Material configuration method, system and equipment of communication base station and medium

Abstract

The invention discloses a material configuration method, system and equipment of a communication base station and a medium. The method comprises the following steps: matching a plurality of candidate base stations in a base station database according to a base station type and a fault type of a target base station; the candidate base station is a base station which has the same base station type as the target base station and has a fault type; carrying out material configuration on the target base station in a first mode or a second mode; according to the first mode, material configuration for solving the fault type is carried out on a target base station based on the amount of completed materials, historical meteorological data and corresponding historical configuration data configured by a plurality of candidate base stations for solving the fault type; and the second mode is that material configuration for solving the fault type is performed on the target base station based on the completed material consumption, the historical meteorological data, the base station type and the fault type of the target base station, similar base stations can be screened according to the base station type and the fault type, multi-source data are fused for material configuration, the configuration accuracy is improved, and the configuration efficiency is improved. The period is shortened, and the first-aid repair efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of communication network material allocation technology, and in particular to a method, system, equipment and medium for material allocation of a communication base station. Background Technology

[0002] With the rapid expansion of 5G / 5G-A networks, the total number of base stations in operation nationwide has exceeded ten million. The outage of a single base station can easily cause service interruption and may trigger cascading network risks during the repair period. Therefore, operators have extremely high requirements for the timeliness of fault location, material allocation and on-site restoration, and must complete the repair in the shortest possible time to reduce losses.

[0003] However, the existing methods for allocating materials to communication base stations rely on manual experience and readily available spare materials, which cannot meet the special requirements of materials such as waterproofing and antifreeze. The estimation of materials depends entirely on the experience of senior employees and lacks authoritative reference. Furthermore, when personnel are away from their posts or out of contact, other personnel cannot make quick and accurate estimates, which seriously affects the efficiency of emergency repairs and leads to low efficiency in material allocation and a high rate of secondary material allocation. Summary of the Invention

[0004] The following is an overview of the subject matter described in detail herein. This overview is not intended to limit the scope of the claims.

[0005] The main objective of this disclosure is to propose a method, system, device, and storage medium for configuring resources for communication base stations. This method can filter similar base stations by base station type and fault type, integrate multi-source data for resource configuration, improve configuration accuracy, and thus shorten the cycle and improve emergency repair efficiency.

[0006] A first aspect of this application provides a method for allocating resources to a communication base station, used in a central controller, the method comprising: Acquire the amount of construction materials used for the completed construction of the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station; Based on the base station type and fault type of the target base station, several candidate base stations are matched in the base station database; the candidate base stations are base stations with the same base station type as the target base station and have experienced the fault type. The target base station is configured with materials using either a first method or a second method. The first method is to configure materials for the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, and the corresponding historical configuration data of the candidate base stations configured to resolve the fault type. The second method is to configure materials for the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, the base station type, and the fault type.

[0007] In some embodiments of this application, the step of configuring materials for resolving the fault type on the target base station based on the completed material usage, the historical meteorological data, and the corresponding historical configuration data of the plurality of candidate base stations configured to resolve the fault type includes: Obtain the corresponding historical completed material usage for the aforementioned candidate base stations; The single-site weighting coefficient of each candidate base station is calculated based on the ratio of the historical configuration data corresponding to each candidate base station to the historical completed material usage. Calculate the mean of the single-site weighting coefficients of the plurality of candidate base stations, and calculate the product between the mean and the amount of materials used upon completion to obtain the estimated amount of material allocation; Based on the estimated amount of material allocation and the historical meteorological data, material allocation is performed on the target base station.

[0008] In some embodiments of this application, the step of allocating resources to the target base station based on the estimated resource allocation and the historical meteorological data includes: Based on the historical meteorological data, determine the meteorological type of the area where the target base station is located; The first additional material configuration for the target base station is determined from the database based on the weather type; the database contains a mapping relationship between the weather type and the materials. Based on the estimated resource allocation and the first additional resource allocation, resource allocation is performed on the target base station.

[0009] In some embodiments of this application, the step of allocating materials to the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, the base station type, and the fault type includes: Based on the fault type of the target base station, determine the basic material configuration quantity corresponding to the fault type; Based on the historical meteorological data, determine the meteorological type of the area where the target base station is located; The second additional material configuration for the target base station is determined from the database based on the weather type; the database contains a mapping relationship between the weather type and the materials. Based on the basic resource allocation and the second additional resource allocation, the target base station is configured with resources.

[0010] In some embodiments of this application, after configuring resources for the target base station using the first or second method, the method further includes: Obtain inventory information of configurable material warehouses; the configurable material warehouses include the home material warehouse to which the target base station belongs and at least one non-home material warehouse; Based on the first method or the second method, determine the material configuration list of the target base station; Based on the material configuration list and the inventory information of the configurable material warehouse, determine the target configuration material warehouse; The target configuration material library is used to execute the configuration task corresponding to the material configuration list, and update the inventory information and material status identifier of the target configuration material library; the material status identifier consists of the fault type of the target base station and the configuration status of the target configuration material library.

[0011] In some embodiments of this application, after executing the configuration task corresponding to the material configuration list through the target configuration material library and updating the inventory information and material status identifier of the target configuration material library, the method further includes: In response to the configuration completion command, obtain the remaining material information of the target base station; Based on the remaining material information, update the inventory information and material status identifier of the target configuration material warehouse; Based on the remaining material information and the material configuration list, the configuration error is calculated; Based on the configuration error, a historical sample of the target base station is generated.

[0012] In some embodiments of this application, generating historical samples of the target base station based on the configuration error includes: Historical data is obtained by combining the completed material usage of the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station. Based on the historical data and the sample tags of the historical data, a historical sample of the target base station is generated; the sample tags are used to distinguish the type of the historical data. The sample label is determined through the following steps: The sample label is determined based on the configuration error; If the configuration error is less than a preset error threshold, the sample label is determined to be a valid sample. If the configuration error is greater than or equal to a preset error threshold, the sample label is determined to be an invalid sample, and a configuration error message is sent.

[0013] The first aspect of this application provides a method for configuring materials for a communication base station. This method involves matching several candidate base stations in a base station database based on the base station type and fault type of the target base station. The candidate base stations are base stations of the same type as the target base station that have experienced the same fault type. Materials are configured for the target base station using either a first method or a second method. The first method is based on the amount of materials used upon completion, historical meteorological data, and corresponding historical configuration data of the candidate base stations configured to resolve the fault type. The second method is based on the amount of materials used upon completion, historical meteorological data, base station type, and fault type of the target base station. This method can filter similar base stations by base station type and fault type, integrate multi-source data for material configuration, improve configuration accuracy, and thus shorten the cycle and improve repair efficiency.

[0014] To achieve the above objectives, a second aspect of this application provides a resource allocation system for a communication base station, the system comprising: The acquisition module is used to acquire the amount of completed construction materials used for the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station; The matching module is used to match several candidate base stations in the base station database according to the base station type and fault type of the target base station; the candidate base stations are base stations with the same base station type as the target base station and have experienced the fault type. A configuration module is used to configure materials for the target base station in either a first method or a second method. The first method is to configure materials for the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, and the corresponding historical configuration data of the several candidate base stations configured to resolve the fault type. The second method is to configure materials for the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, the base station type, and the fault type.

[0015] To achieve the above objectives, a third aspect of this application provides an electronic device, including: at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor, which, when executed by the at least one control processor, enable the at least one control processor to perform the above-described method for configuring resources for a communication base station.

[0016] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the above-described method for configuring materials for a communication base station.

[0017] It is understood that the beneficial effects of the second to fourth aspects compared with the related technologies are the same as the beneficial effects of the first aspect compared with the related technologies. Please refer to the relevant description in the first aspect above, which will not be repeated here. Attached Figure Description

[0018] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart illustrating a method for allocating resources for a communication base station according to an embodiment of this application. Figure 2 This is a schematic diagram of the structure of a material allocation system for a communication base station provided in an embodiment of this application; Figure 3 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0019] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0020] In the description of this application, the use of terms such as "first," "second," etc., is for the purpose of distinguishing technical features only and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0021] In the description of this application, it should be understood that the orientation descriptions, such as up, down, etc., are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0022] In the description of this application, it should be noted that, unless otherwise explicitly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0023] With the rapid expansion of 5G / 5G-A networks, the total number of base stations in operation nationwide has exceeded ten million. Any single base station outage can cause service interruptions and become a cascading network vulnerability during repair periods. Operators generally require fault location, material allocation, and on-site restoration to be completed in the shortest possible time. However, current repair material allocation still heavily relies on manual experience and readily available spare parts, failing to integrate digital and intelligent methods, resulting in a high rate of secondary replenishment and lengthy repair times. Specifically, the current material allocation estimation methods have the following main shortcomings: The weather dimension of the target base station is missing: extreme weather such as rainstorms, strong winds, low temperatures, and high temperatures directly affect the needs of materials for waterproofing, reinforcement, antifreeze, and heat dissipation, but existing emergency repair plans generally do not incorporate meteorological factors into the material estimation model.

[0024] Material estimation is highly dependent on human experience: assessing the total amount of materials needed for emergency repairs relies entirely on the practical experience of senior employees. When senior employees cannot be contacted or are away from their posts, other personnel find it difficult to quickly and accurately estimate the materials, which greatly affects the efficiency of emergency repairs.

[0025] The information associated with the target base station was not fully utilized: the information from the as-built drawings of the target base station was not adequately utilized during the emergency repair process, and the amount of materials used in the project construction was not used as a reference for the amount of materials used in the emergency repair.

[0026] The value of historical emergency repair data of base stations has not been explored: After the target base station or similar base stations completed the handling of the same type of fault alarm in the past 30 times, the corresponding emergency repair material consumption was not recorded and utilized, resulting in a lack of calibration mechanism for the amount of materials required for emergency repair.

[0027] Based on this, the embodiments of this application provide a method, system, electronic device and medium for the allocation of materials for communication base stations. The aim is to filter similar base stations by using feature codes and alarm codes, weighted expand samples, and integrate multi-source data to generate a configuration list, thereby improving the accuracy of material allocation and reducing the secondary replenishment rate, thus shortening the cycle and improving the efficiency of emergency repair.

[0028] The communication base station material allocation method, system, electronic equipment and medium provided in the embodiments of this application are specifically described through the following embodiments. First, the communication base station material allocation method in the embodiments of this application is described.

[0029] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0030] Foundational technologies in artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0031] The communication base station resource allocation method provided in this application relates to the field of communication network resource allocation technology. The communication base station resource allocation method provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application implementing the communication base station resource allocation method, but is not limited to the above forms.

[0032] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0033] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0034] Therefore, referring to Figure 1 This application provides a method for allocating resources for a communication base station. This method is applied to a central controller, which can be a server, an electronic device, or a mobile terminal, etc. There are no specific limitations here. The method includes the following steps S110 to S130.

[0035] Step S110: Obtain the amount of completed construction materials used for the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station; Step S120: Based on the base station type and fault type of the target base station, match several candidate base stations in the base station database; the candidate base stations are base stations with the same base station type as the target base station and have experienced the fault type. Step S130: Configure materials for the target base station using either the first method or the second method. The first method is to configure materials for the target base station based on the amount of materials used upon completion, historical meteorological data, and corresponding historical configuration data of several candidate base stations configured to resolve fault types. The second method is to configure materials for the target base station based on the amount of materials used upon completion, historical meteorological data, base station type, and fault type.

[0036] In this step, we acquire the completed construction materials usage of the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station. Among them, the completed construction materials usage of the target base station is the actual material consumption data during the base station construction phase, covering the specific usage of all categories of materials such as core equipment, cables, and auxiliary materials. It is an authoritative benchmark reflecting the scale and configuration standards of the base station hardware and directly determines the basic quantity of material configuration. The historical meteorological data of the area where the target base station is located is obtained through the meteorological platform interface, covering a 1km radius around the base station. It includes precipitation, temperature, wind force, and other data for the past preset duration (e.g., 24 hours) and the future preset duration (e.g., 12 hours). According to industry standards, it is divided into types such as rainstorm and low temperature, which is the key basis for determining whether additional special materials are needed. The base station type and fault type of the target base station are the core identifiers for scenario matching and demand positioning. The base station type is associated with the scale difference of material configuration, and the fault type (e.g., transmission fault, power fault) is uniquely identified through alarm code, directly corresponding to the core emergency repair needs.

[0037] Furthermore, through a dual-dimensional screening process, candidate base stations with highly similar scenarios and requirements to the target base station are identified, namely, those with the same base station type and those with matching fault types. The same base station type ensures consistency between the candidate and target base stations in terms of hardware scale, coverage, and configuration standards, avoiding discrepancies in resource requirements due to differences in base station type. The same fault type ensures that the historical configuration data of the candidate base station is directly related to the current emergency repair needs of the target base station, providing direct reference value for its past experience in resource configuration for resolving similar faults.

[0038] Specifically, the matching process is implemented through the retrieval function of the base station database. Using the target base station's base station type and fault type as joint search conditions, several candidate base stations meeting the criteria are selected from a massive amount of existing base station data. Then, historical configuration data of these candidate base stations is extracted to form a sample pool, providing data support for the usage estimation in the first method. If a sufficient number of candidate base stations are not selected (not reaching the preset sample threshold), the process will switch to the second method to ensure the continuity of the configuration process. This allows for determining the appropriate scenario based on the number of candidate base station samples and selecting the corresponding method to execute resource configuration, ensuring that the configuration process is both accurate and robust.

[0039] Furthermore, by adaptively selecting two differentiated configuration methods, scenarios with sufficient and insufficient historical samples are respectively adapted to ensure accurate and efficient material allocation in different scenarios. The first method is suitable for scenarios with a sufficient number of candidate base stations (reaching a preset sample threshold). Specifically, it uses the completed material usage of the target base station as the base level, combines historical configuration data of candidate base stations for resolving similar faults (through pooling and weighted extraction of common patterns), and overlays the specific material requirements corresponding to historical meteorological data to finally determine the material allocation scheme. This method relies on the historical experience of the group and can minimize estimation errors. The second method is suitable for scenarios with an insufficient number of candidate base stations (not reaching the preset sample threshold) and unable to support historical experience estimation. Specifically, it uses the completed material usage as the base level, combines the standard configuration template corresponding to the base station type, the core material requirements corresponding to the fault type, and supplements the specific materials corresponding to historical meteorological data to form a standardized configuration scheme. Although this method does not rely on historical samples, it can ensure sufficient coverage of basic emergency repair needs through solidified industry experience and standard templates.

[0040] In one embodiment, the system of this embodiment is constructed using a communication base station material allocation method for calculating and allocating material allocation during base station emergency repairs. The specific process is as follows: Step 1: Alarm Locking (≤1s). The system adopts a "stream-batch fusion" architecture. The "real-time stream" is used to enter the memory for calculation as soon as the alarm is generated, and the locking is completed within 1 second. The "offline batch" is used to periodically reconfirm the alarms of the past period in the background to complete the calibration and backtracking correction. Fusion: The underlying unified SQL and operator logic achieves sub-second low latency. It relies on Flink Checkpoint to complete state sharing and ensures zero data loss through "batch supplementation stream" in the event of failure or version upgrade.

[0041] Furthermore, the system subscribes to Kafka / MQTT topics pushed by heterogeneous vendor adaptation layers (Huawei, ZTE, Ericsson, Nokia, etc.) through the gRPC-NG northbound interface, and integrates and aggregates alarms from environmental monitoring, transmission, and wireless systems in real time. A sliding window CEP engine is introduced to perform 500ms-granular "Storm Topology" pattern matching on the original alarm stream, triggering locking to avoid false alarms. Alarm text is mapped to a triplet of "professional name, equipment / cable type, alarm code" using preset rules, with "equipment / cable type" automatically categorized using a BERT-BiLSTM recognition model. A 24-bit feature code is simultaneously assigned to the "base station ID" associated with the alarm: each 4 bits represent traffic volume, terrain type, altitude level, power supply type, and base station type, with the last 4 bits used for CRC-4 checksum. Finally, a single data entry of "base station ID—feature code—fault time—professional name—equipment / cable type—alarm code" is written to the system database, generating the target base station identification information within seconds.

[0042] Step 2: Data Access (≤5s). First, access historical alarm material usage data. Experiments show that when the sample size is <30, the 95% confidence interval of the single emergency repair material consumption distribution is too wide, resulting in a prediction length error >±20%; while when the sample size is ≥30, the error can be reduced to within ±8%, meeting the engineering redundancy requirements. Therefore, having 30 emergency repair material usage records for the same alarm code is a prerequisite for enabling the system to perform material calculations; when the threshold is lower, the general emergency repair material configuration standard is followed.

[0043] Furthermore, statistical analysis of material usage data based on alarms from a single base station is prone to the problem of "insufficient samples." A "pooling + weighting" strategy can be adopted to make reasonable use of samples with the same alarm code and feature code but different base station IDs: "Pooling" involves "merging" alarm records from multiple similar base stations into a large pool. In step one, base stations are divided into clusters based on the code values ​​of the feature codes obtained from five dimensions: "traffic volume, terrain category, altitude classification, power supply type, and base station type." Different base stations with the same feature code can be regarded as belonging to the same cluster. The emergency repair material usage records associated under the same cluster will be regarded as unified and shared valid samples of that cluster, thereby solving the problem of insufficient samples from a single station. After pooling, the "group samples" are restored to "individual factors," and the group samples are "weighted" through a global correction factor.

[0044] The formulas for the single-station weighting coefficient, the average weighting coefficient, and the estimated amount of repair materials for the target base station are as follows: ; ; .

[0045] Furthermore, the system transforms previously isolated single-site data into a unified and shared group sample. Then, using a three-stage weighting process of "proportion-mean-restoration," it solves the statistical problem of insufficient samples while preserving the unique physical differences of each base station, thus improving the accuracy of material estimation. The entire process has low computational complexity, balancing efficiency and feasibility. Additionally, by integrating drawing information, the system, through the collaborative work of the as-built drawing digitization interface and the GIS network analysis engine, automatically extracts the quantities of materials used by the base station, such as the length of feeders, optical cables, power lines, and the number of junction boxes. Based on this, it calculates the required quantities of auxiliary materials, serving as a reference for the materials needed for emergency repairs.

[0046] Specifically, as a document recording the final state of a project, as-built drawings most accurately reflect the material usage on-site: namely, construction information such as the length of feeder lines, optical cables, power lines, and the number of junction boxes used in this project. By introducing as-built drawings into a digital interface and collaborating with a GIS network analysis engine, the automatic parsing and three-dimensional quantification of all elements can be completed in the cloud, calculating the total usage of auxiliary materials for this project within seconds. This solves the pain point of "paper drawings being inconvenient to carry around," and transforms static authoritative data into digital assets that can be accessed in real time, allowing the estimation of emergency repair materials to be traced directly back to the design source, simultaneously improving accuracy, compliance, and response speed.

[0047] Furthermore, the as-built drawings are imported into a unified coordinate system, and the "path length" and "node count" calculations are performed on the line layer using GIS network analysis functions to obtain the geometric length, inflection point coordinates, and junction box spatial location of each cable segment. Subsequently, the geometric data is mapped one-to-one with the engineering construction ledger (model, specifications, number of cores) through attribute hooking to generate a structured data table containing "length + quantity + specifications", so that the as-built drawing information can be effectively used in the process of emergency repair material calculation.

[0048] Furthermore, by accessing meteorological data, the system obtains relevant meteorological data from the local meteorological station within a 1km radius of the target base station in real time via a RESTful interface. This includes datasets for the past 24 hours and the next 12 hours, which are categorized by data characteristics as follows: Rainfall exceeding 50 mm in the past 24 hours or expected to exceed 50 mm in the next 12 hours is classified as "heavy rain"; minimum temperature ≤ -5℃ in the past 24 hours or the next 12 hours is classified as "low temperature"; maximum temperature ≥ 35℃ in the past 24 hours or the next 12 hours is classified as "high temperature"; gusts exceeding 17.2 m / s in any 3 seconds in the past 24 hours or the next 12 hours are classified as "strong wind"; all other conditions are classified as "normal".

[0049] The duration of this observation window is based on the meteorological industry recommended standard "QX / T116-2018", and it is widely used by emergency industries such as power and transportation as the "golden window for emergency repair decision-making". At the same time, the meteorological data with a 1km grid granularity has high accuracy, with precipitation error ≤±3mm, temperature error ≤±0.5℃, and wind error ≤±1m / s. The accuracy level meets the requirements of short-term fine forecasting and satisfies the decision-making needs of base station emergency repair.

[0050] Step 3, Fault Matching and Inventory Generation (≤30s): The system uses the target base station's three-source fusion model of "meteorological data - historical alarms - drawing reference" as its core, and completes the entire closed loop from alarm parsing to differentiated emergency repair package output within 30s, significantly reducing the need for on-site material replenishment.

[0051] Specifically, firstly, the alarm codes of the target base station are used to filter the historical alarm material usage data accessed in step two, and the records of emergency repair material usage under the same alarm code are found, denoted as H (History). Then, the system obtains the type and model of emergency repair materials through the "Alarm Code - Material Association Rule Table" (Table 1 below provides an example rule table, and the actual rules can be dynamically expanded according to operation and maintenance needs), and matches it with the data accessed from the drawing information in step two to obtain the material quantity and supporting auxiliary material quantity of the materials required for emergency repair in the engineering construction, denoted as D (Diagram). Thus, the basic estimated quantity of emergency repair materials B (Base) = MAX(H, D).

[0052] Table 1

[0053] When the number of historical alarm material samples is less than 30, the system directly uses the alarm code to associate with the standard package according to preset rules to configure the B value: optical cable alarms are configured with 500m of the same type and core number optical cable, 3 sets of junction boxes and other tools; main equipment alarms are configured with 1 spare board of the same type, 2 jumpers and other tools; power supply alarms are configured with 1 set of 12V low temperature batteries, 1 2kW portable generator and 5L of fuel oil.

[0054] Further, based on the geographical location of the target base station, the meteorological data access in step two is performed. After classifying the target base station by weather, additional materials are added, denoted as W (Weather): for high-temperature weather, heat dissipation components (such as cabinet heat sinks, thermal grease, etc.) are added; for heavy rain weather, waterproof components (such as IP67 waterproof junction boxes, quick-drying water-resistant tape, etc.) are added; for low-temperature weather, antifreeze components (such as flexible silicone heating film, low-temperature lubricating grease, etc.) are added; and for windy weather, wind-resistant reinforcement components (such as wind-resistant clamps, reinforcing cable ties, etc.) are added.

[0055] Therefore, the final estimated quantity Q (Quantity) = B + W. When the number of reference historical alarm material quantity samples for the target base station is ≥30, B = MAX(H, D); otherwise, the value of B is configured according to the standard package corresponding to the alarm type.

[0056] Step 4: Material Outbound Management (≤5min). Based on the generated emergency repair material list (B), the system analyzes the asset data from the operator's construction project digital management platform via an interface. Priority is given to outbound from the local county-level warehouse. If the local county-level warehouse's inventory is insufficient, cross-county warehouses or city-level warehouses are considered for allocation. The final allocation plan and the current fault alarm code are then transmitted back to the construction project digital management platform, which completes the outbound process. Furthermore, once the outbound scanning operation is completed, the corresponding inventory quantity is deducted from the asset data, and the material status is marked as "alarm code + emergency repair en route," achieving "synchronization of accounts and physical inventory" for total inventory, and enabling comprehensive management and tracking of material assets.

[0057] Step 5: Returning Remaining Materials to Warehouse. After the on-site emergency repairs are completed, the remaining materials are transported back to the material receiving warehouse. The barcode is scanned at the receiving point, and the current remaining quantity of materials is entered. The asset data is automatically added back to the inventory, and the material usage for this emergency repair is calculated. This portion of the materials is marked as "Alarm Code + Used for Emergency Repair," completing the synchronization of accounts and inventory.

[0058] Step Six: Closed-Loop Calibration. The system periodically retrieves asset data from the construction project digital management platform for materials with "alarm code + emergency repair usage" entries. It compares the estimated material quantity (B) corresponding to the alarm code with the actual consumption. When the error exceeds a preset threshold, the system initiates a manual root cause analysis function. Emergency repair personnel at the fault site report whether there were extreme scenarios such as sudden weather changes, construction errors, or external damage. The system auditor then reviews the data. If the deviation is indeed an unreproducible extreme event, the data set is marked as an "abnormal sample" and not written into the historical alarm material usage database. When the error is within the preset threshold range, the system automatically binds the material usage to the "Base Station ID—Feature Code—Fault Time—Professional Name—Equipment / Cable Type—Alarm Code" associated with the alarm at that time, and adds it to the historical alarm material usage database for dynamic calibration of the sample database.

[0059] Step 7: Hazard Remediation. The system periodically retrieves alarms from the database for analysis. If a base station experiences three or more alarms for the same single-board fault within six consecutive months, the system marks it as a "hardware defect" and pushes it to the operator's operation and maintenance system, requiring the operation and maintenance unit to complete root cause inspection and repair within a specified period. If it is confirmed to be a firmware defect, the manufacturer is required to complete the software upgrade within a specified period. If a base station experiences three or more alarms for the same professional domain cable fault within six consecutive months, the system marks it as a "line hazard" and pushes it to the operator, requiring the line maintenance unit to conduct on-site inspection and root cause inspection, and then complete the line relocation within a specified period.

[0060] Therefore, after acquiring the characteristic information of the alarm base station, this embodiment integrates three sources: historical alarm material usage, material usage associated with drawings, and local weather conditions. Using terrain feature coefficients as anchors, it dynamically weights the data according to local conditions, improving the scientific and rational estimation of emergency repair material usage. Regardless of complex terrain such as high mountains and rivers or severe weather such as wind and rain, it can output a differentiated emergency repair material list within minutes, reducing the probability of secondary replenishment, improving emergency repair efficiency, and completely transforming material allocation from experience-driven to data-driven. The minute-level output of the allocation list and the cross-warehouse linkage outbound process further compress the response time. The closed-loop calibration operation after the emergency repair is completed can continuously improve the accuracy of the historical emergency repair usage database based on actual consumption data, while providing a reference for adjusting the inventory structure of warehouse spare parts, reducing redundant materials and providing early warning of material shortage risks, significantly reducing inventory capital occupation, and improving the scientific and economical nature of inventory management.

[0061] Meanwhile, it can accurately identify and push network vulnerabilities related to single boards or lines to relevant personnel for handling, improving the timeliness and accuracy of vulnerability remediation. Moreover, it can extend from post-event repairs to pre-event prevention, and can expand the emergency repair material estimation function into an "intelligent operation and maintenance system" with self-learning and self-diagnosis capabilities.

[0062] In some embodiments, in step S130, based on the completed material usage, historical meteorological data, and corresponding historical configuration data of several candidate base stations configured for resolving fault types, the target base station is configured with materials for resolving fault types, including the following steps S210 to S240: Step S210: Obtain the corresponding historical completed material usage of several candidate base stations; Step S220: Calculate the single-site weighting coefficient of each candidate base station based on the ratio of historical configuration data and historical completed material usage corresponding to each candidate base station. Step S230: Calculate the average of the single-site weighting coefficients of several candidate base stations, and calculate the product between the average and the amount of materials used upon completion to obtain the estimated amount of material allocation. Step S240: Based on the estimated material allocation and historical meteorological data, allocate materials to the target base station.

[0063] In this embodiment, when the number of candidate base stations is sufficient (reaching a preset sample threshold), material allocation is performed using a first method. Specifically, the historical material usage of several candidate base stations is first obtained. The historical material usage represents the actual material consumption data during the base station construction phase, covering the usage of all categories of materials such as core equipment, cables, and auxiliary materials, directly reflecting the hardware configuration standards and scale of the candidate base stations.

[0064] Furthermore, based on historical data on completed material usage and configuration, a single-site weighting coefficient for each candidate base station is calculated to eliminate scale differences and provide a unified basis for comparison and integration of candidate base station samples of different sizes and configurations. Specifically, each candidate base station is treated as an independent accounting unit, and the calculation formula is as follows: ; Furthermore, based on the weighting coefficients of several candidate base stations and the amount of completed materials used by the target base station, the first configuration of the target base station is calculated. Specifically, the average weighting coefficient is first calculated by averaging the weighting coefficients of all candidate base stations to balance the individual differences of different candidate base stations. Then, the average weighting coefficient is multiplied by the amount of completed materials used by the target base station to obtain the estimated material configuration of the target base station.

[0065] Furthermore, by integrating the estimated quantity of materials to be allocated with specific meteorological requirements, a final materials allocation plan covering all scenarios is formed. Among them, the specific meteorological requirements are obtained based on the historical meteorological data of the target base station, and the corresponding preset list of meteorological materials is determined by the meteorological type (such as rainstorm, low temperature, high temperature, strong wind, etc.) corresponding to the historical meteorological data.

[0066] Specifically, the core framework is based on the estimated quantity of materials to be allocated, which clarifies the type, name, and quantity of basic materials. Then, corresponding special materials are matched according to the weather type (such as adding waterproof junction boxes and water-blocking tape in rainy weather, and adding antifreeze heating film in low temperature weather). The quantity of special materials is added to the estimated quantity of materials to be allocated, forming a complete material allocation plan. This ensures that the basic needs for core fault repair are met, while also adapting to special emergency repair scenarios under extreme weather conditions. This effectively reduces the need for secondary replenishment or repair delays caused by insufficient material adaptability, ensuring that the final solution of the first allocation method is both accurate and comprehensive.

[0067] In some embodiments, in step S240, the target base station is configured with resources based on the estimated resource allocation quantity and historical meteorological data, including the following steps S310 to S330: Step S310: Determine the weather type in the area where the target base station is located based on historical meteorological data; Step S320: Determine the first additional material configuration for the target base station from the database based on the weather type; the database contains the mapping relationship between weather types and materials; Step S330: Based on the estimated material allocation and the first additional material allocation, perform material allocation for the target base station.

[0068] In this embodiment, historical meteorological data of the target base station is first analyzed to determine the meteorological type of the area where the target base station is located. The analysis process follows preset standardized classification rules. For example: cumulative precipitation in the past 24 hours or expected precipitation in the next 12 hours ≥ 50 mm is classified as "heavy rain"; minimum temperature ≤ -5℃ is classified as "low temperature"; maximum temperature ≥ 35℃ is classified as "high temperature"; any 3-second gust ≥ 17.2 m / s (level 8 wind) is classified as "strong wind"; all other situations are classified as "normal". This standardized determination transforms multi-dimensional meteorological data into a unique and clear meteorological type, laying the foundation for subsequent accurate matching.

[0069] Furthermore, the first additional material configuration for the target base station is determined from the database based on the weather type. The database contains the mapping relationship between weather types and materials. It is a standardized set of materials customized based on long-term emergency repair practice and weather impact patterns. Each weather type corresponds to a unique additional material configuration scheme, which accurately matches the functional adaptation requirements of weather for emergency repair.

[0070] For example, in heavy rain, waterproof materials such as IP67 waterproof junction boxes, quick-drying water-blocking tape, and waterproof sealant are used to solve the problem of line insulation failure caused by rainwater immersion; in low temperature weather, antifreeze materials such as flexible silicone heating film, low temperature lubricant, and cold-proof insulation sleeves are used to prevent equipment from failing to start or cables from becoming brittle due to low temperatures; in high temperature weather, heat dissipation materials such as cabinet cooling fans, thermal grease, and cooling sprays are used to prevent equipment from overheating and shutting down; in windy weather, wind-resistant and reinforcing materials such as windproof clamps, reinforcing cable ties, and anti-fall anchors are used to ensure the safety of the repair process and the stability of the lines; normal weather corresponds to an empty list (no need to add).

[0071] Furthermore, based on the estimated quantity of materials and the first additional material allocation, materials are allocated to the target base station. This not only ensures the basic needs for core fault repair but also adapts to the special challenges brought by the weather, effectively reducing the delays in secondary replenishment or emergency repairs caused by insufficient material adaptability, and ensuring that the final solution of the first allocation method is both accurate and comprehensive.

[0072] In some embodiments, the resource allocation of the target base station in step S130 is performed in a first or second manner, including the following steps S410 to S440: Step S410: Determine the basic material configuration quantity corresponding to the fault type based on the fault type of the target base station; Step S420: Determine the weather type in the area where the target base station is located based on historical meteorological data; Step S430: Determine the second additional material configuration for the target base station from the database based on the weather type; the database contains the mapping relationship between weather types and materials; Step S440: Based on the basic material configuration quantity and the second additional material configuration, configure the target base station with materials.

[0073] In this embodiment, when the number of candidate base stations is insufficient (not reaching the preset sample threshold), resource allocation is performed using a second method. Specifically, firstly, the basic resource allocation quantity corresponding to the fault type is determined based on the fault type of the target base station, providing a stable basic framework for subsequent allocation. The mapping relationship between fault types and basic configurations has been solidified through a preset rule table.

[0074] For example, a transmission cable fault corresponds to the second configuration of "500m of the same type of optical cable, 3 sets of junction boxes, and 1 set of fusion splicing tools", and a power supply fault corresponds to the second configuration of "1 set of low temperature compatible batteries, 1 portable generator, and 5L of spare fuel".

[0075] Furthermore, based on historical meteorological data, the weather type within the target base station's area is determined. This allows for the identification of a second set of supplementary supplies from the database, ensuring the supplies can meet the unique challenges of extreme weather conditions and preventing repair delays due to incompatibility with standard basic configurations. The database contains a mapping between weather types and supplies. The preset weather configuration list is a customized set of supplies for various weather types, with each type corresponding to a unique supplementary configuration plan, directly addressing the functional requirements of weather-related repairs.

[0076] Furthermore, with the basic material allocation as the core framework, the second supplementary material allocation is used as a supplement to allocate materials to the target base station. This is to meet the core needs of line repair while also adapting to the waterproof requirements in rainstorm environments, thereby effectively reducing the probability of secondary replenishment and ensuring the efficient progress of emergency repair work.

[0077] In some embodiments, after configuring the target base station with resources in step S130 using the first or second method, the following steps S510 to S540 are further included: Step S510: Obtain inventory information of configurable material warehouses; configurable material warehouses include the home material warehouse to which the target base station belongs and at least one non-home material warehouse; Step S520: Determine the material configuration list for the target base station based on either the first or second method; Step S530: Determine the target configuration material warehouse based on the material configuration list and the inventory information of the configurable material warehouse; Step S540: Through the target configuration material library, execute the configuration task corresponding to the material configuration list, and update the inventory information and material status identifier of the target configuration material library; the material status identifier consists of the fault type of the target base station and the configuration status of the target configuration material library.

[0078] In this embodiment, inventory information of configurable material warehouses is obtained. These configurable material warehouses include the local material warehouse belonging to the target base station and at least one non-local material warehouse. Specifically, the local material warehouse is the local county bureau warehouse to which the target base station belongs. Its core advantages are proximity and simplified allocation process, which can minimize material transportation time and accurately match the core requirement of "timeliness first" for base station emergency repairs. The non-local material warehouses include cross-county warehouses, city-level warehouses, and other warehouses in higher-level or neighboring areas, serving as a supplementary guarantee to the local warehouses and avoiding delays in emergency repairs due to local inventory shortages or incomplete material specifications.

[0079] Specifically, inventory information can be obtained in real time by accessing asset data from the operator's digital management platform for construction projects via an interface. This data covers key information such as the type, specifications, current quantity, and storage location of the corresponding materials in each material warehouse, ensuring the real-time nature and accuracy of the data.

[0080] Furthermore, based on either the first or second method, a material configuration list for the target base station is determined, thereby identifying the final material configuration list required for the target base station. The inventory information of the local material warehouse is then checked, comparing the material types, specifications, and quantities in the material configuration list one by one. If the local warehouse can fully meet the list's requirements, it is directly designated as the target material warehouse, fully leveraging the time advantage of nearby allocation to minimize the time required to deliver materials to the repair site. If the local material warehouse has issues such as shortages of some materials or mismatched specifications, and cannot fully meet the list's requirements, the comparison is further expanded to non-local material warehouses. Priority is given to cross-county or city-level warehouses with sufficient inventory, shorter transportation distances, and convenient allocation processes. If necessary, a multi-warehouse joint allocation mode can be activated to ensure that all material requirements in the configuration list are fully covered, thus balancing allocation timeliness and feasibility while avoiding resource waste or repair delays caused by blind cross-regional allocation.

[0081] Furthermore, when executing configuration tasks, the target configuration material warehouse initiates a standardized outbound process based on the material configuration list. Through digital operations such as barcode scanning and system verification, it ensures that the type, specifications, and quantity of outbound materials are completely consistent with the list, thus avoiding material mismatch and omission issues caused by manual sorting and verification.

[0082] Furthermore, while the outbound operation is completed, the inventory information is updated in real time, and the inventory quantity of the corresponding outbound materials in the target configuration material warehouse is deducted, realizing the instant synchronization of inventory data with the actual outbound situation and ensuring the accuracy of inventory data. At the same time, the material status identifier is dynamically updated. The material status identifier is composed of the fault type of the target base station (associated with the fault identifier locked in the early stage, such as "transmission cable fault" and "power fault") and the configuration status (such as "in transit for repair" and "used for repair"). This not only realizes the precise binding of outbound materials with specific fault repair scenarios, but also clearly reflects the circulation stage of materials. This allows operation and maintenance management personnel to track the destination, use and current status of each batch of materials in real time, meeting the needs of overall material coordination and visual management. It not only ensures the rapid and accurate delivery of repair materials, but also strengthens the scientific and standardized nature of inventory management through dynamic asset control. It provides accurate asset data support for subsequent processes such as surplus material return, closed-loop calibration and sample optimization, forming a complete material management and configuration closed loop.

[0083] In some embodiments, after executing the configuration task corresponding to the material configuration list through the target configuration material library in step S530, and updating the inventory information and material status identifier of the target configuration material library, the following steps S610 to S640 are further included: Step S610: In response to the configuration completion command, obtain the remaining material information of the target base station; Step S620: Based on the remaining material information, update the inventory information and material status identifier of the target configuration material warehouse; Step S630: Calculate the configuration error based on the remaining material information and the material configuration list; Step S640: Based on the configuration error, generate historical samples of the target base station.

[0084] In this embodiment, upon receiving a configuration completion command, the remaining material information of the target base station is obtained. The configuration completion command is triggered by on-site repair personnel after the target base station fault is repaired, marking the official end of the material usage phase. Specifically, the remaining material information is obtained using digital methods such as barcode scanning. Its core content corresponds one-to-one with the material configuration list, including the type, specific name, and actual usage of the remaining materials, fully reflecting the actual consumption of materials during this repair operation and laying a data foundation for closed-loop management.

[0085] Furthermore, after obtaining the remaining material information, the inventory information is updated, and the quantity of the remaining materials is added back to the inventory data of the target configured material warehouse to achieve dynamic correction of the total inventory and ensure that the inventory data is completely consistent with the actual material status. The material status identifier is also updated. Materials previously marked as "fault type + emergency repair in transit" will be restored to the "normal inventory" status after the remaining part is returned to the warehouse, and the consumed part will be marked as "fault type + emergency repair used". This enables the visualization of the entire life cycle trajectory of materials from the time they are issued to the time they are returned, which makes it easier for maintenance personnel to trace the usage scenario of each batch of materials and provides support for refined asset management.

[0086] Furthermore, the actual consumption of materials in this emergency repair is calculated by the difference between the quantity in the material allocation list and the remaining quantity. Then, the allocation error is calculated to provide an objective standard for judging the validity of subsequent historical samples. The formula for calculating the allocation error is as follows: ; Furthermore, historical samples are generated based on configuration errors and preset error thresholds. The core basis for these historical samples is the comparison between the configuration error and the preset error threshold: when the configuration error is less than the preset threshold, it indicates that the accuracy of the current material configuration meets expectations, and the corresponding full data has extremely high reference value. The completed material usage, feature codes, alarm codes, historical meteorological data, material configuration lists, and remaining material information of the target base station are structurally integrated to form complete historical sample data, which is stored in the historical alarm material usage database. This expands the sample size for similar scenarios and optimizes the statistical regularity of the group samples through the added data, making subsequent base station material estimations more closely aligned with actual needs. If the configuration error is greater than or equal to the preset threshold, the data set is marked as invalid (to avoid contaminating the sample database), and manual root cause analysis is triggered to ensure the purity and effectiveness of the sample database, continuously strengthening the system's self-learning ability and estimation accuracy.

[0087] In some embodiments, in step S640, historical samples of the target base station are generated based on the configuration error, including the following steps S710 to S720: Step S710: Combine the completed material usage of the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station to obtain historical data; Step S720: Generate historical samples of the target base station based on historical data and sample labels of historical data; the sample labels are used to distinguish the types of historical data. The sample labels are determined through the following steps: Determine the sample label based on the configuration error; If the configuration error is less than the preset error threshold, the sample label is determined to be a valid sample; If the configuration error is greater than or equal to the preset error threshold, the sample label is determined to be an invalid sample, and a configuration error message is sent.

[0088] In this embodiment, historical data is first obtained by combining the completed material usage of the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station. Then, through sample label determination and full-link data integration, historical samples with both quality identification and complete dimensions are generated, which not only ensures the purity of the historical sample library, but also provides high-quality data support for subsequent pooling weighted estimation. The entire process is divided into two key steps: sample label determination and multi-dimensional data combination. Label determination is a prerequisite for data combination, ensuring that only samples that meet the quality requirements have practical reference value.

[0089] Specifically, in the sample label determination stage, the core criterion is the comparison between the configuration error and the preset error threshold. When the configuration error is less than the threshold, it indicates that the estimated result of this material configuration is highly consistent with the actual needs, and the corresponding configuration data has statistical reference value. Therefore, the sample label of the historical data is determined as "valid sample". When the configuration error is greater than or equal to the threshold, it means that there is a significant deviation in this configuration. There may be unreproducible extreme scenarios behind it, such as sudden weather changes or construction misoperation. If the data is included in the sample library, it will interfere with the accuracy of the subsequent estimation model. Therefore, the sample label is determined as "invalid sample".

[0090] Simultaneously, for invalid samples, a configuration anomaly alert is sent, covering the core data of this configuration (such as fault type, weather type, configuration list, and error value). The purpose is to trigger manual intervention to analyze the root cause, providing a basis for handling this anomaly and accumulating experience for subsequent optimization of configuration rules and avoidance of similar deviations, thus forming a closed-loop control system of "anomaly detection - root cause investigation - rule optimization".

[0091] Furthermore, in the multi-dimensional data combination stage, sample labels and core data across the entire chain are structurally integrated to form a complete historical sample. This ensures that when the sample is used subsequently, the configuration scenario, estimation logic, and actual deviation can be accurately traced, providing a comprehensive data analysis basis for model optimization and continuously improving the accuracy of subsequent material allocation.

[0092] like Figure 2 As shown in some embodiments of this application, a material allocation system for a communication base station is provided. The system includes an acquisition module 210, a matching module 220, and a configuration module 230. Specifically: The acquisition module 210 is used to acquire the amount of completed construction materials used for the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station; The matching module 220 is used to match several candidate base stations in the base station database according to the base station type and fault type of the target base station; the candidate base stations are base stations with the same base station type as the target base station and have experienced the fault type. The configuration module 230 is used to configure materials for the target base station in either a first method or a second method. The first method is to configure materials for the target base station to resolve the fault type based on the amount of materials used upon completion, historical meteorological data, and corresponding historical configuration data of several candidate base stations configured to resolve the fault type. The second method is to configure materials for the target base station to resolve the fault type based on the amount of materials used upon completion, historical meteorological data, base station type, and fault type.

[0093] It should be noted that the communication base station material allocation system provided in this embodiment is based on the same inventive concept as the communication base station material allocation method described above. Therefore, the relevant content of the communication base station material allocation method described above also applies to the content of the communication base station material allocation system. Therefore, it will not be repeated here.

[0094] In this embodiment, the system matches several candidate base stations in the base station database based on the target base station's base station type and fault type. Candidate base stations are those with the same base station type as the target base station and have experienced the same fault type. The system then configures resources for the target base station using either a first method or a second method. The first method configures resources for the target base station based on the amount of completed materials used, historical meteorological data, and corresponding historical configuration data of the candidate base stations configured to resolve the fault type. The second method configures resources for the target base station based on the amount of completed materials used, historical meteorological data, base station type, and fault type. This allows for the selection of similar base stations based on base station type and fault type, and the fusion of multi-source data for resource configuration, improving configuration accuracy, shortening the cycle, and increasing repair efficiency.

[0095] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-mentioned method for allocating resources for a communication base station.

[0096] like Figure 3 , Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. The electronic device includes: At least one battery; At least one memory; At least one processor; At least one program; The program is stored in memory, and the processor executes at least one program to implement the above-described method for configuring materials for a communication base station.

[0097] This electronic device can be any smart terminal, including mobile phones, tablets, personal digital assistants (PDAs), and in-vehicle computers.

[0098] The electronic devices according to embodiments of this application will now be described in detail.

[0099] The processor 1600 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this disclosure. The memory 1700 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 1700 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1700 and is called and executed by the processor 1600 to execute a method for configuring resources in a communication base station according to an embodiment of this disclosure.

[0100] The input / output interface 1800 is used to implement information input and output. The communication interface 1900 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 2000 transmits information between various components of the device (e.g., processor 1600, memory 1700, input / output interface 1800, and communication interface 1900); The processor 1600, memory 1700, input / output interface 1800 and communication interface 1900 are connected to each other within the device via bus 2000.

[0101] This disclosure also provides a storage medium, which is a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the above-described method for configuring materials for a communication base station.

[0102] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0103] The embodiments described in this disclosure are for the purpose of more clearly illustrating the technical solutions of this disclosure and do not constitute a limitation on the technical solutions provided by this disclosure. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by this disclosure are also applicable to similar technical problems.

[0104] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this disclosure, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0105] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0106] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0107] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any related variations, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0108] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0110] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0111] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0112] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0113] The above is a detailed description of the preferred embodiments of this application. However, the embodiments of this application are not limited to the above-described implementation methods. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the embodiments of this application. All such equivalent modifications or substitutions are included within the scope defined by the claims of the embodiments of this application.

[0114] The embodiments of this application have been described in detail above with reference to the accompanying drawings. However, this application is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of this application.

Claims

1. A method for allocating resources for a communication base station, characterized in that, The method includes: Acquire the amount of construction materials used for the completed construction of the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station; Based on the base station type and fault type of the target base station, several candidate base stations are matched in the base station database; the candidate base stations are base stations with the same base station type as the target base station and have experienced the fault type. The target base station is configured with materials using either a first method or a second method. The first method is to configure materials for the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, and the corresponding historical configuration data of the candidate base stations configured to resolve the fault type. The second method is to configure materials for the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, the base station type, and the fault type.

2. The method for allocating resources for a communication base station according to claim 1, characterized in that, The step of configuring materials for resolving the fault type on the target base station based on the completed material usage, the historical meteorological data, and the corresponding historical configuration data of the several candidate base stations configured to resolve the fault type includes: Obtain the corresponding historical completed material usage for the aforementioned candidate base stations; The single-site weighting coefficient of each candidate base station is calculated based on the ratio of the historical configuration data corresponding to each candidate base station to the historical completed material usage. Calculate the mean of the single-site weighting coefficients of the candidate base stations, and calculate the product between the mean and the amount of materials used upon completion to obtain the estimated amount of material allocation; Based on the estimated amount of material allocation and the historical meteorological data, material allocation is performed on the target base station.

3. The material allocation method for a communication base station according to claim 2, characterized in that, The process of allocating resources to the target base station based on the estimated resource allocation and the historical meteorological data includes: Based on the historical meteorological data, determine the meteorological type of the area where the target base station is located; The first additional material configuration for the target base station is determined from the database based on the weather type; the database contains a mapping relationship between the weather type and the materials. Based on the estimated resource allocation and the first additional resource allocation, resource allocation is performed on the target base station.

4. The material allocation method for a communication base station according to claim 1, characterized in that, The step of allocating materials to the target base station based on the completed material usage, historical meteorological data, base station type, and fault type to resolve the fault type includes: Based on the fault type of the target base station, determine the basic material configuration quantity corresponding to the fault type; Based on the historical meteorological data, determine the meteorological type of the area where the target base station is located; The second additional material configuration for the target base station is determined from the database based on the weather type; the database contains a mapping relationship between the weather type and the materials. Based on the basic resource allocation and the second additional resource allocation, the target base station is configured with resources.

5. The method for allocating resources for a communication base station according to claim 1, characterized in that, After configuring resources for the target base station using the first or second method, the method further includes: Obtain inventory information of configurable material warehouses; the configurable material warehouses include the home material warehouse to which the target base station belongs and at least one non-home material warehouse; Based on the first method or the second method, determine the material configuration list of the target base station; Based on the material configuration list and the inventory information of the configurable material warehouse, determine the target configuration material warehouse; The target configuration material library is used to execute the configuration task corresponding to the material configuration list, and update the inventory information and material status identifier of the target configuration material library; the material status identifier consists of the fault type of the target base station and the configuration status of the target configuration material library.

6. The material allocation method for a communication base station according to claim 5, characterized in that, After executing the configuration task corresponding to the material configuration list through the target configuration material library, and updating the inventory information and material status identifier of the target configuration material library, the method further includes: In response to the configuration completion command, obtain the remaining material information of the target base station; Based on the remaining material information, update the inventory information and material status identifier of the target configuration material warehouse; Based on the remaining material information and the material configuration list, the configuration error is calculated; Based on the configuration error, a historical sample of the target base station is generated.

7. The method for allocating resources for a communication base station according to claim 6, characterized in that, The step of generating historical samples of the target base station based on the configuration error includes: Historical data is obtained by combining the completed material usage of the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station. Based on the historical data and the sample tags of the historical data, a historical sample of the target base station is generated; the sample tags are used to distinguish the type of the historical data. The sample label is determined through the following steps: The sample label is determined based on the configuration error; If the configuration error is less than a preset error threshold, the sample label is determined to be a valid sample. If the configuration error is greater than or equal to a preset error threshold, the sample label is determined to be an invalid sample, and a configuration error message is sent.

8. A material allocation system for a communication base station, characterized in that, The system includes: The acquisition module is used to acquire the amount of completed construction materials used for the target base station, historical meteorological data of the area where the target base station is located, and the base station type and fault type of the target base station; The matching module is used to match several candidate base stations in the base station database according to the base station type and fault type of the target base station; the candidate base stations are base stations with the same base station type as the target base station and have experienced the fault type. A configuration module is used to configure materials for the target base station in either a first method or a second method. The first method is to configure materials for the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, and the corresponding historical configuration data of the several candidate base stations configured to resolve the fault type. The second method is to configure materials for the target base station to resolve the fault type based on the completed material usage, the historical meteorological data, the base station type, and the fault type.

9. An electronic device, characterized in that, It includes at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor, which, when executed by the at least one control processor, enable the at least one control processor to perform a material allocation method for a communication base station as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform a material allocation method for a communication base station as described in any one of claims 1 to 7.

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