 101 is used to obtain the area to be installed of the optical fiber and the corresponding regional wiring requirements, locate the wiring area in the area to be installed according to the regional wiring requirements, collect regional building information and regional spatial data corresponding to the wiring area, and construct a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information;

[0154] The installation cost calculation module 102 is configured to perform gridding processing on the spatial topology model to obtain a spatial topology grid, identify grid nodes in the spatial topology grid and their corresponding node metadata, wherein the grid nodes include: a starting installation node and a subsequent installation node, and calculate the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata;

[0155] The optical fiber adaptation modeling module 103 is configured to plan an optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid using a preset intelligent path planning algorithm based on the optical fiber installation cost and the preset installation expenditure, query optical fiber installation equipment and installed optical fiber information in the optical fiber installation route, and perform adaptive modeling of the optical fiber in the optical fiber installation route and the spatial topology model based on the optical fiber installation equipment and the installed optical fiber information to obtain an optical fiber adaptation virtual model.

[0156] The environmental coupling degree calculation module 104 is used to evaluate the fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environmental attributes of the grid nodes, and calculate the environmental coupling degree corresponding to the optical fibers in the optical fiber installation line based on the node environmental attributes;

[0157] The line optimization module 105 is configured to optimize the optical fiber installation line based on the optical fiber interference, the line complexity, and the environmental coupling degree to obtain an optimized installation line for the optical fiber in the area to be installed.

[0158] In detail, each module described in the embodiment of the present application is used in the system 100 for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm. Figure 1 The technical means described in the above text are the same as the method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm, and can produce the same technical effects, so they will not be repeated here.

[0159] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for realizing efficient optical fiber cabling planning based on an intelligent path planning algorithm, characterized in that: The method comprises: Obtaining an area to be installed for optical fibers and its corresponding regional wiring requirements, locating a wiring area in the area to be installed based on the regional wiring requirements, collecting regional building information and regional spatial data corresponding to the wiring area, and constructing a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information; Gridding the spatial topology model to obtain a spatial topology grid, identifying grid nodes in the spatial topology grid and their corresponding node metadata, the grid nodes including: a starting installation node and a subsequent installation node; and calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata; In combination with the optical fiber installation cost and the preset installation expenditure, a preset intelligent path planning algorithm is used to plan an optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, optical fiber installation equipment and installation optical fiber information in the optical fiber installation route are queried, and in combination with the optical fiber installation equipment and the installation optical fiber information, optical fibers in the optical fiber installation route are adaptively modeled with the spatial topology model to obtain an optical fiber adaptation virtual model; Evaluating the fiber interference between optical fibers in the optical fiber adaptation virtual model, drawing an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculating the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collecting node environmental attributes corresponding to the grid nodes, and calculating the environmental coupling degree corresponding to the optical fibers in the optical fiber installation line based on the node environmental attributes; The optical fiber installation line is optimized based on the optical fiber interference, the line complexity, and the environmental coupling degree to obtain an optimized installation line for the optical fiber in the area to be installed.

2. The method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm according to claim 1, characterized in that: The step of locating the wiring area in the area to be installed according to the area wiring requirements includes: Performing text recognition on the wiring requirements of the area to obtain a wiring requirement text; Analyzing the semantics of the requirement text corresponding to the wiring requirement text, and performing requirement classification processing on the wiring requirement text based on the semantics of the requirement text to obtain a requirement category; Extracting key requirement information from the wiring requirement text based on the requirement category; Based on the key requirement information, a wiring area in the area to be installed is located.

3. The method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm according to claim 1, characterized in that: The step of combining the regional spatial data and the regional building information to construct a spatial topology model corresponding to the wiring area includes: Calculating a spatial distance value between each data in the regional spatial data, and calculating a distance variance between each data in the regional spatial data based on the spatial distance value; Combining the distance variance and the spatial distance value, removing discrete data in the regional spatial data to obtain target spatial data; Identifying building entity elements in the regional building information, marking data corresponding to the building entity elements in the target spatial data, and obtaining physical spatial data; Analyzing the positional relationship between the entity spatial data, and determining the element topological relationship between the building entity elements based on the positional relationship; The spatial topology model corresponding to the wiring area is constructed by combining the physical space data and the element topological relationship.

4. The method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm according to claim 1, characterized in that: The calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata includes: Analyzing the spatial geometric features corresponding to the subsequent installation node, and extracting geometric metadata corresponding to the spatial geometric features from the node metadata; Calculating the installation complexity corresponding to the subsequent installation node by combining the geometric metadata and the spatial geometric features; Identifying node obstacles between the initial installation node and the subsequent installation node, and calculating the optical fiber wiring length between the initial installation node and the subsequent installation node; The optical fiber installation cost between the initial installation node and the subsequent installation node is calculated based on the node obstacles, the installation complexity, and the optical fiber wiring length.

5. The method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm according to claim 4, characterized in that: The calculating the installation complexity corresponding to the subsequent installation node by combining the geometric metadata and the spatial geometric features includes: Determining, based on the geometric metadata, a feature metric value corresponding to the spatial geometric feature; Querying a standard metric value corresponding to the spatial geometric feature, and calculating a complex contribution corresponding to the spatial geometric feature by combining the feature metric value and the standard metric value; The geometric weight corresponding to the spatial geometric feature is calculated, and the installation complexity corresponding to the subsequent installation node is calculated by combining the geometric weight and the complexity contribution using the following formula: ； Among them, A represents the installation complexity corresponding to the subsequent installation node, It represents the geometric weight corresponding to the ath feature in the spatial geometric feature, a represents the feature sequence number corresponding to the spatial geometric feature, and q represents the number of features of the spatial geometric feature. Indicates the complex contribution corresponding to the ath feature in the spatial geometric features.

6. The method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm according to claim 1, characterized in that: The method of planning a fiber optic installation route between the starting installation node and the subsequent installation node in the spatial topology grid by using a preset intelligent path planning algorithm in combination with the fiber optic installation cost and the preset installation expenditure includes: Identifying an installation backup node corresponding to the successor installation node, and evaluating a node priority corresponding to the successor installation node based on the installation backup node; In combination with the node priorities, a preset intelligent path planning algorithm is used to perform path planning for the starting installation node and the subsequent installation nodes in the spatial topology grid to obtain a node planning path; Calculating a planned path cost corresponding to the node planned path according to the optical fiber installation cost; In combination with the optical fiber installation cost and the preset installation expenditure, the optical fiber installation route between the starting installation node and the subsequent installation node is screened out from the node planning path.

7. The method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm according to claim 1, characterized in that: The evaluating the optical fiber interference between optical fibers in the optical fiber adaptation virtual model includes: Dynamically discretizing the optical fiber model in the optical fiber adaptation virtual model to obtain a discrete optical fiber model; Traversing the model discrete points of the discrete optical fiber model to obtain spatial coordinate information corresponding to the model discrete points; Calculating the discrete point distances between the discrete points of the model based on the spatial coordinate information; The fiber radius corresponding to the discrete fiber model is determined. Combining the fiber radius and the discrete point distance, the relative distance coefficient between optical fibers in the fiber adaptation virtual model can be calculated using the following formula: ； Where E represents the relative distance coefficient between optical fibers in the optical fiber adaptation virtual model, Indicates the discrete point distance between the dth model and the d+1th model in the discrete fiber model. represents the fiber radius corresponding to the dth model in the discrete fiber model, Indicates the fiber radius corresponding to the d+1th model in the discrete fiber model, d and d+1 respectively represent the serial numbers corresponding to the discrete fiber models; The fiber interference between the optical fibers in the optical fiber adaptation virtual model is evaluated according to the relative distance coefficient.

8. The method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm according to claim 1, characterized in that: The calculating, based on the adaptation model diagram, the line complexity corresponding to the optical fiber installation line includes: Performing line extraction processing on the adaptation model graph to obtain a model line, and performing smoothing processing on the model line to obtain a smoothed model line; Counting the line crossing frequency in the smooth model line and measuring the line curvature in the smooth model line; Combined with the line crossing frequency and the line curvature, the line complexity corresponding to the optical fiber installation line is calculated using the following formula: ； Among them, F represents the line complexity corresponding to the optical fiber installation line, G represents the line crossing frequency, represents the reference crossover frequency, represents the curvature of the e-th line in the smooth model line, r represents the number of smooth model lines, represents the reference curvature, represents the cross-bend correlation factor.

9. The method for realizing efficient optical fiber cabling planning based on intelligent path planning algorithm according to claim 1, characterized in that: The calculating, based on the node environment attribute, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line includes: Analyzing environmental attribute factors corresponding to the node environmental attributes, and identifying optical fiber influencing factors from the environmental attribute factors; Based on the optical fiber influencing factors, filtering the node environment attributes to obtain target environment attributes; Standardizing the target environment attributes to obtain standard environment attributes; According to the standard environmental attributes, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line is calculated using a preset geometric mean method.

10. An efficient fiber optic cabling planning system is implemented based on an intelligent path planning algorithm, characterized in that: The system comprises: A spatial model construction module is used to obtain the area to be installed of the optical fiber and the corresponding regional wiring requirements, locate the wiring area in the area to be installed according to the regional wiring requirements, collect regional building information and regional spatial data corresponding to the wiring area, and construct a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information; An installation cost calculation module is configured to perform gridding processing on the spatial topology model to obtain a spatial topology grid, identify grid nodes in the spatial topology grid and their corresponding node metadata, wherein the grid nodes include: a starting installation node and a subsequent installation node, and calculate the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata; a fiber adaptation modeling module for planning a fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid using a preset intelligent path planning algorithm based on the fiber installation cost and the preset installation expenditure, querying information about fiber installation equipment and installed fibers in the fiber installation route, and adapting and modeling the fibers in the fiber installation route to the spatial topology model based on the fiber installation equipment and the installed fibers to obtain a fiber adaptation virtual model; an environmental coupling degree calculation module, configured to evaluate the optical fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect node environmental attributes corresponding to the grid nodes, and calculate the environmental coupling degree corresponding to the optical fibers in the optical fiber installation line based on the node environmental attributes; The line optimization module is used to optimize the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling degree to obtain an optimized installation line of the optical fiber in the area to be installed.

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