Intelligent inventory management method and device, medium and product

Abstract

The invention relates to the technical field of inventory management, in particular to an intelligent inventory management method and device, a medium and a product, and the method comprises the steps: controlling an inventory management system to carry out inventory data query based on query parameters corresponding to an inventory query instruction when the inventory query instruction is detected. And when an inventory updating instruction carrying the inventory updating data is detected, performing inventory updating based on the inventory updating data and the current inventory data to obtain updated inventory data. Carrying out inventory analysis on the basis of the updated inventory data and an inventory early warning rule, and determining an inventory analysis result; and when the inventory analysis result is that the inventory is abnormal, generating inventory early warning information. The intelligent inventory management method is adopted, multiple APIs and automatic processes are integrated, the defect of insufficient intelligence in traditional school uniform inventory management is effectively overcome, real-time synchronization and automatic processing of inventory data are achieved, and the efficiency and accuracy of inventory management are improved.

Description

Technical Field

[0001] The present application relates to the technical field of inventory management, and in particular to an intelligent inventory management method, equipment, medium and product. Background Art

[0002] In the education industry, school uniforms are a symbol of student identity and an important part of campus culture. Their inventory management has always been a key link in school logistics management. However, traditional school uniform inventory management methods have many drawbacks, which seriously restrict the improvement of management efficiency and service quality.

[0003] Traditional school uniform inventory management usually relies on manual statistics and paper records, which result in untimely data updates and are prone to errors. Due to the lack of intelligent means, schools often purchase school uniforms based on historical data and experience, but this method cannot accurately predict future demand, easily leads to waste or shortage of resources, and cannot promptly detect and handle inventory anomalies.

[0004] Therefore, how to provide an intelligent inventory management method is an urgent problem to be solved by those skilled in the art. Summary of the invention

[0005] The purpose of this application is to provide an intelligent inventory management method, device, medium and product to solve at least one of the above technical problems.

[0006] The above invention objectives of the present application are achieved through the following technical solutions: In the first aspect, the present application provides an intelligent inventory management method, which adopts the following technical solutions: An intelligent inventory management method, comprising: Obtain inventory query API interface, inventory update API interface and inventory warning API interface. Among them, multiple API interfaces are used to build connections between the inventory management system and related systems; When an inventory query instruction is detected, based on the query parameters corresponding to the inventory query instruction, the inventory management system is controlled to query the inventory data, obtain the target inventory data, and return the target inventory data to the first associated system through the inventory query API interface, wherein the inventory query instruction is a query instruction generated by the first associated system by calling the inventory query API interface; When an inventory update instruction carrying inventory update data is detected, the inventory is updated based on the inventory update data and the current inventory data to obtain updated inventory data, wherein the inventory update instruction is an inventory update instruction generated by the second associated system by calling the inventory update API interface; Returning the updated inventory data to the second associated system via the inventory update instruction helps determine whether the inventory update operation is successfully performed; Acquire inventory warning rules, perform inventory analysis based on the updated inventory data and the inventory warning rules, and determine inventory analysis results; When the inventory analysis result is an inventory abnormality, inventory warning information is generated, and the inventory warning information is sent to the third related system through the inventory warning API interface, which helps to respond to inventory abnormalities in a timely manner and optimize inventory resource allocation.

[0007] By adopting the above technical solution, multiple API interfaces are used to establish a connection between the inventory management system and the associated system, so that data exchange and functional interaction between the systems are realized, thereby obtaining an inventory query API interface, an inventory update API interface and an inventory warning API interface. When an inventory query instruction is detected, the inventory management system is controlled to query the inventory data based on the query parameters corresponding to the inventory query instruction, obtain the target inventory data, and return the target inventory data to the first associated system through the inventory query API interface. When an inventory update instruction carrying inventory update data is detected, the inventory is updated based on the inventory update data and the current inventory data to obtain the updated inventory data, and the updated inventory data is returned to the second associated system through the inventory update instruction, which helps to determine whether the inventory update operation is successfully executed. After that, an inventory analysis is performed based on the updated inventory data and the inventory warning rules to determine the inventory analysis results; when the inventory analysis result is an inventory abnormality, an inventory warning information is generated, and the inventory warning information is sent to the third associated system through the inventory warning API interface, which helps to respond to inventory abnormalities in a timely manner and optimize inventory resource allocation. The adoption of intelligent inventory management methods and the integration of multiple API interfaces and automated processes effectively solves the lack of intelligence faced by traditional school uniform inventory management, realizes real-time synchronization and automated processing of inventory data, and improves the efficiency and accuracy of inventory management.

[0008] In a preferred example, the present application can be further configured as follows: the method for determining the inventory warning rule includes: Acquire historical sales data, perform multidimensional data analysis based on the historical sales data, and determine the multidimensional analysis results, wherein the multidimensional data analysis includes: seasonal analysis, sales trend analysis, and related factor analysis; Calculate the basic threshold based on the average sales volume and inventory turnover rate corresponding to the historical sales data to determine the basic inventory warning threshold; Based on the basic inventory warning threshold and the multi-dimensional analysis result, a warning threshold dynamic analysis is performed to determine an inventory warning threshold sequence, and the inventory warning threshold sequence is used as an evaluation criterion in the inventory warning rule, wherein the inventory warning threshold sequence is a dynamically changing inventory warning threshold set arranged in chronological order.

[0009] In a preferred example, the present application may be further configured as follows: performing inventory analysis based on the updated inventory data and the inventory warning rule to determine the inventory analysis result includes: Performing inventory update forecast based on the updated inventory data to determine target inventory data corresponding to a target time period, wherein the target time period is a time period starting from the current time and spanning a preset time period; Selecting warning thresholds based on the inventory warning rules and the target period, and determining a target warning threshold sequence corresponding to the target period; An inventory analysis is performed based on the target inventory data and the target early warning threshold sequence to determine an inventory analysis result.

[0010] In a preferred example, the present application can be further configured as follows: Invite participants in the school uniform supply chain to become nodes in the blockchain network and jointly build a school uniform inventory management platform based on blockchain technology; Storing inventory data corresponding to the inventory management system on the blockchain so that each node can view and verify the inventory data; Leverage smart contract technology to automate inventory allocation and replenishment logic.

[0011] In a preferred example, the present application can be further configured as follows: the implementation method of the replenishment logic includes: Perform replenishment analysis based on inventory data to determine a replenishment analysis result, and automatically trigger a replenishment process when the replenishment analysis result indicates that there is a replenishment demand; When the replenishment process is triggered, replenishment invitations are automatically sent to suppliers in the school uniform supply chain, and bidding information fed back by each supplier is collected, wherein the bidding information includes: replenishment quotation and delivery time; Based on the bidding information corresponding to each supplier, intelligent analysis is performed to determine the target supplier, obtain the replenishment order and send it to the target supplier to complete the intelligent replenishment operation of school uniforms.

[0012] In a preferred example, the present application can be further configured as follows: Monitor the operation instructions in real time, and obtain the user identity data, operation data information, and response result information corresponding to the operation instructions, wherein the operation instructions include: inventory query instructions and inventory update instructions; Recording entries based on the user identity data, the operation data information, and the response result information to determine log entries; Obtaining an inventory change log, and filling the log entry into the inventory change log to implement a database operation audit trail; When it is detected that the log audit cycle has been reached, an operation behavior analysis is performed based on the inventory change log to generate a log audit report.

[0013] In a second aspect, the present application provides an electronic device, which adopts the following technical solution: at least one processor; Memory; At least one application, wherein the at least one application is stored in the memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned intelligent inventory management method.

[0014] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program, which, when executed in a computer, causes the computer to execute the above-mentioned intelligent inventory management method.

[0015] In a fourth aspect, the present application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program, and when the computer program is executed by a processor, the intelligent inventory management method is implemented.

[0016] In summary, the present application includes at least one of the following beneficial technical effects: A variety of API interfaces are used to establish a connection between the inventory management system and the associated systems, so that data exchange and functional interaction between the systems are realized. Therefore, the inventory query API interface, inventory update API interface and inventory warning API interface are obtained. When an inventory query instruction is detected, the inventory management system is controlled to query the inventory data based on the query parameters corresponding to the inventory query instruction, and the target inventory data is obtained, and the target inventory data is returned to the first associated system through the inventory query API interface. When an inventory update instruction carrying inventory update data is detected, the inventory is updated based on the inventory update data and the current inventory data to obtain the updated inventory data, and the updated inventory data is returned to the second associated system through the inventory update instruction, which helps to determine whether the inventory update operation is successfully executed. After that, the inventory analysis is performed based on the updated inventory data and the inventory warning rules to determine the inventory analysis results; when the inventory analysis result is an inventory abnormality, the inventory warning information is generated, and the inventory warning information is sent to the third associated system through the inventory warning API interface, which helps to respond to the inventory abnormality in time and optimize the inventory resource configuration. The adoption of intelligent inventory management methods and the integration of multiple API interfaces and automated processes effectively solves the lack of intelligence faced by traditional school uniform inventory management, realizes real-time synchronization and automated processing of inventory data, and improves the efficiency and accuracy of inventory management.

[0017] Based on the historical sales data, multidimensional data analysis is performed to determine the multidimensional analysis results, where the multidimensional data analysis includes: seasonal analysis, sales trend analysis and related factor analysis. Then, the basic threshold is calculated based on the average sales volume and inventory turnover rate corresponding to the historical sales data to determine the basic inventory warning threshold. After that, the warning threshold is dynamically analyzed based on the basic inventory warning threshold and the multidimensional analysis results to determine the inventory warning threshold sequence, and the inventory warning threshold sequence is used as the evaluation standard in the inventory warning rule. Through multidimensional data analysis, the changing laws and influencing factors of school uniform sales can be more accurately grasped, so as to formulate inventory warning rules that are closer to actual needs, which will help reduce losses caused by excessive or insufficient inventory and improve the accuracy and efficiency of inventory management. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flowchart of an intelligent inventory management method according to one embodiment of the present application; Figure 2 It is a structural schematic diagram of an intelligent inventory management device according to one embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device according to one embodiment of the present application. DETAILED DESCRIPTION

[0019] The following combination Figures 1 to 3 This application is described in further detail.

[0020] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, a person skilled in the art may make non-creative modifications to the present embodiment as needed, but such modifications are protected by the patent law as long as they are within the scope of the present application.

[0021] In order to make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application. It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the data related to the object is involved in the embodiment of the present application, it needs to be obtained through the authorization and consent of the object, the authorization and consent of the relevant departments, and in accordance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiment, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained, and the embodiment also needs to be implemented with the authorization and consent of the object.

[0022] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0023] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0024] The embodiment of the present application provides an intelligent inventory management method, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited to this. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and the embodiment of the present application does not limit this. Figure 1 As shown, the method includes step S101, step S102, step S103 and step S104, wherein: Step S101: Acquire an inventory query API interface, an inventory update API interface, and an inventory warning API interface, wherein the various API interfaces are used to establish a connection between the inventory management system and the associated system.

[0025] For the embodiments of the present application, multiple API interfaces are used to establish a connection between the inventory management system and the related systems, thereby realizing data exchange and functional interaction between the systems, allowing the systems to exchange information in a structured manner, thereby ensuring the real-time and consistency of inventory data. For multiple API interfaces, an inventory query API interface, an inventory update API interface, and an inventory warning API interface are pre-set, wherein the inventory query API interface enables querying inventory information in the database according to request parameters; the inventory update API interface supports operations of increasing and decreasing inventory data; the inventory warning API interface is used to send automatically generated warning information to related systems, which helps to respond to inventory anomalies in a timely manner and optimize inventory resource allocation.

[0026] Step S102: When an inventory query instruction is detected, based on the query parameters corresponding to the inventory query instruction, the inventory management system is controlled to query the inventory data, obtain the target inventory data, and return the target inventory data to the first associated system through the inventory query API interface, wherein the inventory query instruction is a query instruction generated by the first associated system by calling the inventory query API interface.

[0027] For the embodiment of the present application, for the inventory query API interface, the inventory query API interface defines multi-dimensional information such as interface name, request method, request parameters, response format, etc., so that the first associated system can generate query instructions by calling the inventory query API interface and query database data. Therefore, when an inventory query instruction is detected, the API gateway deployed by the inventory management system verifies the validity of the request, including but not limited to: checking the API key, request method (such as GET or POST), request header, etc., to ensure that the request comes from an authorized source and meets security requirements. Under the condition of meeting the validity, the query parameters are parsed from the inventory query instruction, and the query parameters include but are not limited to: product ID, warehouse ID, quantity range, date range, sorting field and direction, etc. The query parameters are used to guide subsequent inventory data query and screening, and the parsed query parameters are verified and cleaned to determine that the format of the query parameters is correct and within a reasonable range, and to prevent security vulnerabilities such as SQL injection. Then, according to the parsed and verified query parameters, an SQL query statement is constructed, and sorting (ORDER BY) and filtering (WHERE) clauses are added to the SQL query statement to achieve the arrangement and filtering of inventory data, and the inventory management system is controlled to execute the SQL query statement to retrieve the target inventory data from the inventory database. Then, the target inventory data is converted into the format required for the API response. If the amount of data of the target inventory data is large, paging processing is performed to reduce the amount of data in a single response and improve the response speed. Then, the target inventory data after the conversion format and / or paging processing is encapsulated to obtain the HTTP response body, and the encapsulated HTTP response is returned to the first associated system through the inventory query API interface. The first associated system can be: an e-commerce platform, a supply chain management system, a financial system, etc.

[0028] Step S103: when an inventory update instruction carrying inventory update data is detected, the inventory is updated based on the inventory update data and the current inventory data to obtain updated inventory data, wherein the inventory update instruction is an inventory update instruction generated by the second associated system by calling the inventory update API interface; returning the updated inventory data to the second associated system through the inventory update instruction helps to determine whether the inventory update operation is successfully executed.

[0029] For the embodiments of the present application, in the inventory management of school uniforms, operations such as warehousing and outbound delivery will affect the changes in inventory data. However, the accuracy and real-time nature of inventory data are crucial to maintaining business continuity. Therefore, by receiving and processing inventory update instructions in real time and updating inventory data based on the inventory update instructions, the real-time nature and accuracy of inventory data can be ensured.

[0030] Specifically, the second associated system generates an inventory update instruction by calling the inventory update API interface, and the API gateway deployed by the inventory management system verifies the legitimacy of the request (for example, verifying the signature, authority and other information) to ensure that only authorized users can initiate an update request to the inventory management system. Then, the inventory update instruction carrying the inventory update data is parsed to clarify the specific update information represented by the update data, such as product ID, quantity change (increase or decrease), update time, etc. Before executing the inventory update, the inventory management system needs to query the current inventory data, which is used to reflect the latest inventory status to ensure the accuracy of the data during the inventory update operation and avoid inconsistencies and errors in the updated data. Then, the inventory is updated according to the parsed inventory update data and the current inventory data to obtain the updated inventory data. Then, the updated inventory data is converted into the format required for the API response. If the amount of data in the updated inventory data is large, paging processing is performed to reduce the amount of data in a single response and improve the response speed. Then, the updated inventory data after the format conversion and / or paging processing is encapsulated to obtain the HTTP response body, and the encapsulated HTTP response is returned to the second associated system through the inventory update instruction. After receiving the HTTP response message, the second associated system will parse and process it to determine whether the inventory update operation is successfully executed, so as to timely discover errors encountered during the inventory update process, which helps to ensure the accuracy of data during the inventory update operation. The second associated system can be: a warehouse management system, a production management system, a supply chain management system, an e-commerce platform, etc.

[0031] Step S104: Obtain inventory warning rules, perform inventory analysis based on the updated inventory data and inventory warning rules, and determine the inventory analysis results; when the inventory analysis result is an inventory abnormality, generate inventory warning information, and send the inventory warning information to the third related system through the inventory warning API interface, which helps to respond to inventory abnormalities in a timely manner and optimize inventory resource allocation.

[0032] For the embodiment of the present application, inventory warning rules are pre-defined in the inventory management system. By continuously obtaining updated inventory data and applying inventory warning rules, it is possible to monitor the inventory status and quickly identify inventory anomalies. The timely discovery mechanism helps inventory managers to adopt targeted measures, which helps to respond to inventory anomalies in a timely manner and optimize inventory resource allocation.

[0033] Specifically, obtain inventory warning rules. There are many ways to determine inventory warning rules. They can be set based on multiple factors such as inventory quantity, inventory turnover rate, safety inventory level, shelf life, etc. Of course, they can also be set according to the needs of inventory management. The embodiment of this application is no longer limited. In an achievable way, the way to determine the inventory warning rules includes: obtaining historical sales data, performing multidimensional data analysis based on historical sales data, and determining the multidimensional analysis results, wherein the multidimensional data analysis includes: seasonal analysis, sales trend analysis, and related factor analysis; performing basic threshold calculation based on the average sales volume and inventory turnover rate corresponding to the historical sales data, and determining the basic inventory warning threshold; performing dynamic analysis of warning thresholds based on the basic inventory warning threshold and the multidimensional analysis results, determining the inventory warning threshold sequence, and using the inventory warning threshold sequence as the evaluation standard in the inventory warning rule, wherein the inventory warning threshold sequence is a dynamically changing inventory warning threshold set arranged in chronological order. Then, perform inventory analysis based on the updated inventory data and inventory warning rules to determine the inventory analysis results, that is, compare the updated inventory data with the inventory warning rules to determine whether the inventory status meets the warning conditions. When the inventory analysis result is an inventory abnormality, the abnormality type and severity are determined, and inventory warning information is generated based on the abnormality type and severity, wherein the inventory warning information includes but is not limited to: abnormality description, scope of impact, recommended measures and other key contents. Then, the inventory warning information is converted into the format required for the API response (for example, JSON, XML, etc.), and the inventory warning information is sent to the third associated system through the inventory warning API interface, wherein the third associated system is usually a warehouse management system, and the sent inventory warning information helps the warehouse management system to more accurately arrange picking, replenishment and other operations, thereby improving warehouse operation efficiency. In the embodiment of the present application, an intelligent inventory management method is adopted, and a variety of API interfaces and automated processes are integrated, which effectively solves the defects of insufficient intelligence faced in traditional school uniform inventory management, realizes real-time synchronization and automated processing of inventory data, and improves the efficiency and accuracy of inventory management.

[0034] It can be seen that in the embodiment of the present application, a variety of API interfaces are used to establish a connection between the inventory management system and the associated system, so that data exchange and functional interaction between the systems are realized, and thus, the inventory query API interface, the inventory update API interface and the inventory warning API interface are obtained. When the inventory query instruction is detected, the inventory management system is controlled to query the inventory data based on the query parameters corresponding to the inventory query instruction, and the target inventory data is obtained, and the target inventory data is returned to the first associated system through the inventory query API interface. When the inventory update instruction carrying the inventory update data is detected, the inventory is updated based on the inventory update data and the current inventory data to obtain the updated inventory data, and the updated inventory data is returned to the second associated system through the inventory update instruction, which is helpful to determine whether the inventory update operation is successfully executed. After that, the inventory analysis is performed based on the updated inventory data and the inventory warning rules to determine the inventory analysis results; when the inventory analysis result is an inventory abnormality, the inventory warning information is generated, and the inventory warning information is sent to the third associated system through the inventory warning API interface, which is helpful to respond to the inventory abnormality in time and optimize the inventory resource configuration. The adoption of intelligent inventory management methods and the integration of multiple API interfaces and automated processes effectively solves the lack of intelligence faced by traditional school uniform inventory management, realizes real-time synchronization and automated processing of inventory data, and improves the efficiency and accuracy of inventory management.

[0035] Furthermore, in order to formulate inventory warning rules that are closer to actual needs and improve the accuracy and efficiency of inventory management, in the embodiment of the present application, the method for determining the inventory warning rules includes: Obtain historical sales data, conduct multidimensional data analysis based on the historical sales data, and determine the multidimensional analysis results, wherein the multidimensional data analysis includes: seasonal analysis, sales trend analysis, and related factor analysis; Calculate the basic threshold based on the average sales volume and inventory turnover rate corresponding to the historical sales data to determine the basic inventory warning threshold; Based on the basic inventory warning threshold and the multi-dimensional analysis results, a warning threshold dynamic analysis is performed to determine the inventory warning threshold sequence, and the inventory warning threshold sequence is used as the evaluation criterion in the inventory warning rule, where the inventory warning threshold sequence is a dynamically changing inventory warning threshold set arranged in chronological order.

[0036] For the embodiment of the present application, historical sales data is obtained, and historical sales data refers to historical school uniform sales data in at least one complete sales cycle in the past, including but not limited to: sales quantity, sales time, sales cycle, etc. Then, multidimensional data analysis is performed based on the historical sales data to determine the multidimensional analysis results, wherein the multidimensional data analysis includes: seasonal analysis, sales trend analysis and related factor analysis. For seasonal analysis, the impact of seasonality on school uniform sales is analyzed, such as the start of school season, graduation season, changes in material demand caused by seasonal changes, etc., and seasonal sales patterns are identified through time series analysis, such as which months are sales peaks in a complete sales cycle. For sales trend analysis, current market trends are focused on, including but not limited to: popular trends, competitor conditions, student demographics, etc., and statistical models are used to predict future sales trends to determine the subsequent sales trends of school uniforms in the sales cycle. For related factor analysis, the impact of special events on school uniform sales and inventory demand is considered, such as school activities, policy changes, emergencies (e.g., delayed school opening), etc., and the degree and direction of the impact of special events on inventory demand (increase or decrease in inventory demand) are analyzed.

[0037] Furthermore, the average sales volume corresponding to the historical sales data is the average value of the historical sales data, reflecting the number of school uniforms that are usually expected to be sold during the sales cycle. The inventory turnover rate refers to the number of times the inventory goods are turned over during the sales cycle. It is a comprehensive indicator to measure and evaluate the management status of each link of the enterprise, such as purchasing inventory, putting into production, and selling and recovering. Based on the inventory turnover rate, the inventory turnover days are determined, where the inventory turnover days = 365 / inventory turnover rate. Then, based on the average sales volume and inventory turnover rate corresponding to the historical sales data, the basic threshold is calculated to determine the basic inventory warning threshold. The calculation formula is: basic inventory warning threshold = (inventory turnover days + replenishment lead time) * average sales volume + safety stock, where the safety stock is the additional inventory retained to deal with uncertain factors (such as demand fluctuations, supply chain delays, etc.), and the replenishment lead time is the time required from placing an order to the arrival of the goods.

[0038] After that, the warning threshold is dynamically analyzed based on the basic inventory warning threshold and the multidimensional analysis results to determine the inventory warning threshold sequence, and the inventory warning threshold sequence is used as the evaluation standard in the inventory warning rule. The inventory warning threshold sequence is a dynamically changing inventory warning threshold set arranged in chronological order. In the process of executing the dynamic analysis of the warning threshold, the size of the basic inventory warning threshold is dynamically adjusted by the multidimensional analysis results. For example, the seasonal analysis represents the existence of a sales peak period. Therefore, before the seasonal peak period, the basic warning threshold is adjusted according to the seasonal coefficient. The specific method is to multiply the basic warning threshold by the seasonal coefficient to obtain the warning threshold applicable to the sales peak period of the season. In the sales trend analysis, if the forecast shows that future sales will increase significantly, the basic warning threshold should be increased accordingly to avoid out-of-stock; if the forecast shows that sales will decrease, the basic warning threshold should be lowered to avoid inventory backlog; the increase or decrease can be set according to the actual situation. In the case of a sudden event of delayed school opening in the relevant factor analysis, which will lead to a sharp decline in sales, the warning threshold should be quickly lowered and the inventory strategy should be adjusted to reduce inventory backlog and capital occupation. Through multi-dimensional data analysis, we can more accurately grasp the changing patterns and influencing factors of school uniform sales, and thus formulate inventory warning rules that are closer to actual needs, which will help reduce losses caused by excessive or insufficient inventory and improve the accuracy and efficiency of inventory management.

[0039] It can be seen that in the embodiment of the present application, a multidimensional data analysis is performed based on the historical sales data to determine the multidimensional analysis results, wherein the multidimensional data analysis includes: seasonal analysis, sales trend analysis and related factor analysis. Then, the basic threshold is calculated based on the average sales volume and inventory turnover rate corresponding to the historical sales data to determine the basic inventory warning threshold. After that, a dynamic analysis of the warning threshold is performed based on the basic inventory warning threshold and the multidimensional analysis results to determine the inventory warning threshold sequence, and the inventory warning threshold sequence is used as the evaluation criterion in the inventory warning rule. Through multidimensional data analysis, it is possible to more accurately grasp the changing laws and influencing factors of school uniform sales, thereby formulating inventory warning rules that are closer to actual needs, which helps to reduce losses caused by excessive inventory or insufficient inventory, and improve the accuracy and efficiency of inventory management.

[0040] Furthermore, in order to obtain more accurate analysis results and predict the trend and degree of future inventory risks, in the embodiment of the present application, inventory analysis is performed based on the updated inventory data and inventory warning rules to determine the inventory analysis results, including: Performing inventory update forecast based on the updated inventory data, and determining the target inventory data corresponding to the target period, wherein the target period is a period starting from the current time and spanning a preset time length; Select warning thresholds based on inventory warning rules and target time periods, and determine the target warning threshold sequence corresponding to the target time period; Perform inventory analysis based on target inventory data and target warning threshold sequence to determine inventory analysis results.

[0041] For the embodiment of the present application, the time series analysis method is used to perform inventory update prediction on the updated inventory data, and determine the target inventory data corresponding to the target period, wherein the target period is a period starting from the current time and spanning a preset time. The specific time length can be set by the user based on actual needs, and the embodiment of the present application is no longer limited, and the target inventory data may include: predicted inventory quantity and inventory change trend and other information. Since the inventory warning threshold sequence is a dynamically changing inventory warning threshold set arranged in chronological order, the warning threshold is selected based on the inventory warning rules and the target period, and the target warning threshold sequence corresponding to the target period is determined. The target warning threshold sequence can reflect the dynamic changes of inventory risks within the target period. Finally, based on the target inventory data and the target warning threshold sequence, according to the time series corresponding comparison, it is determined whether there is excess inventory, shortage or other abnormal conditions, and the relevant conditions corresponding to the comparison results are recorded as inventory analysis results. Through real-time prediction and dynamic early warning, the risk of inventory shortage or surplus can be discovered in advance, and corresponding measures can be taken to prevent and correct it. Combining target inventory data and target early warning threshold sequence for inventory analysis can obtain more accurate analysis results, which can not only reflect the health of the current inventory status, but also predict the trend and degree of future inventory risks.

[0042] It can be seen that in the embodiment of the present application, an inventory update forecast is performed based on the updated inventory data to determine the target inventory data corresponding to the target period, and then, a warning threshold is selected based on the inventory warning rules and the target period to determine the target warning threshold sequence corresponding to the target period. Finally, an inventory analysis is performed based on the target inventory data and the target warning threshold sequence to determine the inventory analysis results. Through real-time prediction and dynamic warning, the risk of inventory shortage or surplus can be discovered in advance. Combining the target inventory data and the target warning threshold sequence for inventory analysis can obtain more accurate analysis results, which can not only reflect the health of the current inventory status, but also predict the trend and degree of future inventory risks.

[0043] Furthermore, in order to ensure real-time synchronization and consistency of data, in the embodiment of the present application, it also includes: Invite participants in the school uniform supply chain to become nodes in the blockchain network and jointly build a school uniform inventory management platform based on blockchain technology; Store the inventory data corresponding to the inventory management system on the blockchain so that each node can view and verify the inventory data; Leverage smart contract technology to automate inventory allocation and replenishment logic.

[0044] For the embodiments of the present application, the participants in the school uniform supply chain include but are not limited to: manufacturers, suppliers, schools, distributors, etc., and each participant is an indispensable part of the school uniform supply chain. Invite the participants in the school uniform supply chain to join the blockchain network as a node. The node can be a physical server or a cloud server, and the corresponding blockchain software needs to be installed and the necessary network parameters need to be configured. At the same time, the nodes are connected through a point-to-point communication protocol to form a decentralized network structure. The decentralized nature of the blockchain ensures real-time synchronization and consistency of data, avoiding errors caused by inconsistent data or delayed updates in traditional systems. Then, the inventory data corresponding to the inventory management system is stored on the blockchain, so that each node can view and verify the inventory data, and realize information sharing and transparency. This highly transparent mechanism can reduce information asymmetry, enhance trust between the participants in the supply chain, and thus optimize the cooperation process.

[0045] Smart contract technology is used to automatically execute inventory allocation and replenishment logic. For example, when a school makes a purchase request, the smart contract can automatically match inventory information, generate a purchase order and send it to the supplier. At the same time, the smart contract can also automatically trigger the replenishment process based on inventory levels and sales forecasts to ensure stable inventory levels.

[0046] It can be seen that in the embodiment of the present application, the participants of the school uniform supply chain are invited to become nodes in the blockchain network to jointly build a school uniform inventory management platform based on blockchain technology. The decentralized nature of the blockchain ensures the real-time synchronization and consistency of the data. Then, the inventory data corresponding to the inventory management system is stored on the blockchain so that each node can view and verify the inventory data. The highly transparent mechanism can reduce information asymmetry and enhance the trust between the participants in the supply chain, thereby optimizing the cooperation process. At the same time, the smart contract technology is used to automatically execute the inventory allocation and replenishment logic.

[0047] Furthermore, in order to increase the competitiveness and flexibility of the supply chain and improve the accuracy and efficiency of replenishment operations, in an embodiment of the present application, the implementation of the replenishment logic includes: Perform replenishment analysis based on inventory data and determine the replenishment analysis results. When the replenishment analysis results show that there is a replenishment demand, the replenishment process is automatically triggered; When the replenishment process is triggered, replenishment invitations are automatically sent to suppliers in the school uniform supply chain, and bidding information fed back by each supplier is collected, where the bidding information includes: replenishment quotation and delivery time; Based on the bidding information corresponding to each supplier, intelligent analysis is performed to determine the target supplier, obtain the replenishment order and send it to the target supplier to complete the intelligent replenishment operation of school uniforms.

[0048] For the embodiment of the present application, the smart contract code records the logical process of judging whether the inventory data needs to be replenished, and the replenishment threshold is pre-set. The replenishment threshold is set according to factors such as the sales speed of school uniforms, the response time of the supply chain, and the safety inventory level. Therefore, when performing the replenishment analysis, the inventory data and the replenishment threshold are compared to evaluate whether replenishment is needed and determine the replenishment analysis result. When the replenishment analysis result shows that there is a replenishment demand, the replenishment process is automatically triggered, and a replenishment invitation is automatically sent to the supplier in the school uniform supply chain, wherein the replenishment invitation includes but is not limited to: replenishment demand, medium date and other information. At the same time, an API interface is designed and opened to receive the supplier's bidding information, wherein the bidding information includes: replenishment quotation and delivery time. Furthermore, based on the bidding information corresponding to each supplier, an intelligent analysis is performed to determine the target supplier. When performing the intelligent analysis operation, the electronic device pre-stores the bidding evaluation criteria, and automatically scores and sorts based on the bidding evaluation criteria and the bidding information corresponding to each supplier, and automatically selects the best supplier as the target supplier according to the scoring criteria, wherein the bidding evaluation criteria are set from multiple dimensions such as price, delivery time, and historical performance. After that, a replenishment order is obtained, which can be automatically generated by the electronic device and manually verified, and sent to the target supplier to complete the intelligent replenishment operation of school uniforms. The introduction of a bidding mechanism enables multiple suppliers in the school uniform supply chain to participate in the replenishment bidding, which increases the competitiveness and flexibility of the supply chain. In addition, the automated replenishment process reduces manual intervention, reduces the risk of human error, and improves the accuracy and efficiency of replenishment operations.

[0049] It can be seen that in the embodiment of the present application, a replenishment analysis is performed based on inventory data to determine the replenishment analysis results. When the replenishment analysis results show that there is a replenishment demand, the replenishment process is automatically triggered. When the replenishment process is triggered, a replenishment invitation is automatically sent to the suppliers in the school uniform supply chain, and the bidding information fed back by each supplier is collected. Finally, an intelligent analysis is performed based on the bidding information corresponding to each supplier, the target supplier is determined, and the replenishment order is obtained and sent to the target supplier to complete the intelligent replenishment operation of school uniforms. The introduction of the bidding mechanism increases the competitiveness and flexibility of the supply chain, and the automated replenishment process reduces manual intervention and improves the accuracy and efficiency of the replenishment operation.

[0050] Furthermore, in order to ensure the stable operation of the database, in the embodiment of the present application, it also includes: Monitor operation instructions in real time, and obtain user identity data, operation data information, and response result information corresponding to the operation instructions, wherein the operation instructions include: inventory query instructions and inventory update instructions; Record entries based on user identity data, operation data information, and response result information to determine log entries; Obtain the inventory change log and populate the log entries into the inventory change log to implement an audit trail of database operations; When it is detected that the log audit cycle has been reached, the operation behavior analysis is performed based on the inventory change log and a log audit report is generated.

[0051] For the embodiment of the present application, an operation instruction monitoring mechanism is pre-set to monitor the inventory query instructions and inventory update instructions sent by the relevant system in real time, and use technical means such as middleware, API gateway or database trigger to intercept and parse the operation instructions to ensure that user identity data (e.g., user ID, user name) and operation data information (e.g., operation type, operation object, operation parameters, etc.) can be extracted from the operation instructions. Of course, it is also necessary to obtain response result information (e.g., operation success / failure). However, based on the user identity data, operation data information, and response result information, a log entry format is assembled to obtain a log entry, wherein the target entry includes but is not limited to fields such as timestamp, operation type, user information, operation details, and result status. Further, the log entry is filled into the inventory change log to ensure that the log system can efficiently store and retrieve a large amount of log data and realize database operation audit tracking. Through real-time monitoring and recording of operation instructions, operations that may cause system instability can be discovered and prevented in a timely manner, thereby ensuring the stable operation of the database.

[0052] When the detection reaches the log audit cycle, the operation behavior analysis is performed based on the inventory change log to generate a log audit report, where the log audit report includes but is not limited to: operation statistics, abnormal behavior identification, performance bottleneck analysis, etc. After that, abnormal behavior monitoring, performance optimization analysis, business process optimization analysis and automated backup operations can also be performed on the inventory change log. For abnormal behavior monitoring, by setting thresholds and rules, abnormal operations in the inventory change log are monitored in real time. Once abnormal behavior is detected, the alarm mechanism is triggered immediately to notify relevant personnel to handle it. For performance optimization analysis, by analyzing the operation type and frequency in the inventory change log, operations that have a greater impact on database performance are identified, and based on the analysis results, performance optimization suggestions are proposed, such as optimizing query statements, adjusting index strategies, and increasing hardware resources. For business process optimization analysis, combined with inventory change logs and business needs, the bottlenecks and redundant links in the business process are analyzed, and based on the analysis results, business process optimization solutions are proposed, such as simplifying process steps and automating tasks. For automated backup operations, an automated backup and recovery strategy is developed based on the analysis results of the inventory change log. When important data changes are detected, the backup operation is automatically triggered; when data recovery is required, the data is quickly restored based on the log records.

[0053] It can be seen that in the embodiment of the present application, the operation instructions are monitored in real time, the user identity data, operation data information, and response result information corresponding to the operation instructions are obtained, and entries are recorded based on the user identity data, operation data information, and response result information to determine the log entries. Then, the inventory change log is obtained, and the log entries are filled into the inventory change log to realize database operation audit tracking. Through real-time monitoring and recording of operation instructions, operations that may cause system instability can be discovered and prevented in a timely manner, thereby ensuring the stable operation of the database. When it is detected that the log audit cycle has been reached, the operation behavior analysis is performed based on the inventory change log, and a log audit report is generated.

[0054] The above-mentioned embodiment introduces an intelligent inventory management method from the perspective of method flow, and the following embodiment introduces an intelligent inventory management device from the perspective of a virtual module or a virtual unit. Please refer to the following embodiment for details.

[0055] The present application embodiment provides an intelligent inventory management device, such as Figure 2 As shown, the intelligent inventory management device may specifically include: The interface acquisition module 210 is used to acquire the inventory query API interface, the inventory update API interface and the inventory warning API interface, wherein the multiple API interfaces are used to establish a connection between the inventory management system and the associated system; The inventory query module 220 is used to control the inventory management system to query inventory data based on the query parameters corresponding to the inventory query instruction when the inventory query instruction is detected, obtain target inventory data, and return the target inventory data to the first associated system through the inventory query API interface, wherein the inventory query instruction is a query instruction generated by the first associated system by calling the inventory query API interface; The inventory update module 230 is used to perform inventory update based on the inventory update data and the current inventory data to obtain updated inventory data when an inventory update instruction carrying inventory update data is detected, wherein the inventory update instruction is an inventory update instruction generated by the second associated system by calling the inventory update API interface; the updated inventory data is returned to the second associated system through the inventory update instruction, which helps to determine whether the inventory update operation is successfully executed; The inventory warning module 240 is used to obtain inventory warning rules, perform inventory analysis based on the updated inventory data and inventory warning rules, and determine the inventory analysis results; when the inventory analysis result is an inventory abnormality, generate inventory warning information, and send the inventory warning information to the third related system through the inventory warning API interface, which helps to respond to inventory abnormalities in a timely manner and optimize inventory resource allocation.

[0056] For the embodiment of the present application, a variety of API interfaces are used to establish a connection between the inventory management system and the associated system, so that data exchange and functional interaction between the systems are realized, thereby obtaining an inventory query API interface, an inventory update API interface, and an inventory warning API interface. When an inventory query instruction is detected, the inventory management system is controlled to query the inventory data based on the query parameters corresponding to the inventory query instruction, obtain the target inventory data, and return the target inventory data to the first associated system through the inventory query API interface. When an inventory update instruction carrying inventory update data is detected, the inventory is updated based on the inventory update data and the current inventory data to obtain the updated inventory data, and the updated inventory data is returned to the second associated system through the inventory update instruction, which helps to determine whether the inventory update operation is successfully executed. After that, an inventory analysis is performed based on the updated inventory data and the inventory warning rules to determine the inventory analysis results; when the inventory analysis result is an inventory abnormality, an inventory warning information is generated, and the inventory warning information is sent to the third associated system through the inventory warning API interface, which helps to respond to inventory abnormalities in a timely manner and optimize inventory resource allocation. The adoption of intelligent inventory management methods and the integration of multiple API interfaces and automated processes effectively solves the lack of intelligence faced by traditional school uniform inventory management, realizes real-time synchronization and automated processing of inventory data, and improves the efficiency and accuracy of inventory management.

[0057] In a possible implementation of the embodiment of the present application, the intelligent inventory management device further includes: The early warning rule determination module is used to obtain historical sales data, perform multidimensional data analysis based on the historical sales data, and determine the multidimensional analysis results, wherein the multidimensional data analysis includes: seasonal analysis, sales trend analysis and related factor analysis; Calculate the basic threshold based on the average sales volume and inventory turnover rate corresponding to the historical sales data to determine the basic inventory warning threshold; Based on the basic inventory warning threshold and the multi-dimensional analysis results, a warning threshold dynamic analysis is performed to determine the inventory warning threshold sequence, and the inventory warning threshold sequence is used as the evaluation criterion in the inventory warning rule, where the inventory warning threshold sequence is a dynamically changing inventory warning threshold set arranged in chronological order.

[0058] In a possible implementation of the embodiment of the present application, when the inventory warning module 240 performs inventory analysis based on the updated inventory data and the inventory warning rules and determines the inventory analysis result, it is used to: Performing inventory update forecast based on the updated inventory data, and determining the target inventory data corresponding to the target period, wherein the target period is a period starting from the current time and spanning a preset time length; Select warning thresholds based on inventory warning rules and target time periods, and determine the target warning threshold sequence corresponding to the target time period; Perform inventory analysis based on target inventory data and target warning threshold sequence to determine inventory analysis results.

[0059] In a possible implementation of the embodiment of the present application, the intelligent inventory management device further includes: The data sharing module is used to invite participants in the school uniform supply chain to become nodes in the blockchain network and jointly build a school uniform inventory management platform based on blockchain technology; Store the inventory data corresponding to the inventory management system on the blockchain so that each node can view and verify the inventory data; Leverage smart contract technology to automate inventory allocation and replenishment logic.

[0060] In a possible implementation of the embodiment of the present application, the intelligent inventory management device further includes: The intelligent replenishment module is used to perform replenishment analysis based on inventory data and determine the replenishment analysis results. When the replenishment analysis results show that there is a replenishment demand, the replenishment process is automatically triggered; When the replenishment process is triggered, replenishment invitations are automatically sent to suppliers in the school uniform supply chain, and bidding information fed back by each supplier is collected, where the bidding information includes: replenishment quotation and delivery time; Based on the bidding information corresponding to each supplier, intelligent analysis is performed to determine the target supplier, obtain the replenishment order and send it to the target supplier to complete the intelligent replenishment operation of school uniforms.

[0061] In a possible implementation of the embodiment of the present application, the intelligent inventory management device further includes: The log audit module is used to monitor the operation instructions in real time and obtain the user identity data, operation data information, and response result information corresponding to the operation instructions, wherein the operation instructions include: inventory query instructions and inventory update instructions; Record entries based on user identity data, operation data information, and response result information to determine log entries; Obtain the inventory change log and populate the log entries into the inventory change log to implement an audit trail of database operations; When it is detected that the log audit cycle has been reached, the operation behavior analysis is performed based on the inventory change log and a log audit report is generated.

[0062] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the intelligent inventory management device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0063] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0064] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0065] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0066] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0067] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0068] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0069] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0070] The embodiment of the present application provides a computer program product, which includes a computer program, which implements the method in any of the above embodiments when executed by a processor. Compared with the related art, the embodiment of the present application uses a variety of API interfaces to connect the inventory management system with the associated system, realizes data exchange and functional interaction between the systems, and thus obtains the inventory query API interface, the inventory update API interface and the inventory warning API interface. When the inventory query instruction is detected, the inventory management system is controlled to query the inventory data based on the query parameters corresponding to the inventory query instruction, obtain the target inventory data, and return the target inventory data to the first associated system through the inventory query API interface. When the inventory update instruction carrying the inventory update data is detected, the inventory is updated based on the inventory update data and the current inventory data to obtain the updated inventory data, and the updated inventory data is returned to the second associated system through the inventory update instruction, which helps to determine whether the inventory update operation is successfully executed. After that, the inventory analysis is performed based on the updated inventory data and the inventory warning rules to determine the inventory analysis results; when the inventory analysis result is an inventory abnormality, the inventory warning information is generated, and the inventory warning information is sent to the third associated system through the inventory warning API interface, which helps to respond to the inventory abnormality in time and optimize the inventory resource configuration. The adoption of intelligent inventory management methods and the integration of multiple API interfaces and automated processes effectively solves the lack of intelligence faced by traditional school uniform inventory management, realizes real-time synchronization and automated processing of inventory data, and improves the efficiency and accuracy of inventory management.

[0071] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0072] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. An intelligent inventory management method, characterized in that: include: Obtain inventory query API interface, inventory update API interface and inventory warning API interface. Among them, multiple API interfaces are used to build connections between the inventory management system and related systems; When an inventory query instruction is detected, based on the query parameters corresponding to the inventory query instruction, the inventory management system is controlled to query the inventory data, obtain the target inventory data, and return the target inventory data to the first associated system through the inventory query API interface, wherein the inventory query instruction is a query instruction generated by the first associated system by calling the inventory query API interface; When an inventory update instruction carrying inventory update data is detected, the inventory is updated based on the inventory update data and the current inventory data to obtain updated inventory data, wherein the inventory update instruction is an inventory update instruction generated by the second associated system by calling the inventory update API interface; Returning the updated inventory data to the second associated system via the inventory update instruction helps determine whether the inventory update operation is successfully performed; Acquire inventory warning rules, perform inventory analysis based on the updated inventory data and the inventory warning rules, and determine inventory analysis results; When the inventory analysis result is an inventory abnormality, inventory warning information is generated, and the inventory warning information is sent to the third related system through the inventory warning API interface, which helps to respond to inventory abnormalities in a timely manner and optimize inventory resource allocation.

2. The intelligent inventory management method according to claim 1, characterized in that: The method for determining the inventory warning rule includes: Acquire historical sales data, perform multidimensional data analysis based on the historical sales data, and determine the multidimensional analysis results, wherein the multidimensional data analysis includes: seasonal analysis, sales trend analysis, and related factor analysis; Calculate the basic threshold based on the average sales volume and inventory turnover rate corresponding to the historical sales data to determine the basic inventory warning threshold; Based on the basic inventory warning threshold and the multi-dimensional analysis result, a warning threshold dynamic analysis is performed to determine an inventory warning threshold sequence, and the inventory warning threshold sequence is used as an evaluation criterion in the inventory warning rule, wherein the inventory warning threshold sequence is a dynamically changing inventory warning threshold set arranged in chronological order.

3. The intelligent inventory management method according to claim 2, characterized in that: The performing inventory analysis based on the updated inventory data and the inventory warning rule to determine the inventory analysis result includes: Performing inventory update forecast based on the updated inventory data to determine target inventory data corresponding to a target time period, wherein the target time period is a time period starting from the current time and spanning a preset time period; Selecting warning thresholds based on the inventory warning rules and the target period, and determining a target warning threshold sequence corresponding to the target period; An inventory analysis is performed based on the target inventory data and the target early warning threshold sequence to determine an inventory analysis result.

4. The intelligent inventory management method according to claim 1, characterized in that: Also includes: Invite participants in the school uniform supply chain to become nodes in the blockchain network and jointly build a school uniform inventory management platform based on blockchain technology; Storing inventory data corresponding to the inventory management system on the blockchain so that each node can view and verify the inventory data; Leverage smart contract technology to automate inventory allocation and replenishment logic.

5. The intelligent inventory management method according to claim 4 is characterized in that: The implementation of the replenishment logic includes: Perform replenishment analysis based on inventory data to determine a replenishment analysis result, and automatically trigger a replenishment process when the replenishment analysis result indicates that there is a replenishment demand; When the replenishment process is triggered, replenishment invitations are automatically sent to suppliers in the school uniform supply chain, and bidding information fed back by each supplier is collected, wherein the bidding information includes: replenishment quotation and delivery time; Based on the bidding information corresponding to each supplier, intelligent analysis is performed to determine the target supplier, obtain the replenishment order and send it to the target supplier to complete the intelligent replenishment operation of school uniforms.

6. The intelligent inventory management method according to claim 1, characterized in that: Also includes: Monitor the operation instructions in real time, and obtain the user identity data, operation data information, and response result information corresponding to the operation instructions, wherein the operation instructions include: inventory query instructions and inventory update instructions; Recording entries based on the user identity data, the operation data information, and the response result information to determine log entries; Obtaining an inventory change log, and filling the log entry into the inventory change log to implement a database operation audit trail; When it is detected that the log audit cycle has been reached, an operation behavior analysis is performed based on the inventory change log to generate a log audit report.

7. An electronic device, characterized in that: include: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the intelligent inventory management method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the intelligent inventory management method as described in any one of claims 1 to 6.

9. A computer program product, characterized in that The invention comprises a computer program, wherein the computer program is executed by a processor to implement the intelligent inventory management method according to any one of claims 1 to 6.

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