Power marketing single soldier equipment operation method, system, device and medium

Abstract

This invention discloses a method, system, equipment, and medium for individual equipment operation in power marketing. The method includes: acquiring equipment operation data of the individual equipment and biometric data of the operator; extracting tool identifiers from the equipment operation data; determining the binding relationship between the individual equipment and the operator based on the tool identifiers and biometric data; and filtering a set of target tools available to the operator from the equipment operation data based on the binding relationship; inputting the set of target tools into a preset tool usage rule base for matching to determine several tool usage parameters; weighting each tool usage parameter, task priority value, and tool usage frequency parameter to obtain a tool scheduling priority sequence corresponding to each tool; and generating a task execution plan based on the tool scheduling priority sequence and work order information. This application enables efficient collaborative scheduling of personnel identity, tool status, and task assignment in power marketing field operations.

Description

Technical Field

[0001] This invention relates to the field of individual soldier equipment operations, and more particularly to methods, systems, equipment and media for individual soldier equipment operations in power marketing. Background Technology

[0002] In the field operations of power marketing, individual equipment refers to a collection of portable work equipment and tools carried and used by on-site personnel to complete specific tasks such as meter reading, meter installation and power connection, fault handling, and customer service. The operational methods directly affect work order execution efficiency, on-site safety, and service quality. With the continuous expansion of power marketing business, the sustained increase in the number of work orders, and the increasing complexity of operational scenarios, the traditional experience-driven operational model is no longer sufficient to meet the requirements of real-time control of equipment status, adherence to personnel operating procedures, and precise matching of tools to tasks.

[0003] However, in existing technologies, individual equipment operations mainly rely on manual preparation and experience-based judgment, lacking real-time perception and unified management of equipment status, making it difficult to obtain key information such as tool battery level, location, and condition in a timely manner. Secondly, tool allocation is mostly based on static ledgers, failing to be dynamically adjusted according to actual operational needs, resulting in low resource utilization efficiency. In addition, during operation, there is a lack of effective verification mechanisms for personnel identity and operating procedures, posing risks of equipment misuse and violations, thus limiting the overall efficiency and safety level of power marketing field operations. Summary of the Invention

[0004] This invention provides a method, system, equipment, and medium for individual equipment operation in power marketing, which enables efficient and coordinated scheduling of personnel identity, tool status, and work tasks in power marketing field operations.

[0005] In a first aspect, embodiments of the present invention provide a method for operating individual equipment in electricity marketing, wherein the individual equipment includes a plurality of tools and implements, and the method includes: Acquire equipment operation data of individual soldiers and biometric data of operators; Extract tool identifiers from the equipment operation data, determine the binding relationship between individual equipment and operators based on the tool identifiers and the biometric data, and filter out a set of target tools available to the operators from the equipment operation data based on the binding relationship; The target set of tools is input into a preset tool usage rule base for matching to determine several tool usage parameters. The tool usage parameters, job priority values ​​and tool usage frequency parameters are weighted and calculated to obtain the tool scheduling priority sequence corresponding to each tool. The job priority value and the tool usage frequency parameter are determined based on the acquired work order information and historical job records, respectively. Based on the tool scheduling priority sequence and the work order information, the tool allocation relationship and job step sequence corresponding to each work order are determined to generate a job execution plan.

[0006] This invention, by acquiring equipment operation data and biometric data, can accurately identify operators and obtain the real-time status of their equipment during power marketing field operations, providing reliable data support for efficient collaborative scheduling of personnel and tools. By filtering the set of target tools available to operators from equipment operation data based on binding relationships, it can automatically establish binding relationships between operators and tools during power marketing field operations, and select operable target tools, achieving efficient matching of personnel identity and tool status, supporting collaborative scheduling. Furthermore, by adding parameters such as tool usage parameters, operation priority values, and tool usage frequency parameters... The weighted calculation yields the tool scheduling priority sequence corresponding to each tool. In power marketing field operations, by comprehensively analyzing tool characteristics, task priorities, and historical usage, a scientific and reasonable tool scheduling priority sequence can be generated, achieving optimized coordination between tool status and task. By determining the tool allocation relationship and task sequence corresponding to each work order based on the tool scheduling priority sequence and work order information to generate a work execution plan, the tool scheduling priority and work order information can be organically combined in power marketing field operations to generate the optimal tool allocation and task sequence plan, achieving efficient coordinated execution of personnel identity, tool status, and task.

[0007] Furthermore, the step of determining the binding relationship between individual soldier equipment and operator based on the tool identifier and the biometric data includes: Feature extraction is performed on the biometric data to obtain a set of biometric points, and the set of biometric points is encoded and converted to obtain biometric codes; The biometric code is matched with a preset authorized personnel feature database to obtain the personnel identity verification result; The personnel authentication results are associated and mapped with the tool identifiers to determine the binding relationship between individual equipment and operators.

[0008] This invention enables rapid verification of personnel identity by encoding and matching the operator's biometric features, and associates the verification results with tool identification. This allows for precise binding of personnel identity with individual equipment in power marketing field operations, thereby supporting efficient collaborative scheduling of personnel, tools, and tasks.

[0009] Furthermore, the step of filtering the set of target tools and implements available to the operator from the equipment operation data based on the binding relationship includes: Based on the binding relationship, the target tool identifier corresponding to the operator is determined, and based on the target tool identifier, the corresponding tool power monitoring data, Beidou positioning information and tool function test parameters are extracted from the equipment operation data. The power monitoring data of the tools, the Beidou positioning information, and the tool function test parameters are normalized to obtain standardized power monitoring data of the tools, standardized Beidou positioning information, and standardized tool function test parameters, respectively. The standardized tool power monitoring data, the standardized Beidou positioning information, the standardized tool function test parameters and preset weights are weighted and summed to obtain the comprehensive status index corresponding to each tool. The comprehensive status indicators are compared with the available status information in the preset tool and equipment inventory ledger to select the target tool and equipment set that meets the preset conditions.

[0010] This invention enables precise identification of a set of target tools by comprehensively evaluating and screening the power, location, and functional status of available tools for operators. This allows for efficient coordination and scheduling of personnel, tools, and tasks in power marketing field operations.

[0011] Furthermore, the step of inputting the target set of tools into a preset tool usage rule base for matching is used to determine several tool usage parameters, including: Based on the tool code of each tool in the target tool set, the tool usage rules corresponding to each tool code are matched from the tool usage rule base to obtain the tool usage rule set. The set of tool usage rules is structured and parsed to extract personnel permission constraints, equipment status constraints, and work scenario adaptation conditions, so as to determine several tool usage parameters based on the personnel permission constraints, equipment status constraints, and work scenario adaptation conditions.

[0012] This invention, through rule-based matching and constraint parsing, accurately determines the usage parameters of each tool and implements intelligent adaptation to personnel permissions, equipment status, and work scenarios, thereby supporting efficient collaborative scheduling in power marketing field operations.

[0013] Furthermore, the step of weighting the tool usage parameters, job priority values, and tool usage frequency parameters to obtain the tool scheduling priority sequence corresponding to each tool includes: Based on the acquired work order information, the job type, job completion deadline, and job target location are extracted, and the job type, job completion deadline, and job target location are quantified to obtain job priority values; Based on the historical work records, the number of times each tool is used is counted, and the number of times each is used is classified and quantified according to the preset usage frequency classification rules to obtain the tool usage frequency parameters. The tool scheduling score for each tool is obtained by weighting the tool usage parameters, the job priority value, the tool usage frequency parameter, and the preset weight coefficient. Based on the scheduling scores of each tool, the tools are sorted to obtain the tool scheduling priority sequence.

[0014] This invention generates a tool scheduling priority sequence by weighting and integrating tool usage parameters, job priority values, and tool usage frequency, thereby achieving a scientific sorting of tools and equipment, and improving the collaborative efficiency of personnel, tools, and tasks in power marketing field operations.

[0015] Furthermore, the step of determining the tool allocation relationship and job step sequence corresponding to each job order based on the tool scheduling priority sequence and the work order information to generate a job execution plan includes: Based on the tool scheduling priority sequence and the job type and worker allocation in the work order information, determine the tools and tool usage order corresponding to each work order, so as to form a tool allocation relationship based on each tool and tool usage order; The tool allocation relationship and the order of work steps are summarized to obtain the work execution plan, wherein the order of work steps is obtained by dividing the work process based on the work type, the work completion time limit and the tool allocation relationship.

[0016] This invention generates tool allocation relationships and work step sequences based on tool scheduling priorities and work order information to form a complete work execution plan, thereby achieving efficient collaborative scheduling of personnel, tools, and tasks in power marketing field operations.

[0017] Furthermore, after determining the tool allocation relationship and work step sequence corresponding to each work order to generate a work execution plan, the method further includes: Collect job execution status data during the execution of the job execution plan, and perform a difference analysis between the job execution status data and the obtained historical operation and maintenance reference data to obtain job operation and maintenance evaluation indicators; The operation and maintenance evaluation indicators and preset tool lifecycle parameters are input into a preset fault early warning model to perform trend extrapolation and obtain equipment operation and maintenance evaluation values. The deviation coefficient between the equipment operation and maintenance assessment value and the preset standard value is calculated, and a deviation level judgment result is generated based on the deviation coefficient. The abnormal situation at the power marketing operation site is responded to based on the deviation level judgment result.

[0018] This invention enables dynamic monitoring and response to abnormal operations at power marketing sites by real-time collection of work execution status, historical comparison, fault early warning trend projection, and deviation level determination, thereby ensuring efficient collaborative scheduling of personnel, tools, and work tasks.

[0019] Secondly, embodiments of the present invention provide a single-soldier equipment operation system for power marketing, the system comprising: an acquisition module, a binding module, a matching module, and an operation module; The acquisition module is used to acquire equipment operation data of individual soldier equipment and biometric data of operators; The binding module is used to extract tool identifiers from the equipment operation data, determine the binding relationship between individual equipment and operators based on the tool identifiers and the biometric data, and filter out a set of target tools available to the operators from the equipment operation data based on the binding relationship. The matching module is used to input the target set of tools into a preset tool usage rule base for matching, so as to determine several tool usage parameters. The tool usage parameters, job priority values ​​and tool usage frequency parameters are weighted and calculated to obtain the tool scheduling priority sequence corresponding to each tool. The job priority value and the tool usage frequency parameters are determined based on the acquired work order information and historical job records, respectively. The job module is used to determine the tool allocation relationship and job step sequence corresponding to each job order based on the tool scheduling priority sequence and the job order information in order to generate a job execution plan.

[0020] This invention achieves efficient collaborative scheduling of personnel identity, tool status, and work tasks in power marketing field operations by acquiring personnel and equipment data, binding operation relationships, matching tool usage rules, and optimizing scheduling order.

[0021] Thirdly, embodiments of the present invention provide a terminal device, including: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction that causes the processor to perform operations of the individual equipment operation method for power marketing as described in this application.

[0022] Fourthly, embodiments of the present invention provide a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device or system where the computer-readable storage medium is located to perform the individual equipment operation method for electricity marketing as described in this application.

[0023] Based on the above-described method embodiments, another embodiment of the present invention provides a computer program product, including a computer program or instructions, which, when executed by a communication device, implements the individual equipment operation method for power marketing according to any embodiment of the present invention.

[0024] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0025] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0026] Figure 1 This is a flowchart illustrating one embodiment of the individual equipment operation method for electricity marketing provided in this application; Figure 2 This is a flowchart illustrating steps S201 to S203 provided in this application; Figure 3 This is a flowchart illustrating steps S301 to S304 provided in this application; Figure 4 This is a schematic diagram of the functional modules of the individual soldier equipment operation management system provided in this application; Figure 5 This is a schematic diagram of a structural embodiment of the individual equipment operation method for electricity marketing provided in this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0029] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0030] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0031] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0032] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0033] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0034] In power marketing field operations, individual equipment refers to portable devices and tools carried and used by individual operators to complete tasks such as meter reading, meter installation and connection, fault handling, and customer service. The operational methods directly impact work order efficiency, safety, and service quality. With the expansion of business scale and the increasing complexity of operational scenarios, traditional experience-driven models struggle to monitor equipment status in real time, constrain personnel operating procedures, and achieve precise matching of tools and tasks. Existing technologies rely on manual preparation and static ledgers, lacking real-time information such as tool power, location, and condition. Tool allocation is not dynamic enough, and there is a lack of identity verification and operational procedure validation, resulting in low resource utilization efficiency, high operational risks, and hindering improvements in field operation efficiency and safety.

[0035] See Figure 1 In order to achieve efficient coordinated scheduling of personnel identity, tool status and work tasks in power marketing field operations, an embodiment of the present invention provides a method for individual equipment operation in power marketing, including steps S101 to S104. Step S101: Obtain equipment operation data of individual soldier equipment and biometric data of operators; In some embodiments, firstly, real-time signals are collected through the radio frequency chip built into the individual soldier's equipment and the RFID tags on the tools. A rapid self-organizing network is then constructed using LoRa technology to achieve efficient data communication between the tools and the equipment. This extracts information such as the tool's unique identifier, factory code, historical usage count, and current storage location. A data acquisition quality sequence is constructed based on the radio frequency signal strength and transmission stability, forming a raw radio frequency data set to provide foundational data for subsequent analysis. Secondly, by accessing the raw radio frequency data set, facial recognition images and fingerprint features of the operator are collected. Feature points are extracted and encoded from the collected biometric data. The processed feature data is compared with an authorized personnel feature database, and feature data meeting the matching criteria are selected to generate a biometric verification result set, enabling accurate verification of the operator's identity. Secondly, after completing personnel identity verification, the biometric verification result set is invoked to obtain the power monitoring data of tools, Beidou positioning information, and tool function test parameters. Various types of data are normalized and multi-source information is integrated through weighted calculation to extract key status indicators, including tool RFID tags, personnel biometric codes, location coordinate parameters, remaining power percentage, and tool integrity coefficient. Finally, equipment operation data of individual soldier equipment is generated, realizing comprehensive and real-time status perception of individual soldier equipment and tools used, providing a data foundation for subsequent inventory ledger matching, intelligent tool scheduling, and collaborative work processes.

[0036] Through the above steps, accurate identification of individual equipment and operators can be achieved, while the status, location and functional parameters of tools and equipment can be obtained, enabling real-time and comprehensive perception of personnel, equipment and tools in power marketing field operations, and providing a data foundation for intelligent scheduling and operational collaboration.

[0037] Step S102: Extract tool identifiers from the equipment operation data, determine the binding relationship between individual equipment and operators based on the tool identifiers and the biometric data, and filter out a set of target tools available to the operators from the equipment operation data based on the binding relationship. Please refer to Figure 2 In some embodiments, determining the binding relationship between individual soldier equipment and operator based on the tool identifier and the biometric data includes: steps S201 to S203; Step S201: Extract features from the biometric data to obtain a set of biometric points, and encode the set of biometric points to obtain biometric codes; In some embodiments, Gaussian filtering is applied to the face recognition image for noise reduction, and the MTCNN face detection model is used for facial region localization. Affine transformation is performed for pose correction, and the coordinates of 68 facial key points are calibrated. Background noise and invalid information are removed to obtain a standardized face image. For the fingerprint image, grayscale processing, binarization transformation, and ridge thinning are performed sequentially, and false feature points are removed to highlight the fingerprint ridge topology, forming a standardized fingerprint image. After preprocessing, deep feature extraction is performed on the standardized face image based on the ArcFace convolutional neural network model to generate a 512-dimensional vector representing the unique features of the face, forming a complete set of facial feature points. Next, ridge tracking and minutiae detection algorithms are applied to the fingerprint image to extract endpoints, bifurcation points, and other minutiae feature points. The planar coordinates, ridge direction angle, feature point type, and topological relationships of adjacent feature points of each feature point are recorded to generate a fingerprint feature point set. Finally, the facial feature point set and fingerprint feature point set are mapped to the [0,1] interval to complete the normalization encoding, so as to eliminate the dimensional differences caused by different acquisition devices and acquisition angles. The SM4 symmetric encryption algorithm is used for encryption conversion to generate fixed-length, uniquely corresponding facial biometric codes and fingerprint biometric codes, forming a biometric code that the system can recognize, providing safe and reliable data input for subsequent similarity comparison.

[0038] Step S202: Match the biometric code with a preset authorized personnel feature database to obtain the personnel identity verification result; In some embodiments, the cosine similarity calculation method is used to compare the collected code with the codes of each authorized person in the feature library one by one. The facial feature matching threshold is set to 90%, the fingerprint feature matching threshold is set to 85%, and the corresponding feature matching threshold is set to 92% in the single feature verification mode. Based on the matching degree result, it is determined whether each biometric feature passes the verification, and finally a comprehensive verification result is generated, including the equipment RFID unique identifier, the operator's identity ID, the facial and fingerprint matching degree, the comprehensive verification judgment result and the verification timestamp, forming a structured personnel identity verification result, providing a basis for binding equipment and personnel.

[0039] Step S203: Associate the personnel authentication result with the tool identifier to determine the binding relationship between individual equipment and operator.

[0040] In some embodiments, the unique RFID identifier and factory code of the equipment are extracted from the raw RFID data generated by the RFID data acquisition submodule. A temporary binding relationship is then established between the verified operator's ID and the corresponding equipment, achieving a one-to-one mapping between individual equipment and operators. This binding relationship not only records the specific equipment range operable by the operator but also provides a foundation for subsequent data retrieval by the multi-dimensional status fusion module, enabling precise association between equipment status and personnel identity. This provides reliable data support for the execution of intelligent tool control, workflow collaboration, and remote control modules.

[0041] In some embodiments, the step of filtering the set of target tools available to the operator from the equipment operation data based on the binding relationship includes: determining the target tool identifier corresponding to the operator based on the binding relationship, and extracting the corresponding tool power monitoring data, BeiDou positioning information, and tool function test parameters from the equipment operation data based on the target tool identifier; normalizing the tool power monitoring data, the BeiDou positioning information, and the tool function test parameters to obtain standardized tool power monitoring data, standardized BeiDou positioning information, and standardized tool function test parameters; weighting and summing the standardized tool power monitoring data, the standardized BeiDou positioning information, the standardized tool function test parameters, and preset weights to obtain a comprehensive status index corresponding to each tool; and comparing each comprehensive status index with the available status information in a preset tool inventory ledger to filter out the set of target tools that meet preset conditions.

[0042] In some embodiments, the target tool identifier corresponding to the operator is determined based on the binding relationship, and the corresponding tool power monitoring data, BeiDou positioning information, and tool function test parameters are extracted from the equipment operation data based on the target tool identifier. Specifically, firstly, based on the generated binding relationship between individual equipment and operators, the target tool identifier corresponding to each operator is determined, and then the real-time operation data corresponding to the target tool is extracted from the equipment operation data, specifically including tool power monitoring data, BeiDou positioning information, and tool function test parameters. The power monitoring data includes the remaining power percentage, estimated battery life, charging status, and power fluctuation trend; the BeiDou positioning information includes real-time latitude and longitude coordinates, altitude information, and offset from the inventory ledger storage location code; the tool function test parameters include tool self-inspection results, key function response time, fault alarm level, and sensor status, etc. By calling the unique RFID identifier in the equipment operation data and matching it with the target tool identifier, a one-to-one correspondence between the operator and the target tool operation data is achieved.

[0043] In some embodiments, the tool power monitoring data, the BeiDou positioning information, and the tool function test parameters are normalized to obtain standardized tool power monitoring data, standardized BeiDou positioning information, and standardized tool function test parameters. Specifically, the extracted tool power monitoring data, BeiDou positioning information, and tool function test parameters are normalized to eliminate differences in the dimensions of various data and unify the scale, resulting in a standardized dataset. First, the tool power monitoring data is linearly mapped to the [0,1] interval, where the remaining power percentage is set to 30%. 100% linear normalization processing, battery life is set to 0. First, the system normalizes the coordinates over a 10-hour interval. Second, it spatially maps the real-time coordinates to the preset coordinates in the inventory ledger using BeiDou positioning information, and linearly maps the position offset to the [0,1] interval according to the maximum tolerable offset (e.g., 5 meters). Finally, the tool function test parameters are normalized according to the importance of each function indicator and preset thresholds; for example, the self-test success rate is normalized to 0. With 100% normalization, the critical response time is linearly mapped to the optimal and worst response times, and the fault warning level is mapped to 0, 0.5, and 1.0 for low, medium, and high risks, respectively. Finally, standardized tool power monitoring data, standardized Beidou positioning information, and standardized tool function test parameters are obtained, providing a unified input for multi-dimensional state fusion calculation.

[0044] In some embodiments, the standardized tool power monitoring data, the standardized BeiDou positioning information, the standardized tool function test parameters, and preset weights are weighted and summed to obtain a comprehensive status index for each tool. Specifically, weights are assigned to various data dimensions: power monitoring data has a weight of 25%, BeiDou positioning information has a weight of 20%, tool function test parameters have a weight of 20%, and RFID tag and biometric data have a combined weight of 35%. Each normalized data value is multiplied by its corresponding weight and then summed to form the comprehensive status index. This index reflects the overall status of each tool across multiple dimensions, including power adequacy, location accuracy, functional integrity, and operator access control, and is used for subsequent inventory matching and scheduling priority ranking.

[0045] In some embodiments, the comprehensive status indicators are compared with the available status information in the preset tool inventory ledger to filter out a set of target tools that meet preset conditions. Specifically, the comprehensive status indicators of each tool are compared with the power threshold, integrity standard, storage location, and usage rights of the corresponding entry in the inventory ledger. When the comprehensive status indicators meet all preset thresholds and the location deviation is within the allowable range, the tool integrity meets the standard, and the operator has usage rights, the tool is included in the available target set; otherwise, it is marked as unavailable or pending maintenance, and an anomaly identifier is generated in the ledger matching result set to ensure that scheduling and job execution only select tools that meet the conditions, thereby achieving intelligent matching and precise scheduling of job tools.

[0046] Through the above steps, a comprehensive status perception and multi-dimensional assessment of the operator's identity, individual equipment, and tools can be achieved, accurately selecting available target tools and providing reliable data support for the intelligent matching and efficient collaborative scheduling of personnel, equipment, and tools in power marketing field operations.

[0047] Step S103: Input the target set of tools into a preset tool usage rule base for matching to determine several tool usage parameters. Perform weighted calculation on each tool usage parameter, job priority value and tool usage frequency parameter to obtain the tool scheduling priority sequence corresponding to each tool. The job priority value and the tool usage frequency parameter are determined based on the acquired work order information and historical job records, respectively. In some embodiments, the step of inputting the target set of tools into a preset tool usage rule base for matching to determine several tool usage parameters includes: matching tool usage rules corresponding to each tool code from the tool usage rule base based on the tool code of each tool in the target set of tools to obtain a tool usage rule set; performing structured parsing on the tool usage rule set to extract personnel permission constraints, equipment status constraints, and work scenario adaptation conditions, so as to determine several tool usage parameters based on the personnel permission constraints, the equipment status constraints, and the work scenario adaptation conditions.

[0048] In some embodiments, based on the tool codes of each tool in the target tool set, the tool usage rules corresponding to each tool code are matched from the tool usage rule base to obtain a tool usage rule set. Specifically, based on the mapping relationship between the preset tool inventory ledger and equipment operation data, the unique code of each tool in the target tool set is associated with the permission rules pre-stored in the rule base. Static rule data (such as high-voltage operation tools can only be operated by high-voltage certified personnel, and insulation tools can only be used by maintenance teams) and dynamic constraint data (such as tool integrity standards, power thresholds, operator permission compliance, etc.) are retrieved, and combined with the work scenario adaptation conditions (such as high-frequency use can only be used by maintenance teams, and emergency work orders can temporarily relax permissions, etc.) to form a complete tool usage rule set covering personnel permissions, equipment status, and work scenario dimensions, providing a comprehensive rule foundation for subsequent scheduling strategies. Taking the intelligent high-voltage detector (unique tool code GY-001) as an example, the matched tool usage rules include the usage permission scope recorded in the inventory database for high-voltage certified personnel and equipment integrity standards. 90%, standard power threshold 30%, and the requirement that high-frequency tools be used only by the maintenance team to adapt to the work scenario, form the rule set entries for this tool.

[0049] In some embodiments, the tool usage rule set is structured and parsed to extract personnel permission constraints, equipment status constraints, and work scenario adaptation conditions. Several tool usage parameters are then determined based on these constraints. Specifically, the tool usage rules are first broken down into three core constraint dimensions: personnel permission constraints, equipment status constraints, and work scenario adaptation conditions. Based on a pre-defined mapping relationship between tool inventory ledgers and equipment operation data, the rules are correlated with on-site dynamic data. Personnel permission constraints are quantified into verifiable thresholds by mapping the scope of usage permissions and the compliance of personnel operation permissions. For example, operators must hold a valid high-voltage electrician's certificate, their personnel ID must be on the authorized list, and the operation permission compliance is marked as compliant. Equipment status constraints are quantified into specific thresholds by mapping tool integrity standards to tool integrity coefficients and fault warning levels, and mapping power standard thresholds to the remaining power percentage. 90%, fault warning level is low risk, battery level 30% are usable normally, 15% Battery 30% is permitted for emergency use only. Operational scenario adaptation conditions are quantified by mapping historical usage records and equipment usage frequency levels. For example, high-frequency tools are only permitted for maintenance teams, while medium-frequency tools can be dispatched across teams, and emergency work orders can have temporarily relaxed approval permissions. Secondly, constraints from various dimensions are integrated into standardized tool usage parameters. Each parameter includes a unique tool code, RFID tag, personnel permission constraints, equipment status constraints, operational scenario constraints, and permission activation logic, achieving a closed-loop association of "tool code - usage rules - executable parameters." This allows the scheduling strategy generation module to directly call these parameters for priority ranking and scheduling decisions.

[0050] Please refer to Figure 3 In some embodiments, the step of weighting the tool usage parameters, job priority values ​​and tool usage frequency parameters to obtain the tool scheduling priority sequence corresponding to each tool includes: steps S301 to S304. Step S301: Based on the acquired work order information, extract the job type, job completion time limit, and job target location, and quantify the job type, job completion time limit, and job target location to obtain job priority values; In some embodiments, based on the acquired work order information, the job type, job completion deadline, and job target location are extracted, and this information is quantified to generate job priority values. The job type is quantified by mapping different work order types to standardized values ​​in the range [0,1]. For example, emergency repair work orders are assigned a value of 1.0, high-voltage work orders are assigned a value of 0.8, routine inspection work orders are assigned a value of 0.6, daily maintenance work orders are assigned a value of 0.4, and standby dispatch work orders are assigned a value of 0.2. The job completion deadline is quantified based on the specified work order completion time; work orders with shorter deadlines and higher urgency are assigned higher weights, such as planned completion deadlines. 2 hours later, the value is assigned as 1.0. 0.8 was assigned after 6 hours. 0.6 is assigned after 12 hours. Assign a value of 0.4 after 24 hours. A value of 0.2 is assigned for 24-hour work. The target location of the task is quantified based on its distance and accessibility to the tool storage warehouse or dispatch team; higher values ​​are assigned for closer proximity or easier dispatch, while lower values ​​are assigned for cross-regional dispatch. Finally, the three quantified indicators—task type, completion time limit, and target location—are weighted and summed according to preset weights (task type 0.5, completion time limit 0.3, target location 0.2) to obtain the task priority value P. After normalization, this value can be directly used for tool allocation weight calculation in multi-work-order parallel dispatch scenarios. Combined with the rule parsing parameter set, tool suitability is determined, achieving intelligent matching between task urgency and tool allocation.

[0051] Step S302: Based on the historical work records, count the number of times each tool is used, and classify and quantify the number of times each tool is used according to the preset usage frequency classification rules to obtain tool usage frequency parameters. In some embodiments, based on historical work records, the number of times each tool is used is statistically analyzed and quantified according to preset usage frequency classification rules to generate tool usage frequency parameters. By calling the historical usage records generated by the inventory ledger matching submodule, the number of times each tool has been used in the past year or a specified period is obtained, and the usage count is mapped to a standardized value to reflect reuse value. High-frequency used tools (annual usage count) are further categorized. 50 uses) assigned a value of 1.0, medium-frequency use tool (20-49 uses per year) assigned a value of 0.7, low-frequency use tool (5-19 uses per year) assigned a value of 0.4, and very rarely used tool (number of uses per year) assigned a value of 0.4. (5 times) Assign a value of 0.1. In addition, by combining the work scenario adaptation constraints, the tool usage frequency parameter is linked to the current tool status (such as integrity, battery level, and permission compliance) for correction. When the status of a high-frequency tool is abnormal or incompatible, its usage frequency parameter value is reduced accordingly to ensure safe and efficient tool scheduling and improve the tool's adaptability in the work scenario.

[0052] Step S303: The tool usage parameters, the job priority value, the tool usage frequency parameters, and the preset weight coefficients are weighted and calculated to obtain the tool scheduling score corresponding to each tool. In some embodiments, tool usage parameters, job priority values, tool usage frequency parameters, and preset weighting coefficients are weighted and calculated to obtain a tool scheduling score for each tool or type of tool. The scheduling score combines four core factors: rule parsing parameter matching degree (A), job priority value (P), tool usage frequency parameter (C), and cross-shift scheduling feasibility (D), using a weighted formula. The calculations are performed, where A quantifies whether the tool meets permission constraints, equipment status thresholds, and scenario adaptation conditions; P is the generated job priority value; C is the generated tool usage frequency parameter; and D quantifies the tool's cross-shift scheduling convenience. Taking the intelligent high-voltage detector GY-001 as an example, when the rule parsing matching degree A=1.0, the job priority value P=0.8, the usage frequency parameter C=0.7, and the cross-shift scheduling feasibility D=1.0, the calculated scheduling score W=0.88, indicating that the tool has a high priority in the current work order and is preferentially assigned to the target job. This forms a logical closed loop with the previous rule parsing and ledger matching results, realizing the dynamic linkage between tool status, job scenario changes, and scheduling priority.

[0053] Step S304: Sort each tool based on its scheduling score to obtain the tool scheduling priority sequence.

[0054] In some embodiments, based on the calculated scheduling scores of each tool, all schedulable tools are sorted to generate a tool scheduling priority sequence. First, by sorting tools from highest to lowest score, high-scoring tools are prioritized for allocation to target work orders, while low-scoring tools are delayed or used as backups. Simultaneously, a tool scheduling configuration table is generated, including information such as the tool's unique code, RFID tag, scheduling score, inventory balance threshold, and scheduling priority sequence. This table is then linked to the ledger matching results and rule parsing parameter set to achieve data closure. For example, when GY-001 scores 0.88, GY-002 scores 0.76, and GY-003 scores 0.65, the priority sequence is GY-001. GY-002 GY-003 automatically dispatches GY-001 to the current high-voltage inspection work order, while GY-002 and GY-003 serve as backups. The priority sequence can be updated in real time, taking into account changes in tool availability, power consumption, permission compliance, and cross-shift dispatch feasibility to achieve intelligent adaptation and scientific scheduling of tools throughout the entire process.

[0055] Through the above steps, the target tools and equipment are combined with operational needs and historical usage data to intelligently generate tool usage parameters and calculate scheduling priority sequences, thereby achieving scientific, dynamic, and efficient collaborative scheduling of tool allocation in power marketing field operations.

[0056] Step S104: Based on the tool scheduling priority sequence and the work order information, determine the tool allocation relationship and job step sequence corresponding to each work order to generate a job execution plan.

[0057] In some embodiments, determining the tool allocation relationship and job step sequence corresponding to each job order based on the tool scheduling priority sequence and the job order information to generate a job execution plan includes: determining the tools and tool usage sequence corresponding to each job order based on the job type and worker allocation in the job order information, so as to form a tool allocation relationship based on each tool and each tool usage sequence; summarizing the tool allocation relationship and job step sequence to obtain a job execution plan, wherein the job step sequence is obtained by dividing the job process based on the job type, the job completion time limit and the tool allocation relationship.

[0058] In some embodiments, the tools and tool usage order corresponding to each work order are determined based on the tool scheduling priority sequence and the job type and personnel allocation in the work order information, so as to form a tool allocation relationship based on each tool and each tool usage order. Specifically, the following steps are taken: First, the job type and personnel allocation information are extracted from the work order information. For example, if the work order type is 10kV high-voltage line fault repair, the personnel are 3 high-voltage certified personnel and a maintenance team. Second, according to the tool scheduling priority sequence, schedulable tools suitable for this job type (such as GY-001, GY-002) are selected, and incompatible tools are excluded. First, ensure that the tools match the work scenario. Second, further verify the usage permission constraints of the selected tools to confirm that the operators have the qualifications to operate the tools and remove tools with incompatible permissions. Then, sort the tools according to their assigned weights or scheduling priorities, with high-scoring tools being assigned to high-urgency work orders first, and generate a tool usage order. For example, place GY-001 (assigned weight 0.88) first and GY-002 (assigned weight 0.85) second. Finally, form a tool allocation relationship table for each work order, clarifying which tools are used in the work order and the order in which they are used, and providing basic data for subsequent work execution plans.

[0059] In some embodiments, the tool allocation relationship and the sequence of work steps are summarized to obtain a work execution plan. The sequence of work steps is obtained by dividing the work process based on the work type, the work completion deadline, and the tool allocation relationship. Specifically, based on the work order type, the work completion deadline, and the tool allocation relationship, the work process is divided into multiple standardized steps, and a work step timeline is generated. Taking the example work order of 10kV high-voltage line fault repair as an example, with 1.5 hours remaining in the work completion deadline, the tool retrieval step is first scheduled within the first 10 minutes of the work, including quickly retrieving GY-001 and GY-002 from their storage location; secondly, the tool inspection and verification step is scheduled between the 10th and 15th minute to confirm the tool's integrity. 90% of battery capacity 30% of operators must possess high-voltage certification; secondly, core operational steps are scheduled between the 15th and 90th minute, performing tasks such as fault detection and insulation operations according to the tool usage sequence, with each step clearly defining the tool user, operator, and operational sequence; finally, auxiliary operational steps such as tool return and work record registration are arranged at the end of the operation. All steps and corresponding tool information are summarized to generate a work execution plan, forming a complete standardized guideline encompassing a work step timeline, tool usage sequence, and operator configuration. This ensures efficient tool allocation, a compact work process, and compliance with safety regulations, achieving precise matching and closed-loop management of work orders and tools.

[0060] It should be noted that before executing each work step, the system calls upon the work specification library and safety operation standards to check whether the tools used meet the requirements of the operation manual, whether the operators have the necessary qualifications, and whether the operating environment meets safety conditions. If any non-compliance is found, the system can prompt for tool replacement or adjustment of the work sequence, thereby ensuring that each work step is executed safely and compliantly, improving the intelligence level of work processes and tool allocation. When the tool status changes (such as decreased integrity or insufficient power), there are temporary changes in operators, or new high-urgent work orders are generated, the tool allocation relationship and work step sequence are recalculated in real time, and the work execution plan is dynamically updated. In addition, high-scoring tools in the priority sequence can be allocated to urgent work orders first, while low-scoring tools are used as backups, ensuring that in multi-work order parallel operation scenarios, each work order can obtain suitable tools, the work process is closely connected, and intelligent closed-loop management of the entire process of "work order demand - tool supply - work execution" is achieved.

[0061] In some embodiments, after determining the tool allocation relationship and work step sequence corresponding to each work order to generate a work execution plan, the method further includes: collecting work execution status data during the execution of the work execution plan, and performing a difference analysis between the work execution status data and the acquired historical operation and maintenance reference data to obtain work operation and maintenance evaluation indicators; inputting the work operation and maintenance evaluation indicators and preset tool life cycle parameters into a preset fault early warning model for trend extrapolation to obtain equipment operation and maintenance evaluation values; calculating the deviation coefficient between the equipment operation and maintenance evaluation values ​​and preset standard values, generating a deviation level determination result based on the deviation coefficient, and responding to abnormal situations at the power marketing operation site based on the deviation level determination result.

[0062] In some embodiments, job execution status data is collected during the execution of the job execution plan, and the job execution status data is compared with the acquired historical operation and maintenance reference data to obtain job operation and maintenance evaluation indicators. Specifically, the job data acquisition submodule acquires real-time data of the entire job process, including tool usage (usage duration, usage frequency, power consumption rate, integrity before, during and after the job, and compliance with operating procedures), job progress (work order completion rate, actual time consumed in each stage and interruption status), equipment operating parameters and fault information, job environment parameters (temperature, humidity, wind speed), and operation compliance verification information. At the same time, the historical data comparison submodule retrieves historical job efficiency, tool wear patterns, operation and maintenance costs, and fault records of similar work orders. By comparing real-time data with historical data, the differences in tool wear and tear, work efficiency, failure risk, maintenance costs, and equipment aging are quantified, and a difference coefficient is generated. This coefficient is then standardized by combining tool lifecycle parameters, work cost standards, and failure warning probabilities. Through weighted summation and trend extrapolation, the final work operation and maintenance evaluation indicators are obtained, including tool wear rate trends, work completion rate statistics, failure warning probabilities, maintenance cost accounting coefficients, and equipment replacement recommendation thresholds.

[0063] In some embodiments, the operation and maintenance evaluation indicators and preset tool lifecycle parameters are input into a preset fault early warning model for trend extrapolation to obtain equipment operation and maintenance evaluation values. Specifically, an LSTM (Long Short-Term Memory) model with multi-feature fusion is adopted, taking the tool's time-series status data (battery power, integrity, usage time, operating parameters), static lifecycle features (design life, cumulative usage time, historical maintenance times, historical fault records), and environmental data (temperature, humidity, wind speed) for the past three months as input. The LSTM layer captures the time-series change pattern of the tool's status, the fully connected layer fuses the time-series features, static features, and environmental features to output a feature vector, the output layer generates a fault early warning probability through the Sigmoid activation function, and outputs the fault type and estimated fault time window through the Softmax function. Finally, the probability of fault warning is weighted and integrated with standardized operating costs, tool lifecycle parameters and difference coefficients. Combined with the trend of future operating cycles to predict changes in tool status, an optimized evaluation value is obtained and mapped to a standardized equipment operation and maintenance evaluation value of 0-100 points. At the same time, five corresponding core related indicators are generated: tool wear rate trend, operation completion rate statistics, fault warning probability, operation and maintenance cost accounting coefficient and equipment update recommendation threshold.

[0064] In some embodiments, the deviation coefficient between the equipment operation and maintenance assessment value and the preset standard value is calculated to generate a deviation level judgment result based on the deviation coefficient. The result is then used to respond to abnormal situations at the power marketing operation site. Specifically, this involves retrieving operation standards, tool operating parameter thresholds, and work order completion time requirements; calculating the deviation coefficient between the assessment value and the standard value; and classifying the deviation range into different levels (e.g., low deviation, medium deviation, high deviation). Based on the deviation level, the status of equipment and work orders at the operation site is classified as normal, slightly deviated, or severely deviated, and corresponding control measures and execution priorities are preset for each level. For example, slightly deviated deviations alert maintenance personnel, while severely deviated deviations trigger remote collaborative control commands. Next, remote collaborative control commands are generated based on the deviation level, including a deviation level index, control measure code, and command issuance timestamp. These commands are sent to the operation site to achieve immediate response to abnormal operations, tool malfunctions, and operation delays. Simultaneously, on-site execution status data is continuously fed back to the data interaction and analysis module, forming a closed-loop monitoring and continuous optimization mechanism.

[0065] For ease of understanding, Figure 4This is a schematic diagram of the functional modules of the individual soldier equipment operation management system provided in this application; it demonstrates the complete process of the system from equipment status perception and intelligent tool management to operation execution and remote control. The system first collects equipment operation data through the equipment status perception module to form a status perception dataset. The intelligent tool control module then verifies usage permissions. If the verification fails, permission correction feedback is provided. Upon successful verification, a tool scheduling configuration table is generated. Simultaneously, the operation process collaboration module generates operation execution guidelines based on the scheduling results. The data interaction analysis module compares the operation status with historical data to calculate equipment operation and maintenance evaluation values. Finally, the remote collaborative control module generates control instructions, achieving closed-loop management of the operation process and dynamic intelligent matching of tools, personnel, and tasks.

[0066] Through the above steps, tools and work order sequences are intelligently allocated based on tool priority and work order information, standardized work execution plans are generated, and work status is monitored in real time. Tool and work efficiency is evaluated, fault risks are predicted, and scheduling strategies are dynamically adjusted. This enables efficient collaborative management and closed-loop optimization of personnel identity, tool status, and work tasks in power marketing field operations.

[0067] like Figure 5 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided; This invention provides a schematic diagram of the structure of a single-soldier equipment operation system for power marketing. The system includes: an acquisition module 100, a binding module 200, a matching module 300, and an operation module 400. The acquisition module 100 is used to acquire equipment operation data of individual soldier equipment and biometric data of operators; The binding module 200 is used to extract tool identifiers from the equipment operation data, determine the binding relationship between individual equipment and operators based on the tool identifiers and the biometric data, and filter out a set of target tools available to the operators from the equipment operation data based on the binding relationship. The matching module 300 is used to input the target set of tools into a preset tool usage rule base for matching, so as to determine several tool usage parameters. The tool usage parameters, job priority values ​​and tool usage frequency parameters are weighted and calculated to obtain the tool scheduling priority sequence corresponding to each tool. The job priority value and the tool usage frequency parameter are determined based on the acquired work order information and historical job records, respectively. The job module 400 is used to determine the tool allocation relationship and job step sequence corresponding to each job order based on the tool scheduling priority sequence and the job order information in order to generate a job execution plan.

[0068] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the individual equipment operation method for electricity marketing provided by any of the above-described method embodiments of the present invention. More detailed workflows and principles of this system can be found, but are not limited to, the relevant descriptions of the above methods.

[0069] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0070] Based on the above-described embodiments of the individual equipment operation method for electricity marketing, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the individual equipment operation method for electricity marketing according to any embodiment of the present invention.

[0071] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0072] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0073] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0074] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the individual equipment operation method for power marketing as described in any of the above-described method embodiments of the present invention.

[0075] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0076] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for individual equipment operation in electricity marketing, characterized in that, The individual soldier equipment includes several tools and implements, and the method includes: Acquire equipment operation data of individual soldiers and biometric data of operators; Extract tool identifiers from the equipment operation data, determine the binding relationship between individual equipment and operators based on the tool identifiers and the biometric data, and filter out a set of target tools available to the operators from the equipment operation data based on the binding relationship; The target set of tools is input into a preset tool usage rule base for matching to determine several tool usage parameters. The tool usage parameters, job priority values ​​and tool usage frequency parameters are weighted and calculated to obtain the tool scheduling priority sequence corresponding to each tool. The job priority value and the tool usage frequency parameter are determined based on the acquired work order information and historical job records, respectively. Based on the tool scheduling priority sequence and the work order information, the tool allocation relationship and job step sequence corresponding to each work order are determined to generate a job execution plan.

2. The individual equipment operation method for electricity marketing as described in claim 1, characterized in that, The process of determining the binding relationship between individual soldier equipment and operators based on the tool identifier and the biometric data includes: Feature extraction is performed on the biometric data to obtain a set of biometric points, and the set of biometric points is encoded and converted to obtain biometric codes; The biometric code is matched with a preset authorized personnel feature database to obtain the personnel identity verification result; The personnel authentication results are associated and mapped with the tool identifiers to determine the binding relationship between individual equipment and operators.

3. The individual equipment operation method for electricity marketing as described in claim 1, characterized in that, The step of filtering the set of target tools and equipment available to the operator from the equipment operation data based on the binding relationship includes: Based on the binding relationship, the target tool identifier corresponding to the operator is determined, and based on the target tool identifier, the corresponding tool power monitoring data, Beidou positioning information and tool function test parameters are extracted from the equipment operation data. The power monitoring data of the tools, the Beidou positioning information, and the tool function test parameters are normalized to obtain standardized power monitoring data of the tools, standardized Beidou positioning information, and standardized tool function test parameters, respectively. The standardized tool power monitoring data, the standardized Beidou positioning information, the standardized tool function test parameters and preset weights are weighted and summed to obtain the comprehensive status index corresponding to each tool. The comprehensive status indicators are compared with the available status information in the preset tool and equipment inventory ledger to select the target tool and equipment set that meets the preset conditions.

4. The individual equipment operation method for electricity marketing as described in claim 1, characterized in that, The step involves inputting the target set of tools into a preset tool usage rule base for matching to determine several tool usage parameters, including: Based on the tool code of each tool in the target tool set, the tool usage rules corresponding to each tool code are matched from the tool usage rule base to obtain the tool usage rule set. The set of tool usage rules is structured and parsed to extract personnel permission constraints, equipment status constraints, and work scenario adaptation conditions, so as to determine several tool usage parameters based on the personnel permission constraints, equipment status constraints, and work scenario adaptation conditions.

5. The individual equipment operation method for electricity marketing as described in claim 1, characterized in that, The step of weighting the usage parameters, job priority values, and tool usage frequency parameters of each tool to obtain the tool scheduling priority sequence corresponding to each tool includes: Based on the acquired work order information, the job type, job completion deadline, and job target location are extracted, and the job type, job completion deadline, and job target location are quantified to obtain job priority values; Based on the historical work records, the number of times each tool is used is counted, and the number of times each is used is classified and quantified according to the preset usage frequency classification rules to obtain the tool usage frequency parameters. The tool scheduling score for each tool is obtained by weighting the tool usage parameters, the job priority value, the tool usage frequency parameter, and the preset weight coefficient. Based on the scheduling scores of each tool, the tools are sorted to obtain the tool scheduling priority sequence.

6. The individual equipment operation method for electricity marketing as described in claim 5, characterized in that, The step of determining the tool allocation relationship and job step sequence corresponding to each job order based on the tool scheduling priority sequence and the work order information to generate a job execution plan includes: Based on the tool scheduling priority sequence and the job type and worker allocation in the work order information, determine the tools and tool usage order corresponding to each work order, so as to form a tool allocation relationship based on each tool and tool usage order; The tool allocation relationship and the order of work steps are summarized to obtain the work execution plan, wherein the order of work steps is obtained by dividing the work process based on the work type, the work completion time limit and the tool allocation relationship.

7. The individual equipment operation method for electricity marketing as described in claim 1, characterized in that, After determining the tool allocation relationship and work step sequence corresponding to each work order to generate a work execution plan, the following is also included: Collect job execution status data during the execution of the job execution plan, and perform a difference analysis between the job execution status data and the obtained historical operation and maintenance reference data to obtain job operation and maintenance evaluation indicators; The operation and maintenance evaluation indicators and preset tool lifecycle parameters are input into a preset fault early warning model to perform trend extrapolation and obtain equipment operation and maintenance evaluation values. The deviation coefficient between the equipment operation and maintenance assessment value and the preset standard value is calculated, and a deviation level judgment result is generated based on the deviation coefficient. The abnormal situation at the power marketing operation site is responded to based on the deviation level judgment result.

8. A single-soldier equipment operation system for electricity marketing, characterized in that, The system includes: an acquisition module, a binding module, a matching module, and a job module; The acquisition module is used to acquire equipment operation data of individual soldier equipment and biometric data of operators; The binding module is used to extract tool identifiers from the equipment operation data, determine the binding relationship between individual equipment and operators based on the tool identifiers and the biometric data, and filter out a set of target tools available to the operators from the equipment operation data based on the binding relationship. The matching module is used to input the target set of tools into a preset tool usage rule base for matching, so as to determine several tool usage parameters. The tool usage parameters, job priority values ​​and tool usage frequency parameters are weighted and calculated to obtain the tool scheduling priority sequence corresponding to each tool. The job priority value and the tool usage frequency parameters are determined based on the acquired work order information and historical job records, respectively. The job module is used to determine the tool allocation relationship and job step sequence corresponding to each job order based on the tool scheduling priority sequence and the job order information in order to generate a job execution plan.

9. A terminal device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the individual equipment operation method for electricity marketing as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the individual equipment operation method for electricity marketing as described in any one of claims 1-7.

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