Medical material warehouse management method and system based on cloud computing and radio frequency identification

Abstract

The invention relates to the technical field of warehouse management, and discloses a medical material warehouse management method and system based on cloud computing and radio frequency identification, and the method comprises the steps: carrying out the signal dimension reduction projection of a radio frequency identification signal set read by a target warehouse, and obtaining a signal center; performing signal separation on the radio frequency identification signal set according to the signal center to obtain a separation signal, and calculating medical material data according to the separation signal; calculating material storage data and medical material prediction data of the target warehouse according to the medical material data; constructing a storage optimization function according to the material storage data and the material prediction data; and carrying out material area distribution by utilizing the storage optimization function to obtain a storage management strategy of the target warehouse. The medical material warehouse management efficiency and accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and in particular to a medical material warehouse management method and system based on cloud computing and radio frequency identification. Background Art

[0002] With the rapid development of the medical industry, the types and quantities of medical supplies are increasing. Traditional warehousing management methods can no longer meet the high requirements of modern medical institutions for material management. For example, traditional management methods often rely on manual work such as material entry and exit registration and inventory. The workload is large and the efficiency is low, which is prone to human errors and inaccurate data.

[0003] In recent years, some advanced technologies have begun to be applied to the storage management of medical supplies. Radio Frequency Identification (RFID) technology, as an automatic identification technology, uses wireless radio frequency to perform non-contact two-way data communication, which can achieve fast and accurate object identification and data collection. It has begun to be widely used in material storage. However, the large amount of data read by the RFID reader in the existing technology needs to be effectively processed and analyzed to provide decision support. However, the current RFID system has limited data processing capabilities, which leads to delayed inventory data updates and difficulty in real-time monitoring of material dynamics, resulting in inventory redundancy or shortages. Therefore, how to improve the efficiency and accuracy of medical material storage management has become an urgent problem to be solved. Summary of the invention

[0004] The present invention provides a medical supplies warehouse management method and system based on cloud computing and radio frequency identification, the main purpose of which is to solve the problem of poor efficiency and accuracy of medical supplies warehouse management.

[0005] To achieve the above objectives, the present invention provides a medical supplies storage management method based on cloud computing and radio frequency identification, comprising: Obtaining a set of radio frequency identification signals read by a target warehouse, and performing signal dimension reduction projection on the set of radio frequency identification signals to obtain a signal center; Performing signal separation on the radio frequency identification signal set according to the signal center to obtain separated signals, and calculating medical material data corresponding to the radio frequency identification signal set according to the separated signals; Calculating the material storage data and medical material forecast data of the target warehouse according to the medical material data; Constructing a storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data; The storage optimization function is used to allocate materials to the target warehouse to obtain a storage management strategy for the target warehouse.

[0006] Optionally, performing signal dimensionality reduction projection on the radio frequency identification signal set to obtain a signal center includes: Demodulating each signal in the radio frequency identification signal set to obtain a demodulated signal; Performing principal component dimensionality reduction according to the signal sampling points in the demodulated signal to obtain a signal projection direction; Performing signal projection on the demodulated signal according to the signal projection direction to obtain a projection signal point; The projection signal points are divided into intervals, and the signal center is calculated according to the result of the interval division.

[0007] Optionally, the performing signal separation on the radio frequency identification signal set according to the signal center to obtain separated signals includes: Calculating the Euclidean distance from each signal point in the RFID signal corresponding to the signal center to the signal center; Classifying the signal points according to the Euclidean distance to obtain classified signal points; A separation signal corresponding to the radio frequency identification signal is constructed according to the classification signal point.

[0008] Optionally, calculating the medical supplies data corresponding to the radio frequency identification signal set according to the separated signal includes: Decoding the separated signal to obtain a decoded signal; Performing phase jump modulation on the decoded signal to obtain a target signal; A signal identifier corresponding to the radio frequency identification signal set is identified according to the target signal, and medical material data is counted according to the signal identifier.

[0009] Optionally, the calculating the material storage data and the medical material forecast data of the target warehouse according to the medical material data includes: Classifying the medical supplies data to obtain category supplies data; Determine the material storage data according to the category material data, and extract the corresponding historical material data from a preset database; Constructing a category data feature according to the historical material data and the category material data; The prediction data of each category of material data is calculated according to the category data characteristics, and the medical material prediction data is determined according to the prediction data.

[0010] Optionally, constructing a category data feature according to the historical material data and the category material data includes: Constructing a periodic data sequence using a preset time span according to the historical material data and the category material data; Calculating a periodic data vector sequence of the periodic data sequence, and performing vector concatenation on the periodic data vector sequence to obtain a fused feature vector; Respectively obtain the data influencing factors corresponding to the periodic data sequence, and construct the influencing feature vectors of the data influencing factors; Normalizing and linearly transforming the influencing feature vector to obtain a standard vector of the influencing feature vector, and performing vector splicing according to the standard vector to obtain an influencing fusion vector; Performing feature fusion on the fused feature vector and the influence fusion vector to obtain category data features; The fusion feature vector and the influence fusion vector are fused by using the following formula: in, Represents the categorical data features, represents the activation function tanh, represents the fused feature vector, represents the influence fusion vector, represents the sigmoid activation function, Indicates the corresponding element multiplication sign.

[0011] Optionally, constructing a storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data includes: Obtaining basic material information of each category of material data in the material storage data; Constructing a material delivery time function and a storage stability function according to the basic material information; A storage optimization function corresponding to the target warehouse is constructed according to the material delivery time function and the storage stability function.

[0012] Optionally, constructing a material delivery time function and a storage stability function according to the material basic information includes: Use the following formula to construct the material delivery time function and storage stability function: in, It represents the material outbound time function. Indicates the target warehouse List, Indicates the total number of rows of shelves in the target warehouse, Indicates the target warehouse OK, Indicates the total number of rows of shelves in the target warehouse, Indicates Medical supplies of this type, Indicates the total number of categories of medical supplies, Indicates that from Ledi The time for the outbound shipment, represents the decision variable, in Medical supplies of this type are stored in Ledi 1 if yes, otherwise 0. Indicates Frequency of use of medical supplies; in, represents the storage stability function, Indicates the target warehouse List, Indicates the total number of rows of shelves in the target warehouse, Indicates the target warehouse OK, Indicates the total number of rows of shelves in the target warehouse, Indicates Medical supplies of this type, Indicates the total number of categories of medical supplies, No. The weight of medical supplies represents the decision variable, in Medical supplies of this type are stored in Ledi 1 if it is true, otherwise 0.

[0013] Optionally, the using the storage optimization function to allocate materials to the target warehouse includes: Initializing an initial particle population, and using the storage optimization function as an objective function to calculate an objective function value of each particle in the initial particle population; Update the velocity of the particle according to the objective function value to obtain the particle velocity; The velocity of the particle is updated using the following formula: in, Indicates The particle in The particle velocity at the update iteration, Indicates The particle in The corresponding preset weight value is , are the preset first impact factor and second impact factor respectively. , represents a random number in the interval (0, 1). Indicates The individual historical optimal particle position of each particle, Indicates The particle position of a particle at the current moment, represents the global optimal position of the particle; Iterate the particle population according to the particle velocity to obtain a target particle population; Calculating the objective function value corresponding to each target particle in the target particle population, and determining the storage location according to the objective function value corresponding to the target particle; Material areas are allocated according to the storage locations to obtain a storage management strategy for the target warehouse.

[0014] In order to solve the above problems, the present invention also provides a medical material storage management system based on cloud computing and radio frequency identification, the system comprising: A signal center calculation module is used to obtain the RFID signal set read by the target warehouse, perform signal dimension reduction projection on the RFID signal set, and obtain the signal center; a medical supplies data calculation module, configured to perform signal separation on the radio frequency identification signal set according to the signal center to obtain a separated signal, and calculate the medical supplies data corresponding to the radio frequency identification signal set according to the separated signal; A target warehouse data calculation module, used to calculate the material storage data and medical material forecast data of the target warehouse according to the medical material data; A storage optimization function construction module, used to construct a storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data; The warehouse management strategy generation module is used to use the warehouse optimization function to allocate materials to the target warehouse and obtain the warehouse management strategy of the target warehouse.

[0015] The embodiment of the present invention can perform signal separation on the conflicting signals in the RFID signal set by calculating the signal center of the RFID signal set, thereby improving the accuracy of subsequent signal tag calculation; calculate the medical supplies data according to the separated signals after separation, thereby improving the accuracy of the medical supplies data calculation; calculate the material storage data and medical supplies forecast data of the target warehouse according to the medical supplies data, and can comprehensively forecast the data in combination with historical data and influencing factors; then calculate the storage optimization function, allocate the material area according to the storage optimization function, and obtain the storage management strategy of the target warehouse, which can minimize the outbound time of medical supplies and ensure the safety of medical supplies storage, and effectively improve the efficiency and accuracy of medical supplies storage management. Therefore, the medical supplies storage management method and system based on cloud computing and RFID proposed by the present invention can solve the problem of poor efficiency and accuracy of medical supplies storage management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of a process of a medical supplies storage management method based on cloud computing and radio frequency identification provided by an embodiment of the present invention; Figure 2 A schematic diagram of a process for separating radio frequency identification signal sets according to an embodiment of the present invention; Figure 3 A schematic diagram of a process for calculating material storage data of a target warehouse and medical material forecast data provided by an embodiment of the present invention; Figure 4 A functional module diagram of a medical supplies storage management system based on cloud computing and radio frequency identification provided by one embodiment of the present invention.

[0017] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0018] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0019] The embodiment of the present application provides a medical supplies storage management method based on cloud computing and radio frequency identification. The execution subject of the medical supplies storage management method based on cloud computing and radio frequency identification includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided in the embodiment of the present application. In other words, the medical supplies storage management method based on cloud computing and radio frequency identification can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0020] Reference Figure 1 FIG. 1 is a flow chart of a medical material storage management method based on cloud computing and radio frequency identification according to an embodiment of the present invention. In this embodiment, the medical material storage management method based on cloud computing and radio frequency identification includes: S1. Obtain a set of radio frequency identification signals read by a target warehouse, perform signal dimension reduction projection on the set of radio frequency identification signals, and obtain a signal center.

[0021] In the embodiment of the present invention, the RFID signal set is a set of signals collected by the signal tags on the medical supplies read by the reader, but there may be a problem that one reader reads the signals on multiple tags at the same time, which is easy to cause information aliasing to form conflicting signals. Therefore, it is necessary to calculate the signal center to perform signal separation for clustering the RFID signal set and identify the information corresponding to each signal in the RFID signal set.

[0022] In the embodiment of the present invention, the step of performing signal dimensionality reduction projection on the RFID signal set to obtain the signal center includes: Demodulating each signal in the radio frequency identification signal set to obtain a demodulated signal; Performing principal component dimensionality reduction according to the signal sampling points in the demodulated signal to obtain a signal projection direction; Performing signal projection on the demodulated signal according to the signal projection direction to obtain a projection signal point; The projection signal points are divided into intervals, and the signal center is calculated according to the result of the interval division.

[0023] In the embodiment of the present invention, signal demodulation is to perform IQ modulation on the RFID signal set, wherein, during the IQ modulation process, the RFID signal set is divided into two signals, respectively called the in-phase component (I) and the orthogonal component (Q), and the two signals are respectively multiplied with two orthogonal carriers (usually cosine and sine waves) and then added to obtain a demodulated signal.

[0024] Furthermore, the demodulated signal point is composed of an I component and a Q component, and the signal point I component and Q component are used as data points to construct a data matrix, and then the signal sampling points in the demodulated signal are subjected to principal component dimensionality reduction to obtain eigenvalues, and the eigenvector corresponding to the maximum eigenvalue is used as the new signal projection direction, and then each sampling point is dot-producted with the signal projection direction to obtain the projected signal point after dimensionality reduction, which can reduce the dimension of the data while retaining the main features of the data.

[0025] Specifically, the projected signal points are divided into several finite and equally spaced intervals, and then the projected signal points in each interval are counted to draw a cluster diagram. Each local peak is the signal center of each cluster. The signal center can be used to separate the conflicting signals in the RFID signal concentration, thereby improving the accuracy of subsequent signal label calculations.

[0026] S2. Perform signal separation on the radio frequency identification signal set according to the signal center to obtain separated signals, and calculate medical material data corresponding to the radio frequency identification signal set according to the separated signals.

[0027] In the embodiment of the present invention, signal separation is to separate the signal points in the conflicting signals in the radio frequency identification signal set, and each cluster center needs to correspond to each signal tag state one by one to complete the signal separation.

[0028] For details, see Figure 2 As shown, the signal separation of the radio frequency identification signal set according to the signal center to obtain the separated signal includes: S21, calculating the Euclidean distance from each signal point in the RFID signal corresponding to the signal center to the signal center; S22, classifying the signal points according to the Euclidean distance to obtain classified signal points; S23: construct a separation signal corresponding to the radio frequency identification signal according to the classification signal point.

[0029] In detail, after signal demodulation, the signal center corresponding to the conflicting signal is Among them, is the number of signals contained in the conflict signal. For example, the conflict signal generated by two tag signals has four signal centers. Then, each signal point is assigned to the corresponding cluster center according to the distance, and then the preset signal attenuation complex coefficient is used for corresponding classification to obtain the classified signal points, and then the separation signal is constructed.

[0030] Specifically, each signal label has a corresponding attenuation complex coefficient, and each signal label contains a segment of the same known signal for identification, so that the signal points corresponding to different signal centers can be matched to obtain classified signal points corresponding to different label signals.

[0031] In an embodiment of the present invention, the step of calculating the medical material data corresponding to the radio frequency identification signal set according to the separated signal includes: Decoding the separated signal to obtain a decoded signal; Performing phase jump modulation on the decoded signal to obtain a target signal; A signal identifier corresponding to the radio frequency identification signal set is identified according to the target signal, and medical material data is counted according to the signal identifier.

[0032] In the embodiment of the present invention, signal decoding is to decode the separated signal using a matched filter. When the signal is transmitted through a channel and may be interfered by noise, the matched filter can help extract the information of the original signal from the noise, thereby improving the signal-to-noise ratio of the separated signal.

[0033] In detail, the matched filter uses the conjugate image of the separated signal as an impulse response, performs a convolution operation on the impulse response and the separated signal, and obtains a decoded signal.

[0034] Specifically, the signal identifier is the detailed information of the material, including name, specifications, etc., and then it can be identified as medical supplies such as syringes, infusion sets, dressings or other tissue items and medical equipment, and the medical supplies corresponding to each signal can be obtained, and the number of materials of the same category can be counted to obtain medical supply data.

[0035] Furthermore, phase jump modulation is to change the phase of the signal by the phase jump principle to transmit information. The original information needs to be restored according to the phase jump pattern. For example, in the RF signal coding scheme, a specific phase jump pattern corresponds to a specific bit sequence. When decoding, the transmitted signal is determined by detecting these phase jump patterns. Therefore, the signal identifier corresponding to the target signal can be identified, and the material data of different categories can be counted by the signal identifier to obtain medical material data.

[0036] In the embodiment of the present invention, by separating the signals and calculating the medical supplies data corresponding to the radio frequency identification signal set, it is possible to avoid recognition errors caused by conflicting signals, thereby effectively improving the accuracy of the calculation of the medical supplies data.

[0037] S3. Calculate the material storage data and medical material forecast data of the target warehouse according to the medical material data.

[0038] In the embodiment of the present invention, the material storage data is the data of different categories of materials that have been stored in the target warehouse, including the materials to be stored in the medical material data and the material data that have been stored in the target warehouse, including the quantity and the storage area in the target warehouse, etc. The medical material forecast data is the data of medical materials that may be stored in the warehouse in the future.

[0039] In the embodiment of the present invention, refer to Figure 3 As shown, the calculation of the material storage data and the medical material forecast data of the target warehouse according to the medical material data includes: S31, classifying the medical supplies data to obtain category supplies data; S32, determining material storage data according to the category material data, and extracting corresponding historical material data from a preset database; S33, constructing category data features according to the historical material data and the category material data; S34. Calculate prediction data of each category of material data according to the category data characteristics, and determine medical material prediction data according to the prediction data.

[0040] In an embodiment of the present invention, the medical supplies are classified according to their categories, and the material storage data of each category of medical supplies in the target warehouse are extracted using a preset database, wherein the database is a data storage medium for recording the medical material data in the target warehouse, and the storage data of each medical supply in the target warehouse can be obtained through the database, including data stored in different time periods.

[0041] In detail, constructing the category data feature according to the historical material data and the category material data includes: Constructing a periodic data sequence using a preset time span according to the historical material data and the category material data; Calculating a periodic data vector sequence of the periodic data sequence, and performing vector concatenation on the periodic data vector sequence to obtain a fused feature vector; Respectively obtain the data influencing factors corresponding to the periodic data sequence, and construct the influencing feature vectors of the data influencing factors; Normalizing and linearly transforming the influencing feature vector to obtain a standard vector of the influencing feature vector, and performing vector splicing according to the standard vector to obtain an influencing fusion vector; The fused feature vector is fused with the influence fusion vector to obtain category data features.

[0042] Furthermore, the fusion feature vector and the influence fusion vector are fused by using the following formula: in, Represents the categorical data features, represents the activation function tanh, represents the fused feature vector, represents the influence fusion vector, represents the sigmoid activation function, Indicates the corresponding element multiplication sign.

[0043] In the embodiment of the present invention, the historical material data and the categorical material data are sorted according to the generation time, and then a periodic data sequence is constructed using a preset time span, and each periodic data in the periodic data sequence is converted into a data vector to obtain a periodic data vector sequence. For example, a periodic data sequence is constructed according to a weekly time span, a monthly periodic data sequence, or a quarterly periodic data sequence, etc., and the periodic data sequence reflects the demand for analog material data in different spans, so as to predict the material demand in a more detailed manner.

[0044] In the embodiment of the present invention, the data influencing factors are factors that affect the demand for medical supplies at different times, such as holidays, flu season, emergency medical rescue, etc. Under different data influencing factors, the demand for different medical supplies will be different, and the category material data will also be different. Therefore, by integrating the data influencing factors to construct the category data features of different medical supplies, the medical supply calculation data can be calculated more accurately.

[0045] In detail, the pre-built fully connected layer can be used to activate the category data features, map the category data features to the corresponding predicted demand vector space, obtain the probability corresponding to each predicted demand, select the maximum probability as the predicted data corresponding to each category of material data, and collect the predicted data corresponding to each category of material data to obtain medical material prediction data.

[0046] In the embodiment of the present invention, by comprehensively calculating the predicted data based on the data influencing factors and the different categories of material data, it is possible to comprehensively perform data prediction in combination with historical data and influencing factors, thereby improving the calculation accuracy of the medical material prediction data.

[0047] S4. Constructing a storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data.

[0048] In the embodiment of the present invention, since different medical supplies have different usage requirements and different material specifications, it is necessary to store the medical supplies scientifically and reasonably utilize the storage space of the target warehouse. For example, medical supplies with high usage frequency are placed near the exit, and medical supplies with low usage frequency are placed far from the exit; materials with large mass are placed on the lower layer, and materials with small mass are placed on the upper layer; large medical supplies are placed on the lower layer, and small medical supplies are placed on the upper layer; medical supplies with high correlation should be stored in adjacent positions as much as possible, etc., to improve the efficiency of medical supply storage.

[0049] In the embodiment of the present invention, the step of constructing a storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data includes: Obtaining basic material information of each category of material data in the material storage data; Constructing a material delivery time function and a storage stability function according to the basic material information; A storage optimization function corresponding to the target warehouse is constructed according to the material delivery time function and the storage stability function.

[0050] In the embodiment of the present invention, the basic material information is the medical material parameter information corresponding to different categories of material data, including weight, material specifications and size, and frequency of use of the medical materials.

[0051] In detail, the target warehouse may contain multiple layers and columns of shelves. Assuming that the ground floor is the first floor and the column closest to the exit is the first column, based on the principle of nearest shipment and accelerated turnover, the medical supplies handling time in each area of ​​the target warehouse is used to construct a material shipment time function.

[0052] Specifically, the material outbound time function is expressed as: in, It represents the material outbound time function. Indicates the target warehouse List, Indicates the total number of rows of shelves in the target warehouse, Indicates the target warehouse OK, Indicates the total number of rows of shelves in the target warehouse, Indicates Medical supplies of this type, Indicates the total number of categories of medical supplies, Indicates that from Ledi The time for the outbound shipment, represents the decision variable, in Medical supplies of this type are stored in Ledi 1 if yes, otherwise 0. Indicates Frequency of use of medical supplies.

[0053] Furthermore, according to the principle of light on top and heavy on the bottom, the storage stability function is expressed as the sum of the products of the mass of medical supplies on each shelf and the layer it is on.

[0054] Specifically, the storage stability function is expressed as: in, represents the storage stability function, Indicates the target warehouse List, Indicates the total number of rows of shelves in the target warehouse, Indicates the target warehouse OK, Indicates the total number of rows of shelves in the target warehouse, Indicates Medical supplies of this type, Indicates the total number of categories of medical supplies, No. The weight of medical supplies represents the decision variable, in Medical supplies of this type are stored in Ledi 1 if it is true, otherwise 0.

[0055] In the embodiment of the present invention, each material outbound time function and the storage stability function are weightedly summed to obtain the objective function, and an optimization function is constructed with the minimum value of the objective function as the optimization target to obtain a storage optimization function.

[0056] In the embodiment of the present invention, by comprehensively considering the basic information of medical supplies and the storage construction optimization function of the target warehouse, the storage of medical supplies can be optimized on the basis of minimizing the outbound delivery time and the safety of material storage, thereby improving the effect of medical supply storage.

[0057] S5. Use the storage optimization function to allocate material areas to the target warehouse to obtain a storage management strategy for the target warehouse.

[0058] In the embodiment of the present invention, the material area allocation is to calculate in which area of ​​the target warehouse each category of medical materials should be stored to maximize the use of the storage conditions of the target warehouse and ensure the maximum efficiency of the medical materials during storage and use.

[0059] In the embodiment of the present invention, the step of using the storage optimization function to allocate materials to the target warehouse includes: Initializing an initial particle population, and using the storage optimization function as an objective function to calculate an objective function value of each particle in the initial particle population; Update the velocity of the particle according to the objective function value to obtain the particle velocity; Iterate the particle population according to the particle velocity to obtain a target particle population; Calculating the objective function value corresponding to each target particle in the target particle population, and determining the storage location according to the objective function value corresponding to the target particle; Material areas are allocated according to the storage locations to obtain a storage management strategy for the target warehouse.

[0060] In the embodiment of the present invention, each particle in the initial particle population represents a different scenario of storing medical supplies in the target warehouse, and then the function corresponding to the storage optimization function corresponding to each particle can be calculated to obtain the objective function value.

[0061] Further, updating the velocity of the particle according to the objective function value to obtain the particle velocity includes: The velocity of the particle is updated using the following formula: in, Indicates The particle in The particle velocity at the update iteration, Indicates The particle in The corresponding preset weight value is , are the preset first impact factor and second impact factor respectively. , represents a random number in the interval (0, 1). Indicates The individual historical optimal particle position of each particle, Indicates The particle position of a particle at the current moment, represents the global optimal position of the particle.

[0062] Furthermore, the particle position of each particle is updated according to the particle speed to obtain an updated particle population, until the number of update iterations is greater than a preset threshold number, to obtain a target particle population, and the function value of the storage optimization function of each particle in the target particle population is calculated to obtain the target function value, so as to minimize the storage position of each medical supply corresponding to the particle corresponding to the target function value as the final storage position.

[0063] In detail, the storage space required for each category of medical supplies is calculated based on the basic information of each category of medical supplies as well as the material storage data and material forecast data. Then, the target warehouse is divided into areas according to the storage location to obtain the material areas corresponding to each category of medical supplies, and then the storage management strategy of the target warehouse is generated.

[0064] Preferably, since the medical supplies in the material forecast data have not been put into storage and the medical supplies in the target warehouse are in real time use, in actual applications the storage space may not need to meet the space required for all material storage data and material forecast data, further improving the utilization rate of the target warehouse.

[0065] In the embodiment of the present invention, by managing the medical supplies in the target warehouse through the warehouse management strategy, the outbound time of the medical supplies can be minimized and the safety of the storage of medical supplies can be ensured. Therefore, the efficiency and accuracy of the warehouse management of medical supplies can be effectively improved.

[0066] like Figure 4 , which is a functional module diagram of a medical supplies storage management system based on cloud computing and radio frequency identification provided by one embodiment of the present invention.

[0067] The medical material warehouse management system 400 based on cloud computing and radio frequency identification of the present invention can be installed in an electronic device. According to the functions implemented, the medical material warehouse management system 400 based on cloud computing and radio frequency identification can include a signal center calculation module 401, a medical material data calculation module 402, a target warehouse data calculation module 403, a warehouse optimization function construction module 404 and a warehouse management strategy generation module 405. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0068] In this embodiment, the functions of each module / unit are as follows: The signal center calculation module 401 is used to obtain the RFID signal set read by the target warehouse, perform signal dimension reduction projection on the RFID signal set, and obtain the signal center; The medical supplies data calculation module 402 is used to perform signal separation on the RFID signal set according to the signal center to obtain separated signals, and calculate the medical supplies data corresponding to the RFID signal set according to the separated signals; The target warehouse data calculation module 403 is used to calculate the material storage data and medical material prediction data of the target warehouse according to the medical material data; The storage optimization function construction module 404 is used to construct the storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data; The warehouse management strategy generation module 405 is used to use the warehouse optimization function to allocate materials to the target warehouse and obtain the warehouse management strategy of the target warehouse.

[0069] In detail, each module described in the medical material storage management system 400 based on cloud computing and radio frequency identification in the embodiment of the present invention is used in the same manner as described above. Figures 1 to 3 The same technical means are used as the medical supplies warehouse management method based on cloud computing and radio frequency identification described in, and can produce the same technical effects, so they will not be repeated here.

[0070] The present invention also provides an electronic device, which may include a processor, a memory, a communication bus and a communication interface, and may also include a computer program stored in the memory and executable on the processor, such as a medical supplies warehousing management method program based on cloud computing and radio frequency identification.

[0071] In some embodiments, the processor may be composed of an integrated circuit, for example, it may be composed of a single packaged integrated circuit, or it may be composed of multiple packaged integrated circuits with the same or different functions, including one or more central processing units (CPU), microprocessors, digital processing chips, graphics processors and a combination of various control chips.

[0072] The memory includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory may be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device.

[0073] The communication bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory and at least one processor, etc.

[0074] The communication interface is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display, an input unit (such as a keyboard), and optionally, the user interface may also be a standard wired interface or a wireless interface.

[0075] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0076] Specifically, the specific implementation method of the processor for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0077] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0078] The modules described as separate components may or may not be physically separated, and the components shown as modules 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 modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0080] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0081] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0082] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0083] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or systems stated in a system claim can also be implemented by one unit or system through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A medical supplies storage management method based on cloud computing and radio frequency identification, characterized in that: The method comprises: Obtaining a set of radio frequency identification signals read by a target warehouse, and performing signal dimension reduction projection on the set of radio frequency identification signals to obtain a signal center; Performing signal separation on the radio frequency identification signal set according to the signal center to obtain separated signals, and calculating medical material data corresponding to the radio frequency identification signal set according to the separated signals; Calculating the material storage data and medical material forecast data of the target warehouse according to the medical material data; Constructing a storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data; The storage optimization function is used to allocate material areas to the target warehouse to obtain a storage management strategy for the target warehouse.

2. The medical supplies storage management method based on cloud computing and radio frequency identification as claimed in claim 1, characterized in that: The performing signal dimension reduction projection on the radio frequency identification signal set to obtain a signal center includes: Demodulating each signal in the radio frequency identification signal set to obtain a demodulated signal; Performing principal component dimensionality reduction according to the signal sampling points in the demodulated signal to obtain a signal projection direction; Performing signal projection on the demodulated signal according to the signal projection direction to obtain a projection signal point; The projection signal points are divided into intervals, and the signal center is calculated according to the result of the interval division.

3. The medical supplies storage management method based on cloud computing and radio frequency identification as claimed in claim 1, characterized in that: The step of performing signal separation on the radio frequency identification signal set according to the signal center to obtain separated signals includes: Calculating the Euclidean distance from each signal point in the RFID signal corresponding to the signal center to the signal center; Classifying the signal points according to the Euclidean distance to obtain classified signal points; A separation signal corresponding to the radio frequency identification signal is constructed according to the classification signal point.

4. The medical supplies storage management method based on cloud computing and radio frequency identification as claimed in claim 1, characterized in that: The calculating the medical material data corresponding to the radio frequency identification signal set according to the separated signal comprises: Decoding the separated signal to obtain a decoded signal; Performing phase jump modulation on the decoded signal to obtain a target signal; A signal identifier corresponding to the radio frequency identification signal set is identified according to the target signal, and medical material data is counted according to the signal identifier.

5. The medical supplies storage management method based on cloud computing and radio frequency identification as claimed in claim 1, characterized in that: The calculating the material storage data and the medical material forecast data of the target warehouse according to the medical material data includes: Classifying the medical supplies data to obtain category supplies data; Determine the material storage data according to the category material data, and extract the corresponding historical material data from a preset database; Constructing a category data feature according to the historical material data and the category material data; The prediction data of each category of material data is calculated according to the category data characteristics, and the medical material prediction data is determined according to the prediction data.

6. The medical supplies storage management method based on cloud computing and radio frequency identification as claimed in claim 5, characterized in that: The constructing of category data features according to the historical material data and the category material data includes: Constructing a periodic data sequence using a preset time span according to the historical material data and the category material data; Calculating a periodic data vector sequence of the periodic data sequence, and performing vector concatenation on the periodic data vector sequence to obtain a fused feature vector; Respectively obtain the data influencing factors corresponding to the periodic data sequence, and construct the influencing feature vectors of the data influencing factors; Normalizing and linearly transforming the influencing feature vector to obtain a standard vector of the influencing feature vector, and performing vector splicing according to the standard vector to obtain an influencing fusion vector; Performing feature fusion on the fused feature vector and the influence fusion vector to obtain category data features; The fusion feature vector and the influence fusion vector are fused by using the following formula: in, Represents the categorical data features, represents the activation function tanh, represents the fused feature vector, represents the influence fusion vector, represents the sigmoid activation function, Indicates the corresponding element multiplication sign.

7. The medical supplies storage management method based on cloud computing and radio frequency identification as claimed in claim 1, characterized in that: The step of constructing a storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data includes: Obtaining basic material information of each category of material data in the material storage data; Constructing a material delivery time function and a storage stability function according to the basic material information; A storage optimization function corresponding to the target warehouse is constructed according to the material delivery time function and the storage stability function.

8. The medical supplies storage management method based on cloud computing and radio frequency identification as claimed in claim 7, characterized in that: The step of constructing a material delivery time function and a storage stability function according to the material basic information includes: Use the following formula to construct the material delivery time function and storage stability function: in, It represents the material outbound time function. Indicates the target warehouse List, Indicates the total number of rows of shelves in the target warehouse, Indicates the target warehouse OK, Indicates the total number of rows of shelves in the target warehouse, Indicates Medical supplies of this type, Indicates the total number of categories of medical supplies, Indicates that from Ledi The time for the outbound shipment, represents the decision variable, in Medical supplies of this type are stored in Ledi 1 if yes, otherwise 0. Indicates Frequency of use of medical supplies; in, represents the storage stability function, Indicates the target warehouse List, Indicates the total number of rows of shelves in the target warehouse, Indicates the target warehouse OK, Indicates the total number of rows of shelves in the target warehouse, Indicates Medical supplies of this type, Indicates the total number of categories of medical supplies, No. The weight of medical supplies represents the decision variable, in Medical supplies of this type are stored in Ledi 1 if it is true, otherwise 0.

9. The medical supplies storage management method based on cloud computing and radio frequency identification as claimed in claim 1, characterized in that: The using the storage optimization function to allocate materials to the target warehouse includes: Initializing an initial particle population, and using the storage optimization function as an objective function to calculate an objective function value of each particle in the initial particle population; Update the velocity of the particle according to the objective function value to obtain the particle velocity; The velocity of the particle is updated using the following formula: in, Indicates The particle in The particle velocity at the update iteration, Indicates The particle in The corresponding preset weight value is , are the preset first impact factor and second impact factor respectively. , represents a random number in the interval (0, 1). Indicates The individual historical optimal particle position of each particle, Indicates The particle position of a particle at the current moment, represents the global optimal position of the particle; Iterate the particle population according to the particle velocity to obtain a target particle population; Calculating the objective function value corresponding to each target particle in the target particle population, and determining the storage location according to the objective function value corresponding to the target particle; Material areas are allocated according to the storage locations to obtain a storage management strategy for the target warehouse.

10. A medical supplies storage management system based on cloud computing and radio frequency identification, characterized in that: The system comprises: A signal center calculation module is used to obtain the RFID signal set read by the target warehouse, perform signal dimension reduction projection on the RFID signal set, and obtain the signal center; a medical supplies data calculation module, configured to perform signal separation on the radio frequency identification signal set according to the signal center to obtain a separated signal, and calculate the medical supplies data corresponding to the radio frequency identification signal set according to the separated signal; A target warehouse data calculation module, used to calculate the material storage data and medical material forecast data of the target warehouse according to the medical material data; A storage optimization function construction module, used to construct a storage optimization function corresponding to the target warehouse according to the material storage data and the material forecast data; The warehouse management strategy generation module is used to use the warehouse optimization function to allocate materials to the target warehouse and obtain the warehouse management strategy of the target warehouse.

Images