Intelligent medicine storage and sorting method and system based on intelligent pharmacy management

Abstract

The invention relates to an intelligent medicine warehousing and sorting method and system based on intelligent pharmacy management, and belongs to the technical field of industrial control systems of medical product warehousing, and the method comprises the following steps: 1) analyzing input data; wherein whether the input data type is article storage data or article sorting data is determined by utilizing an article type strategy method; 2) analyzing whether the input data is article storage data or article sorting data by adopting a category noise reduction method so as to determine the type of the input data; step 3), performing data storage on the determined input data in a key matching mode; 4) extracting the stored data which are determined to be input, performing actual operation on the data which are determined to be input, and tracking an actual operation track; 5) ending the operation; the system has the beneficial effect that the accuracy of warehousing and sorting operation is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial control systems for medical goods storage, and in particular relates to an intelligent medicine storage and sorting method and system based on smart pharmacy management. Background Art

[0002] The operation of goods storage and sorting has gone through four stages: manual, mechanized, automated and intelligent. In the manual era, people completed various operations such as cargo handling, shelving, storage and sorting; in the mechanical era, cranes, lifts and other mechanical vehicles were used for operation; in the automatic era, automatic rail vehicles were used for transportation based on mechanization, and handling robots were used for automatic handling, sorting and transporting of goods; in the intelligent era, based on automation, combined with digitalization, the information of goods was collected and processed through the Internet of Things or Internet technology, and the cloud analyzed and issued instructions to achieve unmanned operation.

[0003] With the continuous development of intelligent technology, warehousing and sorting systems are widely used in various industries. With the increasing types and quantities of materials in warehousing and sorting, warehousing and sorting management operations have become very complex and diversified. Intelligent warehousing and sorting are generally composed of a warehousing and sorting management system and a control system. Among them, the warehousing and sorting management system is responsible for the data management of warehousing and sorting, and the control system is responsible for the execution of warehousing and sorting. The execution commands of the warehousing and sorting management system need to be executed by the control system to enable the operating equipment to operate. Warehousing and sorting operations are mainly carried out through the warehousing and sorting management system for the storage and sorting of items or medicines. However, when the warehousing and sorting management system is executed or operated through the control system, the operation accuracy is not high. How to make the warehousing and sorting management system improve the operation accuracy of the warehousing and sorting operations of items is a technical problem that urgently needs to be solved. Summary of the invention

[0004] The technical problem to be solved by the present invention is how to improve the accuracy of warehousing and sorting operations. The present invention provides an intelligent drug warehousing and sorting method and system based on smart pharmacy management. The method determines whether the input data type is item warehousing data or item sorting data through a category strategy method or a category noise reduction method, and then operates the determined input data, thereby improving the accuracy of warehousing and sorting operations.

[0005] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0006] An intelligent drug storage and sorting method based on smart pharmacy management includes the following steps:

[0007] Step 1): Analyze the input data; wherein, use the category strategy method to determine whether the input data type is item storage data or item sorting data;

[0008] Step 2): Use the object type noise reduction method to analyze whether the input data is item storage data or item sorting data to determine the input data type;

[0009] Step 3): The input data is stored by key matching;

[0010] Step 4): extract the stored input data, perform actual operation on the input data, and track the actual operation trajectory;

[0011] Step 5): End the operation.

[0012] Optionally, in step 1), the object strategy method uses the following formula (1):

[0013] (1);

[0014] in, is the total data model of the object class, For item storage data, For item sorting data, the total item data model includes item storage data and item sorting data; is the amount of data for item storage data, The amount of data to sort the items; is the proportion of item storage data in the total data of the category, The proportion of item sorting data in the total data of the category; Strategies for storing data for items, Strategies for sorting data for items; Comparison of the strategy for item storage data and the strategy for item sorting data. is the comparison function between the strategy of item storage data and the strategy of item sorting data, The comparison result of the strategy for outputting the item storage data and the strategy for the item sorting data;

[0015] When the item storage data strategy Strategies that are larger than item sorting data hour, Output item storage data strategy, the input data is determined as item storage data;

[0016] When the item storage data strategy Strategy for sorting data smaller than items hour, Output item sorting data strategy, and the input data is determined as item sorting data.

[0017] Optionally, in step 2), the object type denoising method adopts the following formula (2):

[0018] (2);

[0019] in, is the total data packet of the category, For item storage data, Sorting data for items, is the denoising of the total data packet of the object class, is the noise reduction function, the noise reduction function Remove item storage data and item sorting data Other data other than

[0020] Store data for items Item sorting data The ratio of To store data for items Item sorting data The comparison function, To export item storage data Item sorting data The ratio of

[0021] To determine the total data packet type of the denoised object class or the data type of the denoised input, To determine the result of the input data type;

[0022] when When the value of is greater than 1, The data input after noise reduction is determined to be the item storage data; When the value of is less than 1, The data representing the input after noise reduction is determined as item sorting data.

[0023] Optionally, in step 3), the key matching method adopts the following formula (3):

[0024] (3);

[0025] in, , and Different verification codes are used respectively. To adjust the program model of the verification code sequence, For the verification code model, The role of making each verification code in the verification code model from top to bottom is , and Arrangement of

[0026] For the verification code matching model, , and They are different matching codes. The order of matching codes from top to bottom is: , and Fixed arrangement;

[0027] To match the verification code model to the verification code matching model, The result of key matching.

[0028] Optionally, in step 4), the actual running trajectory is tracked by a real-time tracking method, and points on the actual running trajectory are collected every one minute.

[0029] Furthermore, if there is a difference between the actual running trajectory and the determined input data used for running, the determined input data is adjusted.

[0030] Optionally, in step 5), the actual operation of the determined input data is stopped.

[0031] An intelligent drug storage and sorting system based on smart pharmacy management, including:

[0032] The first analysis module is used to determine the input data type by the object strategy method;

[0033] A second analysis module is used to determine the data type of the input by a type denoising method;

[0034] A data storage module, used for storing the input data;

[0035] A data operation module, used for actually operating the input data, and the data operation module controls the operation device;

[0036] A trajectory collection module, used for collecting the running trajectory of the running device, feeding back the running trajectory of the running device to the data storage module, and the data storage module re-adjusting the determined input data in the data storage module;

[0037] The first analysis module or the second analysis module transmits the determined input data type to the data storage module, the data storage module transmits the determined input to the data operation module, the data operation module controls the operation device, the operation trajectory of the operation device is fed back to the data storage module, and the data storage module readjusts the determined input data in the data storage module.

[0038] Beneficial effects of the present invention:

[0039] The present invention mainly determines whether the input data type is item storage data or item sorting data through the category strategy method or the category noise reduction method, and then uses the determined input data for actual operation. The category strategy method or the category noise reduction method both use the capacity ratio between the output item storage data and the item sorting data in the total category data to determine the main type of the entire total category data. In this way, it can be determined whether the input data is mainly item storage data or item sorting data, and the main type of the entire total category data can be more accurately judged. Other data other than the main type can be filtered or excluded, thereby improving the accuracy of the operation of the storage and sorting operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0042] Figure 2 It is the work flow chart of the present invention. DETAILED DESCRIPTION

[0043] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0044] Example 1

[0045] like Figure 1 As shown, this embodiment provides an intelligent drug storage and sorting system based on smart pharmacy management, including: a first analysis module, a second analysis module, a data storage module, a data operation module and a trajectory collection module;

[0046] The first analysis module is used to determine the input data type by the type strategy method;

[0047] The second analysis module is used to determine the input data type by the object type denoising method;

[0048] The data storage module is used for storing the input data;

[0049] The data operation module is used to actually operate the input data, and the data operation module controls the operation device;

[0050] The trajectory acquisition module is used to collect the running trajectory of the running device, and feed the running trajectory of the running device back to the data storage module, and the data storage module readjusts the determined input data in the data storage module;

[0051] The first analysis module or the second analysis module transmits the determined input data type to the data storage module, the data storage module transmits the determined input to the data operation module, the data operation module controls the operation device, the operation trajectory of the operation device is fed back to the data storage module, and the data storage module readjusts the determined input data in the data storage module.

[0052] In addition, when the first analysis module or the second analysis module transmits the determined input data type to the data storage module, the data storage module requires key matching for the determined input data transmitted by the first analysis module or the second analysis module.

[0053] Example 2

[0054] like Figure 2 As shown, an intelligent drug storage and sorting method based on smart pharmacy management includes the following steps:

[0055] Step 1): Analyze the input data; wherein, use the category strategy method to determine whether the input data type is item storage data or item sorting data;

[0056] Step 2): Use the object type noise reduction method to analyze whether the input data is item storage data or item sorting data to determine the input data type;

[0057] Step 3): The input data is stored by key matching;

[0058] Step 4): extract the stored input data, perform actual operation on the input data, and track the actual operation trajectory;

[0059] Step 5): End the operation.

[0060] The type of input data is determined to be item storage data or item sorting data through the item category strategy method or the item category noise reduction method, and then the determined input data is stored using a key matching method.

[0061] Specifically, in step 1), the object strategy method adopts the following formula (1):

[0062] (1);

[0063] in, is the total data model of the object class, For item storage data, For item sorting data, the total item data model includes item storage data and item sorting data; is the amount of data for item storage data, The amount of data to sort the items; is the proportion of item storage data in the total data of the category, The proportion of item sorting data in the total data of the category; Strategies for storing data for items, Strategies for sorting data for items; Comparison of the strategy for item storage data and the strategy for item sorting data. is the comparison function between the strategy of item storage data and the strategy of item sorting data, The comparison result of the strategy for outputting the item storage data and the strategy for the item sorting data;

[0064] When the item storage data strategy Strategies that are larger than item sorting data hour, Output item storage data strategy, the input data is determined as item storage data;

[0065] When the item storage data strategy Strategy for sorting data smaller than items hour, Output item sorting data strategy, and the input data is determined as item sorting data.

[0066] In step 2), the object type denoising method uses the following formula (2):

[0067] (2);

[0068] in, is the total data packet of the category, For item storage data, Sorting data for items, is the denoising of the total data packet of the object class, is the noise reduction function, the noise reduction function Remove item storage data and item sorting data Other data other than

[0069] Store data for items Item sorting data The ratio of To store data for items Item sorting data The comparison function, To export item storage data Item sorting data The ratio of

[0070] To determine the total data packet type of the denoised object class or the data type of the denoised input, To determine the result of the input data type;

[0071] when When the value of is greater than 1, The data input after noise reduction is determined to be the item storage data; When the value of is less than 1, The data representing the input after noise reduction is determined as item sorting data.

[0072] The category strategy method or category noise reduction method uses the output item storage data in the category total data Item sorting data The capacity ratio between them has determined the main type of the total data of the entire category. In this way, it can be determined whether the input data is mainly item storage data or item sorting data. The main type of the total data of the entire category can be determined more accurately, and other data outside the main type can be filtered or excluded.

[0073] In step 3), the key matching method adopts the following formula (3):

[0074] (3);

[0075] in, , and Different verification codes are used respectively. To adjust the program model of the verification code sequence, For the verification code model, The role of making each verification code in the verification code model from top to bottom is , and Arrangement of

[0076] For the verification code matching model, , and They are different matching codes. The order of matching codes from top to bottom is: , and Fixed arrangement;

[0077] To match the verification code model to the verification code matching model, The result of key matching.

[0078] Step 3) is to adjust the program model of the verification code sequence Make each verification code in the verification code model from top to bottom , and The order of the matching codes in the verification code matching model from top to bottom is , and Fixed arrangement, by adjusting each verification code from top to bottom , and The order of the matching codes in the verification code matching model from top to bottom is , and The arrangement of , and Corresponding to each , and The data type determined by the first analysis module or the second analysis module can be transmitted to the data storage module through key matching, that is, the data storage module needs a verification code to accept the data determined by the first analysis module or the second analysis module.

[0079] In step 4), the actual running trajectory is tracked by a real-time tracking method, and points on the actual running trajectory are collected every one minute. If there is a difference between the actual running trajectory and the determined input data used for operation, the determined input data is adjusted.

[0080] In step 5), the actual operation of the determined input data is stopped.

[0081] Example 3

[0082] Based on Examples 1-2, in the present invention, the first analysis module adopts the class strategy method to determine the input data type or the second analysis module adopts the class noise reduction method to determine the input data type, the first analysis module or the second analysis module transmits the determined input data type to the data storage module, the data storage module transmits the determined input to the data operation module, the data operation module controls the operation device, the operation trajectory of the operation device is fed back to the data storage module, and the data storage module readjusts the determined input data in the data storage module.

[0083] The running track of the running device is collected by signals from various point sensors on the running device. If there is no collection signal from the point sensor at a certain point or multiple points, the running track needs to be adjusted. This is an existing technology and will not be described in detail here.

[0084] The present invention mainly determines whether the input data type is item storage data or item sorting data by using the item strategy method or the item noise reduction method, and then stores the determined input data by key matching. The stored data is used for actual operation. The item strategy method or the item noise reduction method both use the output item storage data in the total item data. Item sorting data The capacity ratio between the two has determined the main type of the total data of the entire category. In this way, it can be determined whether the input data is mainly item storage data or item sorting data. The main type of the total data of the entire category can be judged more accurately, and other data outside the main type can be filtered or excluded, which improves the accuracy of warehousing and sorting operations.

[0085] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope of the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An intelligent drug storage and sorting method based on smart pharmacy management, characterized in that: The steps include: Step 1): Analyze the input data; wherein, use the category strategy method to determine whether the input data type is item storage data or item sorting data; Step 2): Use the object type noise reduction method to analyze whether the input data is item storage data or item sorting data to determine the input data type; Step 3): The input data is stored by key matching; Step 4): extract the stored input data, perform actual operation on the input data, and track the actual operation trajectory; Step 5): End the operation.

2. According to claim 1, a smart drug storage and sorting method based on smart pharmacy management is characterized in that: In the step 1), the object strategy method adopts the following formula (1): (1)； in, is the total data model of the object class, For item storage data, For item sorting data, the total item data model includes item storage data and item sorting data; is the amount of data for item storage data, The amount of data to sort the items; is the proportion of item storage data in the total data of the category, The proportion of item sorting data in the total data of the category; Strategies for storing data for items, Strategies for sorting data for items; Comparison of the strategy for item storage data and the strategy for item sorting data. is the comparison function between the strategy of item storage data and the strategy of item sorting data, The comparison result of the strategy for outputting the item storage data and the strategy for the item sorting data; When the item storage data strategy Strategies that are larger than item sorting data hour, Output item storage data strategy, the input data is determined as item storage data; When the item storage data strategy Strategy for sorting data smaller than items hour, Output item sorting data strategy, the input data is determined as item sorting data.

3. According to claim 1, a smart drug storage and sorting method based on smart pharmacy management is characterized in that: In the step 2), the object type noise reduction method adopts the following formula (2): (2)； in, is the total data packet of the category, For item storage data, Sorting data for items, is the denoising of the total data packet of the object class, is the noise reduction function, the noise reduction function Remove item storage data and item sorting data Other data other than Store data for items Item sorting data The ratio of To store data for items Item sorting data The comparison function, To export item storage data Item sorting data The ratio of To determine the total data packet type of the denoised object class or the data type of the denoised input, To determine the result of the input data type; when When the value of is greater than 1, The data input after noise reduction is determined to be the item storage data; When the value of is less than 1, The data representing the input after noise reduction is determined as item sorting data.

4. According to claim 1, a smart drug storage and sorting method based on smart pharmacy management is characterized in that: In step 3), the key matching method adopts the following formula (3): (3)； in, , and Different verification codes are used respectively. To adjust the program model of the verification code sequence, For the verification code model, The role of making each verification code in the verification code model from top to bottom is , and Arrangement of For the verification code matching model, , and They are different matching codes. The order of matching codes from top to bottom is: , and Fixed arrangement; To match the verification code model to the verification code matching model, The result of key matching.

5. According to claim 1, a smart drug storage and sorting method based on smart pharmacy management is characterized in that: In the step 4), the actual running track is tracked by a real-time tracking method, and points on the actual running track are collected every one minute.

6. The intelligent drug storage and sorting method based on smart pharmacy management according to claim 5 is characterized in that: If there is a difference between the actual operation trajectory and the determined input data for operation, the determined input data is adjusted.

7. The intelligent drug storage and sorting method based on smart pharmacy management according to claim 1 is characterized in that: In the step 5), the actual operation of the input data is stopped.

8. An intelligent drug storage and sorting system based on smart pharmacy management, characterized in that: Used to implement an intelligent drug warehousing and sorting method based on smart pharmacy management according to any one of claims 1 to 7, comprising: The first analysis module is used to determine the input data type by the object strategy method; A second analysis module is used to determine the data type of the input by a type denoising method; A data storage module, used for storing the input data; A data operation module, used for actually operating the input data, and the data operation module controls the operation device; A trajectory collection module, used for collecting the running trajectory of the running device, feeding back the running trajectory of the running device to the data storage module, and the data storage module re-adjusting the determined input data in the data storage module; The first analysis module or the second analysis module transmits the determined input data type to the data storage module, the data storage module transmits the determined input to the data operation module, the data operation module controls the operation device, the operation trajectory of the operation device is fed back to the data storage module, and the data storage module readjusts the determined input data in the data storage module.

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