Drug inventory supervision method and system based on artificial intelligence

Abstract

The invention provides a drug inventory supervision method and system based on artificial intelligence, relates to the technical field of drug inventory supervision based on artificial intelligence, and aims to obtain warehousing drug information, sequence information sorting, drug failure coefficient calculation, drug failure risk judgment and corresponding drug sorting. Obtaining warehouse-out time sequence information of the risk drugs; the method comprises the steps of obtaining dynamic update information of each medicine type, calculating a dynamic update coefficient, obtaining dynamic update feature information, carrying out feature update labeling, calculating a medicine vacancy coefficient to carry out vacancy labeling on the medicine types, and then supplementing vacant medicines. According to the technical scheme, inventory information is updated in real time, effective supervision of the medicine inventory is achieved, vacancy labeling and supplementing can be carried out in time according to the vacancy condition of the medicine, sufficient supply of the medicine is ensured, and the efficiency and accuracy of medicine inventory management are improved.

Description

Technical Field

[0001] The present invention proposes a drug inventory supervision method and system based on artificial intelligence, which relates to the technical field of inventory supervision, and specifically to the technical field of drug inventory supervision based on artificial intelligence. Background Art

[0002] Traditional drug inventory management mainly relies on manual operations, including the steps of drug warehousing, storage, outbound and inventory counting. This method has many shortcomings, such as low efficiency, high error rate, information lag, etc., especially in large medical institutions or drug warehouses, these problems are particularly prominent. When drugs are put into storage, the traditional manual management method often cannot quickly and accurately obtain detailed information about the drugs and perform effective partition storage, resulting in difficulty in locating drugs and low efficiency in finding and outbound. At the same time, due to the lack of real-time updated inventory information, it is difficult for managers to accurately grasp the inventory status of drugs, and thus cannot make timely replenishment decisions. During the storage process of drugs, due to the different shelf life and storage conditions of different drugs, it is difficult for traditional management methods to conduct compatible assessment and early warning of the outbound order and failure risk of drugs. Once the drugs are expired or about to expire, it will not only cause waste of drugs, but also pose a potential threat to the health of patients. Summary of the invention

[0003] The present invention provides a drug inventory supervision method and system based on artificial intelligence to solve the above problems: The present invention proposes a drug inventory supervision method and system based on artificial intelligence, and the supervision method includes: S1. Obtain the information of incoming drugs, perform partition storage, and then obtain the drug location information, associate the incoming drug information with the drug location information, and then sort the time sequence information to obtain the drug outgoing time sequence information; S2. Obtain the expiration date of the drug, calculate the drug expiration coefficient, determine the expiration risk of the drug, obtain the drug expiration coefficient of the drug with the expiration risk determination, sort the corresponding drugs, obtain the drug risk sorting, partially update the drug delivery time sequence information, and obtain the risk drug delivery time sequence information; S3. Obtain dynamic update information of each drug type, calculate a dynamic update coefficient, obtain dynamic update feature information, perform feature update annotation, and obtain feature update annotation information; S4. Obtain idle data on drug locations, calculate drug vacancy coefficients, mark vacancies in drug categories, and then supplement missing drugs.

[0004] Furthermore, the S1 includes: obtaining the information of the medicines in storage, and marking the information of the medicines by using the RFID method; Obtain drug category information of stored drug information, partition and store drugs according to preset drug category placement areas, and obtain drug location information; Performing a location code on the drug according to the drug location information, associating the drug storage information with the location code, and obtaining drug location association information; Sorting the drug location-related information of each drug category according to the drug entry time to obtain the drug entry time sequence information of each drug category; The drug delivery is sorted according to the drug category timing information to obtain the drug delivery timing information of each drug category.

[0005] Further, the S2 includes: Obtaining drug production cycle information of each drug of each drug category, and obtaining the drug expiration date based on the drug production cycle information; Calculate the drug expiration coefficient based on the drug expiration date combined with the drug delivery time sequence information; Comparing the drug failure coefficient with a preset failure threshold to obtain failure comparison information; Determine the failure risk of the drug according to the failure comparison information to obtain drug failure risk determination information; Obtaining a drug failure coefficient of a drug with failure risk determination according to drug failure risk determination information; According to the drug failure coefficient, the drugs with failure risk of each drug category are ranked to obtain the drug risk ranking; By ranking the drugs at risk, the drugs that are judged to have failure risks will be updated in the drug delivery sequence, thereby obtaining the risk drug delivery sequence information.

[0006] Further, the S3 includes: Obtain dynamic update information of drug categories based on drug outbound timing information and drug inbound information of each drug category; Calculating a dynamic update coefficient for each drug type according to the dynamic update information; Acquire a preset update characteristic range corresponding to the dynamic update coefficient, and determine the dynamic update characteristic information of the drug type according to the preset update characteristic range; Compare the dynamic update characteristic information with a preset update threshold to obtain an update comparison result; Acquire dynamically updated feature update information according to the update comparison result; The feature update annotation is dynamically updated according to the feature update information to obtain the feature update annotation information.

[0007] Further, the S4 includes: Obtaining idle drug location data according to the updated comparison result, and obtaining an idle drug location area according to the idle drug location data; Calculate the drug vacancy coefficient for each drug type based on the idle area data of drug locations; Comparing the drug vacancy coefficient with a preset vacancy threshold to obtain a vacancy update comparison result; The drug categories are marked for vacancies according to the vacancy update comparison results to obtain vacancy marking information.

[0008] Supplement the missing drugs according to the missing marking information and obtain supplementary data.

[0009] Furthermore, the supervision system includes: The association sorting module is used to obtain the information of incoming drugs, perform partition storage, and then obtain the drug location information, associate the incoming drug information with the drug location information, and then sort the time sequence information to obtain the drug outgoing time sequence information; The expiration ranking module is used to obtain the expiration date of the drug, calculate the drug expiration coefficient, determine the expiration risk of the drug, obtain the drug expiration coefficient of the drug with the expiration risk determination, sort the corresponding drugs, obtain the drug risk ranking, partially update the drug outbound timing information, and obtain the risk drug outbound timing information; A dynamic update module is used to obtain dynamic update information of each drug type, calculate a dynamic update coefficient, obtain dynamic update feature information, perform feature update annotation, and obtain feature update annotation information; The vacancy replenishment module is used to obtain idle data on drug locations, calculate drug vacancy coefficients, mark vacancies in drug categories, and then replenish missing drugs.

[0010] Furthermore, the association sorting module includes: The information labeling module is used to obtain the information of the medicines in the warehouse and label the medicines with information through the RFID method; The drug positioning module is used to obtain drug category information of the stored drug information, partition and store the drugs according to the preset drug category placement area, and obtain drug positioning information; A positioning association module, used to perform positioning coding on the drugs according to the drug positioning information, and associate the drug storage information with the positioning code to obtain drug positioning association information; The entry sorting module is used to sort the drug location related information of each drug type according to the drug entry time, and obtain the drug entry time sequence information of each drug type; The outbound sorting module is used to sort the outbound delivery of drugs according to the drug type timing information, and obtain the drug outbound delivery timing information of each drug type.

[0011] Furthermore, the failure sorting module includes: An information acquisition module, used to acquire drug production cycle information of each drug of each drug type, and acquire drug expiration date according to the drug production cycle information; An expiration calculation module, used to calculate a drug expiration coefficient according to the drug expiration date combined with drug delivery time sequence information; A failure comparison module, used to compare the failure coefficient of the drug with a preset failure threshold to obtain failure comparison information; A failure risk analysis module, used to determine the failure risk of the drug based on the failure comparison information, and obtain drug failure risk determination information; Obtaining a drug failure coefficient of a drug with failure risk determination according to drug failure risk determination information; The failure risk ranking module is used to rank the drugs with failure risk of each drug type according to the drug failure coefficient to obtain the drug risk ranking; The expiration ranking update module is used to update the drug ranking of drugs with expiration risk in the drug delivery sequence through drug risk ranking, and then obtain the risk drug delivery sequence information.

[0012] Furthermore, the dynamic update module includes: A dynamic update module, used to obtain dynamic update information of drug categories based on drug outbound timing information and drug inbound information of each drug category; An update calculation module, used to calculate a dynamic update coefficient for each drug type according to the dynamic update information; A feature update module, used to obtain a preset update feature range corresponding to the dynamic update coefficient, and determine the dynamic update feature information of the drug type according to the preset update feature range; An update comparison module, used to compare the dynamic update characteristic information with a preset update threshold to obtain an update comparison result; Acquire dynamically updated feature update information according to the update comparison result; The feature annotation module is used to perform dynamically updated feature update annotation according to the feature update information to obtain the feature update annotation information.

[0013] Furthermore, the vacancy supplement module includes: An idle acquisition module, used to acquire idle data of drug locations according to the update comparison result, and acquire idle areas of drug locations according to the idle data of drug locations; A vacancy calculation module is used to calculate the drug vacancy coefficient of each drug type based on the idle area data of the drug location; Comparing the drug vacancy coefficient with a preset vacancy threshold to obtain a vacancy update comparison result; The vacancy marking module is used to mark the vacancy of the drug category according to the vacancy update comparison result to obtain the vacancy marking information.

[0014] The supplement module is used to supplement the missing drugs according to the missing marking information and obtain the supplement data.

[0015] Beneficial effects of the present invention: Through automated and intelligent means, rapid acquisition and accurate processing of drug information are achieved, greatly improving the efficiency of inventory management. Through failure risk determination and priority outbound delivery strategies, the losses caused by expired drugs are effectively reduced and the inventory turnover rate is improved. By dynamically updating drug information and feature annotations, the system can more accurately predict future demand changes, thereby optimizing the inventory structure and reducing inventory backlogs and out-of-stock phenomena. Timely drug replenishment and accurate inventory management can ensure adequate supply of drugs and improve customer satisfaction and loyalty. Through intelligent inventory supervision, manual intervention and error rates are reduced, and operating costs and management difficulties are reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of a drug inventory monitoring method based on artificial intelligence; Figure 2 Schematic diagram of a drug inventory monitoring system based on artificial intelligence. DETAILED DESCRIPTION

[0017] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0018] In one embodiment of the present invention, a drug inventory supervision method and system based on artificial intelligence is proposed in the present invention, and the supervision method includes: S1. Obtain the information of incoming drugs, perform partition storage, and then obtain the drug location information, associate the incoming drug information with the drug location information, and then sort the time sequence information to obtain the drug outgoing time sequence information; S2. Obtain the expiration date of the drug, calculate the drug expiration coefficient, determine the expiration risk of the drug, obtain the drug expiration coefficient of the drug with the expiration risk determination, sort the corresponding drugs, obtain the drug risk sorting, partially update the drug delivery time sequence information, and obtain the risk drug delivery time sequence information; S3. Obtain dynamic update information of each drug type, calculate a dynamic update coefficient, obtain dynamic update feature information, perform feature update annotation, and obtain feature update annotation information; S4. Obtain idle data on drug locations, calculate drug vacancy coefficients, mark drug vacancies, and then supplement vacant drugs, such as Figure 1 shown.

[0019] The working principle of the above technical solution is as follows: when a drug enters the warehouse, first obtain detailed information of the drug, such as drug name, specification, batch number, quantity, etc., by scanning or other automated means. According to the storage conditions (such as temperature, humidity, light, etc.) and type of the drug, the drug is allocated to the corresponding storage area and its location information is recorded. The information of the drug entering the warehouse is associated with the drug location information to form a complete drug inventory database. According to the time sequence of the drug entering the warehouse, the time sequence information is sorted so that the subsequent outbound delivery is carried out according to the first-in-first-out principle. The expiration date of each drug is extracted from the drug information. The expiration coefficient of the drug is calculated based on the current date and the expiration date. This coefficient reflects the time urgency of the drug before it expires. The expiration risk of all drugs is determined, and the drugs are sorted according to the expiration coefficient to form the outbound timing information of risky drugs. Drugs close to the expiration date will be arranged to be outbound first to reduce inventory losses. Through regular or real-time data collection, dynamic update information such as sales and demand changes of each drug type is obtained. The dynamic update coefficient is calculated, which reflects the changing trend and speed of drug demand. Extract dynamically updated feature information, such as sales growth rate, demand stability, etc., and make feature update annotations so that the system can more accurately predict future drug demand. Calculate the drug vacancy coefficient by analyzing the idle drug location data, which reflects the shortage of a certain type of drug in the drug inventory. Mark the shortage of drug categories so that managers can notice these shortages in time. Arrange supplementary purchases of drugs based on the vacancy annotation information to ensure that the inventory level can meet future demand.

[0020] The technical effects of the above technical solutions are as follows: through automation and intelligent means, the rapid acquisition and accurate processing of drug information are realized, greatly improving the efficiency of inventory management. Through failure risk determination and priority outbound strategy, the losses caused by expired drugs are effectively reduced and the inventory turnover rate is improved. By dynamically updating drug information and feature annotations, the system can more accurately predict future demand changes, thereby optimizing the inventory structure and reducing inventory backlogs and out-of-stock phenomena. Timely drug replenishment and accurate inventory management can ensure adequate supply of drugs and improve customer satisfaction and loyalty. Through intelligent inventory supervision, manual intervention and error rates are reduced, and operating costs and management difficulties are reduced.

[0021] In one embodiment of the present invention, the S1 includes: Obtain the information of the medicines in the warehouse and mark the information of the medicines through RFID method; Obtain drug category information of stored drug information, partition and store drugs according to preset drug category placement areas, and obtain drug location information; Performing a location code on the drug according to the drug location information, associating the drug storage information with the location code, and obtaining drug location association information; Sorting the drug location-related information of each drug category according to the drug entry time to obtain the drug entry time sequence information of each drug category; The drug delivery is sorted according to the drug category timing information to obtain the drug delivery timing information of each drug category.

[0022] The working principle of the above technical solution is as follows: when the medicine is put into storage, the information of the medicine is marked using RFID (radio frequency identification) technology. The RFID tag contains detailed information of the medicine, such as the name of the medicine, specification, batch number, production date, expiration date, etc. The RFID reader reads the tag information and transmits the detailed information of the medicine to the inventory management system. According to the preset drug type placement area, the system classifies the received drug information and instructs the warehouse staff to place the medicine in the corresponding storage area. After the medicine is placed in the designated location, the system records the location information as the drug positioning information. The system generates a unique positioning code for each drug in the storage location, which is associated with the physical location of the drug. The drug entry information is associated with the positioning code to form drug location association information. In this way, the system can query the detailed information of any drug and its storage location at any time. The system records the entry time of each drug type and sorts the drug location association information of each drug type according to the entry time. The sorted information is the drug entry timing information of each drug type, which reflects the order of drug entry. According to the entry timing information of the drug type, the system can generate drug outbound sorting rules. The outbound sorting rules can be based on the first-in-first-out (FIFO) principle, or other factors such as the expiration date of the drug, demand priority, etc. According to the outbound sorting rules, the system generates the outbound timing information of each drug type and guides the warehouse staff to perform the outbound operation of the drug.

[0023] The technical effects of the above technical solution are as follows: RFID technology enables fast and accurate reading of drug information, reduces manual input errors, and improves the accuracy of inventory information. Through partition storage and positioning coding, the system can track the storage location and inventory status of drugs in real time, and optimize the inventory management process. According to the outbound sorting rules generated by the incoming timing information, the warehouse staff is guided to carry out drug outbound in the optimal order, which improves the outbound efficiency. The system can sort the outbound delivery of drugs according to their expiration dates, give priority to drugs that are close to their expiration dates, and reduce the losses caused by expired drugs. Accurate inventory information and efficient outbound delivery processes ensure the timely supply of drugs and improve customer satisfaction. Through automated and intelligent inventory management, manual intervention and error rates are reduced, and operating costs are reduced.

[0024] In one embodiment of the present invention, S2 includes: Obtaining drug production cycle information of each drug of each drug category, and obtaining the drug expiration date based on the drug production cycle information; Calculate the drug expiration coefficient based on the drug expiration date combined with the drug delivery time sequence information; The calculation formula of the drug failure coefficient is:

[0025] Among them, YSX is the drug failure coefficient, f is the function, T s is the expiration date of the drug, T d is the current date of the drug, T c is the drug release date, α is the adjustment coefficient (preset value) to reflect the relative importance of the production cycle to the failure risk assessment, and D is the production cycle (days).

[0026] Comparing the drug failure coefficient with a preset failure threshold to obtain failure comparison information; Determine the failure risk of the drug according to the failure comparison information to obtain drug failure risk determination information; Obtaining a drug failure coefficient of a drug with failure risk determination according to drug failure risk determination information; According to the drug failure coefficient, the drugs with failure risk of each drug category are ranked to obtain the drug risk ranking; Through the drug risk ranking, the drug ranking corresponding to the drugs with expiration risk judgment in the drug outbound timing sequence is updated, and then the risk drug outbound timing information is obtained. This means that only the ranking of the drugs with expiration risk judgment in the drug outbound timing information is updated according to the drug risk ranking. For example, in the drug outbound timing information of 1-10, the drugs 3, 5 and 7 have expiration risk judgments, and the drug rankings of 3, 5 and 7 are updated according to the drug risk rankings obtained from 3, 5 and 7, and then the updated drug outbound timing information obtained is the risk drug outbound timing information.

[0027] The working principle of the above technical solution is: obtain the production cycle information of each drug of each drug type, which usually includes the production start date, production end date and total time required for production. Based on the production cycle information and the expiration date of the drug (usually provided by the manufacturer), the system calculates the expiration date of each drug. The system compares the expiration date of each drug with its position in the drug outbound timing information (i.e., the expected outbound time). Calculate the expiration coefficient of each drug, which reflects the urgency of the drug to the expiration date. The system compares the calculated drug expiration coefficient with the preset expiration threshold. If the drug expiration coefficient exceeds the threshold, it is determined that the drug has an expiration risk, and generates drug expiration risk determination information. The system sorts all drugs with expiration risks according to the drug expiration coefficient, and generates drug risk ranking based on the original outbound sorting. It takes into account both the outbound cycle and the expiration risk; the sorting principle is that the drugs with higher expiration coefficients (i.e., greater expiration risks) in the original outbound sequence are ranked first. The system updates the ranking of drugs with expiration risk determination in the drug outbound timing information according to the drug risk sorting. The updated drug outbound timing information is the risk drug outbound timing information, which reflects the drug outbound order adjusted according to the risk of expiration. Warehouse staff perform drug outbound operations based on the risk drug outbound timing information, giving priority to outbound drugs with a higher risk of expiration.

[0028] The technical effect of the above technical solution is: by accurately calculating the drug expiration coefficient and updating the outbound timing information in real time, the system can give priority to outbound drugs that are close to the expiration date, thereby significantly reducing the losses caused by expired drugs. The system automatically handles the risk determination and outbound sorting of drugs, reducing manual intervention and error rates, and improving the efficiency and accuracy of inventory management. By updating the outbound timing information in real time, the system can ensure that the drugs are circulated to patients as soon as possible within the validity period, improving the utilization rate of drugs and patient satisfaction. Automated and intelligent inventory management reduces labor costs and error costs, and reduces overall operating costs. By giving priority to the outbound delivery of high-risk drugs, the system helps reduce the risk of expired drugs entering the market and enhances the safety of drug use. The system provides drug expiration risk determination information and risk drug outbound timing information.

[0029] In one embodiment of the present invention, S3 includes: Obtain dynamic update information of drug categories based on drug outbound timing information and drug inbound information of each drug category; Calculating a dynamic update coefficient for each drug type according to the dynamic update information; The calculation formula of dynamic update coefficient is:

[0030] Among them, DG is the dynamic update coefficient, y is the number of drugs in the drug category, T ci is the delivery time (days) of the ith drug of the drug category, T ri is the storage time (days) of the i-th drug of the drug category, ΔT g is the average time interval of continuous drug storage up to the current time, β is the adjustment coefficient used to avoid the situation where the denominator is zero or too small, and PYSX is the average value of all drug expiration coefficients of the drug type.

[0031] Acquire a preset update characteristic range corresponding to the dynamic update coefficient, and determine the dynamic update characteristic information of the drug type according to the preset update characteristic range; Compare the dynamic update characteristic information with a preset update threshold to obtain an update comparison result; Acquire dynamically updated feature update information according to the update comparison result; The feature update annotation is dynamically updated according to the feature update information to obtain the feature update annotation information.

[0032] The working principle of the above technical solution is: according to the drug outbound timing information and drug inbound information of each drug type, the dynamic update information of the drug type is calculated. Including key indicators such as drug outbound speed, inbound speed, inventory turnover rate, etc. The dynamic update coefficient of each drug type is calculated according to the dynamic update information. This coefficient reflects the dynamic characteristics of the drug type such as inventory status and demand changes. The system obtains the preset update feature range corresponding to the dynamic update coefficient. These ranges are used to represent the feature information corresponding to different dynamic update coefficients. According to the preset update feature range, the system determines the dynamic update feature information of each drug type, such as "high demand growth", "tight inventory", "stable demand", etc. The system compares the dynamic update feature information with the preset update thresholds. These thresholds are used to determine whether the dynamic update characteristics of the drug type have reached the level where certain measures need to be taken. According to the comparison results, the system obtains the dynamically updated feature update information, which reflects the inventory and demand change trends of the drug type in a specific time period. According to the feature update information, the system marks the dynamically updated feature updates of the drug type. These marking information are usually presented in the form of visual charts, text descriptions or alarms to remind managers to pay attention to the inventory and demand changes of specific drug types.

[0033] The technical effect of the above technical solution is: by acquiring and analyzing the dynamic update information of drug types in real time, the system can more accurately predict and evaluate the inventory demand of drugs, thereby improving the accuracy and efficiency of inventory management. Dynamic update of feature information and feature update annotations enable managers to adjust procurement plans in a timely manner according to the changing trend of drug demand to avoid inventory backlogs and out-of-stock phenomena. The system can monitor the dynamic changes of drug types in real time and issue alarms or reminders in time when necessary, so that managers can respond quickly and take corresponding measures to ensure the timely supply of drugs and patients' medication needs.

[0034] By optimizing inventory management and purchasing plans, the system helps reduce inventory backlogs, lower inventory costs, and avoid sales losses due to out-of-stocks, thereby reducing overall operating costs. Feature update annotations are usually presented in a visual form, allowing managers to intuitively understand the inventory and demand trends of drug types and improve the accuracy and efficiency of decision-making.

[0035] In one embodiment of the present invention, the S4 includes: Obtaining idle drug location data according to the updated comparison result, and obtaining an idle drug location area according to the idle drug location data; Calculate the drug vacancy coefficient for each drug type based on the idle area data of drug locations; The calculation formula of the drug vacancy coefficient is:

[0036] Among them, KQ y is the drug vacancy coefficient, A ku is the number of idle spaces in the area where the u-th drug is located, T z is the total number of spaces, N is the total number of drug types, W u The number of spaces required to store the u-th type of medicine.

[0037] Comparing the drug vacancy coefficient with a preset vacancy threshold to obtain a vacancy update comparison result; The drug categories are marked for vacancies according to the vacancy update comparison results to obtain vacancy marking information.

[0038] Supplement the missing drugs according to the missing marking information and obtain supplementary data.

[0039] The working principle of the above technical solution is: obtain drug information at various locations in the drug warehouse through sensors, RFID technology, manual input, etc., and compare this information with the latest inventory records to determine which drug locations are idle. These idle status data include location number, idle time, etc. According to the idle data of drug locations obtained in the previous step, determine which areas (such as shelves, warehouses) have idle drugs as a whole or in part. These areas may not need to store drugs temporarily due to uneven drug sales, storage strategy adjustments, etc. The system further analyzes the inventory of each drug category and calculates the drug vacancy coefficient of each drug category based on historical sales data, current inventory, expected demand, etc. This coefficient reflects the degree of inventory shortage of the drug category and is a dynamically changing indicator. The system compares the calculated drug vacancy coefficient with the preset vacancy threshold. According to the comparison result, the system marks the drug category as vacant. If the vacancy coefficient of a drug category exceeds the preset vacancy threshold, it is marked as a drug category that needs to be replenished and generates vacancy marking information. Finally, the system automatically generates or instructs warehouse managers to replenish the missing drugs based on the missing drug information, including determining the type, quantity, source, and time of replenishment.

[0040] The technical effects of the above technical solutions are: managing drug inventory in an automated and intelligent manner, reducing manual intervention and errors, and improving the accuracy and efficiency of inventory management. The system can track drug inventory in real time, promptly discover and replenish missing drugs, avoid drug shortages or backlogs, and optimize the allocation of drug resources. By ensuring the adequacy of drug inventory, the system can improve the availability of drugs, thereby meeting patients' medication needs and improving customer satisfaction. By reducing losses caused by inventory shortages and backlogs, the system can help warehouses reduce operating costs and improve overall economic benefits. The drug vacancy coefficient and vacancy marking information provided by the system can provide strong data support for warehouse managers, helping them to better formulate inventory management and replenishment strategies.

[0041] In one embodiment of the present invention, the supervision system comprises: The association sorting module is used to obtain the information of incoming drugs, perform partition storage, and then obtain the drug location information, associate the incoming drug information with the drug location information, and then sort the time sequence information to obtain the drug outgoing time sequence information; The expiration ranking module is used to obtain the expiration date of the drug, calculate the drug expiration coefficient, determine the expiration risk of the drug, obtain the drug expiration coefficient of the drug with the expiration risk determination, sort the corresponding drugs, obtain the drug risk ranking, partially update the drug outbound timing information, and obtain the risk drug outbound timing information; A dynamic update module is used to obtain dynamic update information of each drug type, calculate a dynamic update coefficient, obtain dynamic update feature information, perform feature update annotation, and obtain feature update annotation information; The vacancy supplement module is used to obtain idle drug location data, calculate the drug vacancy coefficient, mark the vacancy of drug categories, and then supplement the vacant drugs, such as Figure 1 shown.

[0042] The working principle of the above technical solution is as follows: when a drug enters the warehouse, first obtain detailed information of the drug, such as drug name, specification, batch number, quantity, etc., by scanning or other automated means. According to the storage conditions (such as temperature, humidity, light, etc.) and type of the drug, the drug is allocated to the corresponding storage area and its location information is recorded. The information of the drug entering the warehouse is associated with the drug location information to form a complete drug inventory database. According to the time sequence of the drug entering the warehouse, the time sequence information is sorted so that the subsequent outbound delivery is carried out according to the first-in-first-out principle. The expiration date of each drug is extracted from the drug information. The expiration coefficient of the drug is calculated based on the current date and the expiration date. This coefficient reflects the time urgency of the drug before it expires. The expiration risk of all drugs is determined, and the drugs are sorted according to the expiration coefficient to form the outbound timing information of risky drugs. Drugs close to the expiration date will be arranged to be outbound first to reduce inventory losses. Through regular or real-time data collection, dynamic update information such as sales and demand changes of each drug type is obtained. The dynamic update coefficient is calculated, which reflects the changing trend and speed of drug demand. Extract dynamically updated feature information, such as sales growth rate, demand stability, etc., and make feature update annotations so that the system can more accurately predict future drug demand. Calculate the drug vacancy coefficient by analyzing the idle drug location data, which reflects the shortage of a certain type of drug in the drug inventory. Mark the shortage of drug categories so that managers can notice these shortages in time. Arrange supplementary purchases of drugs based on the vacancy annotation information to ensure that the inventory level can meet future demand.

[0043] The technical effects of the above technical solutions are as follows: through automation and intelligent means, the rapid acquisition and accurate processing of drug information are realized, greatly improving the efficiency of inventory management. Through failure risk determination and priority outbound strategy, the losses caused by expired drugs are effectively reduced and the inventory turnover rate is improved. By dynamically updating drug information and feature annotations, the system can more accurately predict future demand changes, thereby optimizing the inventory structure and reducing inventory backlogs and out-of-stock phenomena. Timely drug replenishment and accurate inventory management can ensure adequate supply of drugs and improve customer satisfaction and loyalty. Through intelligent inventory supervision, manual intervention and error rates are reduced, and operating costs and management difficulties are reduced.

[0044] In one embodiment of the present invention, the association sorting module includes: The information labeling module is used to obtain the information of the medicines in the warehouse and label the medicines with information through the RFID method; The drug positioning module is used to obtain drug category information of the stored drug information, partition and store the drugs according to the preset drug category placement area, and obtain drug positioning information; A positioning association module, used to perform positioning coding on the drugs according to the drug positioning information, and associate the drug storage information with the positioning code to obtain drug positioning association information; The entry sorting module is used to sort the drug location related information of each drug type according to the drug entry time, and obtain the drug entry time sequence information of each drug type; The outbound sorting module is used to sort the outbound delivery of drugs according to the drug type timing information, and obtain the drug outbound delivery timing information of each drug type.

[0045] The working principle of the above technical solution is as follows: when the medicine is put into storage, the information of the medicine is marked using RFID (radio frequency identification) technology. The RFID tag contains detailed information of the medicine, such as the name of the medicine, specification, batch number, production date, expiration date, etc. The RFID reader reads the tag information and transmits the detailed information of the medicine to the inventory management system. According to the preset drug type placement area, the system classifies the received drug information and instructs the warehouse staff to place the medicine in the corresponding storage area. After the medicine is placed in the designated location, the system records the location information as the drug positioning information. The system generates a unique positioning code for each drug in the storage location, which is associated with the physical location of the drug. The drug entry information is associated with the positioning code to form drug location association information. In this way, the system can query the detailed information of any drug and its storage location at any time. The system records the entry time of each drug type and sorts the drug location association information of each drug type according to the entry time. The sorted information is the drug entry timing information of each drug type, which reflects the order of drug entry. According to the entry timing information of the drug type, the system can generate drug outbound sorting rules. The outbound sorting rules can be based on the first-in-first-out (FIFO) principle, or other factors such as the expiration date of the drug, demand priority, etc. According to the outbound sorting rules, the system generates the outbound timing information of each drug type and guides the warehouse staff to perform the outbound operation of the drug.

[0046] The technical effects of the above technical solution are as follows: RFID technology enables fast and accurate reading of drug information, reduces manual input errors, and improves the accuracy of inventory information. Through partition storage and positioning coding, the system can track the storage location and inventory status of drugs in real time, and optimize the inventory management process. According to the outbound sorting rules generated by the incoming timing information, the warehouse staff is guided to carry out drug outbound in the optimal order, which improves the outbound efficiency. The system can sort the outbound delivery of drugs according to their expiration dates, give priority to drugs that are close to their expiration dates, and reduce the losses caused by expired drugs. Accurate inventory information and efficient outbound delivery processes ensure the timely supply of drugs and improve customer satisfaction. Through automated and intelligent inventory management, manual intervention and error rates are reduced, and operating costs are reduced.

[0047] In one embodiment of the present invention, the failure sorting module includes: An information acquisition module, used to acquire drug production cycle information of each drug of each drug type, and acquire drug expiration date according to the drug production cycle information; An expiration calculation module, used to calculate a drug expiration coefficient according to the drug expiration date combined with drug delivery time sequence information; The calculation formula of the drug failure coefficient is:

[0048] Among them, YSX is the drug failure coefficient, f is the function, T s is the expiration date of the drug, T d is the current date of the drug, T c is the drug release date, α is the adjustment coefficient (preset value) to reflect the relative importance of the production cycle to the failure risk assessment, and D is the production cycle (days).

[0049] A failure comparison module, used to compare the failure coefficient of the drug with a preset failure threshold to obtain failure comparison information; A failure risk analysis module, used to determine the failure risk of the drug based on the failure comparison information, and obtain drug failure risk determination information; Obtaining a drug failure coefficient of a drug with failure risk determination according to drug failure risk determination information; The failure risk ranking module is used to rank the drugs with failure risk of each drug type according to the drug failure coefficient to obtain the drug risk ranking; The failure ranking update module is used to update the ranking of drugs corresponding to the failure risk judgment in the drug outbound timing sequence through drug risk ranking, and then obtain the risk drug outbound timing sequence information. It means that only the ranking of drugs with failure risk judgment in the drug outbound timing sequence information is updated according to the drug risk ranking. For example, in the drug outbound timing sequence information of 1-10, drugs 3, 5 and 7 have failure risk judgments, then the drug rankings of 3, 5 and 7 are updated according to the drug risk rankings obtained from 3, 5 and 7, and the updated drug outbound timing sequence information obtained is the risk drug outbound timing sequence information.

[0050] The working principle of the above technical solution is: obtain the production cycle information of each drug of each drug type, which usually includes the production start date, production end date and total time required for production. Based on the production cycle information and the expiration date of the drug (usually provided by the manufacturer), the system calculates the expiration date of each drug. The system compares the expiration date of each drug with its position in the drug outbound timing information (i.e., the expected outbound time). Calculate the expiration coefficient of each drug, which reflects the urgency of the drug to the expiration date. The system compares the calculated drug expiration coefficient with the preset expiration threshold. If the drug expiration coefficient exceeds the threshold, it is determined that the drug has an expiration risk, and generates drug expiration risk determination information. The system sorts all drugs with expiration risks according to the drug expiration coefficient, and generates drug risk ranking based on the original outbound sorting. It takes into account both the outbound cycle and the expiration risk; the sorting principle is that the drugs with higher expiration coefficients (i.e., greater expiration risks) in the original outbound sequence are ranked first. The system updates the ranking of drugs with expiration risk determination in the drug outbound timing information according to the drug risk sorting. The updated drug outbound timing information is the risk drug outbound timing information, which reflects the drug outbound order adjusted according to the risk of expiration. Warehouse staff perform drug outbound operations based on the risk drug outbound timing information, giving priority to outbound drugs with a higher risk of expiration.

[0051] The technical effect of the above technical solution is: by accurately calculating the drug expiration coefficient and updating the outbound timing information in real time, the system can give priority to outbound drugs that are close to the expiration date, thereby significantly reducing the losses caused by expired drugs. The system automatically handles the risk determination and outbound sorting of drugs, reducing manual intervention and error rates, and improving the efficiency and accuracy of inventory management. By updating the outbound timing information in real time, the system can ensure that the drugs are circulated to patients as soon as possible within the validity period, improving the utilization rate of drugs and patient satisfaction. Automated and intelligent inventory management reduces labor costs and error costs, and reduces overall operating costs. By giving priority to the outbound delivery of high-risk drugs, the system helps reduce the risk of expired drugs entering the market and enhances the safety of drug use. The system provides drug expiration risk determination information and risk drug outbound timing information.

[0052] In one embodiment of the present invention, the dynamic update module includes: A dynamic update module, used to obtain dynamic update information of drug categories based on drug outbound timing information and drug inbound information of each drug category; An update calculation module, used to calculate a dynamic update coefficient for each drug type according to the dynamic update information; The calculation formula of dynamic update coefficient is:

[0053] Among them, DG is the dynamic update coefficient, y is the number of drugs in the drug category, T ci is the delivery time (days) of the ith drug of the drug category, T ri is the storage time (days) of the i-th drug of the drug category, ΔT g is the average time interval of continuous drug storage up to the current time, β is the adjustment coefficient used to avoid the situation where the denominator is zero or too small, and PYSX is the average value of all drug expiration coefficients of the drug type.

[0054] A feature update module, used to obtain a preset update feature range corresponding to the dynamic update coefficient, and determine the dynamic update feature information of the drug type according to the preset update feature range; an update comparison module, used to compare the dynamic update feature information with a preset update threshold value to obtain an update comparison result; Acquire dynamically updated feature update information according to the update comparison result; The feature annotation module is used to perform dynamically updated feature update annotation according to the feature update information to obtain the feature update annotation information.

[0055] The working principle of the above technical solution is: according to the drug outbound timing information and drug inbound information of each drug type, the dynamic update information of the drug type is calculated, including key indicators such as drug outbound speed, inbound speed, inventory turnover rate, etc.

[0056] The dynamic update coefficient of each drug category is calculated based on the dynamic update information. This coefficient reflects the dynamic characteristics of the drug category, such as inventory status and demand changes. The system obtains the preset update characteristic range corresponding to the dynamic update coefficient. These ranges are used to represent the characteristic information corresponding to different dynamic update coefficients. Based on the preset update characteristic range, the system determines the dynamic update characteristic information of each drug category, such as "high demand growth", "tight inventory", "stable demand", etc. The system compares the dynamic update characteristic information with the preset update thresholds. These thresholds are used to determine whether the dynamic update characteristics of the drug category have reached the level that requires certain measures. Based on the comparison results, the system obtains the dynamically updated characteristic update information, which reflects the inventory and demand change trends of the drug category in a specific time period. Based on the characteristic update information, the system annotates the dynamically updated characteristic updates of the drug category. These annotated information are usually presented in the form of visual charts, text descriptions or alarms to remind managers to pay attention to the inventory and demand changes of specific drug categories.

[0057] The technical effect of the above technical solution is: by acquiring and analyzing the dynamic update information of drug types in real time, the system can more accurately predict and evaluate the inventory demand of drugs, thereby improving the accuracy and efficiency of inventory management. Dynamic update of feature information and feature update annotations enable managers to adjust procurement plans in a timely manner according to the changing trend of drug demand to avoid inventory backlogs and out-of-stock phenomena. The system can monitor the dynamic changes of drug types in real time and issue alarms or reminders in time when necessary, so that managers can respond quickly and take corresponding measures to ensure the timely supply of drugs and patients' medication needs.

[0058] By optimizing inventory management and purchasing plans, the system helps reduce inventory backlogs, lower inventory costs, and avoid sales losses due to out-of-stocks, thereby reducing overall operating costs. Feature update annotations are usually presented in a visual form, allowing managers to intuitively understand the inventory and demand trends of drug types and improve the accuracy and efficiency of decision-making.

[0059] In one embodiment of the present invention, the vacancy supplementation module comprises: An idle acquisition module, used to acquire idle data of drug locations according to the update comparison result, and acquire idle areas of drug locations according to the idle data of drug locations; A vacancy calculation module is used to calculate the drug vacancy coefficient of each drug type based on the idle area data of the drug location; The calculation formula of the drug vacancy coefficient is:

[0060] Among them, KQ y is the drug vacancy coefficient, Aku is the number of idle spaces in the area where the u-th drug is located, T z is the total number of spaces, N is the total number of drug types, W u The number of spaces required to store the u-th type of medicine.

[0061] Comparing the drug vacancy coefficient with a preset vacancy threshold to obtain a vacancy update comparison result; The vacancy marking module is used to mark the vacancy of the drug category according to the vacancy update comparison result to obtain the vacancy marking information.

[0062] The supplement module is used to supplement the missing drugs according to the missing marking information and obtain the supplement data.

[0063] The working principle of the above technical solution is: obtain drug information at various locations in the drug warehouse through sensors, RFID technology, manual input, etc., and compare this information with the latest inventory records to determine which drug locations are idle. These idle status data include location number, idle time, etc. According to the idle data of drug locations obtained in the previous step, determine which areas (such as shelves, warehouses) have idle drugs as a whole or in part. These areas may not need to store drugs temporarily due to uneven drug sales, storage strategy adjustments, etc. The system further analyzes the inventory of each drug category and calculates the drug vacancy coefficient of each drug category based on historical sales data, current inventory, expected demand, etc. This coefficient reflects the degree of inventory shortage of the drug category and is a dynamically changing indicator. The system compares the calculated drug vacancy coefficient with the preset vacancy threshold. According to the comparison result, the system marks the drug category as vacant. If the vacancy coefficient of a drug category exceeds the preset vacancy threshold, it is marked as a drug category that needs to be replenished and generates vacancy marking information. Finally, the system automatically generates or instructs warehouse managers to replenish the missing drugs based on the missing drug information, including determining the type, quantity, source, and time of replenishment.

[0064] The technical effects of the above technical solutions are: managing drug inventory in an automated and intelligent manner, reducing manual intervention and errors, and improving the accuracy and efficiency of inventory management. The system can track drug inventory in real time, promptly discover and replenish missing drugs, avoid drug shortages or backlogs, and optimize the allocation of drug resources. By ensuring the adequacy of drug inventory, the system can improve the availability of drugs, thereby meeting patients' medication needs and improving customer satisfaction. By reducing losses caused by inventory shortages and backlogs, the system can help warehouses reduce operating costs and improve overall economic benefits. The drug vacancy coefficient and vacancy marking information provided by the system can provide strong data support for warehouse managers, helping them to better formulate inventory management and replenishment strategies.

[0065] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A drug inventory supervision method based on artificial intelligence, characterized in that: The regulatory approaches include: S1. Obtain the information of incoming drugs, perform partition storage, and then obtain the drug location information, associate the incoming drug information with the drug location information, and then sort the time sequence information to obtain the drug outgoing time sequence information; S2. Obtain the expiration date of the drug, calculate the drug expiration coefficient, determine the expiration risk of the drug, obtain the drug expiration coefficient of the drug with the expiration risk determination, sort the corresponding drugs, obtain the drug risk sorting, partially update the drug outbound timing information, and obtain the risk drug outbound timing information; S3. Obtain dynamic update information of each drug type, calculate a dynamic update coefficient, obtain dynamic update feature information, perform feature update annotation, and obtain feature update annotation information; S4. Obtain idle data on drug locations, calculate drug vacancy coefficients, mark vacancies in drug categories, and then supplement missing drugs.

2. According to claim 1, a drug inventory supervision method based on artificial intelligence is characterized in that: The S1 includes: obtaining the information of the medicines in the warehouse and marking the information of the medicines by using the RFID method; Obtain drug category information of stored drug information, partition and store drugs according to preset drug category placement areas, and obtain drug location information; Performing a location code on the drug according to the drug location information, associating the drug storage information with the location code, and obtaining drug location association information; Sorting the drug location-related information of each drug category according to the drug entry time to obtain the drug entry time sequence information of each drug category; The drug delivery is sorted according to the drug category timing information to obtain the drug delivery timing information of each drug category.

3. According to the artificial intelligence-based drug inventory supervision method of claim 1, it is characterized in that: The S2 includes: Obtaining drug production cycle information of each drug of each drug category, and obtaining the drug expiration date based on the drug production cycle information; Calculate the drug expiration coefficient based on the drug expiration date combined with the drug delivery time sequence information; Comparing the drug failure coefficient with a preset failure threshold to obtain failure comparison information; Determine the failure risk of the drug according to the failure comparison information to obtain drug failure risk determination information; Obtaining a drug failure coefficient of a drug with failure risk determination according to drug failure risk determination information; According to the drug failure coefficient, the drugs with failure risk of each drug category are ranked to obtain the drug risk ranking; By ranking the drugs at risk, the drugs that are judged to have failure risks will be updated in the drug delivery sequence, thereby obtaining the risk drug delivery sequence information.

4. According to claim 1, a drug inventory supervision method based on artificial intelligence is characterized in that: The S3 includes: Obtain dynamic update information of drug categories based on drug outbound timing information and drug inbound information of each drug category; Calculating a dynamic update coefficient for each drug type according to the dynamic update information; Acquire a preset update characteristic range corresponding to the dynamic update coefficient, determine the dynamic update characteristic information of the drug type according to the preset update characteristic range; compare the dynamic update characteristic information with a preset update threshold value to obtain an update comparison result; Acquire dynamically updated feature update information according to the update comparison result; The feature update annotation is dynamically updated according to the feature update information to obtain the feature update annotation information.

5. According to claim 1, a drug inventory supervision method based on artificial intelligence is characterized in that: The S4 includes: Obtaining idle drug location data according to the updated comparison result, and obtaining an idle drug location area according to the idle drug location data; Calculate the drug vacancy coefficient for each drug type based on the idle area data of drug locations; Comparing the drug vacancy coefficient with a preset vacancy threshold to obtain a vacancy update comparison result; Marking the drug category for vacancies according to the vacancies update comparison result to obtain vacancies marking information; Supplement the missing drugs according to the missing marking information and obtain supplementary data.

6. An artificial intelligence-based drug inventory monitoring system, characterized in that: The regulatory system includes: The association sorting module is used to obtain the information of incoming drugs, perform partition storage, and then obtain the drug location information, associate the incoming drug information with the drug location information, and then sort the time sequence information to obtain the drug outgoing time sequence information; The expiration ranking module is used to obtain the expiration date of the drug, calculate the drug expiration coefficient, determine the expiration risk of the drug, obtain the drug expiration coefficient of the drug with the expiration risk determination, sort the corresponding drugs, obtain the drug risk ranking, partially update the drug outbound timing information, and obtain the risk drug outbound timing information; A dynamic update module is used to obtain dynamic update information of each drug type, calculate a dynamic update coefficient, obtain dynamic update feature information, perform feature update annotation, and obtain feature update annotation information; The vacancy replenishment module is used to obtain idle data on drug locations, calculate drug vacancy coefficients, mark vacancies in drug categories, and then replenish missing drugs.

7. According to claim 6, a drug inventory monitoring system based on artificial intelligence is characterized in that: The association sorting module comprises: The information labeling module is used to obtain the information of the medicines in the warehouse and label the medicines with information through the RFID method; The drug positioning module is used to obtain drug category information of the stored drug information, partition and store the drugs according to the preset drug category placement area, and obtain drug positioning information; A positioning association module, used to perform positioning coding on the drugs according to the drug positioning information, and associate the drug storage information with the positioning code to obtain drug positioning association information; The entry sorting module is used to sort the drug location related information of each drug type according to the drug entry time, and obtain the drug entry time sequence information of each drug type; The outbound sorting module is used to sort the outbound delivery of drugs according to the drug type timing information, and obtain the drug outbound delivery timing information of each drug type.

8. According to claim 6, the drug inventory monitoring system based on artificial intelligence is characterized in that: The failure sorting module comprises: An information acquisition module, used to acquire drug production cycle information of each drug of each drug type, and acquire drug expiration date according to the drug production cycle information; An expiration calculation module, used to calculate a drug expiration coefficient according to the drug expiration date combined with drug delivery time sequence information; A failure comparison module, used to compare the failure coefficient of the drug with a preset failure threshold to obtain failure comparison information; A failure risk analysis module, used to determine the failure risk of the drug based on the failure comparison information, and obtain drug failure risk determination information; Obtaining a drug failure coefficient of a drug with failure risk determination according to drug failure risk determination information; The failure risk ranking module is used to rank the drugs with failure risk of each drug type according to the drug failure coefficient to obtain the drug risk ranking; The expiration ranking update module is used to update the drug ranking of drugs with expiration risk in the drug delivery sequence through drug risk ranking, and then obtain the risk drug delivery sequence information.

9. According to claim 6, the drug inventory monitoring system based on artificial intelligence is characterized in that: The dynamic update module includes: A dynamic update module, used to obtain dynamic update information of drug categories based on drug outbound timing information and drug inbound information of each drug category; An update calculation module, used to calculate a dynamic update coefficient for each drug type according to the dynamic update information; A feature update module, used to obtain a preset update feature range corresponding to the dynamic update coefficient, and determine the dynamic update feature information of the drug type according to the preset update feature range; an update comparison module, used to compare the dynamic update feature information with a preset update threshold value to obtain an update comparison result; Acquire dynamically updated feature update information according to the update comparison result; The feature annotation module is used to perform dynamically updated feature update annotation according to the feature update information to obtain the feature update annotation information.

10. The drug inventory monitoring system based on artificial intelligence according to claim 6 is characterized in that: The vacancy supplementation module comprises: An idle acquisition module, used to acquire idle data of drug locations according to the update comparison result, and acquire idle areas of drug locations according to the idle data of drug locations; A vacancy calculation module is used to calculate the drug vacancy coefficient of each drug type based on the idle area data of the drug location; Comparing the drug vacancy coefficient with a preset vacancy threshold to obtain a vacancy update comparison result; A gap marking module, used to mark the gaps of drug categories according to the gap update comparison result, and obtain gap marking information; The supplement module is used to supplement the missing drugs according to the missing marking information and obtain the supplement data.

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