Medicine wisdom warehouse visual management system based on digital twinning

Abstract

The application belongs to the technical field of digital twinning, and discloses a medicine intelligent warehouse visual management system based on digital twinning, which comprises a multi-source data fusion acquisition module, which is used for acquiring multi-dimensional original data in a medicine warehouse, uniformly performing space-time tagging processing on the multi-dimensional original data, and generating a fusion data stream; a digital twinning construction module, which is used for constructing a medicine warehouse digital twinning body according to the fusion data stream, establishing a bidirectional mapping relationship between a physical warehouse and the digital twinning body, and respectively outputting medicine attribute information and a warehouse location topology information; and a priority sorting module, which is used for calculating an expiration date urgency value of the medicine based on the medicine attribute information, sorting the medicine, and generating an expiration date priority sorting table; and simultaneously calculating a warehouse location out-of-warehouse value coefficient based on the warehouse location topology information, sorting the warehouse location, and generating a warehouse location value sorting table; and the risk control capability, operation efficiency and resource utilization rate are improved.

Description

Technical Field

[0001] This invention relates to the field of digital twin technology, and more specifically, to a digital twin-based intelligent pharmaceutical warehouse visualization management system. Background Technology

[0002] Existing digital twin-based intelligent pharmaceutical warehouse visualization management systems mainly suffer from the following problems:

[0003] The pharmaceutical distribution industry is characterized by a wide variety of products, numerous batches, and high sensitivity to expiration dates. The warehousing process must meet both drug quality and safety requirements while balancing operational efficiency and inventory turnover. With the increasing application of digital twin technology in smart warehousing, constructing a digital twin that maps physical and virtual warehousing spaces in real time—enabling visualization of inventory status, traceability of operational processes, and dynamic monitoring of operational status—has become an important direction for improving the refined management of pharmaceutical warehousing.

[0004] However, existing pharmaceutical warehouse management systems based on digital twins typically remain at a simple time-based sorting level in terms of expiration date management. Most systems only rank or issue warnings based on the expiration date or remaining shelf life of drugs, failing to comprehensively evaluate drugs by incorporating operational factors such as inventory structure, batch distribution, historical outbound rhythm, and actual turnover capacity. For different batches of drugs with similar remaining expiration dates, existing systems often rely on fixed rules or human experience for judgment, lacking unified quantitative standards. This makes it difficult to provide comparable and sortable numerical expressions of the comprehensive expiration risk of different drugs on the same scale, thus hindering the automatic linkage of storage location optimization, migration decisions, and outbound strategies. Expiration date management results are mostly limited to the level of prompts or alarms, failing to provide system-level decision support.

[0005] In terms of warehouse location management and outbound scheduling, existing technologies mostly rely on the physical location of warehouse locations or empirical order to arrange outbound shipments. They typically only consider the straight-line distance to the outbound exit or fixed shelf numbers, lacking comprehensive quantitative analysis of warehouse topology, operational aisle connectivity, and path limitations. Due to the lack of a unified warehouse location value assessment model, frequently outbound medicines may be placed at low-efficiency path nodes, leading to increased picking, handling, and scheduling costs. When warehouse structure is adjusted or aisle accessibility changes, traditional methods struggle to reflect new operational efficiency differences in a timely manner, cannot dynamically update warehouse location ranking results, and fail to meet the needs of intelligent scheduling and visualized management.

[0006] In view of this, the present invention proposes a digital twin-based intelligent pharmaceutical warehouse visualization management system to solve the above problems. Summary of the Invention

[0007] To overcome the aforementioned shortcomings of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a digital twin-based intelligent pharmaceutical warehouse visualization management system, comprising: The multi-source data fusion acquisition module is used to collect multi-dimensional raw data in pharmaceutical warehousing, perform unified spatiotemporal labeling processing on the multi-dimensional raw data, and generate a fused data stream. The digital twin construction module is used to build a digital twin of pharmaceutical warehousing based on the fused data flow, and establish a two-way mapping relationship between physical warehousing and digital twin, outputting drug attribute information and warehouse location topology information respectively; The priority ranking module is used to calculate the urgency of drug expiration dates based on drug attribute information, and to rank the drugs to generate an expiration date priority ranking table; at the same time, it calculates the outbound value coefficient of the storage location based on the storage location topology information, ranks the storage locations, and generates a storage location value ranking table. The expiration date and storage location matching optimization module is used to calculate the matching degree between drugs and storage locations based on the expiration date priority sorting table and the storage location value sorting table. Under the condition of meeting the preset environmental constraints, it assigns the storage location with the highest matching degree to the drug and generates a storage location migration task when the matching degree is lower than the preset matching degree threshold. The visualization management module receives storage location allocation results and storage location migration tasks. It uses a digital twin to visualize the drug expiration status, storage location value distribution, and drug storage location matching relationship, and generates an outbound prompt when the drug expiration reaches the warning condition.

[0008] Preferably, the method for obtaining the multi-dimensional raw data includes: The multi-dimensional raw data includes environmental data, inventory drug data, equipment operation data, operational behavior data, and system business data. Among them, environmental data is collected through environmental sensing terminals set up in different storage areas, passage areas, and operation areas of the pharmaceutical warehouse. Specifically, it includes temperature parameters, humidity parameters, air quality parameters, as well as corresponding collection timestamps and area identification information. Inventory drug data is obtained through automatic identification of unique drug identifiers, which are linked to drug packaging via RFID electronic tags or QR codes. Inventory drug data includes batch information, expiration date information, inventory quantity information, drug status information, and drug location information within the warehouse space. Each medicine in a pharmaceutical warehouse is assigned a unique identifier upon entry. This unique identifier is linked to the medicine packaging via an RFID electronic tag or QR code. During the operation of the pharmaceutical warehouse, automatic identification terminals installed at the entry and exit points and in the shelving aisles automatically identify the unique identifiers to obtain inventory data. This inventory data includes batch information, expiration date information, inventory quantity information, medicine status information, and the location information of the medicine within the warehouse space. Equipment operation data is acquired through the control system and sensor interfaces of the automated pharmaceutical warehousing equipment, including equipment start / stop status, operating speed, load parameters, and fault alarm information; operational behavior data is acquired by sensing and recording the operation process of pharmaceutical warehousing, including time information and operation type information corresponding to picking, shelving, and outbound operations; system business data is acquired through data interface with the pharmaceutical warehousing management terminal, including inbound orders, outbound orders, inventory records, and drug storage constraint information.

[0009] Preferably, the method for generating the fused data stream includes: Based on a preset time base, a unified timestamp identifier is added to the multi-dimensional raw data from different data sources, and the location information in the multi-dimensional raw data is mapped to the three-dimensional spatial coordinate system of pharmaceutical warehousing to form corresponding coordinate parameters. The acquired timestamps and coordinate parameters are used as spatiotemporal labels and bound to the corresponding multi-dimensional raw data to form structured spatiotemporal data units. The spatiotemporal data units are arranged and combined in chronological order to form a fused data stream with unified time and space dimensions.

[0010] Preferably, the method for constructing a digital twin of a pharmaceutical warehouse includes: Based on the spatiotemporal data units in the fused data stream, the physical objects in the pharmaceutical warehouse are digitally abstracted, and the warehouse space entities, storage location entities, drug entities and equipment entities are identified and generated. A digital description structure containing a unique entity identifier, spatial coordinate parameters, attribute parameter set and state parameter set is established for each entity. Based on spatial coordinate parameters, each storage location entity is mapped to a unified three-dimensional spatial coordinate system. According to the relative positional relationship of each storage location entity in the three-dimensional spatial coordinate system, the adjacency relationship, hierarchical relationship and accessibility relationship between storage locations are determined, which are then embedded into the digital description structure of the storage location entity as constraints of the storage space organization structure. The system parses inventory drug data from the fused data stream, associates the inventory drug data with the spatial location of storage location entities, and establishes a binding relationship between drug entities and storage location entities. When changes in the attribute parameters or status parameters of an entity are detected in the fused data stream, the system triggers a status update for the corresponding entity. Using the digital description structure of each entity as the basic building block, and the organizational constraints and binding relationships of the warehouse space organization structure as organizational constraints, a unified digital space model is performed on the warehouse space entity, storage location entity, drug entity, and equipment entity. The digital space model is continuously updated under the drive of fused data flow, thereby forming a digital twin of pharmaceutical warehousing.

[0011] Preferably, the method for outputting drug attribute information and storage location topology information respectively includes: The digital twin construction module is used to build a digital twin of pharmaceutical warehousing based on the fused data flow, and establish a two-way mapping relationship between physical warehousing and digital twin, outputting drug attribute information and warehouse location topology information respectively; Based on the spatiotemporal data units in the fused data stream, the storage space, storage location, medicines, and equipment in the physical warehouse are associated one-to-one with the corresponding entities in the digital twin according to the unique entity identifier. When changes in the location of medicines, changes in inventory quantity, or changes in the operating status of equipment are detected in the fused data stream, the spatial coordinate parameters, attribute parameter sets, or status parameter sets of the corresponding entities in the digital twin are automatically updated to achieve a positive mapping from the physical warehouse status to the pharmaceutical warehouse digital twin. When the storage location allocation result is generated in the pharmaceutical warehouse digital twin, the storage location allocation result is fed back to the pharmaceutical warehouse management terminal to achieve a reverse mapping from the pharmaceutical warehouse digital twin to the physical warehouse. Based on the establishment of a two-way mapping relationship, drug attribute information is generated based on inventory drug data and historical business data. The spatial coordinate parameters of the storage location entities in the digital twin, the adjacency relationship between storage locations, the hierarchical relationship and the accessibility relationship of the channels are uniformly organized and associated with the unique entity identifier of the corresponding storage location entity to form storage location topology information that reflects the spatial organization structure between storage locations. Drug attribute information includes the drug's expiration date, nominal shelf life, current inventory quantity, and historical average outbound volume within the preset statistical period; warehouse location topology information includes the location parameters of the warehouse location in the three-dimensional spatial coordinate system of pharmaceutical warehousing, the spatial distance between the warehouse location and the preset outbound port, the type of operating channel where the warehouse location is located, and the connectivity between the warehouse location and the operating channel.

[0012] Preferably, the method for generating the expiration date priority ranking table includes: Retrieve drug attribute information corresponding to each stocked drug from the digital twin, calculate the remaining shelf life of each drug at the current system time based on a preset time benchmark, generate a remaining shelf life ratio factor that reflects the time pressure of drug expiration based on the ratio between the remaining shelf life and the corresponding nominal shelf life, and generate an inventory correction factor that reflects the degree of drug inventory backlog based on the ratio between the current inventory quantity of each drug and the historical average outbound quantity within the preset statistical period. By logically coupling the remaining expiration period ratio factor with the inventory adjustment factor, the urgency of each drug's expiration date is obtained, which comprehensively characterizes the overall expiration date risk level of the drug under the remaining expiration date and inventory turnover status. Based on the urgency of each drug's expiration date, the drugs are prioritized in descending order to generate an expiration date priority ranking table.

[0013] Preferably, the method for generating the storage location value ranking table includes: The topological information of each storage location in the pharmaceutical warehouse is obtained from the digital twin. Based on the position parameters of the storage location in the three-dimensional spatial coordinate system of the pharmaceutical warehouse, the spatial distance between each storage location and the preset outlet is calculated. Based on the connectivity between storage locations and operational channels, the accessibility status of operational channels for storage locations is determined. Based on spatial distance and the accessibility status of operational channels for storage locations, an outbound value evaluation function is constructed to generate the outbound value coefficient corresponding to each storage location. After obtaining the outbound value coefficient corresponding to each storage location, the storage locations are sorted from high to low according to the outbound value coefficient to generate a storage location value ranking table.

[0014] Preferably, the method for calculating the matching degree between drugs and storage locations includes: Obtain the expiration urgency of all drugs from the expiration priority ranking table, and sort the drugs from high to low expiration urgency; obtain the outbound value coefficient of all storage locations from the storage location value ranking table, and sort the storage locations from high to low outbound value coefficient. Based on the urgency of the drug's expiration date and the value coefficient of the drug's delivery, a set of fuzzy comprehensive evaluation indicators is constructed, and a membership function is established for each fuzzy comprehensive evaluation indicator. The urgency of the expiration date and the value coefficient of the drug's delivery are mapped to the corresponding fuzzy membership degree through the membership function. Preset weights are assigned to each fuzzy comprehensive evaluation index. For each drug-storage location combination, the matching degree value is calculated according to the membership degree and corresponding weight of each fuzzy comprehensive evaluation index, and the matching degree of each drug in each storage location is obtained.

[0015] Preferably, the method for generating the storage location migration task includes: After obtaining the matching degree of each drug for each storage location, the candidate storage location with the highest matching degree is selected as the allocation object for each drug in turn, and it is determined whether the candidate storage location meets the preset environmental constraints, including temperature and humidity range, hazardous materials isolation requirements and storage location capacity limit. When a candidate storage location meets the preset environmental constraints, the candidate storage location is assigned to the current drug and the storage location status is updated to occupied. Under the preset environmental constraints, the drug is assigned the storage location with the highest matching degree. When the matching degree between the drug and the candidate storage location is lower than the preset matching degree threshold, or when all candidate storage locations do not meet the preset environmental constraints, a storage location migration task is generated.

[0016] Preferably, the method for generating a release notification when the drug's expiration date reaches the warning condition includes: Receive storage location allocation results and storage location migration tasks, map the storage location allocation results and storage location migration tasks to the pharmaceutical warehousing digital twin, realize two-way status synchronization between physical warehousing and digital twin, and update drug location, storage location occupancy status and matching degree information of each drug in each storage location; Based on drug attribute information and expiration urgency, the expiration status of each drug in the warehouse is dynamically displayed, and the expiration urgency of the drugs is presented using color. According to the storage location value ranking table and the outbound value coefficient, the value level of each storage location is marked in the digital twin, and the matching degree between the allocated drugs and storage locations is visualized through icons. The expiration dates of drugs are monitored in real time. When the expiration urgency of a drug reaches the preset expiration urgency threshold, an outbound prompt instruction is generated, and warehouse operators are reminded to perform the outbound operation through message notification or scheduling interface.

[0017] Compared with the prior art, the present invention has the following beneficial effects: This invention logically couples the remaining shelf life of pharmaceutical products with inventory turnover status to generate a single expiration urgency value, enabling a comprehensive quantitative assessment of pharmaceutical expiration risk and avoiding evaluation distortion caused by relying solely on a single time indicator. By introducing an inventory correction factor, the remaining shelf life ratio is dynamically adjusted, allowing pharmaceuticals with similar expiration dates but significantly different inventory statuses to be effectively distinguished in the ranking results, thereby improving the consistency between expiration priority ranking and actual warehouse operation status. By prioritizing and ranking pharmaceuticals with higher overall expiration risk, this invention can trigger outbound or warehouse location adjustment strategies in advance, effectively reducing the risk of backlog and spoilage of near-expiration pharmaceuticals due to unreasonable inventory structure. Utilizing a digital twin to map and visualize the expiration urgency results in real time, managers can intuitively grasp the distribution of pharmaceutical expiration risk within the warehouse, improving the controllability and decision-making efficiency of warehouse operations.

[0018] By logically coupling the spatial distance exponential decay function with the accessibility status of operational channels, the ease of outbound delivery of storage locations is quantified into an outbound value coefficient, enabling a unified assessment of storage location value. Based on real-time acquisition of the three-dimensional coordinates of storage locations and channel connectivity using digital twins, the system can dynamically reflect the impact of warehouse structure or channel adjustments on storage location value, improving the flexibility of storage location scheduling and outbound operations, and achieving dynamic optimization. The generated storage location value ranking table prioritizes the allocation of high-value storage locations to frequently dispatched medicines or urgent orders, reducing handling paths and picking time; it supports intelligent storage location management and inventory optimization, significantly improving warehouse resource utilization and operational efficiency. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the structure of the digital twin-based intelligent pharmaceutical warehouse visualization management system of the present invention; Figure 2 This is a schematic diagram of the process of the intelligent pharmaceutical warehouse visualization management method based on digital twins according to the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1 Please see Figure 1 As shown, this embodiment provides a digital twin-based intelligent pharmaceutical warehouse visualization management system, which specifically includes the following steps: The multi-source data fusion acquisition module is used to collect multi-dimensional raw data in pharmaceutical warehousing, perform unified spatiotemporal labeling processing on the multi-dimensional raw data, and generate a fused data stream. The digital twin construction module is used to build a digital twin of pharmaceutical warehousing based on the fused data flow, and establish a two-way mapping relationship between physical warehousing and digital twin, outputting drug attribute information and warehouse location topology information respectively; The priority ranking module is used to calculate the urgency of drug expiration dates based on drug attribute information, and to rank the drugs to generate an expiration date priority ranking table; at the same time, it calculates the outbound value coefficient of the storage location based on the storage location topology information, ranks the storage locations, and generates a storage location value ranking table. The expiration date and storage location matching optimization module is used to calculate the matching degree between drugs and storage locations based on the expiration date priority sorting table and the storage location value sorting table. Under the condition of meeting the preset environmental constraints, it assigns the storage location with the highest matching degree to the drug and generates a storage location migration task when the matching degree is lower than the preset matching degree threshold. The visualization management module receives storage location allocation results and storage location migration tasks. It uses a digital twin to visualize the drug expiration status, storage location value distribution, and drug storage location matching relationship, and generates an outbound prompt when the drug expiration reaches the warning condition.

[0022] Methods for obtaining multi-dimensional raw data include: The multi-dimensional raw data includes environmental data, inventory drug data, equipment operation data, operational behavior data, and system business data. Among them, environmental data is collected through environmental sensing terminals set up in different storage areas, passage areas, and operation areas of the pharmaceutical warehouse. Specifically, it includes temperature parameters, humidity parameters, air quality parameters, as well as corresponding collection timestamps and area identification information. Inventory drug data is obtained through automatic identification of unique drug identifiers, which are bound to drug packaging via RFID electronic tags or QR codes. The inventory drug data includes batch information, expiration date information, inventory quantity information, drug status information, and the location information of the drug in the storage space, which is used to construct the corresponding drug entity. Each medicine in a pharmaceutical warehouse is assigned a unique identifier upon entry. This unique identifier is linked to the medicine packaging via an RFID electronic tag or QR code. During the operation of the pharmaceutical warehouse, automatic identification terminals installed at the entry and exit points and in the shelving aisles automatically identify the unique identifiers to obtain inventory data. This inventory data includes batch information, expiration date information, inventory quantity information, medicine status information, and the location information of the medicine within the warehouse space. Equipment operation data is acquired through the control system and sensor interfaces of the automated pharmaceutical warehousing equipment, including equipment start / stop status, operating speed, load parameters, and fault alarm information; operational behavior data is acquired by sensing and recording the operation process of pharmaceutical warehousing, including time information and operation type information corresponding to picking, shelving, and outbound operations; system business data is acquired through data interface with the pharmaceutical warehousing management terminal, including inbound orders, outbound orders, inventory records, and drug storage constraint information.

[0023] Methods for generating fused data streams include: Based on a preset time base, a unified timestamp identifier is added to the multi-dimensional raw data from different data sources, and the location information in the multi-dimensional raw data is mapped to the three-dimensional spatial coordinate system of pharmaceutical warehousing to form corresponding coordinate parameters. The acquired timestamps and coordinate parameters are used as spatiotemporal labels and bound to the corresponding multi-dimensional raw data to form structured spatiotemporal data units. The spatiotemporal data units are arranged and combined in chronological order to form a fused data stream with unified time and space dimensions.

[0024] In this embodiment, the preset time base is the system standard time; based on the location information carried in the multi-dimensional raw data, the actual location of the medicine in the pharmaceutical warehouse is determined, and the location description format is standardized; the standardized actual location is mapped to a three-dimensional spatial coordinate system to form the corresponding coordinate parameters; Specifically, a three-dimensional spatial coordinate system is established with the geometric center point of the physical space of the pharmaceutical warehouse as the origin of the coordinate system. This system includes an X-axis set along the horizontal aisle direction, a Y-axis set along the vertical shelf layout direction, and a Z-axis set along the vertical height direction. The coordinate parameters include the X-axis coordinates, Y-axis coordinates, and Z-axis coordinates used to represent the location of the pharmaceutical warehouse space. Taking a certain stocked drug A as an example, the location information of A includes the storage area identifier, aisle number, shelf number, and layer code. First, the storage area range where A is located is determined based on the storage area identifier. Then, the horizontal X-axis coordinate and vertical Y-axis coordinate of A in the three-dimensional spatial coordinate system are determined based on the aisle number and shelf number. Finally, the Z-axis coordinate of A in the vertical height direction is determined by the layer code, thus forming the coordinate parameters of A in the three-dimensional spatial coordinate system, realizing the digital expression of the drug's storage location.

[0025] Methods for constructing digital twins of pharmaceutical warehousing include: Based on the spatiotemporal data units in the fused data stream, the physical objects in the pharmaceutical warehouse are digitally abstracted, and the warehouse space entities, storage location entities, drug entities and equipment entities are identified and generated. A digital description structure containing a unique entity identifier, spatial coordinate parameters, attribute parameter set and state parameter set is established for each entity. It should be noted that the process of establishing a digital description structure for each entity includes the following steps: First, extract the basic identification information corresponding to the target physical object from the spatiotemporal data units in the fused data stream, and assign a unique and non-repeatable entity unique identifier to each type of entity. Among them, the entity unique identifier of the warehouse space entity is generated according to the preset spatial coding rules, the entity unique identifier of the storage location entity is generated according to the combination of area number, aisle number, shelf number and layer code, the entity unique identifier of the pharmaceutical entity is generated by mapping the pharmaceutical unique identifier, and the entity unique identifier of the equipment entity is generated by mapping the equipment number. Secondly, based on the location information contained in the spatiotemporal data unit, the corresponding physical object is mapped to a unified three-dimensional spatial coordinate system, and spatial coordinate parameters representing the spatial location of the entity are calculated. The spatial coordinate parameters include at least the X-axis coordinate, Y-axis coordinate, and Z-axis coordinate. Thirdly, based on the business attribute types of different entities, business field information related to the entity is extracted from the fused data stream to construct an attribute parameter set. The attribute parameter set for the drug entity includes batch information, expiration date information, inventory quantity information, and drug status information. The attribute parameter set for the storage location entity includes storage location capacity parameters, storage constraints, and current occupancy status. The attribute parameter set for the equipment entity includes equipment type, rated parameters, and functional configuration parameters. The attribute parameter set for the warehouse space entity includes area category and environmental control requirements. Simultaneously, data fields reflecting the real-time operation or changes of entities are extracted from the fused data stream to construct a set of state parameters, which is used to characterize the current operating state or dynamic change state of the entity. Finally, the entity's unique identifier, spatial coordinate parameters, attribute parameter set, and state parameter set are structurally encapsulated according to a preset data structure model to form a digital description structure of the corresponding entity.

[0026] Based on spatial coordinate parameters, each storage location entity is mapped to a unified three-dimensional spatial coordinate system. According to the relative positional relationship of each storage location entity in the three-dimensional spatial coordinate system, the adjacency relationship, hierarchical relationship and accessibility relationship between storage locations are determined, which are then embedded into the digital description structure of the storage location entity as constraints of the storage space organization structure. It should be noted that in this embodiment, based on the spatial coordinate parameters carried in the fused data stream, each storage location entity within the pharmaceutical warehouse is uniformly mapped to a pre-established three-dimensional spatial coordinate system, ensuring that each storage location entity corresponds to a unique spatial location identifier in the digital space. After completing the spatial mapping of the storage location entities, the system analyzes the spatial relationships between storage locations based on the relative positional relationships of each storage location entity in the three-dimensional spatial coordinate system.

[0027] Specifically, for storage location entities located at the same height level and with a horizontal distance less than a preset adjacent distance threshold, an adjacency relationship is determined between them; for storage location entities that are basically the same in the horizontal direction but exhibit height differences in the vertical direction, a hierarchical relationship is determined between them; simultaneously, combining the positional relationship between the storage location entity and the storage aisle area in three-dimensional space, it is determined whether the storage location entity forms an unobstructed or passable path with the corresponding aisle, thereby determining the accessibility relationship between the storage location entity and the aisle; based on the above adjacency relationship, hierarchical relationship, and accessibility relationship, each storage location entity and its spatial association relationship are structurally described and embedded as a constraint of the storage space organization structure into the digital description structure of the storage location entity; The system parses inventory drug data from the fused data stream, associates the inventory drug data with the spatial location of storage location entities, and establishes a binding relationship between drug entities and storage location entities. When changes in the attribute parameters or status parameters of an entity are detected in the fused data stream, the system triggers a status update for the corresponding entity. Using the digital description structure of each entity as the basic building block, and the organizational constraints and binding relationships of the warehouse space organization structure as organizational constraints, a unified digital space model is performed on the warehouse space entity, storage location entity, drug entity, and equipment entity. The digital space model is continuously updated under the drive of fused data flow, thereby forming a digital twin of pharmaceutical warehousing.

[0028] It should be noted that the system uses a fused data stream as the unified data carrier for the operational status of pharmaceutical warehousing, continuously receiving and parsing information related to inventory drugs. The system first parses and classifies the inventory drug data based on the drug's unique identifier, aggregating data belonging to the same drug entity to form a digital twin that corresponds one-to-one with the drug in the physical warehouse.

[0029] After parsing the inventory drug data, the system determines the storage location of the drug entity in the warehouse space based on the location information carried in the inventory drug data. The location information is matched with the spatial coordinate parameters and structural relationships of each warehouse location entity in the warehouse location topology information. The target warehouse location entity corresponding to the drug entity is determined through the location matching result. Thus, a binding relationship between the drug entity and the warehouse location entity is established in the digital twin, so that the drug entity not only has attribute information description, but also has a clear spatial affiliation and hierarchical location, thereby associating the inventory drug status with the warehouse space organization structure.

[0030] During the operation of pharmaceutical warehousing, the fused data stream continuously receives the latest status information from the physical warehouse. When drug entry, transfer, picking or exit operations occur, the attribute parameters or status parameters of the corresponding drug entity or storage location entity in the fused data stream change. By continuously monitoring the fused data stream, the system detects parameter changes, automatically locates the affected entity objects, and triggers the status update operation of the corresponding drug entity, storage location entity or equipment entity in the digital twin.

[0031] Methods for outputting drug attribute information and storage location topology information separately include: Based on the spatiotemporal data units in the fused data stream, the storage space, storage location, medicines, and equipment in the physical warehouse are associated one-to-one with the corresponding entities in the digital twin according to the unique entity identifier. When changes in the location of medicines, changes in inventory quantity, or changes in the operating status of equipment are detected in the fused data stream, the spatial coordinate parameters, attribute parameter sets, or status parameter sets of the corresponding entities in the digital twin are automatically updated to achieve a positive mapping from the physical warehouse status to the pharmaceutical warehouse digital twin. When the storage location allocation result is generated in the pharmaceutical warehouse digital twin, the storage location allocation result is fed back to the pharmaceutical warehouse management terminal to achieve a reverse mapping from the pharmaceutical warehouse digital twin to the physical warehouse. Based on the establishment of a two-way mapping relationship, drug attribute information is generated based on inventory drug data and historical business data. The spatial coordinate parameters of the storage location entities in the digital twin, the adjacency relationship between storage locations, the hierarchical relationship and the accessibility relationship of the channels are uniformly organized and associated with the unique entity identifier of the corresponding storage location entity to form storage location topology information that reflects the spatial organization structure between storage locations. Drug attribute information includes the drug's expiration date, nominal shelf life, current inventory quantity, and historical average outbound volume within the preset statistical period; warehouse location topology information includes the location parameters of the warehouse location in the three-dimensional spatial coordinate system of pharmaceutical warehousing, the spatial distance between the warehouse location and the preset outbound port, the type of operating channel where the warehouse location is located, and the connectivity between the warehouse location and the operating channel.

[0032] It should be noted that, based on the establishment of a two-way mapping relationship between physical warehousing and pharmaceutical warehousing digital twins, the system aggregates data belonging to the same pharmaceutical entity according to the unique identifier of the pharmaceutical entity based on the inventory pharmaceutical data parsed from the fused data stream, and extracts the expiration date information as the expiration date of the pharmaceutical. The system determines the drug variety identifier of a batch based on the batch information corresponding to the drug entity. Then, using this drug variety identifier as an index, it queries the pre-stored basic drug information in the system's business data. It reads the storage period corresponding to the drug variety, which is the nominal shelf life. The read storage period is written into the attribute parameter set of the drug entity as the nominal shelf life of that batch of drugs. Based on inventory records, the system calculates the current inventory quantity and performs time window filtering and quantity aggregation on historical business data's outbound records within a preset statistical period. It calculates the average outbound quantity per unit time, thus forming drug attribute information including the expiration date, nominal shelf life, current inventory quantity, and historical average outbound quantity.

[0033] Simultaneously, based on the spatial coordinate parameters of each storage location entity in the digital twin, the system determines the location parameters of the storage location in the three-dimensional spatial coordinate system and calculates the spatial distance between the storage location and the preset outlet. It determines the adjacency relationship based on the horizontal distance between storage locations, determines the hierarchical relationship based on the vertical height difference, and determines the accessibility relationship of the channel and the type of operation channel where the storage location is located by combining the spatial location relationship between the storage location and the storage channel area. The system then organizes the above location parameters, spatial distances, operation channel types, and connectivity relationships and associates them with the unique identifier of the corresponding storage location entity to form storage location topology information that reflects the spatial organization structure between storage locations.

[0034] Methods for generating a priority ranking table of expiration dates include: Retrieve drug attribute information corresponding to each stocked drug from the digital twin, calculate the remaining shelf life of each drug at the current system time based on a preset time benchmark, generate a remaining shelf life ratio factor that reflects the time pressure of drug expiration based on the ratio between the remaining shelf life and the corresponding nominal shelf life, and generate an inventory correction factor that reflects the degree of drug inventory backlog based on the ratio between the current inventory quantity of each drug and the historical average outbound quantity within the preset statistical period. By logically coupling the remaining expiration period ratio factor with the inventory adjustment factor, the urgency of each drug's expiration date is obtained, which comprehensively characterizes the overall expiration date risk level of the drug under the remaining expiration date and inventory turnover status. Based on the urgency of each drug's expiration date, the drugs are prioritized in descending order to generate an expiration date priority ranking table.

[0035] The urgency of the expiration date is: ;in, Indicates the first This type of medicine at all times The urgency of the expiration date; Index identifiers for pharmaceuticals, used to distinguish different types of pharmaceuticals within a pharmaceutical warehouse; This indicates the current system time, which is determined based on a preset time base. Indicates the first The expiration date of the corresponding drug; Indicates the first The nominal shelf life of a drug from the date of its entry into the warehouse; Indicates the first The remaining shelf life of the drug at the current moment; Indicates the first The remaining shelf life ratio factor for a drug is used to reflect the ratio of the remaining shelf life of the drug to its shelf life. Indicates the first The current inventory quantity of this drug at the current system time; Indicates the first The historical average outbound volume of a certain drug is obtained by statistically analyzing historical outbound records within a preset statistical period. Indicates medicine The ratio between the current inventory quantity and the historical average outbound quantity within the preset statistical period; The inventory correction factor, which reflects the degree of drug inventory backlog, is used to adjust the remaining expiration rate factor, so that drugs with large inventory and slow turnover have a relatively lower expiration priority in the overall ranking. Methods for generating a warehouse location value ranking table include: The topological information of each storage location within the pharmaceutical warehouse is obtained from the digital twin. Based on the location parameters of each storage location in the three-dimensional spatial coordinate system of the pharmaceutical warehouse, the spatial distance between each storage location and the preset exit is calculated. ;in, Indicates the first The coordinates of each storage location in the three-dimensional spatial coordinate system of pharmaceutical warehousing along the horizontal direction; Indicates the first The coordinates of each storage location along the vertical direction in the three-dimensional spatial coordinate system of pharmaceutical warehousing; Indicates the first The coordinates of each storage location in the three-dimensional spatial coordinate system of pharmaceutical warehousing along the vertical height direction; This indicates the coordinates of the preset outbound port in the three-dimensional spatial coordinate system of pharmaceutical warehousing along the horizontal direction; This indicates the coordinates of the preset outbound port along the longitudinal direction in the three-dimensional coordinate system of pharmaceutical warehousing. This indicates the coordinates of the preset outbound port along the vertical height direction in the three-dimensional coordinate system of pharmaceutical warehousing; Based on the connectivity between the storage location and the work passage, the accessibility status of the work passage for the storage location is determined. The accessibility status reflects the degree to which the storage location is constrained by the path during picking and handling operations. Based on the spatial distance and the accessibility status of the storage location's operational channels, an outbound value evaluation function is constructed to generate an outbound value coefficient for each storage location. The outbound value coefficient comprehensively represents the convenience and operational efficiency of the storage location in the current warehousing topology. After obtaining the outbound value coefficient for each storage location, the storage locations are sorted from high to low according to the outbound value coefficient to generate a storage location value ranking table.

[0036] The outbound value evaluation function is: ;in, Indicates the first Outbound value coefficient for each storage location; This indicates the storage location index identifier, used to distinguish different storage locations in pharmaceutical warehousing; Indicates the first The spatial distance from each storage location to the preset outlet; This represents a preset distance parameter used to standardize spatial distances, enabling the exponential decay function to reflect the impact of distance decay on a uniform scale. This represents the exponential decay function of spatial distance, used to map the distance between storage locations and the convenience of outbound delivery to a continuous, monotonically decreasing quantitative value; This represents the accessibility weighting coefficient, used to adjust the gain on outbound value when the storage location is located in the operational access area; Indicates the first Location identifier of each storage location; This represents the set of storage locations corresponding to the operation channel; This indicates an indicator function that quantifies the connectivity between storage locations and operational channels. When a storage location... The set of storage locations corresponding to the operation channel When the time is within the specified range, the value is 1; otherwise, it is 0. This represents the accessibility correction factor, which maps channel attribute information into numerical gain and, together with the spatial distance factor, determines the final outbound value coefficient. Methods for calculating the matching degree between drugs and storage locations include: Obtain the expiration urgency of all drugs from the expiration priority ranking table, and sort the drugs from high to low expiration urgency; obtain the outbound value coefficient of all storage locations from the storage location value ranking table, and sort the storage locations from high to low outbound value coefficient. Based on the urgency of the drug's expiration date and its outbound value coefficient, a set of fuzzy comprehensive evaluation indicators is constructed. ;in, Indicators indicating the urgency of the expiration date The outbound value coefficient index is represented; and a membership function is established for each fuzzy comprehensive evaluation index. The membership function maps the expiration urgency and the outbound value coefficient to the corresponding fuzzy membership degree. The corresponding fuzzy membership degree is: ;in, Indicates the first Fuzzy membership degree corresponding to a drug under the expiration date urgency index; Indicates the first The fuzzy membership degree of each storage location under the outbound value coefficient index; This represents the membership function set for the urgency index of drug expiration date. It can be in the form of a linear function, a piecewise function, or a nonlinear function, and is set according to the characteristics of the expiration date risk changing over time. This represents the membership function set for the warehouse location outbound value coefficient. It can be a monotonically increasing function that reflects the positive correlation between the warehouse location outbound value and its membership degree. Preset weights are assigned to each fuzzy comprehensive evaluation index. For each drug-storage location combination, the matching degree value is calculated according to the membership degree and corresponding weight of each fuzzy comprehensive evaluation index, and the matching degree of each drug in each storage location is obtained.

[0037] The matching degree is: ;in, Indicates medicine With storage location The degree of matching between them; The preset weights of the expiration date urgency indicator; This indicates the preset weight of the outbound value coefficient indicator; Methods for generating storage location migration tasks include: After obtaining the matching degree of each drug for each storage location, the candidate storage location with the highest matching degree is selected as the allocation object for each drug in turn, and it is determined whether the candidate storage location meets the preset environmental constraints, including temperature and humidity range, hazardous materials isolation requirements and storage location capacity limit. When a candidate storage location meets preset environmental constraints, it is assigned to the current drug, and the location status is updated to occupied. Under the same preset environmental constraints, the drug is assigned the storage location with the highest matching degree. When the matching degree between the drug and the candidate storage location is lower than a preset matching degree threshold, or when all candidate storage locations do not meet the preset environmental constraints, a storage location migration task is generated. The storage location migration task includes drug relocation, activation or release of empty storage locations, environmental constraint optimization, operation channel adjustment, manual intervention prompts, and digital twin updates.

[0038] When the matching degree between drugs and candidate storage locations is lower than the preset matching degree threshold, or when all candidate storage locations fail to meet the preset environmental constraints, it indicates that the current occupancy structure of the storage space can no longer achieve the unity of environmental constraint satisfaction and matching degree optimization goals under the existing state. In this case, direct allocation will lead to a decrease in resource utilization efficiency or the continued existence of constraint conflicts. Therefore, it is necessary to generate storage location migration tasks to readjust the existing binding relationship between drugs and storage locations, release more suitable storage location resources, thereby restoring the consistency between the storage location allocation results and the matching degree evaluation system, and achieving the overall optimization of the storage space structure.

[0039] It should be noted that drug relocation means moving drugs with low matching degree or low priority in the occupied storage space to other storage spaces that meet environmental constraints, so as to free up storage spaces with high matching degree for high-urgency drugs; activating or releasing empty storage spaces means activating or releasing temporarily occupied storage spaces that were originally unused, so that they can be used for the allocation of high-urgency drugs; environmental constraint optimization means adjusting the storage space or adjacent storage spaces for drugs that require specific temperature and humidity, hazardous materials isolation or capacity restrictions, so that the allocated storage space meets the environmental constraints. Operation channel adjustment optimizes the usage sequence of operation channels or the access sequence of storage locations to ensure that medicines can smoothly enter or leave their assigned storage locations during picking and handling operations; manual intervention prompts generate prompts for medicines that cannot be automatically migrated or are subject to special conditions, guiding warehouse management personnel to manually adjust storage locations or handle them specially; digital twin updates update the storage location status, medicine location, and matching information in the digital twin in real time after storage location migration, maintaining the synchronization between physical warehousing and the digital twin.

[0040] Methods for generating a release notification when a drug's expiration date reaches the warning criteria include: Receive storage location allocation results and storage location migration tasks, map the storage location allocation results and storage location migration tasks to the pharmaceutical warehousing digital twin, realize two-way status synchronization between physical warehousing and digital twin, and update drug location, storage location occupancy status and matching degree information of each drug in each storage location; Based on drug attribute information and expiration urgency, the expiration status of each drug in the warehouse is dynamically displayed, and the expiration urgency of the drugs is presented using color; according to the storage location value ranking table and outbound value coefficient, the value level of each storage location is marked in the digital twin, and the matching degree between the allocated drugs and storage locations is visualized through icons. For example, in a digital twin's 3D warehouse model, an icon or symbol is placed for each storage location to indicate its match with the medicine. The shape, size, or color of the icon can represent the matching level; for example, a large circle indicates a high matching level, and a small triangle indicates a low matching level. The expiration dates of medicines are monitored in real time. When the urgency of a medicine's expiration date reaches a preset threshold, a release prompt is generated, reminding warehouse operators to perform the release operation via message notification or scheduling interface.

[0041] The preset matching threshold is set by staff. By collecting different matching scores, the average of multiple semantic matching scores is taken as the preset matching threshold. Similarly, the preset expiration date urgency threshold is set.

[0042] This embodiment logically couples the remaining shelf life of a drug with its inventory turnover status to generate a single expiration urgency value, enabling a comprehensive quantitative assessment of drug expiration risk and avoiding evaluation distortion caused by relying solely on a single time indicator. By introducing an inventory correction factor, the remaining shelf life ratio is dynamically adjusted, allowing drugs with similar expiration dates but significantly different inventory statuses to be effectively distinguished in the ranking results, thereby improving the consistency between expiration priority ranking and actual warehouse operation status. By prioritizing and ranking drugs with higher overall expiration risk, this invention can trigger outbound or warehouse location adjustment strategies in advance, effectively reducing the risk of backlog and spoilage of near-expiration drugs due to unreasonable inventory structure. Real-time mapping and visualization of the expiration urgency results using a digital twin allows managers to intuitively grasp the distribution of drug expiration risk within the warehouse, improving the controllability and decision-making efficiency of warehouse operations.

[0043] By logically coupling the spatial distance exponential decay function with the accessibility status of operational channels, the ease of outbound delivery of storage locations is quantified into an outbound value coefficient, enabling a unified assessment of storage location value. Based on real-time acquisition of the three-dimensional coordinates of storage locations and channel connectivity using digital twins, the system can dynamically reflect the impact of warehouse structure or channel adjustments on storage location value, improving the flexibility of storage location scheduling and outbound operations, and achieving dynamic optimization. The generated storage location value ranking table prioritizes the allocation of high-value storage locations to frequently dispatched medicines or urgent orders, reducing handling paths and picking time; it supports intelligent storage location management and inventory optimization, significantly improving warehouse resource utilization and operational efficiency.

[0044] Example 2 Please see Figure 2 As shown, the parts not described in detail in this embodiment are described in Embodiment 1. A digital twin-based intelligent pharmaceutical warehouse visualization management method is provided, including: S1. Collect multi-dimensional raw data from pharmaceutical warehousing, perform unified spatiotemporal labeling processing on the multi-dimensional raw data, and generate a fused data stream; S2. Construct a digital twin of pharmaceutical warehousing based on the fused data flow, and establish a two-way mapping relationship between the physical warehouse and the digital twin, outputting drug attribute information and warehouse location topology information respectively; S3. Calculate the urgency of drug expiration dates based on drug attribute information, sort the drugs, and generate an expiration date priority ranking table; at the same time, calculate the outbound value coefficient of the storage location based on the storage location topology information, sort the storage locations, and generate a storage location value ranking table. S4. Calculate the matching degree between drugs and storage locations based on the expiration date priority ranking table and the storage location value ranking table. Assign the storage location with the highest matching degree to the drug under the preset environmental constraints, and generate a storage location migration task when the matching degree is lower than the preset matching degree threshold. S5. Receive storage location allocation results and storage location migration tasks, visualize the drug expiration status, storage location value distribution and drug storage location matching relationship using digital twins, and generate outbound prompts when the drug expiration date reaches the warning conditions.

[0045] Since the electronic device described in this embodiment is the electronic device used in implementing the digital twin-based intelligent pharmaceutical warehouse visualization management system described in this application embodiment, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the digital twin-based intelligent pharmaceutical warehouse visualization management system described in this application embodiment. Therefore, how the electronic device implements the method in this application embodiment will not be described in detail here. As long as those skilled in the art implement the electronic device used in implementing the digital twin-based intelligent pharmaceutical warehouse visualization management system described in this application embodiment, it falls within the protection scope of this application.

[0046] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0047] The above description is merely a preferred embodiment of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for users of ordinary technical skills, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A digital twin-based intelligent pharmaceutical warehouse visualization management system, characterized in that, include: The multi-source data fusion acquisition module is used to collect multi-dimensional raw data in pharmaceutical warehousing, perform unified spatiotemporal labeling processing on the multi-dimensional raw data, and generate a fused data stream. The digital twin construction module is used to build a digital twin of pharmaceutical warehousing based on the fused data flow, and establish a two-way mapping relationship between physical warehousing and digital twin, outputting drug attribute information and warehouse location topology information respectively; The priority ranking module is used to calculate the urgency of drug expiration dates based on drug attribute information, and to rank the drugs to generate an expiration date priority ranking table; at the same time, it calculates the outbound value coefficient of the storage location based on the storage location topology information, ranks the storage locations, and generates a storage location value ranking table. The expiration date and storage location matching optimization module is used to calculate the matching degree between drugs and storage locations based on the expiration date priority sorting table and the storage location value sorting table. Under the condition of meeting the preset environmental constraints, it assigns the storage location with the highest matching degree to the drug and generates a storage location migration task when the matching degree is lower than the preset matching degree threshold. The visualization management module receives storage location allocation results and storage location migration tasks. It uses a digital twin to visualize the drug expiration status, storage location value distribution, and drug storage location matching relationship, and generates an outbound prompt when the drug expiration reaches the warning condition.

2. The pharmaceutical intelligent warehouse visualization management system based on digital twin as described in claim 1, characterized in that, The methods for obtaining the multi-dimensional raw data include: The multi-dimensional raw data includes environmental data, inventory drug data, equipment operation data, operational behavior data, and system business data. Among them, environmental data is collected through environmental sensing terminals set up in different storage areas, passage areas, and operation areas of the pharmaceutical warehouse. Specifically, it includes temperature parameters, humidity parameters, air quality parameters, as well as corresponding collection timestamps and area identification information. Inventory drug data is obtained through automatic identification of unique drug identifiers, which are linked to drug packaging via RFID electronic tags or QR codes. Inventory drug data includes batch information, expiration date information, inventory quantity information, drug status information, and drug location information within the warehouse space. Each medicine in a pharmaceutical warehouse is assigned a unique identifier upon entry. This unique identifier is linked to the medicine packaging via an RFID electronic tag or QR code. During the operation of the pharmaceutical warehouse, automatic identification terminals installed at the entry and exit points and in the shelving aisles automatically identify the unique identifiers to obtain inventory data. This inventory data includes batch information, expiration date information, inventory quantity information, medicine status information, and the location information of the medicine within the warehouse space. Equipment operation data is acquired through the control system and sensor interfaces of the automated pharmaceutical warehousing equipment, including equipment start / stop status, operating speed, load parameters, and fault alarm information; operational behavior data is acquired by sensing and recording the operation process of pharmaceutical warehousing, including time information and operation type information corresponding to picking, shelving, and outbound operations; system business data is acquired through data interface with the pharmaceutical warehousing management terminal, including inbound orders, outbound orders, inventory records, and drug storage constraint information.

3. The pharmaceutical intelligent warehouse visualization management system based on digital twins according to claim 2, characterized in that, The method for generating the fused data stream includes: Based on a preset time base, a unified timestamp identifier is added to the multi-dimensional raw data from different data sources, and the location information in the multi-dimensional raw data is mapped to the three-dimensional spatial coordinate system of pharmaceutical warehousing to form corresponding coordinate parameters. The acquired timestamps and coordinate parameters are used as spatiotemporal labels and bound to the corresponding multi-dimensional raw data to form structured spatiotemporal data units. The spatiotemporal data units are arranged and combined in chronological order to form a fused data stream with unified time and space dimensions.

4. The pharmaceutical intelligent warehouse visualization management system based on digital twins according to claim 3, characterized in that, The method for constructing a digital twin of a pharmaceutical warehouse includes: Based on the spatiotemporal data units in the fused data stream, the physical objects in the pharmaceutical warehouse are digitally abstracted, and the warehouse space entities, storage location entities, drug entities and equipment entities are identified and generated. A digital description structure containing a unique entity identifier, spatial coordinate parameters, attribute parameter set and state parameter set is established for each entity. Based on spatial coordinate parameters, each storage location entity is mapped to a unified three-dimensional spatial coordinate system. According to the relative positional relationship of each storage location entity in the three-dimensional spatial coordinate system, the adjacency relationship, hierarchical relationship and accessibility relationship between storage locations are determined, which are then embedded into the digital description structure of the storage location entity as constraints of the storage space organization structure. The system parses inventory drug data from the fused data stream, associates the inventory drug data with the spatial location of storage location entities, and establishes a binding relationship between drug entities and storage location entities. When changes in the attribute parameters or status parameters of an entity are detected in the fused data stream, the system triggers a status update for the corresponding entity. Using the digital description structure of each entity as the basic building block, and the organizational constraints and binding relationships of the warehouse space organization structure as organizational constraints, a unified digital space model is performed on the warehouse space entity, storage location entity, drug entity, and equipment entity. The digital space model is continuously updated under the drive of fused data flow, thereby forming a digital twin of pharmaceutical warehousing.

5. The pharmaceutical intelligent warehouse visualization management system based on digital twins according to claim 4, characterized in that, The methods for outputting drug attribute information and storage location topology information respectively include: The digital twin construction module is used to build a digital twin of pharmaceutical warehousing based on the fused data flow, and establish a two-way mapping relationship between physical warehousing and digital twin, outputting drug attribute information and warehouse location topology information respectively; Based on the spatiotemporal data units in the fused data stream, the storage space, storage location, medicines, and equipment in the physical warehouse are associated one-to-one with the corresponding entities in the digital twin according to the unique entity identifier. When changes in the location of medicines, changes in inventory quantity, or changes in the operating status of equipment are detected in the fused data stream, the spatial coordinate parameters, attribute parameter sets, or status parameter sets of the corresponding entities in the digital twin are automatically updated to achieve a positive mapping from the physical warehouse status to the pharmaceutical warehouse digital twin. When the storage location allocation result is generated in the pharmaceutical warehouse digital twin, the storage location allocation result is fed back to the pharmaceutical warehouse management terminal to achieve a reverse mapping from the pharmaceutical warehouse digital twin to the physical warehouse. Based on the establishment of a two-way mapping relationship, drug attribute information is generated based on inventory drug data and historical business data. The spatial coordinate parameters of the storage location entities in the digital twin, the adjacency relationship between storage locations, the hierarchical relationship and the accessibility relationship of the channels are uniformly organized and associated with the unique entity identifier of the corresponding storage location entity to form storage location topology information that reflects the spatial organization structure between storage locations. Drug attribute information includes the drug's expiration date, nominal shelf life, current inventory quantity, and historical average outbound volume within the preset statistical period; warehouse location topology information includes the location parameters of the warehouse location in the three-dimensional spatial coordinate system of pharmaceutical warehousing, the spatial distance between the warehouse location and the preset outbound port, the type of operating channel where the warehouse location is located, and the connectivity between the warehouse location and the operating channel.

6. The pharmaceutical intelligent warehouse visualization management system based on digital twin as described in claim 5, characterized in that, The method for generating the validity period priority ranking table includes: Retrieve drug attribute information corresponding to each stocked drug from the digital twin, calculate the remaining shelf life of each drug at the current system time based on a preset time benchmark, generate a remaining shelf life ratio factor that reflects the time pressure of drug expiration based on the ratio between the remaining shelf life and the corresponding nominal shelf life, and generate an inventory correction factor that reflects the degree of drug inventory backlog based on the ratio between the current inventory quantity of each drug and the historical average outbound quantity within the preset statistical period. By logically coupling the remaining expiration period ratio factor with the inventory adjustment factor, the urgency of each drug's expiration date is obtained, which comprehensively characterizes the overall expiration date risk level of the drug under the remaining expiration date and inventory turnover status. Based on the urgency of each drug's expiration date, the drugs are prioritized in descending order to generate an expiration date priority ranking table.

7. The pharmaceutical intelligent warehouse visualization management system based on digital twin as described in claim 6, characterized in that, The method for generating the warehouse location value ranking table includes: The topological information of each storage location in the pharmaceutical warehouse is obtained from the digital twin. Based on the position parameters of the storage location in the three-dimensional spatial coordinate system of the pharmaceutical warehouse, the spatial distance between each storage location and the preset outlet is calculated. Based on the connectivity between storage locations and operational channels, the accessibility status of operational channels for storage locations is determined. Based on spatial distance and the accessibility status of operational channels for storage locations, an outbound value evaluation function is constructed to generate the outbound value coefficient corresponding to each storage location. After obtaining the outbound value coefficient corresponding to each storage location, the storage locations are sorted from high to low according to the outbound value coefficient to generate a storage location value ranking table.

8. The pharmaceutical intelligent warehouse visualization management system based on digital twins according to claim 7, characterized in that, The method for calculating the matching degree between drugs and storage locations includes: Obtain the expiration urgency of all drugs from the expiration priority ranking table, and sort the drugs from high to low expiration urgency; obtain the outbound value coefficient of all storage locations from the storage location value ranking table, and sort the storage locations from high to low outbound value coefficient. Based on the urgency of the drug's expiration date and the value coefficient of the drug's delivery, a set of fuzzy comprehensive evaluation indicators is constructed, and a membership function is established for each fuzzy comprehensive evaluation indicator. The urgency of the expiration date and the value coefficient of the drug's delivery are mapped to the corresponding fuzzy membership degree through the membership function. Preset weights are assigned to each fuzzy comprehensive evaluation index. For each drug-storage location combination, the matching degree value is calculated according to the membership degree and corresponding weight of each fuzzy comprehensive evaluation index, and the matching degree of each drug in each storage location is obtained.

9. The pharmaceutical intelligent warehouse visualization management system based on digital twins according to claim 8, characterized in that, The method for generating storage location migration tasks includes: After obtaining the matching degree of each drug for each storage location, the candidate storage location with the highest matching degree is selected as the allocation object for each drug in turn, and it is determined whether the candidate storage location meets the preset environmental constraints, including temperature and humidity range, hazardous materials isolation requirements and storage location capacity limit. When a candidate storage location meets the preset environmental constraints, the candidate storage location is assigned to the current drug and the storage location status is updated to occupied. Under the preset environmental constraints, the drug is assigned the storage location with the highest matching degree. When the matching degree between the drug and the candidate storage location is lower than the preset matching degree threshold, or when all candidate storage locations do not meet the preset environmental constraints, a storage location migration task is generated.

10. The pharmaceutical intelligent warehouse visualization management system based on digital twins according to claim 9, characterized in that, The method for generating a release notification when the expiration date of a drug reaches the warning condition includes: Receive storage location allocation results and storage location migration tasks, map the storage location allocation results and storage location migration tasks to the pharmaceutical warehousing digital twin, realize two-way status synchronization between physical warehousing and digital twin, and update drug location, storage location occupancy status and matching degree information of each drug in each storage location; Based on drug attribute information and expiration urgency, the expiration status of each drug in the warehouse is dynamically displayed, and the expiration urgency of the drugs is presented using color. According to the storage location value ranking table and the outbound value coefficient, the value level of each storage location is marked in the digital twin, and the matching degree between the allocated drugs and storage locations is visualized through icons. The expiration dates of drugs are monitored in real time. When the expiration urgency of a drug reaches the preset expiration urgency threshold, an outbound prompt instruction is generated, and warehouse operators are reminded to perform the outbound operation through message notification or scheduling interface.

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