A full-automatic reagent library full-virtual location management system and a use method thereof

Abstract

The application belongs to the technical field of vaccine reagent storage, in particular to a full-automatic reagent library full-virtual storage location management system and a use method thereof. The system comprises a visual identification module, a transportation module, a storage module and a storage calculation module. The storage calculation module identifies the specific storage area of the reagent box in the storage module through the visual identification module, optimizes the transportation path, and executes the transportation storage by the transportation module. The application can identify the specific storage area of the reagent box in the storage module, optimize the transportation path, collect the size, contour, color and surface pattern data of the reagent box through the surface scanning of the reagent box, generate the vaccine storage reference indication information in different time periods, and analyze the reagent use storage vaccine reagent use early warning situation and reagent expiration early warning situation for the reference of the user.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of vaccine reagent storage, and specifically relates to a full-automatic reagent library full-virtual storage location management system and a use method thereof. BACKGROUND

[0002] The quality of a vaccine depends on its storage conditions, because many vaccines need highly specific warehouses to maintain effectiveness, and any deviation can have a great impact on the activity of the vaccine, and in the worst case, can make the vaccine ineffective. Therefore, how to efficiently store vaccines and accurately control vaccine reagents is a current research hotspot. For example, patent number CN202311792225.0 is a vaccine management system based on cloud AI and edge computing, which clusters vaccines on each edge according to the future demand of each type of vaccine, the frequency of each type of vaccine in and out of the warehouse, and obtains the vaccine clustering results of each edge. The edge server predicts the future vaccine demand of the intelligent cold storage based on the trained AI prediction model and then provides procurement suggestions. The cloud platform sends the vaccine clustering results of each edge to each edge server, and each edge server provides intelligent cold storage vaccine storage location suggestions according to the vaccine clustering results. However, it lacks accurate evaluation of vaccine storage quality. Patent number CN202111665985.6 is an intelligent warehouse service management system based on cloud computing, which can display 3D visual display of goods information in the warehouse, execute automatic warehouse according to the order number of the user, and realize intelligent management of the warehouse. However, the existing technology lacks sufficient precision in vaccine control, especially the size of the vaccine box may not be the same, and each position may not be compatible when placed. The inventory setting is set in advance according to the details of the current inventory, and if the number of vaccine box types changes or new vaccine box types are encountered, the storage location needs to be adjusted again, which is very disadvantageous for future equipment maintenance. Therefore, it is necessary to develop a new management system. SUMMARY

[0003] The purpose of the present application is mainly to overcome the shortcomings of the prior art. The full-automatic reagent library full-virtual storage location management system can adapt to the storage of various vaccine reagent boxes and can track the vaccine storage status in real time.

[0004] To achieve the above purpose, the technical scheme adopted by the present application is:

[0005] The application discloses a full-automatic reagent library full-virtual warehouse position management system, which comprises a visual identification module, a transportation module, a warehouse module and a storage calculation module; the visual identification module and the storage calculation module are connected with each other in data, the collected data is sent to the storage calculation module, and the identification strategy is adjusted according to the instruction of the storage calculation module; the transportation module and the storage calculation module are connected with each other in data, and the reagent box is transported according to the instruction of the storage calculation module; the warehouse module and the storage calculation module are connected with each other in data, and the position information of the stored reagent box is sent to the storage calculation module; the storage calculation module identifies the specific storage area of the reagent box in the warehouse module through the visual identification module, optimizes the transportation path, and executes the transportation storage through the transportation module.

[0006] Preferably, the visual identification module comprises a wide-angle camera and a high-definition camera; the wide-angle camera scans the surface of the reagent box, collects the size, contour, color and surface pattern data of the reagent box, establishes the appearance database of the reagent box, and the high-definition camera identifies the nameplate information and barcode information on the surface of the reagent box, collects the dosage form, ingredient and applicable scene data of the reagent in the reagent box, and forms the reagent key information database.

[0007] Preferably, the transportation module comprises a conveying belt and a transportation unmanned vehicle; the conveying belt is used for transporting the reagent box to each area of the warehouse, and the transportation unmanned vehicle is used for transporting the reagent box to a designated shelf.

[0008] Preferably, the warehouse module divides the warehouse space into different areas, numbers each area, numbers the shelf positions in the area, and forms different warehouse area classification storage reagent boxes.

[0009] Preferably, the storage calculation module comprises a cloud computer management program, divides different areas of the warehouse, divides the functions, calculates the reagent box out-of-warehouse quantity and in-warehouse quantity of each area, marks the storage reagent box data according to the area, divides the reagents in the reagent boxes in different areas into stages, generates marking information, calculates the storage period, expiration invalid time and in-warehouse and out-of-warehouse route of various reagents, uses a deep learning model to construct the optimal storage model of the area, analyzes the use quantity and storage quantity of the vaccines in different reagent boxes through the reagent box label, introduces weather and warehouse energy consumption parameters, associates the use characteristics of different seasons of people, and generates vaccine storage reference indication information in different time periods.

[0010] Preferably, the construction of the area optimal storage model is specifically: in different storage areas, the kit storage information of a single function area is classified, the classified data information is graded, and corresponding weights are given according to the use degree during grading; according to the processing logic, the kits of high weight data are first identified and analyzed; at different time nodes, the user interface preferentially presents high weight kits; when the user searches the system associated with multiple kits, high weight data is preferentially displayed; by sorting different kits according to the user search frequency, high use frequency kits are placed in the optimal position.

[0011] Preferably, the model construction of deep learning is specifically: the collected data is constructed by using an expansion convolution residual network to form an encoding and decoding mechanism, a data model of a vaccine kit is formed, an optimized residual network is used to extract appearance data and vaccine data of the kit to construct a feature correlation graph, and model parameters of kits in different areas under the optimal transportation path are formed, so as to facilitate the shortest time and highest efficiency to get the kit.

[0012] Preferably, the weather parameter includes the storage time of low-temperature vaccine reagent in high-temperature seasons, and collects specific temperature data, temperature differences of different paths, and stability of vaccines during transportation, for evaluating the risk of storing vaccine reagents in different seasons.

[0013] The use method of the full-automatic reagent library full-virtual storage location management system provided in the application comprises:

[0014] The characteristics of the kit are identified by the visual recognition module, data is sent to the storage calculation module, the kit is matched to a specific storage location, kits of the same type are classified, the optimal transportation route is analyzed, and instructions are sent for execution by the transportation module;

[0015] The kit is transported to the corresponding shelf by the conveyor belt of the transportation module, and then transported to the specific storage location by the transportation unmanned vehicle; the storage module receives the kit, and sends the used storage location and unused storage location data information to the storage calculation module;

[0016] The storage calculation module analyzes the reagent use and storage vaccine reagent use early warning situation and reagent expiration early warning situation for the user to refer.

[0017] Compared with the prior art, the application has the following beneficial effects:

[0018] This application discloses a fully automated reagent library virtual storage management system, comprising a visual recognition module, a transportation module, a storage module, and a storage computing module. It can identify the specific storage area of ​​the reagent kits within the storage module, optimize transportation routes, and collect data on the size, outline, color, and surface graphics of the reagent kits through surface scanning to establish a reagent appearance database. It can also identify nameplate and barcode information on the surface, collect data on the dosage form, ingredients, and applicable scenarios of the reagents within the kits, forming a key reagent information database. This ensures quality tracking during vaccine storage, correlates with the usage characteristics of different populations in different seasons, generates vaccine storage reference instructions for different time periods, and analyzes reagent usage and storage warnings, as well as reagent expiration warnings, for user reference. Attached Figure Description

[0019] Figure 1 This is a logical diagram of this application. Detailed Implementation

[0020] Example 1

[0021] A fully automated reagent library virtual storage management system includes a visual recognition module, a transportation module, a storage module, and a storage computing module. The visual recognition module and the storage computing module are data-connected, with the visual recognition module sending collected data to the storage computing module and adjusting the recognition strategy according to instructions from the storage computing module. The transportation module and the storage computing module are also data-connected, transporting reagent kits according to the instructions from the storage computing module. The storage module and the storage computing module are also data-connected, sending the location information of the stored reagent kits to the storage computing module. The storage computing module uses the visual recognition module to identify the specific storage area of ​​the reagent kit within the storage module, optimizes the transportation route, and the transportation module executes the transportation and storage. The visual recognition module includes a wide-angle camera and a high-definition camera. The wide-angle camera scans the surface of the reagent kits, collecting data on their size, outline, color, and surface graphics to establish an appearance database. The high-definition camera identifies the nameplate and barcode information on the surface of the reagent kits, collecting data on the dosage form, ingredients, and applicable scenarios of the reagents within the kits, forming a key reagent information database.

[0022] As a preferred embodiment, the transportation module includes a conveyor belt and a transport drone. The conveyor belt is used to transport the test kits to various areas of the warehouse, and the transport drone is used to transport the test kits to designated shelves.

[0023] As a preferred method, the storage module divides the storage space into different areas, assigns a number to each area, and then assigns a number to the shelf locations within that area, thus forming different storage area classification and storage kits.

[0024] As a preferred mode, the storage computing module includes a cloud computer management program, which divides different areas of the warehouse, distinguishes functions, calculates the out-of-warehouse and in-warehouse quantities of each area, and marks the storage kit data according to the area; and the kits in different areas are staged, the labeled information is generated, the storage period, expiration time, and in-warehouse and out-of-warehouse route of various reagents are calculated, and the optimal storage model of the area is constructed using a deep learning model; the use amount and storage amount of different vaccines in the kit are analyzed by analyzing the kit label, weather and warehouse energy consumption parameters are introduced, the use characteristics of different seasons of people are associated, and the vaccine storage reference indication information in different time periods is generated;

[0025] As a preferred mode, the construction of the optimal storage model of the area is specifically: in different warehouse areas, the kit storage information of a single functional area is classified, the classified data information is graded, and corresponding weights are given according to the use degree during grading; the user interface presents high-weight kits first at different time nodes; when the user searches the system associated with multiple kits, high-weight data is displayed first; different kits are sorted by the user search frequency, and high-use-frequency kits are in the optimal position;

[0026] As a preferred mode, the model construction of deep learning is specifically: the collected data is constructed with a residual network of dilated convolution to form an encoding and decoding mechanism, a data model of vaccine kits is formed, an optimized residual network is used to extract appearance data and vaccine data of the kit to construct a feature correlation graph, and model parameters of different area kits under the optimal transportation path are formed to facilitate the shortest time and highest efficiency to get the kit;

[0027] As a preferred mode, the weather parameter includes the storage time of low-temperature vaccine reagents in high-temperature seasons, and collects specific temperature data, temperature differences of different paths, and stability of vaccines during transportation to evaluate the risk of storing vaccines in different seasons.

[0028] A use method of a full-automatic reagent library full-virtual storage location management system, comprising:

[0029] The visual recognition module recognizes the characteristics of the kit, sends the data to the storage computing module, matches the kit to a specific location in the warehouse, classifies the same kits, analyzes the optimal transportation route, and sends instructions for execution by the transportation module;

[0030] The conveyor belt of the transportation module transports the kit to the corresponding shelf, and then the kit is transported to the specific storage location by the transportation unmanned vehicle; the warehouse module receives the kit, sends the used storage location and unused storage location data information to the storage computing module;

[0031] The storage computing module analyzes the storage kit to analyze the storage vaccine reagent use, reagent expiration warning, and reagent use warning for the user.

[0032] Embodiment 2

[0033] The full-automatic reagent library full-virtual storage location management system comprises a visual recognition module, a transportation module, a storage module, and a storage computing module; the visual recognition module and the storage computing module are data-connected, the collected data is sent to the storage computing module, and the recognition strategy is adjusted according to the instruction of the storage computing module; the transportation module and the storage computing module are data-connected, and the reagent kit is transported according to the instruction of the storage computing module; the storage module and the storage computing module are data-connected, and the position information of the storage reagent kit is sent to the storage computing module; the storage computing module identifies the specific storage area of the reagent kit in the storage module through the visual recognition module, optimizes the transportation path, and executes the transportation storage by the transportation module; the visual recognition module comprises a wide-angle camera and a high-definition camera; the wide-angle camera scans the surface of the reagent kit to collect the size, contour, color, and surface pattern data of the reagent kit, builds the appearance database of the reagent kit, and the high-definition camera identifies the nameplate information and barcode information on the surface of the reagent kit, collects the dosage form, composition, and application scenario data of the reagent in the reagent kit, and forms the key information database of the reagent; the high-definition camera has a macro recognition function, and when the wide-angle camera identifies that the surface of the reagent kit is abnormal, the high-definition camera focuses on scanning the key area;

[0034] The transportation module comprises a conveyor belt and a transportation unmanned vehicle; the conveyor belt is used to transport the reagent kit to each area of the warehouse, and the transportation unmanned vehicle is used to transport the reagent kit to the designated shelf;

[0035] The storage module divides the storage space into different areas, numbers each area, numbers the storage locations of the shelves in the area, and forms different storage area classification storage reagent kits;

[0036] The storage computing module comprises a cloud computer management program, divides different areas of the storage, divides the functions, calculates the reagent kit out-of-warehouse quantity and in-warehouse quantity of each area, marks the storage reagent kit data according to the area, divides the reagents in the reagent kits in different areas, generates the marking information, calculates the storage period, expiration invalid time, and in-warehouse and out-of-warehouse route of various reagents, uses a deep learning model to build the optimal storage model of the area, analyzes the use quantity and storage quantity of the vaccines in different reagent kits through the reagent kit label, introduces weather and warehouse energy consumption parameters, associates the use characteristics of different seasons of people, and generates the vaccine storage reference indication information in different time periods;

[0037] As a preferred mode, the construction of the regional optimal storage model is specifically: in different storage areas, the kit storage information of a single function area is classified, the classified data information is graded, and corresponding weights are given according to the use degree during grading; according to the processing logic, the kits of high weight data are first identified and analyzed; at different time nodes, the user interface preferentially presents high weight kits; when the user searches the system associated with multiple kits, high weight data is preferentially displayed; by sorting different kits according to the user search frequency, high use frequency kits are placed in the optimal position.

[0038] The model construction of deep learning is specifically: the collected data is constructed with an expansion convolution residual network to form an encoding and decoding mechanism, and a data model of the vaccine kit is formed; the appearance data and vaccine data of the kit are extracted with an optimized residual network to construct a feature correlation graph, and model parameters of the kits in different regions under the optimal transportation path are formed to facilitate the shortest time and highest efficiency to get the kits.

[0039] The weather parameters include the storage time of low-temperature vaccine reagents in high-temperature seasons, and collect specific temperature data, temperature differences of different paths, and stability of vaccines during transportation to evaluate the risk of storing vaccine reagents in different seasons.

[0040] A use method of a full-automatic reagent library full-virtual storage location management system, comprising:

[0041] The characteristics of the kit are identified by the visual recognition module, the data is sent to the storage calculation module, the kit is matched to the specific storage location, the same type of kits are classified, the optimal transportation route is analyzed, and the instruction is sent to be executed by the transportation module; when the visual recognition module identifies that the kit is deformed and damaged, the specific characteristics are collected by the high-definition macro lens camera; to identify the damage degree and judge whether it has storage value;

[0042] The kit is transported to the corresponding shelf by the conveyor belt of the transportation module, and then transported to the specific storage location by the transportation unmanned vehicle; the storage module receives the kit, and sends the used storage location and unused storage location data information to the storage calculation module;

[0043] As a preferred mode, the storage calculation module analyzes the reagent use, storage, vaccine reagent use warning, and reagent expiration warning for the user's reference according to the stored kits.

Claims

1. A full-automatic reagent library full-virtual location management system, characterized in that, The system comprises a visual recognition module, a transportation module, a storage module, and a storage calculation module; the visual recognition module and the storage calculation module are data-connected, the collected data is sent to the storage calculation module, and the identification strategy is adjusted according to the instruction of the storage calculation module; the transportation module and the storage calculation module are data-connected, and the reagent box is transported according to the instruction of the storage calculation module; the storage module and the storage calculation module are data-connected, and the position information of the stored reagent box is sent to the storage calculation module; the storage calculation module identifies the specific storage area of the reagent box in the storage module through the visual recognition module, optimizes the transportation path, and executes the transportation storage by the transportation module; the storage calculation module comprises a cloud computer management program, divides different areas of the storage, divides the functions, calculates the quantity of the reagent box in and out of each area, marks the data of the stored reagent box according to the area, and divides the reagents in different reagent boxes into stages, generates marking information, calculates the storage period, expiration time, and in-out warehouse route of various reagents, uses a deep learning model to construct the optimal storage model of the area, analyzes the use and storage of different reagent boxes through the reagent box label, introduces weather and warehouse energy consumption parameters, associates the use characteristics of different seasons of people, and generates reference indication information of vaccine storage in different time periods; the weather parameters include the storage time of low-temperature vaccine reagents in high-temperature seasons, collect specific temperature data, temperature differences of different paths, and stability of vaccines in transportation, and are used to evaluate the risk of storage of vaccine reagents in different seasons.

2. The full-automatic reagent warehouse full-virtual location management system according to claim 1, characterized in that, The visual recognition module comprises a wide-angle camera and a high-definition camera; the wide-angle camera scans the surface of the reagent box, collects the size, contour, color, and surface pattern data of the reagent box, builds an appearance database of the reagent box, and the high-definition camera identifies the nameplate information and barcode information on the surface of the reagent box, collects the dosage form, ingredients, and application scenario data of the reagents in the reagent box, and forms a reagent key information database.

3. The full-automatic reagent warehouse full-virtual location management system according to claim 1, characterized in that, The transportation module comprises a conveyor belt and a transportation unmanned vehicle; the conveyor belt is used to transport the reagent box to each area of the warehouse, and the transportation unmanned vehicle is used to transport the reagent box to the designated shelf.

4. The full-automatic reagent warehouse full-virtual location management system according to claim 1, characterized in that, The storage module divides the storage space into different areas, numbers each area, numbers the shelf positions in the area, and forms different storage area classification storage reagent boxes.

5. The full-automatic reagent warehouse full-virtual location management system according to claim 1, characterized in that, The construction of the optimal storage model of the area is as follows: in different storage areas, the storage information of the reagent boxes in a single functional area is classified, the classified data information is graded, a corresponding weight is given according to the use degree during grading, the reagent boxes with high weight data are identified and analyzed first according to the processing logic; the user interface presents the high-weight reagent boxes first at different time nodes; when the user searches the system associated with multiple reagent boxes, the high-weight data is displayed first; the high-use-frequency reagent boxes are sorted to the optimal position by sorting different reagent boxes according to the user search frequency.

6. The full-automatic reagent warehouse full-virtual location management system according to claim 1, characterized in that, The model of deep learning is constructed as follows: an encoding-decoding mechanism is constructed by using an extended convolutional residual network for the collected data to form a data model of the vaccine kit, feature correlation graphs are constructed by using an optimized residual network to extract appearance data and vaccine data of the kit, and model parameters of the kit in different regions under an optimal transportation path are formed to facilitate obtaining the kit in the shortest time and with the highest efficiency.

7. The use of the full-automatic reagent warehouse full-virtual location management system according to claim 1, characterized in that, The method comprises the following steps: a visual recognition module is used to recognize the characteristics of the kit, data is sent to a storage calculation module, the kit is matched to a specific storage location, similar kits are classified, an optimal transportation route is analyzed, and an instruction is sent for execution by a transportation module; a conveyor belt of the transportation module is used to transport the kit to a corresponding shelf, and then an unmanned transportation vehicle is used to transport the kit to a specific storage location; the storage module receives the kit, and sends data information of used storage locations and unused storage locations to the storage calculation module; the storage calculation module analyzes the storage of the kit, and provides a user with a warning of the use of the stored vaccine and a warning of the expiration of the kit for reference.

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