Smart warehouse management method and system

Abstract

The present disclosure provides a smart warehouse management method and system, which belongs to the field of warehouse management technology. The method includes: determining the cargo identification based on the information of incoming goods. If the cargo identification is a special cargo identification, the cargo corresponding to the special cargo identification is managed based on the first inspection instruction. The first inspection instruction is used to instruct the inspection robot to manage the cargo based on the first inspection mode. If the cargo identification is an ordinary cargo identification, the cargo corresponding to the ordinary cargo identification is managed based on the second inspection instruction. The second inspection instruction is used to instruct the inspection robot to manage the cargo based on the second inspection mode. The inspection frequency of the first inspection mode is greater than the inspection frequency of the second inspection mode. The smart warehouse management method and system provided by the present disclosure can improve the intelligence level of warehouse management.

Description

Technical Field

[0001] The present disclosure belongs to the field of warehouse management technology, and more specifically, to a smart warehouse management method and system. Background Art

[0002] With the development of the warehousing industry, society's demand for intelligent and efficient warehouse management is growing. Traditional warehouse management methods still suffer from a single management method and lack of precision when it comes to managing different types of goods, monitoring cargo status, and updating warehouse data, leading to irrational allocation of management resources.

[0003] Traditional methods for monitoring cargo status rely on regular manual visual inspections, making it difficult to accurately and accurately monitor cargo status in real time. Traditional methods for updating warehouse data often rely on manual data entry, which is not only inefficient but also prone to data errors. Frequent inflows and outflows of goods in warehouses can lead to inaccurate inventory information due to untimely data updates. In summary, the warehousing industry still needs more intelligent management methods to improve efficiency. Summary of the Invention

[0004] The purpose of this disclosure is to provide a smart warehouse management method and system to improve the intelligence level of warehouse management.

[0005] A first aspect of the embodiments of the present disclosure provides a smart warehouse management method, including:

[0006] Determine cargo identification based on incoming cargo information;

[0007] If the cargo identifier is a special cargo identifier, the cargo corresponding to the special cargo identifier is managed based on the first inspection instruction; the first inspection instruction is used to instruct the inspection robot to manage the cargo based on the first inspection mode;

[0008] If the cargo identification is a common cargo identification, the cargo corresponding to the common cargo identification is managed based on the second inspection instruction; the second inspection instruction is used to instruct the inspection robot to manage the cargo based on the second inspection mode; the inspection frequency of the first inspection mode is greater than the inspection frequency of the second inspection mode.

[0009] A second aspect of the embodiments of the present disclosure provides a smart warehouse management system, including:

[0010] Goods identification module, used to determine goods identification based on incoming goods information;

[0011] A first inspection module is configured to manage the goods corresponding to the special goods identification based on a first inspection instruction if the goods identification is a special goods identification; the first inspection instruction is configured to instruct the inspection robot to manage the goods based on a first inspection mode;

[0012] The second inspection module is used to manage the goods corresponding to the ordinary goods identification based on the second inspection instruction if the goods identification is an ordinary goods identification; the second inspection instruction is used to instruct the inspection robot to manage the goods based on the second inspection mode; the inspection frequency of the first inspection mode is greater than the inspection frequency of the second inspection mode.

[0013] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above-mentioned intelligent warehouse management method when executing the computer program.

[0014] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned intelligent warehouse management method are implemented.

[0015] The beneficial effects of the smart warehouse management method and system provided by the embodiments of the present disclosure are:

[0016] By accurately distinguishing between special and general cargo labels and implementing different inspection strategies for different cargoes, special cargo receives special attention while general cargo is properly managed, ensuring that each type of cargo receives appropriate management. Due to their importance and sensitivity, special cargo is inspected at a high frequency to ensure quality; general cargo is inspected at a lower frequency to avoid excessive resource consumption and ensure accurate and efficient use of inspection resources.

[0017] Accurate cargo management and resource allocation reduce issues like cargo damage and expiration, lowering operating costs. At the same time, a rational inspection model reduces unnecessary operational processes, speeds up overall warehouse operations, and makes warehouse management more intelligent and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 A flowchart of a smart warehouse management method provided in one embodiment of the present disclosure;

[0020] Figure 2 A structural diagram of a smart warehouse management system provided by an embodiment of the present disclosure;

[0021] Figure 3 A schematic block diagram of an electronic device provided in one embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present disclosure. However, it will be apparent to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present disclosure with unnecessary detail.

[0023] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below with reference to the accompanying drawings.

[0024] Please refer to Figure 1 , Figure 1 This is a flow chart of a smart warehouse management method provided in one embodiment of the present disclosure. The method may include S101 to S103.

[0025] S101: Determine the cargo identification of the cargo based on the incoming cargo information.

[0026] In this embodiment, incoming goods information refers to the information recorded when goods are received, such as basic attributes such as the name, specifications, and characteristics of the goods. A goods identifier is a mark used to uniquely identify the goods. The goods identifier can be a QR code, RFID tag, or other such code.

[0027] For example, incoming goods information can be obtained through manual entry, scanning, or integration with supplier systems. The incoming goods information is analyzed and categorized into different categories, such as special goods or general goods. Based on these categories and the incoming goods information, a unique goods identifier is assigned to the goods. The resulting goods identifier not only indicates basic information about the goods but also distinguishes the goods' category.

[0028] For example, a barcode scanner, RFID reader, or other scanning device can be used to read the basic attribute information of the goods as they enter the warehouse, and collect the goods' real-time appearance and quality information. Based on this basic attribute information, the goods' real-time appearance, and the goods' quality, the goods are classified and a goods identification is generated. For example, for food goods, each item can be classified as special goods or general goods based on information such as its production date, shelf life, storage conditions, and manufacturer. The corresponding goods identification is generated based on the goods' category and basic attribute information.

[0029] S102: If the cargo identification is a special cargo identification, the cargo corresponding to the special cargo identification is managed based on a first inspection instruction. The first inspection instruction is used to instruct the inspection robot to manage the cargo based on a first inspection mode.

[0030] In this embodiment, the special cargo identifier is used to indicate special cargo that has high storage environment requirements, high value, is easily perishable, or is damaged. The high or low storage environment requirements, high or low value, and whether or not it is easily perishable or easily damaged can be defined based on a pre-set relationship mapping table, threshold, or classification standard.

[0031] The first inspection instruction is a set of commands instructing the inspection robot to manage special cargo. The first inspection instruction may include parameters such as inspection frequency and inspection content. The first inspection mode represents the manner in which the inspection robot performs its inspection tasks. The first inspection mode can be used to determine, among other things, the inspection frequency, inspection speed, cargo inspection method, and data recording method.

[0032] For example, when the smart warehouse management system identifies a cargo identification as a special cargo identification, it generates a first inspection instruction. The first inspection instruction is set based on cargo characteristic parameters contained in the special cargo identification to ensure that the inspection robot can monitor the cargo status in a timely and accurate manner.

[0033] Following the first inspection instruction and the first inspection mode, the inspection robot moves within the warehouse to the area containing the special cargo and conducts cargo inspections. The inspection robot wirelessly communicates with various sensors or detection equipment near the special cargo to obtain information about the storage environment and the cargo's status. Furthermore, following the first inspection instruction, the inspection robot uses its own detection equipment to inspect the cargo and feeds the collected data back to the smart warehouse management system. Based on this data, the smart warehouse management system can determine whether the cargo is in normal condition and issue an alert if any abnormality is detected.

[0034] For example, a large agricultural product storage center stores a batch of fresh durians. Because these durians are extremely sensitive to temperature and humidity and easily deteriorate, they are marked with a special cargo identification. Based on this special cargo identification, the smart warehouse management system generates a first inspection instruction, including a schedule for inspections of the durian storage area every three hours. In the first inspection mode, the inspection robot moves along a planned route to the durian storage area at a speed of 15 meters per minute, connects to the temperature and humidity sensors in the storage area, obtains environmental parameters, and uses an image recognition camera to detect cracks in the durian skin, mold, and other conditions.

[0035] If no abnormalities are detected during a particular inspection, the inspection will continue based on the first inspection mode. If an abnormality is detected during a particular inspection, the abnormal area and type will be recorded and the recorded abnormality data will be fed back to the smart warehouse management system. The smart warehouse management system will adjust the first inspection mode based on the abnormality data, increase the inspection frequency of the first inspection mode, and manage the outbound delivery of goods in the abnormal area.

[0036] For example, when the inspection robot detects that the humidity of a certain cargo location is higher than the standard value, it can immediately issue an alarm to remind warehouse managers to take measures, such as increasing ventilation in the area, to prevent durian from rotting faster due to excessive humidity and ensure the quality of special goods.

[0037] S103: If the cargo identification is a common cargo identification, the cargo corresponding to the common cargo identification is managed based on a second inspection instruction. The second inspection instruction is used to instruct the inspection robot to manage the cargo based on a second inspection mode. The inspection frequency of the first inspection mode is greater than the inspection frequency of the second inspection mode.

[0038] In this embodiment, the "normal cargo" tag is used to identify goods other than those with special cargo tags, specifically ordinary goods with low storage requirements, low value, and high resistance to deterioration. The second inspection instruction is a set of commands instructing the inspection robot to manage normal cargo. The second inspection mode represents the inspection method used by the inspection robot for normal cargo.

[0039] For example, when the smart warehouse management system identifies the goods to be managed as ordinary goods, it generates a second inspection command, instructing the inspection robot to enter the ordinary goods storage area in the second inspection mode. Through movement and inspection, a preliminary inspection of the goods' condition is performed. Ordinary goods are relatively stable and do not require frequent inspections. A lower inspection frequency ensures goods management while avoiding resource waste. During the inspection, the robot feeds back the data to the smart warehouse management system and stores it.

[0040] As can be seen from the above, this embodiment accurately distinguishes between special and general cargo identification and implements different inspection strategies for different types of cargo, ensuring that special cargo receives special attention and general cargo is properly managed, ensuring that each type of cargo receives appropriate management. Special cargo, due to its importance and sensitivity, is inspected at a high frequency to ensure quality; general cargo is inspected at a lower frequency to avoid excessive resource consumption and ensure accurate and efficient use of inspection resources.

[0041] Accurate cargo management and resource allocation reduce issues like cargo damage and expiration, lowering operating costs. At the same time, a rational inspection model reduces unnecessary operational processes, speeds up overall warehouse operations, and makes warehouse management more intelligent and efficient.

[0042] In one embodiment of the present disclosure, managing goods based on the first inspection mode includes:

[0043] For goods marked as special goods:

[0044] The cargo is monitored based on the first inspection frequency to obtain target monitoring information of the cargo.

[0045] A cargo management instruction is generated based on the target monitoring information, and the cargo is managed based on the cargo management instruction.

[0046] In this embodiment, the target monitoring information includes cargo quality and environmental information. The cargo management instructions include cargo outbound instructions, replenishment instructions, and inspection frequency update instructions.

[0047] Generate cargo management instructions based on target monitoring information, including:

[0048] If the cargo quality is greater than or equal to the first threshold, the cargo quality in the second time period to be detected is predicted based on the detected cargo quality in the first time period and the environmental information to obtain the predicted cargo quality.

[0049] An inspection frequency update instruction is generated based on the predicted cargo quality. The inspection frequency update instruction is used to instruct to update the first inspection frequency of the cargo to obtain a second inspection frequency.

[0050] If the quality of the goods is less than the first threshold, a goods delivery instruction and a replenishment instruction are generated.

[0051] In this embodiment, the first inspection frequency refers to the frequency at which the inspection robot regularly inspects goods with special cargo labels. Target monitoring information may include cargo quality and environmental information. Cargo quality may include the physical and chemical properties of the goods. Environmental information may include temperature, humidity, and light intensity. Cargo delivery instructions may include the cargo number, quantity, and destination. Replenishment instructions may include the type and quantity of goods.

[0052] The first threshold is a pre-set standard value used to determine whether goods meet quality standards. Forecasting goods quality refers to analyzing data collected during the first time period to predict the quality of goods in the second time period. For example, by analyzing data such as the active ingredient content and storage environment of a drug over the past week (the first time period), changes in active ingredient content can be predicted over the next month (the second time period), allowing for pre-emptive management measures.

[0053] For example, lobsters stored in a seafood warehouse are marked with special cargo identification. The first inspection frequency is set at once every five hours. The warehouse is equipped with various sensors, including temperature and humidity sensors for monitoring the water temperature and humidity of the lobsters' living environment, which must be maintained at 18-22°C and a salinity of 28-32‰; water quality monitors for water quality; and image recognition equipment for observing lobster activity, limb integrity, and other quality indicators.

[0054] During the inspection process, if the inspection robot detects that the lobster's quality information (such as good activity and intact limbs) exceeds a first threshold, it will predict the lobster's survival status for the next week based on historical inspection data and current environmental parameters. If the predicted lobster quality is low (i.e., the lobster's survival status will be poor in the coming period), the smart warehouse management system will generate an inspection frequency update instruction, increasing the inspection frequency from every five hours to every three hours, so that the lobster's condition can be monitored more promptly and appropriate measures can be taken.

[0055] If, during a patrol inspection, the inspection robot detects that some lobsters have significantly decreased in activity, indicating that the quality of the goods is below the first threshold, the smart warehouse management system will immediately respond and generate a shipment instruction. Relevant staff will follow this instruction to remove the less active lobsters from the warehouse to prevent them from affecting other healthy lobsters. Simultaneously, the smart warehouse management system will generate a replenishment instruction and send it to the purchasing department, reminding them to purchase fresh lobsters to replenish inventory. This ensures that the quality of the lobsters in the warehouse remains high and ensures a stable market supply.

[0056] This embodiment accurately monitors the status of goods, acquiring monitoring information for special goods through high-frequency inspections and promptly identifying potential issues. This embodiment effectively ensures the quality of goods. When goods fall below standard, dispatch and replenishment instructions are quickly generated to remove low-quality goods and replenish them with new ones, maintaining the high quality of goods in the warehouse. This embodiment optimizes the allocation of warehouse resources, improves warehouse operational efficiency, reduces cargo loss, and ensures a stable and high-quality market supply of special goods.

[0057] In one embodiment of the present disclosure, managing goods based on the second inspection mode includes:

[0058] For goods marked as ordinary goods:

[0059] In response to receiving the cargo management instruction, the cargo is inspected based on the cargo management instruction to obtain inspection information.

[0060] Manage cargo based on cargo management instructions and inspection information.

[0061] In this embodiment, the inspection information includes various inspection data about the goods collected by the inspection robot during the inspection task. The goods management instructions in the second inspection mode may include goods entry instructions, goods exit instructions, goods inspection instructions, etc.

[0062] For example, a warehouse management system generates cargo management instructions for general cargo based on the warehouse's operational schedule or scheduled tasks. Upon receiving these instructions, inspection robots conduct inspections of the cargo according to the instructions. The inspection robots collect inspection information through their onboard visual recognition equipment and by connecting to other monitoring devices in the warehouse, and feed this information back to the warehouse management system. The warehouse management system combines these instructions with inspection information to make decisions regarding cargo data updates, storage, and allocation. For example, if insufficient cargo is detected, restocking is arranged; if damaged cargo is detected, staff are alerted to isolate or scrap the cargo.

[0063] This embodiment ensures the orderliness of daily warehouse operations. Based on management instructions and inspection information, goods are rationally allocated to ensure adequate inventory and timely delivery and inbound / outbound shipments. This embodiment promptly identifies cargo issues and takes timely action to reduce cargo losses. Through data feedback and decision-making, cargo data is updated in real time, making warehouse management more accurate and efficient, and effectively improving the overall level of warehouse management.

[0064] In one embodiment of the present disclosure, determining a cargo identification of cargo based on inbound cargo information includes:

[0065] Determine the cargo type and basic cargo information based on the incoming cargo information.

[0066] If the cargo type of the cargo is first-class cargo, the cargo identification of the cargo is determined to be a special cargo identification.

[0067] If the cargo type of the cargo is secondary cargo, the cargo identification of the cargo is determined based on the basic information of the cargo.

[0068] In this embodiment, the cargo types include first-class cargo and second-class cargo. The cargo value, cargo storage condition requirements and market demand of first-class cargo are all higher than those of second-class cargo.

[0069] Determine the cargo type based on the incoming cargo information, including:

[0070] Determine the cargo name based on the incoming cargo information.

[0071] If the cargo name belongs to the first cargo list, the cargo type of the cargo is determined to be first-level cargo.

[0072] If the cargo name belongs to the second cargo list, the cargo type of the cargo is determined to be secondary cargo.

[0073] If the name of the goods does not belong to the first goods list and the second goods list, the goods type of the goods is determined based on the basic goods information of the goods.

[0074] In this embodiment, determining the cargo identification of the cargo based on the basic cargo information includes:

[0075] Determine the price of goods, storage requirements and market demand for goods based on the basic information of the goods.

[0076] Substitute the commodity price, commodity storage condition requirements and market commodity demand into the commodity evaluation function to obtain the commodity evaluation index.

[0077] The goods evaluation function is:

[0078]

[0079] Among them, F(x) represents the goods evaluation index, P represents the goods price, S represents the goods storage condition requirements, and S can be obtained by quantifying storage conditions such as temperature, humidity, ventilation, and other factors. D represents the market demand for goods. For example, D can be calculated using data such as the number of orders over a period of time and the demand heat of market research. Indicates the minimum price of all goods. Indicates the maximum value of all commodity prices. Indicates the minimum value of all cargo storage condition requirements. Indicates the maximum value of all cargo storage condition requirements. Indicates the minimum price of all goods. Indicates the maximum value of all commodity prices. 、 、 represents the weight coefficient, =1.

[0080] If the cargo evaluation index is greater than or equal to the second threshold, the cargo identification of the cargo is determined to be a special cargo identification.

[0081] If the cargo evaluation index is less than the second threshold, the cargo identification of the cargo is determined to be a common cargo identification.

[0082] In this embodiment, cargo types can be categorized based on their characteristics. Class-one cargo typically represents cargo with extremely high requirements for storage environment and management, or is of high value or strategic significance. Class-two cargo typically has relatively lower requirements. For example, in an electronic component warehouse, high-end chips might be classified as class-one cargo, while common resistors and capacitors might be classified as class-two cargo.

[0083] In this embodiment, cargo type is a classification of cargo based on specific criteria, divided into primary cargo and secondary cargo, used to distinguish the degree of difference in cargo value, storage conditions, and market demand. Primary cargo is a category of cargo with high cargo value, high storage requirements, and high market demand. Secondary cargo is a category of cargo with relatively lower cargo value, storage requirements, and market demand compared to primary cargo.

[0084] The first cargo list is a pre-defined list of first-level cargo names, each corresponding to its first-level cargo type. The second cargo list is a pre-defined list of second-level cargo names, each corresponding to its second-level cargo type. Basic cargo information includes various basic attributes of the cargo, such as price, storage requirements, and market demand.

[0085] The cargo evaluation index is a value calculated by the cargo evaluation function and is used to determine whether the cargo should be assigned a special cargo label or a general cargo label. The second threshold is a pre-set critical value used to distinguish between special cargo labels and general cargo labels.

[0086] For example, the inspection robot obtains incoming goods information and extracts the goods name. It then compares the goods name with the first and second goods lists. If the goods name is in the first list, it is directly identified as first-class goods and assigned a special goods identification. If it is in the second list, it is identified as second-class goods.

[0087] If the goods name is not listed in either list, the basic goods information is used to determine the goods price, storage requirements, and market demand. These parameters are then substituted into the goods valuation function to calculate the goods valuation index. The goods valuation index is then compared with a second threshold. If the goods valuation index is greater than or equal to the second threshold, the goods are designated as special goods; if the goods valuation index is less than the second threshold, the goods are designated as ordinary goods.

[0088] In this embodiment, given the complexity and diversity of warehoused goods, accurate classification of goods (primary and secondary goods) based solely on their names is insufficient. However, calculating the goods type for each individual item would be computationally prohibitive. Therefore, this embodiment provides a two-tiered classification approach. First, based on the goods name, certain goods with high value, storage requirements, and market demand are directly classified as primary goods, while the remaining goods are classified as secondary goods. Secondary goods are then further classified. By calculating comprehensive evaluation indicators based on their value, storage requirements, and market demand, the goods identification (special goods identification or general goods identification) can be accurately determined for each secondary item.

[0089] For example, consider the arrival of a batch of high-end electronic products: a new batch of M computers arrives. After obtaining the arrival information, the inspection robot extracts the cargo name. After comparing it with the first cargo list, it finds the M computers listed and immediately identifies them as Class 1 cargo, assigning them a special cargo designation.

[0090] A batch of ordinary stationery arrives: A batch of M&G gel pens arrives. The inspection robot extracts the product name and finds the corresponding information in the second-tier goods list, identifying it as second-tier goods. These are inexpensive, require only room temperature and a dry environment for storage, and have stable market demand, but low volume.

[0091] Specialty Agricultural Products Arrival: A new type of organic blueberry, not listed in either list, was brought in. Analysis of basic information revealed its high price, requiring specific cold chain storage, and recent high market demand. Substituting price, storage conditions, and market demand into the evaluation function, the calculated index exceeded the second threshold. Although classified as Class II goods, it was assigned a special goods designation to facilitate subsequent management and ensure quality.

[0092] This embodiment utilizes a two-tiered classification method, first quickly locating primary and secondary cargo by name, significantly reducing computational effort and accommodating the complex and diverse nature of stored goods. Secondary cargo is further evaluated and its identification is determined based on its value, storage conditions, and market demand. This ensures that special cargo is managed with priority and general cargo is managed appropriately, avoiding resource waste and achieving precise management. Special identification is assigned to cargo with special requirements, ensuring proper storage during warehousing and ensuring quality.

[0093] In one embodiment of the present disclosure, the smart warehouse management method further includes:

[0094] In response to receiving a warehouse data update instruction, an update trigger source type is determined based on the warehouse data update instruction.

[0095] The data update type and target update items are determined based on the update trigger source type.

[0096] The target cargo information is determined based on the data update type and the target update item.

[0097] Target update data is calculated based on target cargo information, and warehouse data is managed based on the target update data.

[0098] In this embodiment, the data update type and target update items are determined based on the update trigger source type, including:

[0099] If the update trigger source type is manual trigger: determine the data update type as level one data update.

[0100] Determine target update items based on warehouse data update instructions.

[0101] If the update trigger source type is external system interaction trigger: determine the data update type as secondary data update.

[0102] Determine the external system identifier and pre-update items based on the warehouse data update instructions.

[0103] The associated update items are determined based on the external system identifier and the preceding update items, and the associated update items are used as target update items.

[0104] In this embodiment, a warehouse data update instruction is generated internally or triggered externally by the system and is used to indicate a command to update warehouse data. The update trigger source type refers to the source category that triggers the warehouse data update request. Update trigger source types can include internal system self-test triggers, manual triggers, and external system interaction triggers.

[0105] Data update types are categorized according to the type of update trigger source. Level 1 data updates correspond to manual triggers and are typically relatively direct, localized data modifications. Level 2 data updates correspond to external system interaction triggers and may involve more complex, interrelated data changes. Target update items are used to specify the specific data content that needs to be updated. Target cargo information refers to detailed cargo information related to the target update item. Target update data is calculated and is used to update the specific values ​​or content of warehouse data. External system identifiers are used to identify external systems that interact with the warehouse system, such as logistics systems and order systems.

[0106] Pre-update items are tasks that need to be completed before warehouse data is updated when an update is triggered by interaction with an external system, such as obtaining order information from the external system and confirming supplier shipping notifications. Related update items are specific content related to warehouse data that requires synchronous updates. For example, changes in customer orders require not only updating inventory data but also adjusting pre-allocation information for goods.

[0107] For example, when a smart warehousing system receives a warehouse data update instruction, it first determines the type of update trigger source. If it is manually triggered, it is determined to be a primary data update, and the target update item is directly determined based on the data update instruction. For example, if a staff member discovers an error in the inventory quantity record of a certain item and manually initiates an update instruction, the smart warehousing system will determine the inventory quantity of the item to be updated based on the data update instruction.

[0108] If triggered by an external system interaction, it is determined to be a secondary data update. The smart warehousing system first obtains the external system identifier and pre-update items from the data update instruction, obtains relevant information through interaction with the external system, and then determines the related update items as the target update items based on this information and preset rules. For example, if the customer order system sends new order information, the warehousing system identifies the external system identifier as the customer order system, and the preset rules determine that its pre-update item is to obtain order details. Based on the order information, the smart warehousing system determines that it must not only update the inventory data, but also update related update items such as the goods delivery plan.

[0109] Determine the target cargo information based on the target update items, calculate the target update data, use the target update data to manage the warehouse data, and complete the data update.

[0110] This embodiment distinguishes update trigger sources, enabling targeted implementation of different update strategies. Manually triggered primary data updates can quickly address local data issues. Secondary data updates, triggered by external system interactions, comprehensively account for changes in related data. This embodiment ensures the timeliness and accuracy of data updates while enhancing the flexibility and efficiency of warehouse data management, ensuring smooth warehouse operations.

[0111] Corresponding to the smart warehouse management method in the above embodiment, Figure 2 This is a block diagram of the structure of the smart warehouse management system provided by one embodiment of the present disclosure. For ease of explanation, only the parts related to the embodiment of the present disclosure are shown. Figure 2 The smart warehouse management system 20 includes: a cargo identification module 21, a first inspection module 22 and a second inspection module 23.

[0112] The cargo identification module 21 is used to determine cargo identification based on the incoming cargo information.

[0113] The first inspection module 22 is configured to manage the goods corresponding to the special goods identification based on a first inspection instruction if the goods identification is a special goods identification. The first inspection instruction is configured to instruct the inspection robot to manage the goods based on a first inspection mode.

[0114] The second inspection module 23 is configured to manage the goods corresponding to the common goods identification based on a second inspection instruction if the goods identification is a common goods identification. The second inspection instruction is configured to instruct the inspection robot to manage the goods based on a second inspection mode. The inspection frequency of the first inspection mode is greater than the inspection frequency of the second inspection mode.

[0115] In one embodiment of the present disclosure, the first inspection module 22 is specifically configured to:

[0116] The cargo is monitored based on the first inspection frequency to obtain target monitoring information of the cargo.

[0117] A cargo management instruction is generated based on the target monitoring information, and the cargo is managed based on the cargo management instruction.

[0118] In one embodiment of the present disclosure, the target monitoring information includes cargo quality and environmental information. Cargo management instructions include cargo delivery instructions, replenishment instructions, and inspection frequency update instructions. The first inspection module 22 is further configured to, if the cargo quality is greater than or equal to a first threshold, predict the cargo quality for a second time period to be inspected based on the cargo quality and environmental information detected during the first time period, thereby obtaining a predicted cargo quality.

[0119] An inspection frequency update instruction is generated based on the predicted cargo quality. The inspection frequency update instruction is used to instruct to update the first inspection frequency of the cargo to obtain a second inspection frequency.

[0120] If the quality of the goods is less than the first threshold, a goods delivery instruction and a replenishment instruction are generated.

[0121] In one embodiment of the present disclosure, the second inspection module 23 is specifically configured to:

[0122] In response to receiving the cargo management instruction, the cargo is inspected based on the cargo management instruction to obtain inspection information.

[0123] Manage cargo based on cargo management instructions and inspection information.

[0124] In one embodiment of the present disclosure, the cargo identification module 21 is specifically configured to determine the cargo type and basic cargo information of the cargo based on the incoming cargo information.

[0125] If the cargo type of the cargo is first-class cargo, the cargo identification of the cargo is determined to be a special cargo identification.

[0126] If the cargo type of the cargo is secondary cargo, the cargo identification of the cargo is determined based on the basic information of the cargo.

[0127] In one embodiment of the present disclosure, the smart warehouse management system 20 further includes: a data update module for determining an update trigger source type based on the warehouse data update instruction in response to receiving the warehouse data update instruction.

[0128] The data update type and target update items are determined based on the update trigger source type.

[0129] The target cargo information is determined based on the data update type and the target update item.

[0130] Target update data is calculated based on target cargo information, and warehouse data is managed based on the target update data.

[0131] In one embodiment of the present disclosure, the data update module is specifically configured to: if the update trigger source type is manual trigger: determine that the data update type is primary data update.

[0132] Determine target update items based on warehouse data update instructions.

[0133] If the update trigger source type is external system interaction trigger: determine the data update type as secondary data update.

[0134] Determine the external system identifier and pre-update items based on the warehouse data update instructions.

[0135] The associated update items are determined based on the external system identifier and the preceding update items, and the associated update items are used as target update items.

[0136] See also Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided by an embodiment of the present disclosure. Figure 3 The electronic device 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of the modules in the above-mentioned system embodiments, such as Figure 2 The functions of modules 21 to 23 are shown.

[0137] It should be understood that in the embodiments of the present disclosure, the processor 301 may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0138] The input device 302 may include a touchpad, a fingerprint collection sensor (for collecting user fingerprint information and fingerprint direction information), a microphone, etc. The output device 303 may include a display (LCD, etc.), a speaker, etc.

[0139] The memory 304 may include a read-only memory and a random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store information about the device type.

[0140] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of the intelligent warehouse management method provided in the embodiments of the present disclosure, and can also execute the implementation methods of the electronic device 300 described in the embodiments of the present disclosure, which will not be repeated here.

[0141] In another embodiment of the present disclosure, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program. The computer program includes program instructions. When the program instructions are executed by a processor, all or part of the process of the method in the above embodiment is implemented. The computer program can also be used to instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of each of the above method embodiments are implemented. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium.

[0142] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the aforementioned embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the computer-readable storage medium can include both an internal storage unit of the electronic device and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or is about to be output.

[0143] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0144] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the electronic devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0145] In the several embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the system embodiments described above are merely schematic. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces or units, or can be an electrical, mechanical or other form of connection.

[0146] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the objectives of the embodiments of the present disclosure.

[0147] In addition, the functional units in the various embodiments of the present disclosure may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0148] The above are only specific embodiments of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or replacements within the technical scope disclosed in this disclosure, and such modifications or replacements should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A smart warehouse management method, characterized in that: include: Determine the cargo type and basic cargo information based on the incoming cargo information; if the cargo type of the cargo is first-class cargo, determine the cargo identification of the cargo as a special cargo identification; if the cargo type of the cargo is second-class cargo, determine the cargo identification of the cargo based on the basic cargo information; If the cargo identifier is a special cargo identifier, the cargo corresponding to the special cargo identifier is managed based on the first inspection instruction; the first inspection instruction is used to instruct the inspection robot to manage the cargo based on the first inspection mode; If the cargo identifier is a common cargo identifier, the cargo corresponding to the common cargo identifier is managed based on a second inspection instruction; the second inspection instruction is used to instruct the inspection robot to manage the cargo based on a second inspection mode; The inspection frequency of the first inspection mode is greater than the inspection frequency of the second inspection mode; Determining the cargo identification of the cargo based on the basic cargo information includes: determining the cargo price, cargo storage condition requirements, and market cargo demand based on the basic cargo information; substituting the cargo price, cargo storage condition requirements, and market cargo demand into a cargo evaluation function to obtain a cargo evaluation index; The goods evaluation function is: Among them, F(x) represents the commodity evaluation index, P represents the commodity price, S represents the commodity storage condition requirements, and D represents the market demand for commodities. Indicates the minimum price of all goods. Indicates the maximum value of all commodity prices. Indicates the minimum value of all cargo storage condition requirements. Indicates the maximum value of all cargo storage condition requirements. represents the minimum value of the market demand for all goods, represents the maximum value among the market demand for all goods, 、 、 represents the weight coefficient, =1; If the cargo evaluation index is greater than or equal to the second threshold, the cargo identification of the cargo is determined to be a special cargo identification; if the cargo evaluation index is less than the second threshold, the cargo identification of the cargo is determined to be a common cargo identification; The managing of the goods based on the first inspection mode includes: for goods identified as special goods: monitoring the goods based on the first inspection frequency to obtain target monitoring information of the goods; generating a goods management instruction based on the target monitoring information, and managing the goods based on the goods management instruction; The target monitoring information includes cargo quality and environmental information; the cargo management instructions include cargo outbound instructions, replenishment instructions and inspection frequency update instructions; the generation of cargo management instructions based on the target monitoring information includes: if the cargo quality is greater than or equal to a first threshold, then based on the cargo quality and environmental information of the detected first time period, predicting the cargo quality of the second time period to be detected to obtain a predicted cargo quality; generating an inspection frequency update instruction based on the predicted cargo quality; the inspection frequency update instruction is used to instruct to update the first inspection frequency of the cargo to obtain a second inspection frequency; if the cargo quality is less than the first threshold, then generating a cargo outbound instruction and a replenishment instruction.

2. The intelligent warehouse management method according to claim 1, characterized in that: The management of goods based on the second inspection mode includes: For goods marked as ordinary goods: In response to receiving the cargo management instruction, performing an inspection on the cargo based on the cargo management instruction to obtain inspection information; The cargo is managed based on the cargo management instruction and the inspection information.

3. The intelligent warehouse management method according to claim 1, characterized in that: Also includes: In response to receiving a warehouse data update instruction, determining an update trigger source type based on the warehouse data update instruction; Determine the data update type and target update item based on the update trigger source type; determining target cargo information based on the data update type and the target update item; Target update data is calculated based on the target goods information, and warehouse data is managed based on the target update data.

4. The intelligent warehouse management method according to claim 3, characterized in that: The determining of the data update type and target update items based on the update trigger source type includes: If the update trigger source type is manual trigger: determining the data update type as primary data update; Determining target update items based on the warehouse data update instruction; If the update trigger source type is an external system interaction trigger: determining that the data update type is a secondary data update; Determining an external system identifier and pre-update items based on the warehouse data update instruction; An associated update item is determined based on the external system identifier and the preceding update item, and the associated update item is used as a target update item.

5. A smart warehouse management system, characterized in that: include: A cargo identification module is used to determine the cargo type and basic cargo information based on the incoming cargo information; if the cargo type of the cargo is first-class cargo, the cargo identification of the cargo is determined to be a special cargo identification; if the cargo type of the cargo is second-class cargo, the cargo identification of the cargo is determined based on the basic cargo information; The cargo identification module is specifically used to determine the cargo price, cargo storage condition requirements and market cargo demand based on the basic cargo information; the cargo price, cargo storage condition requirements and market cargo demand are substituted into the cargo evaluation function to obtain the cargo evaluation index; The goods evaluation function is: Among them, F(x) represents the commodity evaluation index, P represents the commodity price, S represents the commodity storage condition requirements, and D represents the market demand for commodities. Indicates the minimum price of all goods. Indicates the maximum value of all commodity prices. Indicates the minimum value of all cargo storage condition requirements. Indicates the maximum value of all cargo storage condition requirements. represents the minimum value of the market demand for all goods, represents the maximum value among the market demand for all goods, 、 、 represents the weight coefficient, =1; If the cargo evaluation index is greater than or equal to the second threshold, the cargo identification of the cargo is determined to be a special cargo identification; if the cargo evaluation index is less than the second threshold, the cargo identification of the cargo is determined to be a common cargo identification; A first inspection module is configured to manage the goods corresponding to the special goods identification based on a first inspection instruction if the goods identification is a special goods identification; the first inspection instruction is configured to instruct the inspection robot to manage the goods based on a first inspection mode; The first inspection module is specifically configured to monitor goods identified as special goods based on a first inspection frequency to obtain target monitoring information of the goods; generate a goods management instruction based on the target monitoring information, and manage the goods based on the goods management instruction; the target monitoring information includes goods quality and environmental information; and the goods management instruction includes a goods outbound instruction, a replenishment instruction, and an inspection frequency update instruction; The first inspection module is further configured to, if the cargo quality is greater than or equal to a first threshold, predict the cargo quality in a second time period to be inspected based on the cargo quality in the first time period and environmental information that have been inspected to obtain a predicted cargo quality; generate an inspection frequency update instruction based on the predicted cargo quality; the inspection frequency update instruction is used to instruct to update the first inspection frequency of the cargo to obtain a second inspection frequency; and generate a cargo dispatch instruction and a replenishment instruction if the cargo quality is less than the first threshold; The second inspection module is used to manage the goods corresponding to the ordinary goods identification based on the second inspection instruction if the goods identification is an ordinary goods identification; the second inspection instruction is used to instruct the inspection robot to manage the goods based on the second inspection mode; the inspection frequency of the first inspection mode is greater than the inspection frequency of the second inspection mode.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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