An intelligent management platform and management method for consumables based on the Internet of Things

Abstract

The present invention discloses an intelligent management platform and method for consumables based on the Internet of Things, relates to the field of intelligent management of consumables, and is used to solve the problem that when consumables are about to expire, they cannot be flexibly called, resulting in waste of consumables. The platform collects the time from expiration to generate analysis information of the consumables, collects the difference value of the use efficiency of consumables, the similarity of medical functions, the difference in the specification size of consumables, and the safety deviation of the use of consumables, establishes a data analysis model, obtains a call evaluation coefficient, and compares and analyzes it with a preset adjustment threshold to obtain a comparison result, sorts the comparison result in sequence according to the marking label of the comparison result and the value of the call evaluation coefficient, determines the priority call of the consumables and the consumables that can be called, and substitutes the distance difference between the consumables and the corresponding remaining consumables and the inventory saturation of the consumables and the corresponding remaining consumables into fuzzy logic to determine the allocation plan of the consumables that can be called, improves resource utilization, and avoids resource waste of the consumables.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management of consumables, and more specifically, to an intelligent management platform and method for consumables based on the Internet of Things. Background Art

[0002] With the continuous development of information technology and medical equipment, medical institutions have an increasing demand for the management of various types of medical consumables. In particular, the Internet of Things technology embeds smart sensors in medical consumables and combines them with wireless networks to realize real-time collection and transmission of consumable information, so that the inventory, consumption and usage of consumables can be automatically uploaded to the management system, making it easier for medical staff and managers to understand the status of consumables in real time.

[0003] The prior art has the following deficiencies:

[0004] At present, the classification of low-value medical consumables is comprehensive and detailed, but lacks consideration of actual use effects, especially for consumables with small size differences and similar functions (such as low-value consumables such as medical masks, which usually have large reserves and frequent use efficiency). They are usually required to be used strictly in accordance with specific specifications. However, this management method results in the inability to flexibly call consumables when they are about to expire, even if the size and function are similar, resulting in waste of consumables and not conducive to the rational use of resources. Therefore, an intelligent management platform and management method for consumables based on the Internet of Things are proposed.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide an intelligent management platform and management method for consumables based on the Internet of Things, which solve the problems raised in the above-mentioned background technology by using different product inspection methods.

[0007] To achieve the above object, the present invention provides the following technical solution, a method for intelligent management of consumables based on the Internet of Things, comprising:

[0008] S1: Collect the time from expiration to generate analysis information of near-expiry consumables. For near-expiry low-value consumables, collect the characteristics of near-expiry consumables and the characteristics of near-expiry consumables replacement, including the difference in consumables use efficiency, medical function similarity, consumables specification size difference, and consumables use safety deviation;

[0009] S2: Obtain the difference in consumables use efficiency, medical function similarity, consumables size difference, and consumables safety deviation, establish a data analysis model, and obtain the call evaluation coefficient;

[0010] S3: Obtain the call evaluation coefficient, and compare and analyze it with the preset adjustment threshold to obtain the comparison result, sort the comparison result in order according to the marking label and the call evaluation coefficient value, and determine the priority call of the expiring consumables and the expiring consumables that can be called;

[0011] S4: Obtain the available expiring consumables, obtain the distance difference between the expiring consumables and the corresponding remaining consumables, and the inventory saturation of the expiring consumables and the corresponding remaining consumables;

[0012] S5: The distance difference between the expiring consumables and the corresponding remaining consumables and the inventory saturation of the expiring consumables and the corresponding remaining consumables are brought into fuzzy logic to determine the allocation plan for the expiring consumables that can be called.

[0013] In a preferred embodiment, the production date and validity period of the consumables are extracted from the consumables label and added to obtain the expiration date, and then the current time is recorded as the reference time for judging the near-expiration status of the consumables, and the expiration date is subtracted from the current time to obtain the time left to expiration;

[0014] The time left to expiration is compared with the preset near-expiration threshold. If the time left to expiration is greater than or equal to the near-expiration threshold, the near-expiry consumables analysis information is generated. Otherwise, no changes are made and the system returns to the previous level.

[0015] In a preferred embodiment, after the analysis information of expiring consumables is generated, the characteristics of expiring consumables and the characteristics of replacement of expiring consumables are collected, the characteristics of expiring consumables include the difference value of consumables use efficiency; the characteristics of replacement of expiring consumables include the similarity of medical functions, the difference in consumables specifications and sizes, and the deviation in the safety of using consumables;

[0016] The difference in consumables usage efficiency is calculated by comparing the remaining consumables usage efficiency with the expiring consumables usage efficiency. ; Wherein, i is the i-th remaining consumable, i.e., the i-th expiring consumable and the remaining consumable;

[0017] The action position, action area and use environment are taken as key indicators, and the corresponding vector value is assigned to each key indicator. Then the cosine similarity is used to calculate the medical function similarity. ;

[0018] Subtract the size of the consumables that are about to expire from the size of the remaining consumables, and then calculate the difference in the size of the consumables that are about to expire by comparing them with the size of the consumables that are about to expire. ;

[0019] The material durability and protection capacity of the expiring consumables and the remaining consumables are weighted and calculated to obtain the safety of the expiring consumables and the remaining consumables, and the safety deviation of the used consumables is obtained by subtracting them. .

[0020] In a preferred embodiment, obtaining the difference value of consumables usage efficiency , Medical function similarity , poor specifications and dimensions of consumables And the use of consumables safety deviation , generating the call evaluation coefficient , according to the formula:

[0021] ;

[0022] In the formula, To call the evaluation coefficients, , , as well as are preset proportional coefficients for the difference in consumables use efficiency, medical function similarity, consumables size difference, and consumables safety deviation, respectively, and , , as well as Both are greater than 0.

[0023] In a preferred embodiment, after obtaining the call evaluation coefficient, the call evaluation coefficient is compared and analyzed with the continuously iterated call threshold;

[0024] If the call evaluation coefficient is greater than or equal to the call threshold, the current expiring consumable is marked as a callable consumable, and a call signal is generated;

[0025] If the call evaluation coefficient is less than the call threshold, the current expiring consumables are marked as non-callable consumables and an unchanged signal is generated.

[0026] In a preferred embodiment, the marking label of the comparison result includes a callable consumable;

[0027] The call evaluation coefficient values ​​corresponding to the callable consumable labels are counted, and the call evaluation coefficients corresponding to the callable consumable labels are sorted from large to small to obtain the arrangement order, and the maximum call evaluation coefficient is used as the priority call of the expiring consumables, and is divided into the corresponding remaining consumables;

[0028] Filter out the consumables that need to be called up first and determine the consumables that are about to expire and can be called up.

[0029] In a preferred embodiment, the actual position coordinates of the expiring consumables and the remaining consumables are collected through the positioning system in the Internet of Things, and the distance difference between the expiring consumables and the corresponding remaining consumables is obtained by calculating the Euclidean distance between the expiring consumables and the remaining consumables;

[0030] The ratio of the current inventory and the maximum capacity of the remaining consumables is calculated to obtain the inventory saturation of the expiring consumables and the corresponding remaining consumables.

[0031] In a preferred embodiment, the distance difference between the expiring consumables and the corresponding remaining consumables and the inventory saturation of the expiring consumables and the corresponding remaining consumables are defined as input variables and divided into different fuzzy sets respectively;

[0032] The allocation results of expired consumables that can be called are defined as output variables and divided into fuzzy sets;

[0033] Formulate fuzzy rules to describe the impact of the distance difference between expiring consumables and the corresponding remaining consumables and the inventory saturation of expiring consumables and the corresponding remaining consumables on the allocation results of expiring consumables that can be called;

[0034] Fuzzy reasoning is performed based on fuzzy rules to determine the allocation plan for expiring consumables that can be called upon.

[0035] An intelligent consumables management platform based on the Internet of Things includes a data collection framework, a data processing framework, a consumables analysis framework and a consumables calling framework;

[0036] The data collection framework is used to collect the time to expiration to generate analysis information on near-expiry consumables. For near-expiry low-value consumables, the near-expiry consumable characteristics and near-expiry consumable replacement characteristics are collected, including the difference in consumable use efficiency, medical function similarity, consumable specification size difference, and consumable use safety deviation, and send them to the data processing framework;

[0037] The data processing framework is used to obtain the difference value of consumables use efficiency, medical function similarity, consumables specification size difference and consumables use safety deviation, establish a data analysis model, obtain the call evaluation coefficient, and send it to the consumables analysis framework;

[0038] The consumables analysis framework is used to obtain the call evaluation coefficient and compare and analyze it with the preset adjustment threshold to obtain the comparison result, sort the comparison result in sequence according to the marking label and the call evaluation coefficient value, determine the priority call of the expiring consumables and the expiring consumables that can be called, and send the expiring consumables that can be called to the consumables call framework;

[0039] The consumables calling framework is used to obtain the expiring consumables that can be called, obtain the distance difference between the expiring consumables and the corresponding remaining consumables, and the inventory saturation of the expiring consumables and the corresponding remaining consumables, and introduce fuzzy logic to determine the allocation plan for the expiring consumables that can be called.

[0040] Technical effects and advantages of the present invention:

[0041] 1. The present invention generates analysis information on expiring consumables by collecting the time left to expiration, and collects the difference in consumables usage efficiency, medical function similarity, consumables specification size difference, and consumables safety deviation, establishes a data analysis model, obtains a call evaluation coefficient, and compares and analyzes it with a preset adjustment threshold to obtain a comparison result, and sorts the comparison results in sequence according to the marking labels of the comparison results and their call evaluation coefficient values, determines the priority call to expiring consumables and the expiring consumables that can be called, improves resource utilization and management efficiency, and avoids waste of resources caused by expiration of expiring consumables.

[0042] 2. The present invention obtains the expiring consumables that can be called, obtains the distance difference between the expiring consumables and the corresponding remaining consumables, and the inventory saturation of the expiring consumables and the corresponding remaining consumables, formulates a set of fuzzy rules for fuzzy reasoning, and determines the allocation plan for the expiring consumables that can be called, so that the expiring consumables can be called to the appropriate remaining consumables in time, optimizes storage management, avoids waste of resources, and reduces the management cost of consumables. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The present invention is a method flow chart of an intelligent consumables management method based on the Internet of Things.

[0044] Figure 2 This is a functional implementation diagram of an intelligent consumables management method based on the Internet of Things of the present invention.

[0045] Figure 3 The present invention is a framework schematic diagram of an intelligent consumables management platform based on the Internet of Things. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Example 1

[0048] See also Figure 1 to Figure 2 , an intelligent management method for consumables based on the Internet of Things, the specific operation process is as follows:

[0049] S1: Collect the time from expiration to generate analysis information of near-expiry consumables. For near-expiry low-value consumables, collect the characteristics of near-expiry consumables and the characteristics of near-expiry consumables replacement, including the difference in consumables use efficiency, medical function similarity, consumables specification size difference, and consumables use safety deviation;

[0050] The time to expiration refers to the time from the low-value consumables to expiration at the current time. Specifically, the longer the time to expiration is, the less likely the current low-value consumables are to expire.

[0051] The logic for obtaining the time to expiration is based on the production date and validity period of low-value consumables. Specifically, the production date and validity period of the consumables are extracted from the consumables label and added to get the expiration date. The current time is then recorded as the reference time for judging the near-expiration status of the consumables. The expiration date is subtracted from the current time to get the time to expiration.

[0052] It should be noted that the consumables label can be a REID label, a QR code, a barcode, etc. The specific application of the consumables label is not limited, but is set by the experimenter according to the specific consumables characteristics and the historical use of the label, which will not be elaborated here;

[0053] Compare the time left to expiration with the preset threshold value of near expiration. If the time left to expiration is greater than or equal to the threshold value of near expiration, generate the analysis information of near expiration consumables. Otherwise, do not make any changes and return to the previous level.

[0054] Among them, the threshold value of the critical period is set by the experimenters according to the actual application requirements and application conditions, and is not limited here;

[0055] After the analysis information of expiring consumables is generated, the characteristics of expiring consumables and the characteristics of replacement of expiring consumables are collected. The characteristics of expiring consumables include the difference value of consumables use efficiency; the characteristics of replacement of expiring consumables include the similarity of medical functions, the difference in consumables specifications and sizes, and the deviation in the safety of using consumables;

[0056] The difference in consumables usage efficiency refers to the difference in usage efficiency between expiring consumables and remaining consumables, which determines whether it is necessary to prioritize the use of expiring consumables. The acquisition logic is to calculate the total number of times the expiring consumables are used and the length of time the consumables are in stock, and then calculate the total number of times the remaining consumables are used and the length of time the consumables are in stock, and then calculate the remaining consumables. The efficiency difference is calculated by comparing the remaining consumables with the expiring consumables. ; Wherein, i is the i-th remaining consumable, i.e., the i-th expiring consumable and the remaining consumable;

[0057] It should be noted that the remaining consumables refer to other consumables of the same type as the expiring consumables. The specific type is consistent. For example, if the current expiring consumables refer to disposable masks, the remaining consumables refer to disposable masks of other sizes consistent therewith. Further, the remaining consumables are limited. For low-value consumables, when the size of the remaining consumables needs to be smaller than the size of the expiring consumables, the expiring consumables may be replaced. Therefore, for the selection of the remaining consumables, the remaining consumables whose size is larger than the expiring consumables are preferentially excluded, which will not be elaborated here.

[0058] Medical function similarity refers to the degree of functional similarity between expiring consumables and remaining consumables. Specifically, it is achieved by comparing the consistency of the key attributes of the two in terms of action position, action area, and use environment. The acquisition logic is to take the action position, action area, and use environment as key indicators, assign a corresponding vector value to each key indicator, and substitute it into the cosine similarity calculation to obtain the medical function similarity. ;

[0059] Specifically, the action position vector is the part covered or protected by the reaction consumables. For the protected parts, medical masks have many types of masks, such as common medical masks that only protect the mouth and nose, or professional medical masks that protect the eyes, mouth and nose, or anti-virus medical masks that protect the entire head, etc. For each protected part, a vector value is set, and the vector value of the common medical mask that protects the mouth and nose is , then the vector value of the professional medical mask that protects the eyes, mouth and nose is , then the antiviral medical mask that protects the entire head area is Etc. Specifically, the four vector standards are: mouth, nose, eyes, and ears, which are not limited here;

[0060] Specifically, the effective area vector refers to the protection range of the consumables, which is assigned according to the physical area. The specific physical area can be obtained by inferring the image taken by the sensor or the physical area information contained in the consumables label;

[0061] The use environment vector refers to the requirements for the use of consumables. For example, the experimenter can set the vector value to sterile environment (1), normal environment (0.5), special environment (0.8), etc., which will not be elaborated here;

[0062] Combine the action position, action area and use environment vector of each consumable into an overall function vector for cosine similarity calculation;

[0063] Among them, the function vector of expiring consumables , the function vector of the remaining consumables ; Substitute into the cosine similarity calculation:

[0064]

[0065] In the formula, is the medical function similarity, is the dot product of vectors, and are the modulus of the function vector of the expiring consumables and the function vector of the remaining consumables respectively;

[0066] The consumables size difference refers to the difference in physical size between two consumables, which quantifies the size matching degree between the expiring consumables and the remaining consumables. The acquisition logic is to subtract the size of the expiring consumables from the size of the remaining consumables, and then calculate the ratio with the size of the expiring consumables to get the consumables size difference. ;

[0067] Specifically, the specifications and dimensions of the expiring consumables and the remaining consumables are obtained through the consumables labels, which will not be described in detail here;

[0068] The formula for obtaining the difference in consumables specifications is:

[0069]

[0070] In the formula, The size of the consumables is different. For the specifications and dimensions of expiring consumables, The specifications and dimensions of the remaining consumables;

[0071] The safety deviation of consumables refers to the difference in safety performance between expiring consumables and remaining consumables in actual use. Specifically, the safety deviation is calculated by analyzing the material durability and protection ability of the consumable labels. The acquisition logic is to weight the material durability and protection ability of expiring consumables and remaining consumables to obtain the safety of expiring consumables and remaining consumables, and then subtract them to obtain the safety deviation of consumables. ;

[0072] Among them, the material durability and protection ability are obtained by the experimenter through tensile strength test or chemical resistance test based on the material characteristics when setting the consumable label, and are not limited here;

[0073] S2: Obtain the difference in consumables use efficiency, medical function similarity, consumables size difference, and consumables safety deviation, establish a data analysis model, and obtain the call evaluation coefficient;

[0074] The data analysis model refers to a weighted analysis model, which generates a call evaluation coefficient through weighted calculation;

[0075] Obtain the difference value of consumables usage efficiency , Medical function similarity , poor specifications and dimensions of consumables And the use of consumables safety deviation , generating the call evaluation coefficient , according to the formula:

[0076]

[0077] In the formula, To call the evaluation coefficients, , , as well as are preset proportional coefficients for the difference in consumables use efficiency, medical function similarity, consumables size difference, and consumables safety deviation, respectively, and , , as well as All are greater than 0;

[0078] Among them, the difference in consumables use efficiency, medical function similarity, consumables size difference, and consumables safety deviation are all data-based manifestations that directly express the trend of the current call level of expired consumables;

[0079] It can be seen from the above formula that when the medical function similarity is greater, the medical function of the expiring consumables and the remaining consumables is closer, indicating that the expiring consumables can better meet the current needs, and the call evaluation coefficient is larger; conversely, the difference in the use efficiency of consumables, the difference in the size of consumables specifications, and the deviation in the safety of the consumables are greater, indicating that the expiring consumables have a large deviation in the use effect, specification matching or safety, and it is difficult to meet the current needs, and the call evaluation coefficient is smaller;

[0080] S3: Obtain the call evaluation coefficient, and compare and analyze it with the preset adjustment threshold to obtain the comparison result, sort the comparison result in order according to the marking label and the call evaluation coefficient value, and determine the priority call of the expiring consumables and the expiring consumables that can be called;

[0081] The logic for obtaining the call threshold is to collect the call sets of historical near-expiry consumables, divide the data set into training set and test set, set the evaluation index and clustering algorithm, and in each round of cross-validation, train the model on the training set and evaluate the model performance on the test set. Then, adjust the call threshold according to the performance of the validation set. Therefore, the call threshold is constantly updated.

[0082] In the present invention, clustering algorithm is a type of unsupervised learning algorithm used to divide data points in a data set into groups or clusters with similarities; a common one is K-means clustering, which divides the data points in a data set into K clusters so that the distance between the data point of each curve and the center point (centroid) of the cluster to which it belongs is minimized, and finally the effect of the adjusted call threshold is measured by the Euclidean distance, so as to set the call threshold;

[0083] After obtaining the call evaluation coefficient, compare and analyze the call evaluation coefficient with the continuously iterated call threshold;

[0084] If the call evaluation coefficient is greater than or equal to the call threshold, the current expiring consumable is marked as a callable consumable, and a call signal is generated;

[0085] If the call evaluation coefficient is less than the call threshold, the current expiring consumables are marked as non-callable consumables, and an unchanged signal is generated;

[0086] Wherein, the marking label of the comparison result includes callable consumables;

[0087] It should be noted that non-recallable consumables mean that the current expiring consumables cannot be transferred to this category, so they are not analyzed;

[0088] The call evaluation coefficient values ​​corresponding to the callable consumable labels are counted, and the call evaluation coefficients corresponding to the callable consumable labels are sorted from large to small to obtain the arrangement order, and the maximum call evaluation coefficient is used as the priority call of the expiring consumables, and is divided into the corresponding remaining consumables;

[0089] Screen out the consumables that are prioritized for use and determine the consumables that are about to expire and can be used;

[0090] It should be noted that the expiring consumables that can be called refer to the remaining consumables corresponding to the call evaluation coefficients corresponding to the remaining callable consumable labels after removing the maximum call evaluation coefficient; specifically, there are many types of remaining consumables, and the maximum value has the closest similarity and matching degree, so the corresponding remaining consumables are used as the call targets of the expiring consumables with priority;

[0091] For example, there are five categories of remaining consumables, namely A, B, C, D and E. Among them, the call evaluation coefficient of the expiring consumables corresponding to the remaining consumables of category A is the highest value. Then the expiring consumables are called as the priority expiring consumables by default and are called into the remaining consumables of category A. Then the remaining four categories of remaining consumables, namely B, C, D and E, are the expiring consumables that can be called.

[0092] The present invention generates analysis information of expiring consumables by collecting the time left to expiration, and collects the difference values ​​of consumables usage efficiency, medical function similarity, consumables specification size difference and consumables safety deviation, establishes a data analysis model, obtains a call evaluation coefficient, and compares and analyzes it with a preset adjustment threshold to obtain a comparison result, sorts the comparison result in sequence according to the marking labels of the comparison result and the value of the call evaluation coefficient, determines the priority call of expiring consumables and the expiring consumables that can be called, improves resource utilization and management efficiency, and avoids resource waste caused by the expiration of expiring consumables.

[0093] Example 2

[0094] In Example 1 of the present invention, an example is given to illustrate that the analysis information of expiring consumables is generated by collecting the time from expiration to expiration, and the difference value of the use efficiency of consumables, the similarity of medical functions, the difference in the size of consumables and the safety deviation of the use of consumables are collected, a data analysis model is established, a call evaluation coefficient is obtained, and a comparison analysis is performed with a preset adjustment threshold to obtain a comparison result, and the comparison result is sorted in sequence according to the marking label of the comparison result and the value of the call evaluation coefficient, and the operation strategy of preferentially calling expiring consumables and expiring consumables that can be called is determined; however, in Example 1, only the call of temporary consumables is analyzed and evaluated, and the specific calling method of the expiring consumables that can be called is not analyzed. Obviously, if the number of remaining consumables corresponding to the priority call of expiring consumables is short, all expiring consumables can be called to the remaining consumables, but in actual conditions, the expiring consumables that can be called cannot be uniformly divided into the remaining consumables corresponding to the priority call of expiring consumables, and there is a lack of a specific allocation plan, which results in the inability of the expiring consumables that can be called to be timely called to the appropriate remaining consumables, resulting in a waste of resources; in view of the above problems, Example 2 of the present invention is further refined;

[0095] S4: Obtain the available expiring consumables, obtain the distance difference between the expiring consumables and the corresponding remaining consumables, and the inventory saturation of the expiring consumables and the corresponding remaining consumables;

[0096] The distance difference between the expiring consumables and the corresponding remaining consumables is calculated based on the spatial positions of the two in the storage area. The acquisition logic is to collect the actual position coordinates of the expiring consumables and the remaining consumables through the positioning system in the Internet of Things, and calculate the Euclidean distance between the expiring consumables and the remaining consumables to obtain the distance difference between the expiring consumables and the corresponding remaining consumables;

[0097] Specifically, the Euclidean distance is obtained by the Euclidean distance, which is a prior art and will not be described in detail here;

[0098] The inventory saturation of expiring consumables and corresponding remaining consumables refers to the storage capacity of the remaining consumables storage area, reflecting the capacity utilization of the remaining consumables area. The acquisition logic is to calculate the ratio of the current inventory of the remaining consumables and the maximum capacity to obtain the inventory saturation of expiring consumables and corresponding remaining consumables;

[0099] Specifically, the current inventory refers to the inventory of the corresponding remaining consumables, and the maximum capacity value refers to the maximum capacity of the storage point of the corresponding remaining consumables, which will not be described in detail here;

[0100] S5: Bring the distance difference between the expiring consumables and the corresponding remaining consumables and the inventory saturation of the expiring consumables and the corresponding remaining consumables into fuzzy logic to determine the allocation plan for the expiring consumables that can be called;

[0101] For example, "Far", "Near", and "Moderate" are used to judge the distance difference between expiring consumables and the corresponding remaining consumables, and "High", "Low", and "Medium" are used to judge the inventory saturation between expiring consumables and the corresponding remaining consumables.

[0102] Formulate a set of fuzzy rules to describe the impact of different input variables on output variables. The definition of rules can be based on professional knowledge or obtained through data analysis and experiments. For example:

[0103] The distance difference between the expiring consumables and the corresponding remaining consumables is marked as X, the inventory saturation of the expiring consumables and the corresponding remaining consumables is marked as U, and the allocation results of the expiring consumables that can be called are marked as C_results;

[0104] Then we can define:

[0105] Rule 1: IF (X is High) AND (U is Far) THEN (C_results is Discourage)

[0106] Rule 2: IF (U is Low) AND (U is Near) THEN (C_results is Recommend) ...

[0107] Perform fuzzy reasoning based on fuzzy rules to determine the allocation plan for expired consumables that can be used;

[0108] It should be noted that the division of fuzzy sets can be adjusted according to actual conditions. For example, although this embodiment takes three fuzzy sets as an example, it can actually be divided into more than three sets to facilitate better accurate adjustment according to different similarities.

[0109] Furthermore, for the judgment of the distance difference between the expiring consumables and the corresponding remaining consumables and the high, medium and low stock saturation of the expiring consumables and the corresponding remaining consumables, the threshold can be set according to the actual situation for judgment. For example, when the distance difference between the expiring consumables and the corresponding remaining consumables exceeds 68%, it is marked as "Far", and when the stock saturation of the expiring consumables and the corresponding remaining consumables is higher than 60%, it is marked as "High", etc., which will not be elaborated here;

[0110] The present invention obtains the expiring consumables that can be called, obtains the distance difference between the expiring consumables and the corresponding remaining consumables, and the inventory saturation of the expiring consumables and the corresponding remaining consumables, formulates a set of fuzzy rules for fuzzy reasoning, and determines the allocation plan for the expiring consumables that can be called, so that the expiring consumables can be called to the appropriate remaining consumables in time, optimizes storage management, avoids waste of resources, and reduces the management cost of consumables.

[0111] Example 3

[0112] See also Figure 3 , an intelligent management platform for consumables based on the Internet of Things, including a data collection framework, a data processing framework, a consumables analysis framework, and a consumables calling framework;

[0113] The data collection framework is used to collect the time to expiration to generate analysis information on near-expiry consumables. For near-expiry low-value consumables, the near-expiry consumable characteristics and near-expiry consumable replacement characteristics are collected, including the difference in consumable use efficiency, medical function similarity, consumable specification size difference, and consumable use safety deviation, and send them to the data processing framework;

[0114] The data processing framework is used to obtain the difference value of consumables use efficiency, medical function similarity, consumables specification size difference and consumables use safety deviation, establish a data analysis model, obtain the call evaluation coefficient, and send it to the consumables analysis framework;

[0115] The consumables analysis framework is used to obtain the call evaluation coefficient and compare and analyze it with the preset adjustment threshold to obtain the comparison result, sort the comparison result in sequence according to the marking label and the call evaluation coefficient value, determine the priority call of the expiring consumables and the expiring consumables that can be called, and send the expiring consumables that can be called to the consumables call framework;

[0116] The consumables calling framework is used to obtain the expiring consumables that can be called, obtain the distance difference between the expiring consumables and the corresponding remaining consumables, and the inventory saturation of the expiring consumables and the corresponding remaining consumables, and introduce fuzzy logic to determine the allocation plan for the expiring consumables that can be called.

[0117] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0118] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0119] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0120] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0122] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0123] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0124] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0125] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0126] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent management method for consumables based on the Internet of Things, characterized in that: include: S1: Collect the time from expiration to generate analysis information of near-expiry consumables. For near-expiry low-value consumables, collect the characteristics of near-expiry consumables and the characteristics of near-expiry consumables replacement, including the difference in consumables use efficiency, medical function similarity, consumables specification size difference, and consumables use safety deviation; S2: Obtain the difference in consumables use efficiency, medical function similarity, consumables size difference, and consumables safety deviation, establish a data analysis model, and obtain the call evaluation coefficient; S3: Obtain the call evaluation coefficient, and compare and analyze it with the preset adjustment threshold to obtain the comparison result, sort the comparison result in order according to the marking label and the call evaluation coefficient value, and determine the priority call of the expiring consumables and the expiring consumables that can be called; S4: Obtain the available expiring consumables, obtain the distance difference between the expiring consumables and the corresponding remaining consumables, and the inventory saturation of the expiring consumables and the corresponding remaining consumables; S5: Bring the distance difference between the expiring consumables and the corresponding remaining consumables and the inventory saturation of the expiring consumables and the corresponding remaining consumables into fuzzy logic to determine the allocation plan for the expiring consumables that can be called; After the analysis information of expiring consumables is generated, the characteristics of expiring consumables and the characteristics of replacement of expiring consumables are collected. The characteristics of expiring consumables include the difference value of consumables use efficiency; the characteristics of replacement of expiring consumables include the similarity of medical functions, the difference in consumables specifications and sizes, and the deviation in the safety of using consumables; The difference in consumables usage efficiency is calculated by comparing the remaining consumables usage efficiency with the expiring consumables usage efficiency. ; Wherein, i is the i-th remaining consumable, i.e., the i-th expiring consumable and the remaining consumable; The action position, action area and use environment are taken as key indicators, and the corresponding vector value is assigned to each key indicator. Then the cosine similarity is used to calculate the medical function similarity. ; Subtract the size of the consumables that are about to expire from the size of the remaining consumables, and then calculate the difference in the size of the consumables that are about to expire by comparing them with the size of the consumables that are about to expire. ; The material durability and protection capacity of the expiring consumables and the remaining consumables are weighted and calculated to obtain the safety of the expiring consumables and the remaining consumables, and the safety deviation of the used consumables is obtained by subtracting them. ; Obtain the difference value of consumables usage efficiency , Medical function similarity , poor specifications and dimensions of consumables And the use of consumables safety deviation , generating the call evaluation coefficient , according to the formula: ； In the formula, To call the evaluation coefficients, , , as well as are preset proportional coefficients for the difference in consumables use efficiency, medical function similarity, consumables size difference, and consumables safety deviation, respectively, and , , as well as All are greater than 0; The actual position coordinates of the expiring consumables and the remaining consumables are collected through the positioning system in the Internet of Things, and the distance difference between the expiring consumables and the corresponding remaining consumables is obtained by calculating the Euclidean distance between the expiring consumables and the remaining consumables; The ratio of the current inventory of the remaining consumables to the maximum capacity is calculated to obtain the inventory saturation of the expiring consumables and the corresponding remaining consumables; The distance difference between the expiring consumables and the corresponding remaining consumables and the inventory saturation between the expiring consumables and the corresponding remaining consumables are defined as input variables and divided into different fuzzy sets respectively; The allocation results of expired consumables that can be called are defined as output variables and divided into fuzzy sets; Formulate fuzzy rules to describe the impact of the distance difference between expiring consumables and the corresponding remaining consumables and the inventory saturation of expiring consumables and the corresponding remaining consumables on the allocation results of expiring consumables that can be called; Fuzzy reasoning is performed based on fuzzy rules to determine the allocation plan for expiring consumables that can be called upon.

2. The method for intelligent management of consumables based on the Internet of Things according to claim 1, characterized in that: The production date and validity period of the consumables are extracted from the consumables label and added to get the expiration date, and then the current time is recorded as the reference time for judging the near-expiration status of the consumables. The expiration date is subtracted from the current time to get the time left to expiration; The time left to expiration is compared with the preset near-expiration threshold. If the time left to expiration is greater than or equal to the near-expiration threshold, the near-expiry consumables analysis information is generated. Otherwise, no changes are made and the system returns to the previous level.

3. The method for intelligent management of consumables based on the Internet of Things according to claim 1, characterized in that: After obtaining the call evaluation coefficient, compare and analyze the call evaluation coefficient with the continuously iterated call threshold; If the call evaluation coefficient is greater than or equal to the call threshold, the current expiring consumable is marked as a callable consumable, and a call signal is generated; If the call evaluation coefficient is less than the call threshold, the current expiring consumables are marked as non-callable consumables and an unchanged signal is generated.

4. The method for intelligent management of consumables based on the Internet of Things according to claim 3, characterized in that: The marking labels of the comparison results include callable consumables; The call evaluation coefficient values ​​corresponding to the callable consumable labels are counted, and the call evaluation coefficients corresponding to the callable consumable labels are sorted from large to small to obtain the arrangement order, and the maximum call evaluation coefficient is used as the priority call of the expiring consumables, and is divided into the corresponding remaining consumables; Filter out the consumables that need to be called up first and determine the consumables that are about to expire and can be called up.

5. An intelligent consumables management platform based on the Internet of Things, used to implement the intelligent consumables management method based on the Internet of Things according to any one of claims 1 to 4, characterized in that: Including data collection framework, data processing framework, consumables analysis framework and consumables calling framework; The data collection framework is used to collect the time to expiration to generate analysis information on near-expiry consumables. For near-expiry low-value consumables, the near-expiry consumable characteristics and near-expiry consumable replacement characteristics are collected, including the difference in consumable use efficiency, medical function similarity, consumable specification size difference, and consumable use safety deviation, and send them to the data processing framework; The data processing framework is used to obtain the difference value of consumables use efficiency, medical function similarity, consumables specification size difference and consumables use safety deviation, establish a data analysis model, obtain the call evaluation coefficient, and send it to the consumables analysis framework; The consumables analysis framework is used to obtain the call evaluation coefficient and compare and analyze it with the preset adjustment threshold to obtain the comparison result, sort the comparison result in sequence according to the marking label and the call evaluation coefficient value, determine the priority call of the expiring consumables and the expiring consumables that can be called, and send the expiring consumables that can be called to the consumables call framework; The consumables calling framework is used to obtain the expiring consumables that can be called, obtain the distance difference between the expiring consumables and the corresponding remaining consumables, and the inventory saturation of the expiring consumables and the corresponding remaining consumables, and introduce fuzzy logic to determine the allocation plan for the expiring consumables that can be called.

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