Method and device for managing information on entry and exit of metering turnover cabinet based on RFID

Abstract

This invention relates to the field of industrial microservices technology, specifically to a method and apparatus for managing the inbound and outbound information of metering turnover cabinets based on RFID. The method includes: acquiring the current work order, historical work orders, and the location of each auxiliary cabinet; acquiring the independent fulfillment factor of each auxiliary cabinet for the current work order based on various information in the current and historical work orders, combined with the spatial location between the work order and each auxiliary cabinet; acquiring several auxiliary cabinet clusters based on the location of each auxiliary cabinet, and selecting several candidate clusters; acquiring the joint fulfillment factor of each candidate cluster for the current work order based on the location of each auxiliary cabinet in each candidate cluster and the current work order; and comparing the joint fulfillment factor of each candidate cluster for the current work order with the independent fulfillment factor of each auxiliary cabinet for the current work order to generate a scheduling scheme for the current work order. This invention improves dispatch efficiency by dynamically assessing the load of each area and quantitatively analyzing the independent and collaborative fulfillment capabilities of auxiliary cabinets to formulate scheduling strategies.

Description

Technical Field

[0001] This invention relates to the field of industrial microservices technology, specifically to a method and device for managing the inbound and outbound information of metering turnover cabinets based on RFID. Background Technology

[0002] This metering turnover cabinet consists of two parts: a main cabinet and a secondary cabinet. The main cabinet is equivalent to a central information processing system, while the secondary cabinet is equivalent to an information collection and electrical equipment storage module. When the main cabinet receives a work order, it will, based on the various information in the work order, direct staff to the designated secondary cabinet to retrieve the corresponding electrical equipment and proceed to the corresponding location on the work order for repair. The work order includes information such as the repair location, the repair completion deadline, and the required quantity of various electrical equipment. However, the traditional method of matching secondary cabinets to work orders usually only matches them based on the distance between the repair location of the work order and each secondary cabinet, or simply performs static allocation based on the real-time inventory of the secondary cabinets. This method fails to reflect the density of work order demand in different areas and the historical consumption rate of electrical equipment in different areas, resulting in low allocation efficiency. Summary of the Invention

[0003] This invention provides a method and device for managing the inbound and outbound information of metering turnover cabinets based on RFID, in order to solve the existing problems: the traditional method of matching work orders with auxiliary cabinets usually only matches based on the distance relationship between the repair location of the work order and each auxiliary cabinet, or simply performs static allocation based on the real-time inventory status of the auxiliary cabinets, resulting in low allocation efficiency.

[0004] The RFID-based method and device for managing the inbound and outbound information of a metering turnover cabinet of the present invention adopts the following technical solution: One embodiment of the present invention provides a method for managing the inbound and outbound information of a metering turnover cabinet based on RFID, the method comprising the following steps: Obtain the current work order, historical work orders, and the location of each auxiliary cabinet. The work order includes the repair location, repair completion deadline, and the required quantity of various electrical equipment. The city is divided into grids to obtain several grid areas. Based on the historical work orders in the grid areas, the spatiotemporal weights of the grid areas are obtained. Combined with the repair completion time limit of the current work order and the distance between the repair location and each sub-counter, the spatiotemporal cost factor of each sub-counter for the current work order is obtained. Combined with the demand for various electrical equipment in the current work order, the inventory of various electrical equipment in each sub-counter, and the historical work orders performed by each sub-counter, the independent performance factor of each sub-counter for the current work order is obtained. Based on the location of each auxiliary cabinet, all auxiliary cabinets are clustered to obtain several auxiliary cabinet clusters, and several candidate clusters are selected. Based on the location of each auxiliary cabinet in each candidate cluster, the repair location of the current work order, the repair completion time of the current work order, and the spatiotemporal weight of the corresponding grid area, the joint cost factor of each candidate cluster for the current work order is obtained. Combining the demand for various electrical equipment in the current work order, the inventory of various electrical equipment in the auxiliary cabinets of each candidate cluster, and their historical work orders, the joint fulfillment factor of each candidate cluster for the current work order is obtained. By comparing the joint fulfillment factor of each candidate cluster class with the independent fulfillment factor of each sub-counter for the current work order, a scheduling scheme is generated for the current work order.

[0005] Preferably, the specific method for obtaining the spatiotemporal weight of the grid area based on historical work orders within the grid area includes: For any grid region, the ratio of the number of historical work orders in the grid region to the total number of all historical work orders is used as the work order density factor of the grid region. The ratio of the average repair completion time of all historical work orders within the grid area to the work order density factor of the grid area is linearly normalized, and the normalized result is used as the spatiotemporal weight of the grid area.

[0006] Preferably, the specific method for obtaining the spatiotemporal cost factors of each sub-counter for the current work order is as follows: For any auxiliary cabinet, the ratio obtained by multiplying the distance between the current work order's repair location and the auxiliary cabinet by the spatiotemporal weight of the grid region corresponding to the current work order by the repair completion time limit of the current work order is used as the spatiotemporal cost factor of the auxiliary cabinet for the current work order.

[0007] Preferably, the specific method for obtaining the independent fulfillment factor of each sub-counter for the current work order is as follows: For any sub-counter, if the inventory quantity of any electrical equipment in the sub-counter is less than the demand quantity of the corresponding electrical equipment in the current work order, the independent fulfillment factor of the sub-counter for the current work order is recorded as 0; If the inventory quantity of each type of electrical equipment in the auxiliary cabinet is greater than or equal to the demand quantity of the corresponding electrical equipment in the current work order, the ratio of the number of historical work orders fulfilled by the auxiliary cabinet to the total number of historical work orders is used as the retrieval frequency of the auxiliary cabinet. For the current work order, the first For this type of electrical equipment, the first item in the current work order... The quantity of electrical equipment in the auxiliary cabinet minus the quantity of the first type of equipment in the current work order The difference in demand for each type of electrical equipment, plus 1, is divided by the product of the time-space cost factor of the current work order and the frequency of retrieval by the sub-cabinet. This ratio is used as the ratio of the sub-cabinet's response to the first type of work order in the current work order. The independent performance coefficient of each type of electrical equipment is the sum of the independent performance coefficients of all types of electrical equipment in the current work order, which is used as the independent performance factor of the sub-cabinet for the current work order.

[0008] Preferably, the method for obtaining the joint cost factor of each candidate cluster class for the current work order based on the location of each auxiliary cabinet in each candidate cluster class, the repair location of the current work order, the repair completion time limit of the current work order, and the spatiotemporal weight of the corresponding grid area includes: For any candidate cluster class, with the current work order repair location as the origin, construct the integrated sub-vector of each sub-cabinet in the candidate cluster class based on the orientation and reciprocal distance of each sub-cabinet location in the candidate cluster class, and use the sum of all integrated sub-vectors as the overall vector of the candidate cluster class. The sub-cabinet corresponding to the integrated sub-vector with the smallest cosine similarity to the overall vector is taken as the starting sub-cabinet, and index labels are assigned to all sub-cabinets in the cluster according to the proximity principle. Based on the distance between adjacent sub-cabinets of the index label, the distance between the last sub-cabinet and the repair position of the current work order, combined with the spatiotemporal weight of the grid area corresponding to the current work order and the repair completion time limit of the current work order, the joint cost factor of the candidate cluster class for the current work order is obtained.

[0009] Preferably, the specific method for obtaining the joint cost factor of the candidate cluster class for the current work order is as follows: In the formula, This represents the joint cost factor of the candidate clusters for the current work order. Indicates the first of the candidate cluster classes The second counter and the first The distance between the auxiliary cabinets; This indicates the distance between the last auxiliary cabinet in the candidate cluster and the repair location of the current work order; This indicates the number of secondary cabinets in the candidate clusters; This indicates the spatiotemporal weight of the grid region corresponding to the current work order; This indicates the repair completion deadline for the current work order.

[0010] Preferably, the specific method for obtaining the joint fulfillment factor of each candidate cluster class for the current work order is as follows: Record any electrical equipment in the current work order as the target equipment. For any sub-cabinet, obtain the sub-cabinet's potential to allocate the target equipment based on the inventory of the target equipment in the sub-cabinet, the frequency of retrieval of the sub-cabinet, and its spatiotemporal cost factor to the current work order. The potential for the sub-cabinet to allocate the target equipment is positively correlated with the inventory of the target equipment in the sub-cabinet, and negatively correlated with the frequency of retrieval of the sub-cabinet and its spatiotemporal cost factor for the current work order. For any candidate cluster, based on the allocation potential of each auxiliary cabinet in the candidate cluster for each type of electrical equipment in the current work order, the demand for each type of electrical equipment in the current work order is allocated to each auxiliary cabinet in the candidate cluster, thereby obtaining the supply quantity of each auxiliary cabinet in the candidate cluster for each type of electrical equipment in the current work order. Based on the supply quantity of each type of electrical equipment in the current work order by each sub-counter in the candidate cluster, the inventory quantity of each type of electrical equipment in the current work order in each sub-counter in the candidate cluster, the retrieval frequency of each sub-counter in the candidate cluster, and the joint cost factor of the candidate cluster for the current work order, the joint fulfillment factor of the candidate cluster for the current work order is obtained.

[0011] Preferably, the specific method for obtaining the joint fulfillment factor of the candidate cluster class for the current work order is as follows: In the formula, This represents the joint fulfillment factor of the candidate cluster class for the current work order; This indicates the types and quantities of electrical equipment required in the current work order; This indicates the number of secondary cabinets in the candidate clusters; Indicates the first [number]th [item] in the current work order The electrical equipment in the candidate cluster is the first The quantity of inventory in each auxiliary counter; Indicates the first of the candidate cluster classes The assistant counter is responsible for the first item in the current work order. The supply of various electrical equipment; This represents the joint cost factor of the candidate cluster class for the current work order; Indicates the first of the candidate cluster classes The frequency of retrieval of each auxiliary counter.

[0012] Preferably, the specific method for generating a scheduling scheme for the current work order by comparing the joint fulfillment factor of each candidate cluster class with the independent fulfillment factor of each sub-counter for the current work order is as follows: Obtain the independent fulfillment factor of each sub-counter for the current work order, and take the sub-counter corresponding to the maximum value of the independent fulfillment factor as the fulfilling sub-counter; obtain the joint fulfillment factor of each candidate cluster class for the current work order, and take the candidate cluster class corresponding to the maximum value of the joint fulfillment factor as the fulfilling sub-counter cluster class; If the independent fulfillment factor of the fulfillment sub-counter for the current work order is greater than or equal to the joint fulfillment factor of the fulfillment sub-counter cluster for the current work order, the fulfillment sub-counter shall provide all electrical equipment in the current work order; if the independent fulfillment factor of the fulfillment sub-counter for the current work order is less than the joint fulfillment factor of the fulfillment sub-counter cluster for the current work order, each sub-counter in the fulfillment sub-counter cluster shall jointly provide all electrical equipment in the current work order according to the amount of each type of electrical equipment provided by each sub-counter in the candidate cluster for each type of electrical equipment in the current work order.

[0013] Another embodiment of the present invention provides an RFID-based metering turnover cabinet inbound and outbound information management device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any of the above-described RFID-based metering turnover cabinet inbound and outbound information management methods.

[0014] The beneficial effects of the technical solution of this invention are as follows: This application analyzes historical work orders to obtain the density and urgency of historical work order demands in each grid area of ​​the city, thereby constructing the spatiotemporal weight of the grid area. Furthermore, by combining the position between the work order and each auxiliary cabinet, the spatiotemporal cost factor of each auxiliary cabinet for the work order is obtained to evaluate the time and space cost of dispatching electrical equipment from each auxiliary cabinet to fulfill the work order. Furthermore, by combining the demand for various electrical equipment in the work order, the inventory of various electrical equipment in each auxiliary cabinet, and the historical work orders fulfilled by each auxiliary cabinet, the independent fulfillment factor of each auxiliary cabinet for the work order is obtained, which is used to quantify the priority of each auxiliary cabinet in independently fulfilling the work order, and this serves as the basis for formulating subsequent electrical equipment dispatching strategies.

[0015] In reality, some work orders may require a large number and variety of electrical equipment, which can only be completed independently by a few auxiliary cabinets. Moreover, the cost of completing the work order independently by a single auxiliary cabinet may be too high. To address this, this application clusters the spatial distribution of each auxiliary cabinet to form several auxiliary cabinet clusters and selects clusters with sufficient total inventory to meet the current work order requirements as candidate clusters. By simulating the optimal equipment retrieval path, the joint cost factor is calculated to quantify the time and space cost of joint execution. The joint cost factor of the candidate clusters for the current work order is obtained, and then the joint execution factor of each candidate cluster for the current work order is obtained to quantify the overall priority of the joint execution of the work order by the candidate clusters. Finally, by comparing the independent execution factor of each auxiliary cabinet for the current work order with the joint execution factor of each candidate cluster for the current work order, the optimal scheduling cluster is determined, thereby improving the allocation efficiency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the steps of the RFID-based metering turnover cabinet inbound and outbound information management method of the present invention. Detailed Implementation

[0018] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the RFID-based metering turnover cabinet inbound and outbound information management method and apparatus proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0019] 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 invention pertains.

[0020] The following description, in conjunction with the accompanying drawings, details the specific scheme of the RFID-based metering turnover cabinet inbound and outbound information management method and device provided by the present invention.

[0021] Please see Figure 1 The diagram illustrates a flowchart of an RFID-based method for managing the inbound and outbound information of a metering turnover cabinet, according to an embodiment of the present invention. The method includes the following steps: Step S001: Obtain the current work order, historical work orders, and the location of each auxiliary counter.

[0022] It should be noted that this metering turnover cabinet consists of two parts: a main cabinet and a secondary cabinet. The main cabinet is equivalent to a central information processing system, while the secondary cabinet is equivalent to an information collection and electrical equipment storage module. When the main cabinet receives a work order, it will, based on the various information in the work order, instruct staff to retrieve the corresponding electrical equipment from the designated secondary cabinet and proceed to the corresponding location on the work order for repair. The work order includes information such as the repair location, the repair completion deadline, and the required quantity of various electrical equipment. However, the traditional method of matching work orders with secondary cabinets usually only matches them based on the distance between the repair location of the work order and each secondary cabinet, or simply allocates them statically based on the real-time inventory of the secondary cabinets. This method fails to reflect the density of work order demand in different areas and the historical consumption rate of electrical equipment in each area, resulting in low allocation efficiency. Therefore, this embodiment proposes an RFID-based method for managing the inbound and outbound information of the metering turnover cabinet. Specifically, by combining various information from historical and current work orders with the spatial location of each secondary cabinet, it dynamically analyzes the density of work order demand in different areas and the historical consumption rate of electrical equipment in each area, thereby formulating an electrical equipment scheduling strategy to improve allocation efficiency.

[0023] Specifically, users upload their requests to the main counter via the mini-program, which then generates a work order and retrieves the specific spatial location of each auxiliary counter in the city. The work order includes information such as the repair location, repair completion deadline, and the required quantity of various electrical equipment; a historical range is preset. The The specific value can be set according to the actual situation. This embodiment does not make a hard requirement. In this embodiment, it is used as... Taking this as an example, we retrieve the most recent data from the historical database. All work orders within a month are recorded as historical work orders.

[0024] Step S002: The city is gridded to obtain several grid areas; based on the historical work orders in the grid areas, the spatiotemporal weights of the grid areas are obtained; combined with the repair completion time limit of the current work order and the distance between the repair location and each sub-counter, the spatiotemporal cost factor of each sub-counter for the current work order is obtained; combined with the demand for various electrical equipment in the current work order, the inventory of various electrical equipment in each sub-counter, and the historical work orders performed by each sub-counter, the independent performance factor of each sub-counter for the current work order is obtained.

[0025] It should be noted that this embodiment, as an RFID-based method for managing the inbound and outbound information of metering turnover cabinets, ultimately aims to formulate an optimal electrical equipment scheduling strategy. When a work order arises in a certain area requiring the scheduling of electrical equipment, to avoid a situation where a large number of work orders need to be completed in a short period of time in the future, causing nearby auxiliary cabinets to be unable to fulfill their obligations, this embodiment analyzes historical work orders to obtain the density and urgency of historical work order demands in each grid area of ​​the city. This information is used to construct the spatiotemporal weight of the grid area. Furthermore, by combining the location between the work order and each auxiliary cabinet, the spatiotemporal cost factor of each auxiliary cabinet for the work order is obtained to assess the time and space costs of scheduling electrical equipment from each auxiliary cabinet to fulfill the work order. Furthermore, by combining the demand for various electrical equipment in the work order, the inventory of various electrical equipment in each auxiliary cabinet, and the historical work orders fulfilled by each auxiliary cabinet, the independent fulfillment factor of each auxiliary cabinet for the work order is obtained. This factor is used to quantify the priority of each auxiliary cabinet in independently fulfilling work orders, and this serves as the basis for formulating subsequent electrical equipment scheduling strategies, thereby improving allocation efficiency.

[0026] Preferably, in a specific embodiment of the present invention, the city is gridded to obtain several grid areas. Since gridding is a well-known prior art, it will not be described in detail in this embodiment. For any grid area, the ratio of the number of historical work orders in the grid area to the total number of historical work orders is used as the work order density factor of the grid area. Furthermore, the ratio of the mean repair completion time of all historical work orders within the grid area to the work order density factor of the grid area is linearly normalized (the normalization range is the ratio of the mean repair completion time of all historical work orders within all grid areas to their corresponding work order density factor), and the normalized result is used as the spatiotemporal weight of the grid area.

[0027] It should be noted that the smaller the spatiotemporal weight of the grid area, the larger the number of historical work orders in the grid area and the shorter the repair completion time of the historical work orders. For areas with dense work orders and short repair completion time, try not to dispatch electrical equipment from nearby auxiliary cabinets to complete the work order. This is to avoid the situation where a large number of work orders need to be completed in a short period of time in the future, which may cause nearby auxiliary cabinets to be unable to fulfill them. Therefore, when evaluating the cost of auxiliary cabinets fulfilling work orders, the fulfillment cost caused by the distance between different auxiliary cabinets and work orders should be reduced, and the spatiotemporal cost factor of auxiliary cabinets for work orders should be obtained.

[0028] Preferably, in a specific embodiment of the present invention, for any sub-cabinet, the ratio obtained by multiplying the distance between the repair location of the current work order and the sub-cabinet by the spatiotemporal weight of the grid area corresponding to the current work order by the repair completion time limit of the current work order is used as the spatiotemporal cost factor of the sub-cabinet for the current work order.

[0029] As an example, the specific formula for calculating the spatiotemporal cost factor of the current work order for the sub-counter is as follows: In the formula, This represents the spatiotemporal cost factor of the secondary counter for the current work order; This indicates the distance between the current work order's repair location and the auxiliary cabinet. This indicates the spatiotemporal weight of the grid region corresponding to the current work order; This indicates the repair completion deadline for the current work order.

[0030] It should be noted that the time-space cost factor of the sub-cabinet for the work order represents the time and space cost incurred by each sub-cabinet in scheduling electrical equipment to fulfill the work order. The larger the value, the greater the space cost of fulfilling the work order by that sub-cabinet, the greater the risk of timeout, and the greater the potential impact on the sub-cabinet's fulfillment of other subsequent work orders. Furthermore, by combining the demand for various electrical equipment in the work order, the inventory of various electrical equipment in each sub-cabinet, and the historical work orders fulfilled by each sub-cabinet, the independent fulfillment factor of each sub-cabinet for the work order is obtained. This factor is used to quantify the priority of each sub-cabinet in independently fulfilling the work order, and based on this, a subsequent electrical equipment scheduling strategy is formulated to improve dispatching efficiency.

[0031] Preferably, in a specific embodiment of the present invention, for any sub-cabinet, if the inventory quantity of any electrical equipment in the sub-cabinet is less than the demand quantity of the corresponding electrical equipment in the current work order, then the independent fulfillment factor of the sub-cabinet for the current work order is recorded as 0. If the inventory quantity of each type of electrical equipment in the auxiliary cabinet is greater than or equal to the demand quantity of the corresponding electrical equipment in the current work order, then the ratio of the number of historical work orders fulfilled by the auxiliary cabinet to the total number of historical work orders is used as the retrieval frequency of the auxiliary cabinet. Furthermore, regarding the first [item] in the current work order... For this type of electrical equipment, the first item in the current work order... The quantity of electrical equipment in the auxiliary cabinet minus the quantity of the first type of equipment in the current work order The difference in demand for each type of electrical equipment, plus 1, is divided by the product of the time-space cost factor of the current work order and the frequency of retrieval by the sub-cabinet. This ratio is used as the ratio of the sub-cabinet's response to the first type of work order in the current work order. The independent performance coefficient of each type of electrical equipment is the sum of the independent performance coefficients of all types of electrical equipment in the current work order, which is used as the independent performance factor of the sub-cabinet for the current work order.

[0032] As an example, the specific formula for calculating the independent fulfillment factor of the current work order for the sub-counter is as follows: In the formula, This indicates the independent fulfillment factor of the sub-counter for the current work order; This indicates the types and quantities of electrical equipment required in the current work order; Indicates the first [number]th [item] in the current work order The quantity of various electrical equipment in the auxiliary cabinet; Indicates the first [number]th [item] in the current work order Demand for this type of electrical equipment; This represents the spatiotemporal cost factor of the secondary counter for the current work order; This indicates the frequency of retrieval from the secondary cabinet.

[0033] It should be noted that if the inventory quantity of any electrical equipment in the auxiliary cabinet is less than the demand quantity of the corresponding electrical equipment in the work order, it means that the auxiliary cabinet cannot independently fulfill the work order; conversely, it means that the auxiliary cabinet can independently fulfill the work order. However, when the demand quantity of various electrical equipment in the work order is closer to the demand quantity of the work order, the auxiliary cabinet cannot independently fulfill the work order. When considering the inventory levels of various electrical equipment in the auxiliary cabinet, the more likely the auxiliary cabinet will run out of inventory after completing a work order, the less likely it is to be able to fulfill other urgent work orders in the vicinity. Therefore, its independent fulfillment factor should be smaller. Conversely, the frequency of retrieval by the auxiliary cabinet indicates that the more frequently the electrical equipment in the auxiliary cabinet is retrieved, the more sufficient inventory should be reserved for the auxiliary cabinet to avoid future inventory shortages. Furthermore, by combining the time-space cost factor of the auxiliary cabinet for the work order, the independent fulfillment factor of the auxiliary cabinet for the current work order can be obtained, which is used to quantify the priority of each auxiliary cabinet in independently fulfilling work orders.

[0034] At this point, the independent fulfillment factor for each sub-counter on the current work order is obtained.

[0035] Step S003: Cluster all auxiliary cabinets according to their locations to obtain several auxiliary cabinet clusters, and select several candidate clusters; based on the location of each auxiliary cabinet in each candidate cluster, the repair location of the current work order, the repair completion time of the current work order, and the spatiotemporal weight of the corresponding grid area, obtain the joint cost factor of each candidate cluster for the current work order; combine the demand for various electrical equipment in the current work order, the inventory of various electrical equipment in the auxiliary cabinets of each candidate cluster, and their historical work orders to obtain the joint fulfillment factor of each candidate cluster for the current work order.

[0036] It should be noted that in reality, some work orders may require a large number and variety of electrical equipment, and only a few auxiliary cabinets may be able to independently provide the electrical equipment for the work order. If the electrical equipment for the work order is forcibly provided by these few auxiliary cabinets, it may result in excessive costs for the auxiliary cabinets to fulfill the work order, potentially leading to timeouts and affecting the auxiliary cabinets' ability to fulfill subsequent work orders. Therefore, this embodiment provides an evaluation of the priority of multiple auxiliary cabinets jointly fulfilling work orders. By comparing the priority of each auxiliary cabinet fulfilling work orders independently, the optimal scheduling strategy is formulated.

[0037] It should be further explained that, firstly, clustering is performed based on the spatial distribution of each auxiliary cabinet to form several auxiliary cabinet clusters, and clusters with sufficient total inventory to meet the current work order requirements are selected as candidate clusters; furthermore, in order to evaluate the comprehensive efficiency of the joint fulfillment of work orders by each candidate cluster, the optimal equipment retrieval path is simulated to calculate the joint cost factor, quantify the time and space cost of joint fulfillment, and obtain the joint cost factor of the candidate cluster for the current work order; furthermore, by combining the demand for various electrical equipment in the current work order, the inventory of various electrical equipment in the auxiliary cabinets of each candidate cluster, and its historical work orders, the joint fulfillment factor of each candidate cluster for the current work order is obtained, so as to quantify the overall priority of the joint fulfillment of work orders by the candidate cluster.

[0038] Preferably, in a specific embodiment of the present invention, the distance between different sub-cabinets is used as the metric distance, and the DBSCAN density clustering algorithm is used to cluster all sub-cabinets to obtain several sub-cabinet clusters. Since the DBSCAN density clustering algorithm is a well-known prior art, it will not be described in detail in this embodiment. For any sub-cabinet cluster, if the demand for each type of electrical equipment in the current work order is less than or equal to the total inventory of the corresponding electrical equipment in all sub-cabinets of the sub-cabinet cluster, the sub-cabinet cluster is recorded as a candidate cluster. For any candidate cluster class, with the current work order repair location as the origin, construct the integrated sub-vector of each sub-cabinet in the candidate cluster class based on the orientation and reciprocal distance of each sub-cabinet location in the candidate cluster class, and use the sum of all integrated sub-vectors as the overall vector of the candidate cluster class. The sub-cabinet corresponding to the integrated sub-vector with the smallest cosine similarity to the overall vector is taken as the starting sub-cabinet, and index labels are assigned to all sub-cabinets in the cluster according to the proximity principle. Based on the distance between adjacent sub-cabinets of the index label, the distance between the last sub-cabinet and the repair position of the current work order, combined with the spatiotemporal weight of the grid area corresponding to the current work order and the repair completion time limit of the current work order, the joint cost factor of the candidate cluster class for the current work order is obtained.

[0039] As an example, the specific method for obtaining the joint cost factor of the candidate cluster class for the current work order is as follows: The direction from the repair location of the current work order to the corresponding location of the auxiliary cabinet in the candidate cluster class is taken as the direction of the integrated sub-vector of the auxiliary cabinet in the candidate cluster class. The reciprocal of the distance between the repair location of the current work order and the corresponding location of the auxiliary cabinet in the candidate cluster class is taken as the magnitude of the integrated sub-vector of the auxiliary cabinet in the candidate cluster class. The integrated sub-vector of the auxiliary cabinet in the candidate cluster class is obtained. The sum of the integrated sub-vectors of all auxiliary cabinets in the candidate cluster class is taken as the overall vector of the candidate cluster class.

[0040] Furthermore, the sub-cabinet corresponding to the sub-vector with the smallest cosine similarity to the overall vector of the candidate cluster class among the integrated sub-vectors of all sub-cabinets in the candidate cluster class is taken as the first sub-cabinet of the candidate cluster class. The secondary cabinet closest to the first secondary cabinet in the candidate cluster class is designated as the second secondary cabinet of the candidate cluster class; the secondary cabinet closest to the second secondary cabinet (excluding the first secondary cabinet) in the candidate cluster class is designated as the third secondary cabinet of the candidate cluster class; and so on, until an index label is assigned to all secondary cabinets in the candidate cluster class.

[0041] It should be noted that the direction from the repair location of the current work order to the location of each auxiliary cabinet is taken as the direction of the integrated sub-vector, representing the directional nature of the auxiliary cabinet relative to the work order. The magnitude of the integrated sub-vector is set to the reciprocal of the distance between the repair location of the current work order and the corresponding location of the auxiliary cabinet in the candidate cluster class, which represents the proximity between the auxiliary cabinet and the work order. By using the similarity between the integrated sub-vector of each auxiliary cabinet in the candidate cluster class and the overall vector of the candidate cluster class, the optimal equipment access path of the candidate cluster class can be simulated. Then, by combining the repair completion time limit of the current work order and the spatiotemporal weight of its corresponding grid area, the joint cost factor of each candidate cluster class for the current work order can be obtained.

[0042] Preferably, in a specific embodiment of the present invention, for any candidate cluster class, based on the distance between adjacent sub-cabinets with index tags in the candidate cluster class, the distance between the last sub-cabinet and the repair position of the current work order, combined with the spatiotemporal weight of the grid region corresponding to the current work order and the repair completion time limit of the current work order, the joint cost factor of the candidate cluster class for the current work order is obtained, and its specific calculation formula is as follows: In the formula, This represents the joint cost factor of the candidate clusters for the current work order. Indicates the first of the candidate cluster classes The second counter and the first The distance between the auxiliary cabinets; This indicates the distance between the last auxiliary cabinet in the candidate cluster and the repair location of the current work order; This indicates the number of secondary cabinets in the candidate clusters; This indicates the spatiotemporal weight of the grid region corresponding to the current work order; This indicates the repair completion deadline for the current work order.

[0043] It should be noted that, This represents the length of the optimal equipment access path simulated by the electrical equipment of the candidate cluster class. The larger the value, the greater the scheduling cost. Combining the repair completion time limit of the current work order and the spatiotemporal weight of the corresponding grid area, the joint cost factor of each candidate cluster class for the current work order is obtained. The logic for obtaining the joint cost factor of the candidate cluster class for the current work order is the same as that for obtaining the spatiotemporal cost factor of the auxiliary cabinet for the current work order.

[0044] It should be further explained that when the current work order is jointly performed by the auxiliary cabinets in the candidate cluster, a specific supply quantity needs to be allocated to the auxiliary cabinets in the candidate cluster in order to accurately assess the overall priority of the work order jointly performed by the candidate cluster. When allocating a specific supply quantity to the auxiliary cabinets in the candidate cluster, it is necessary to quantify the allocation potential of each auxiliary cabinet in the candidate cluster for various electrical equipment in the current work order, so as to allocate the optimal supply quantity to the auxiliary cabinets in the candidate cluster.

[0045] Preferably, in a specific embodiment of the present invention, any electrical equipment in the current work order is recorded as the target equipment. For any sub-cabinet, the allocation potential of the sub-cabinet to the target equipment is obtained based on the inventory of the target equipment in the sub-cabinet, the frequency of retrieval of the sub-cabinet, and its spatiotemporal cost factor to the current work order. The potential for the sub-cabinet to allocate the target equipment is positively correlated with the inventory of the target equipment in the sub-cabinet, and negatively correlated with the frequency of retrieval of the sub-cabinet and its spatiotemporal cost factor for the current work order. For any candidate cluster, based on the allocation potential of each auxiliary cabinet in the candidate cluster for each type of electrical equipment in the current work order, the demand for each type of electrical equipment in the current work order is allocated to each auxiliary cabinet in the candidate cluster, thereby obtaining the supply quantity of each auxiliary cabinet in the candidate cluster for each type of electrical equipment in the current work order.

[0046] As an example, the specific method for obtaining the supply quantity of each sub-cabinet in the candidate cluster class for each type of electrical equipment in the current work order is as follows: For any sub-cabinet in any candidate cluster and the first in the current work order For this type of electrical equipment, the first item in the current work order... The ratio of the inventory quantity of a type of electrical equipment in the auxiliary cabinet within the candidate cluster to the product of the retrieval frequency of the auxiliary cabinet within the candidate cluster multiplied by the spatiotemporal cost factor of the current work order, is used as the ratio of the auxiliary cabinet in the candidate cluster to the quantity of the equipment in the current work order. The allocation potential coefficient for a type of electrical equipment, for the sub-cabinet in the candidate cluster, in the current work order. The allocation potential coefficient of each type of electrical equipment is weighted and normalized (its normalization range is the sum of the values ​​of all auxiliary cabinets in the candidate cluster for the current work order). The allocation potential coefficient of the electrical equipment is normalized and used as the sub-cabinet in the candidate cluster class for the current work order. The potential weighting of various electrical equipment.

[0047] Furthermore, for any sub-cabinet in any candidate cluster class and the first sub-cabinet in the current work order... For this type of electrical equipment, the first item in the current work order... The demand for a certain type of electrical equipment, multiplied by the number of auxiliary cabinets in the current work order in the candidate cluster. The product of the potential weights of the electrical equipment is used as the sub-cabinet in the candidate cluster class for the current work order. Theoretical supply quantity of this type of electrical equipment; Furthermore, the sub-cabinet in the candidate cluster class is compared with the first sub-cabinet in the current work order. The integer and fractional parts of the theoretical supply quantity of a certain type of electrical equipment are respectively denoted as the auxiliary cabinet in the candidate cluster class for the current work order. Basic and excess supply of various electrical equipment; Similarly, obtain the first sub-counter in the current work order from each of the candidate clusters. The basic and excess supply quantities of various electrical equipment; all auxiliary cabinets in the candidate clusters will be assigned to the current work order. The sum of the excess supply of each type of electrical equipment is used as the basis for evaluating the current work order for all sub-cabinets in the candidate cluster. The remaining allocation of a type of electrical equipment is denoted as According to each sub-counter in the candidate cluster class, the current work order is processed by the first sub-counter. The excess supply quantities of electrical equipment are sorted in descending order to obtain all auxiliary cabinets in the candidate cluster for the current work order. The allocation sequence of various electrical equipment; Furthermore, all sub-cabinets in the candidate clusters will be matched with the first sub-cabinet in the current work order. The first in the allocation sequence of electrical equipment Each assistant counter is responsible for the current work order. The basic supply quantity of each type of electrical equipment plus 1 is used as its basis for the current work order. The quantity of electrical equipment provided; All auxiliary cabinets in the candidate clusters will be assigned to the first item in the current work order. The first in the allocation sequence of electrical equipment The next auxiliary cabinet (including the first auxiliary cabinet) Each of the assistant counters will handle the current work order. The basic supply quantity of this type of electrical equipment, as its contribution to the current work order. The quantity of various electrical equipment supplied.

[0048] It should be noted that the theoretical supply of electrical equipment is based on the allocation of the potential weights of each auxiliary cabinet, and the calculation based solely on the allocation potential weights may contain decimal parts. Since each auxiliary cabinet can only provide an integer number of electrical equipment, the integer part of the theoretical supply is taken as the minimum electrical equipment that each auxiliary cabinet must provide. This is the first allocation of electrical equipment. If the first allocation cannot meet the demand of the current work order, a second allocation will be performed. The remaining allocation amount is the total amount of electrical equipment allocated in the second allocation (the sum of the excess supply of all auxiliary cabinets is an integer). The larger the excess supply of an auxiliary cabinet, the more electrical equipment the auxiliary cabinet should provide for the current work order. Therefore, the second allocation is performed based on the excess supply to achieve an integer allocation between the demand of the current work order and the supply of auxiliary cabinets. After obtaining the optimal supply amount for the auxiliary cabinets in the candidate clusters, the joint fulfillment factor of each candidate cluster for the current work order can be obtained by combining the inventory of various electrical equipment of the auxiliary cabinets in the candidate clusters, their historical work orders, and the joint cost factor of the candidate clusters for the current work order.

[0049] Preferably, in a specific embodiment of the present invention, for any candidate cluster, based on the supply quantity of each type of electrical equipment in the current work order by each sub-counter in the candidate cluster, the inventory quantity of each type of electrical equipment in the current work order in each sub-counter in the candidate cluster, combined with the retrieval frequency of each sub-counter in the candidate cluster and the joint cost factor of the candidate cluster for the current work order, the joint fulfillment factor of the candidate cluster for the current work order is obtained, and the specific calculation formula is as follows: In the formula, This represents the joint fulfillment factor of the candidate cluster class for the current work order; This indicates the types and quantities of electrical equipment required in the current work order; This indicates the number of secondary cabinets in the candidate clusters; Indicates the first [number]th [item] in the current work order The electrical equipment in the candidate cluster is the first The quantity of inventory in each auxiliary counter; Indicates the first of the candidate cluster classes The assistant counter is responsible for the first item in the current work order. The supply of various electrical equipment; This represents the joint cost factor of the candidate cluster class for the current work order; Indicates the first of the candidate cluster classes The frequency of retrieval of each auxiliary counter.

[0050] It should be noted that when the supply of various electrical equipment in the current work order is greater for the auxiliary cabinets in the candidate cluster, and the inventory of the corresponding electrical equipment in the auxiliary cabinets is smaller, it indicates that the candidate cluster is more likely to run out of inventory after fulfilling the current work order. The joint fulfillment factor of the candidate cluster for the current work order should be smaller. On the other hand, the higher the frequency of auxiliary cabinet retrieval in the candidate cluster, the higher the retrieval frequency of the auxiliary cabinets in the candidate cluster. Sufficient inventory should be reserved for the auxiliary cabinets in the candidate cluster. Furthermore, by combining the joint cost factor of the candidate cluster for the current work order, the joint fulfillment factor of the candidate cluster for the current work order can be obtained, which is used to quantify the joint fulfillment priority of the candidate cluster for the current work order.

[0051] At this point, the joint fulfillment factor of the candidate cluster class for the current work order is obtained.

[0052] Step S004: Compare the joint fulfillment factor of each candidate cluster class for the current work order with the independent fulfillment factor of each sub-counter for the current work order, and generate a scheduling scheme for the current work order.

[0053] It should be noted that after obtaining the independent fulfillment factor of each sub-counter for the current work order and the joint fulfillment factor of each candidate cluster for the current work order through steps S002 and S003 respectively, the independent fulfillment factor of each sub-counter for the current work order and the joint fulfillment factor of each candidate cluster for the current work order can be compared to evaluate the priority of the sub-counter's independent fulfillment of the work order and the priority of the candidate cluster's joint fulfillment of the work order, thereby determining the optimal scheduling cluster and improving dispatch efficiency.

[0054] Specifically, obtain the independent fulfillment factor of each sub-counter for the current work order, and take the sub-counter corresponding to the maximum value of the independent fulfillment factor as the fulfilling sub-counter; obtain the joint fulfillment factor of each candidate cluster class for the current work order, and take the candidate cluster class corresponding to the maximum value of the joint fulfillment factor as the fulfilling sub-counter cluster class; Furthermore, if the independent fulfillment factor of the fulfillment sub-counter for the current work order is greater than or equal to the joint fulfillment factor of the fulfillment sub-counter cluster for the current work order, then the fulfillment sub-counter shall provide all electrical equipment in the current work order; if the independent fulfillment factor of the fulfillment sub-counter for the current work order is less than the joint fulfillment factor of the fulfillment sub-counter cluster for the current work order, then each sub-counter in the fulfillment sub-counter cluster shall jointly provide all electrical equipment in the current work order according to the amount of each type of electrical equipment provided by each sub-counter in the candidate cluster for each type of electrical equipment in the current work order.

[0055] It should be noted that, in this embodiment, after the scheduling plan is generated, staff members go to the designated auxiliary cabinet according to the specific scheduling plan and complete the outbound verification of electrical equipment in real time by scanning the RFID tag. The system automatically updates the inventory data and binds it to the current work order, forming accurate inbound and outbound records. If there are surplus materials or replacement of old parts, they can also be returned or put into storage via RFID scanning, updating the inventory status. This realizes the scientific management of the inbound and outbound information of the metering turnover cabinet from intelligent scheduling decision-making to accurate RFID verification and real-time synchronization of inventory data. In order to avoid the denominator being zero during fraction calculation, this embodiment adds 0.01 to the denominator when the denominator is 0 during fraction calculation.

[0056] Another embodiment of the present invention provides an RFID-based metering turnover cabinet inbound and outbound information management device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the RFID-based metering turnover cabinet inbound and outbound information management method in steps S001 to S004.

[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for managing the inbound and outbound information of a metering turnover cabinet based on RFID, characterized in that, The method includes the following steps: Obtain the current work order, historical work orders, and the location of each auxiliary cabinet. The work order includes the repair location, repair completion deadline, and the required quantity of various electrical equipment. The city is divided into grids to obtain several grid areas. Based on the historical work orders in the grid areas, the spatiotemporal weights of the grid areas are obtained. Combined with the repair completion time limit of the current work order and the distance between the repair location and each sub-counter, the spatiotemporal cost factor of each sub-counter for the current work order is obtained. Combined with the demand for various electrical equipment in the current work order, the inventory of various electrical equipment in each sub-counter, and the historical work orders performed by each sub-counter, the independent performance factor of each sub-counter for the current work order is obtained. Based on the location of each auxiliary cabinet, all auxiliary cabinets are clustered to obtain several auxiliary cabinet clusters, and several candidate clusters are selected. Based on the location of each auxiliary cabinet in each candidate cluster, the repair location of the current work order, the repair completion time of the current work order, and the spatiotemporal weight of the corresponding grid area, the joint cost factor of each candidate cluster for the current work order is obtained. Combining the demand for various electrical equipment in the current work order, the inventory of various electrical equipment in the auxiliary cabinets of each candidate cluster, and their historical work orders, the joint fulfillment factor of each candidate cluster for the current work order is obtained. By comparing the joint fulfillment factor of each candidate cluster class with the independent fulfillment factor of each sub-counter for the current work order, a scheduling scheme is generated for the current work order.

2. The RFID-based method for managing the inbound and outbound information of a metering turnover cabinet according to claim 1, characterized in that, The specific method for obtaining the spatiotemporal weight of the grid area based on historical work orders within the grid area includes: For any grid region, the ratio of the number of historical work orders in the grid region to the total number of all historical work orders is used as the work order density factor of the grid region. The ratio of the average repair completion time of all historical work orders within the grid area to the work order density factor of the grid area is linearly normalized, and the normalized result is used as the spatiotemporal weight of the grid area.

3. The RFID-based method for managing the inbound and outbound information of a metering turnover cabinet according to claim 1, characterized in that, The specific methods for obtaining the spatiotemporal cost factors of each sub-counter for the current work order are as follows: For any auxiliary cabinet, the ratio obtained by multiplying the distance between the current work order's repair location and the auxiliary cabinet by the spatiotemporal weight of the grid region corresponding to the current work order by the repair completion time limit of the current work order is used as the spatiotemporal cost factor of the auxiliary cabinet for the current work order.

4. The RFID-based method for managing the inbound and outbound information of a metering turnover cabinet according to claim 1, characterized in that, The specific method for obtaining the independent fulfillment factor of each sub-counter for the current work order is as follows: For any sub-counter, if the inventory quantity of any electrical equipment in the sub-counter is less than the demand quantity of the corresponding electrical equipment in the current work order, the independent fulfillment factor of the sub-counter for the current work order is recorded as 0; If the inventory quantity of each type of electrical equipment in the auxiliary cabinet is greater than or equal to the demand quantity of the corresponding electrical equipment in the current work order, the ratio of the number of historical work orders fulfilled by the auxiliary cabinet to the total number of historical work orders is used as the retrieval frequency of the auxiliary cabinet. For the current work order, the first For this type of electrical equipment, the first item in the current work order... The quantity of electrical equipment in the auxiliary cabinet minus the quantity of the first type of equipment in the current work order The difference in demand for each type of electrical equipment, plus 1, is divided by the product of the time-space cost factor of the current work order and the frequency of retrieval by the sub-cabinet. This ratio is used as the ratio of the sub-cabinet's response to the first type of work order in the current work order. The independent performance coefficient of each type of electrical equipment is the sum of the independent performance coefficients of all types of electrical equipment in the current work order, which is used as the independent performance factor of the sub-cabinet for the current work order.

5. The RFID-based method for managing the inbound and outbound information of a metering turnover cabinet according to claim 1, characterized in that, The method for obtaining the joint cost factor of each candidate cluster class for the current work order based on the location of each auxiliary cabinet in each candidate cluster class, the repair location of the current work order, the repair completion time limit of the current work order, and the spatiotemporal weight of the corresponding grid area includes the following: For any candidate cluster class, with the current work order repair location as the origin, construct the integrated sub-vector of each sub-cabinet in the candidate cluster class based on the orientation and reciprocal distance of each sub-cabinet location in the candidate cluster class, and use the sum of all integrated sub-vectors as the overall vector of the candidate cluster class. The sub-cabinet corresponding to the integrated sub-vector with the smallest cosine similarity to the overall vector is taken as the starting sub-cabinet, and index labels are assigned to all sub-cabinets in the cluster according to the proximity principle. Based on the distance between adjacent sub-cabinets of the index label, the distance between the last sub-cabinet and the repair position of the current work order, combined with the spatiotemporal weight of the grid area corresponding to the current work order and the repair completion time limit of the current work order, the joint cost factor of the candidate cluster class for the current work order is obtained.

6. The RFID-based method for managing the inbound and outbound information of a metering turnover cabinet according to claim 5, characterized in that, The specific method for obtaining the joint cost factor of the candidate cluster class for the current work order is as follows: In the formula, This represents the joint cost factor of the candidate clusters for the current work order. Indicates the first of the candidate cluster classes The second counter and the first The distance between the auxiliary cabinets; This indicates the distance between the last auxiliary cabinet in the candidate cluster and the repair location of the current work order; This indicates the number of secondary cabinets in the candidate clusters; This indicates the spatiotemporal weight of the grid region corresponding to the current work order; This indicates the repair completion deadline for the current work order.

7. The RFID-based method for managing the inbound and outbound information of a metering turnover cabinet according to claim 4, characterized in that, The specific method for obtaining the joint fulfillment factor of each candidate cluster class for the current work order is as follows: Record any electrical equipment in the current work order as the target equipment. For any sub-cabinet, obtain the sub-cabinet's potential to allocate the target equipment based on the inventory of the target equipment in the sub-cabinet, the frequency of retrieval of the sub-cabinet, and its spatiotemporal cost factor to the current work order. The potential for the sub-cabinet to allocate the target equipment is positively correlated with the inventory of the target equipment in the sub-cabinet, and negatively correlated with the frequency of retrieval of the sub-cabinet and its spatiotemporal cost factor for the current work order. For any candidate cluster, based on the allocation potential of each auxiliary cabinet in the candidate cluster for each type of electrical equipment in the current work order, the demand for each type of electrical equipment in the current work order is allocated to each auxiliary cabinet in the candidate cluster, thereby obtaining the supply quantity of each auxiliary cabinet in the candidate cluster for each type of electrical equipment in the current work order. Based on the supply quantity of each type of electrical equipment in the current work order by each sub-counter in the candidate cluster, the inventory quantity of each type of electrical equipment in the current work order in each sub-counter in the candidate cluster, the retrieval frequency of each sub-counter in the candidate cluster, and the joint cost factor of the candidate cluster for the current work order, the joint fulfillment factor of the candidate cluster for the current work order is obtained.

8. The RFID-based method for managing the inbound and outbound information of a metering turnover cabinet according to claim 7, characterized in that, The specific method for obtaining the joint fulfillment factor of the candidate cluster class for the current work order is as follows: In the formula, This represents the joint fulfillment factor of the candidate cluster class for the current work order; This indicates the types and quantities of electrical equipment required in the current work order; This indicates the number of secondary cabinets in the candidate clusters; Indicates the first [number]th [item] in the current work order The electrical equipment in the candidate cluster is the first The quantity of inventory in each auxiliary counter; Indicates the first of the candidate cluster classes The assistant counter is responsible for the first item in the current work order. The supply of various electrical equipment; This represents the joint cost factor of the candidate cluster class for the current work order; Indicates the first of the candidate cluster classes The frequency of retrieval of each auxiliary counter.

9. The RFID-based method for managing the inbound and outbound information of a metering turnover cabinet according to claim 7, characterized in that, The method for generating a scheduling scheme for the current work order by comparing the joint fulfillment factor of each candidate cluster class with the independent fulfillment factor of each sub-counter for the current work order includes: Obtain the independent fulfillment factor of each sub-counter for the current work order, and take the sub-counter corresponding to the maximum value of the independent fulfillment factor as the fulfilling sub-counter; obtain the joint fulfillment factor of each candidate cluster class for the current work order, and take the candidate cluster class corresponding to the maximum value of the joint fulfillment factor as the fulfilling sub-counter cluster class; If the independent fulfillment factor of the fulfillment sub-counter for the current work order is greater than or equal to the joint fulfillment factor of the fulfillment sub-counter cluster for the current work order, the fulfillment sub-counter shall provide all electrical equipment in the current work order; if the independent fulfillment factor of the fulfillment sub-counter for the current work order is less than the joint fulfillment factor of the fulfillment sub-counter cluster for the current work order, each sub-counter in the fulfillment sub-counter cluster shall jointly provide all electrical equipment in the current work order according to the amount of each type of electrical equipment provided by each sub-counter in the candidate cluster for each type of electrical equipment in the current work order.

10. An RFID-based metering turnover cabinet inbound and outbound information management device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is executed by the processor, it implements the steps of the RFID-based metering turnover cabinet inbound and outbound information management method as described in any one of claims 1-9.

Images