Medical fabric information input method and device

Abstract

The invention discloses a medical fabric information input method and device, and belongs to the field of medical fabric information management. In the application, the target image can be analyzed based on the image recognition algorithm, and the recommended fabric data of the batch of medical fabrics placed in the target area can be provided, so that an inexperienced operator can be prompted, and the error rate of information input is reduced. Meanwhile, the content of the corresponding field in the real fabric data of the batch of medical fabrics is generated based on the content of the corresponding field of the selected control, so that an operator only needs to select the corresponding control to complete information input if the recommended data is judged to be correct after verification, manual search or input is not needed, and the input efficiency is improved.

Description

A method and apparatus for inputting information on medical fabrics Technical Field

[0001] This invention belongs to the field of medical textile information management, and specifically relates to a method and apparatus for inputting medical textile information. Background Technology

[0002] To track the usage of medical textiles throughout their lifecycle, RFID (Radio Frequency Identification) tags, commonly known as "electronic tags," are sewn into each piece of medical textile. Each RFID tag has a unique number, which can be read contactlessly using an RFID reader or writer. This facilitates the tracking of washing, usage, and other information for each piece of medical textile throughout its lifecycle. When the RFID tags are first sewn into the medical textile, the electronic information management system does not yet have these unique numbers. Therefore, specialized personnel need to bind these unique numbers to the textile information (such as fabric type, which may include whether the textile belongs to a doctor's gown, nurse's uniform, or bed sheet) to ultimately input the medical textile information into the electronic information management system.

[0003] In related technologies, when entering medical fabric information into an electronic information management system, operators often need to visually identify the fabric information and then select from multiple options on the system's interface (e.g., multiple options are displayed, each corresponding to one of the fabric types, patterns, colors, etc.) to complete the information entry. This method of entering medical fabric information is time-consuming, leading to low efficiency, especially for inexperienced operators who need to manually judge the various fabric details. Summary of the Invention

[0004] The purpose of this invention is to solve at least one of the above problems by providing a method and apparatus for inputting medical fabric information, which can reduce the error rate of inputting fabric information and improve the efficiency of inputting fabric information.

[0005] To achieve the above-mentioned objective, the present invention provides a method for inputting information on medical fabrics, the method comprising:

[0006] Obtain the RFID tag numbers corresponding to a batch of medical fabrics located in the target area, as read by the reader;

[0007] Acquire target images of a batch of medical fabrics located in the target area, captured by imaging equipment;

[0008] The target image is analyzed based on an image recognition algorithm to determine the recommended fabric data for the batch of medical fabrics; wherein, the recommended fabric data consists of a preset number of fields, and the content of each field is used to identify a piece of recommended fabric information;

[0009] The software interface displays multiple controls that correspond one-to-one with each field of the recommended fabric data; each control displays the content of the corresponding field.

[0010] The system receives a user's selection operation on any one or more of the multiple controls, and generates the content of the corresponding field in the real fabric data of the batch of medical fabrics based on the content of the corresponding field of the selected control; wherein, the real fabric data consists of a preset number of fields, and each field is used to identify a piece of real fabric information;

[0011] When the preset conditions are met, the batch RFID tag number corresponding to the batch of medical fabrics and the actual fabric data of the batch of medical fabrics are bound together.

[0012] As a further improvement, a photoelectric sensor is disposed at the edge of the target area. The photoelectric sensor emits a first signal when it is unobstructed and emits a second signal when it is obstructed. The method further includes:

[0013] When the number of RFID tags read by the reader changes from zero to non-zero, the change in the signal emitted by the photoelectric sensor is monitored.

[0014] When the change in the signal emitted by the photoelectric sensor is detected as a change from the second signal to the first signal, the imaging device is triggered to acquire a target image of a batch of medical fabrics in the target area.

[0015] As a further improvement, the binding of the batch of RFID tag numbers corresponding to the batch of medical fabrics with the actual fabric data of the batch of medical fabrics specifically includes:

[0016] Write the batch of RFID tag numbers corresponding to the batch of medical fabrics and the actual fabric data of the batch of medical fabrics into the same target file;

[0017] The writing process includes: first, writing all the RFID tag numbers corresponding to the batch of medical fabrics into the target file, and then appending the actual fabric data of the batch of medical fabrics to the end of the target file to obtain the target file after writing.

[0018] As a further improvement, the method also includes:

[0019] Obtain the target length; wherein, the target length is the length of the batch RFID tag number corresponding to the Nth batch of medical fabrics in the target area read by the reader;

[0020] Based on the target length, set the target compression parameters corresponding to the Nth target file; where N is a positive integer, and the Nth target file is the target file obtained by binding the batch RFID tag number corresponding to the Nth batch of medical fabrics and the actual fabric data of the batch of medical fabrics; the target compression parameters include the target search buffer length and the target advance buffer length, both of which are equal to the target length;

[0021] The LZ77 compression algorithm corresponding to the target compression parameters is invoked to compress the Nth target file, resulting in the Nth target compressed package.

[0022] Send the Nth target compressed package to the server.

[0023] As a further improvement, the step of writing all the RFID tag numbers corresponding to the batch of medical fabrics into the target file specifically includes:

[0024] The batch of RFID tag numbers corresponding to the batch of medical fabrics are sorted according to a preset sorting rule; wherein, the preset sorting rule includes ascending order or descending order.

[0025] Based on the sorted order, the numbers of each RFID tag are written into the target file in sequence.

[0026] As a further improvement, the step of sorting the batch of RFID tag numbers corresponding to the batch of medical fabrics according to a preset sorting rule specifically includes:

[0027] Extract a preset segment of the RFID tag number corresponding to the batch of medical fabrics; wherein, the preset segment is the last few digits of the RFID tag number;

[0028] Based on the preset bit range, the RFID tag numbers corresponding to the batch of medical fabrics are sorted according to the preset sorting rules.

[0029] As a further improvement, TheThe LZ77 compression algorithm includes a compression process and a decompression process; the compression process includes:

[0030] Step 1: For the string in the window's lookahead buffer starting from the current compression position, search for the longest matching string in the window's search buffer. If found, proceed to Step 2; otherwise, proceed to Step 3.

[0031] Step 2: Output the tuple (len, c), then slide the window forward len+1 characters and jump to Step 1; where len is the length of the match and c is the next character of the longest match string in the lookahead buffer.

[0032] Step 3: Output the tuple (0, c), then slide the window back one character and jump to step 1;

[0033] The decompression process includes:

[0034] Step 4: Determine if the len field in the tuple (len, c) at the current decompression position in the compressed file is 0. If not, proceed to step 5; otherwise, proceed to step 6.

[0035] Step 5: Starting from the position in the search buffer of the window with an offset of -Q relative to the start position of the lookahead buffer, copy the target string of length len to the start position of the lookahead buffer of the window, and copy the c field to the position after the target string. Then slide the window forward len+1 characters, and move the decompression position in the compressed package to the next tuple, and jump to step 4; where Q is the length of the search buffer.

[0036] Step 6: Copy field c to the beginning of the window's lookahead buffer, slide the window back one character, move the decompression location in the compressed file to the next tuple, and jump to step 4.

[0037] As a further improvement, when the preset conditions are met, the batch RFID tag number corresponding to the batch of medical fabrics is bound to the actual fabric data of that batch of medical fabrics, specifically including:

[0038] When it is detected that the batch RFID tag number corresponding to the N+1th batch of medical fabrics does not have the same RFID tag number as the batch RFID tag number corresponding to the Nth batch of medical fabrics, the batch RFID tag number corresponding to the Nth batch of medical fabrics is bound to the actual fabric data of that batch of medical fabrics.

[0039] As a further improvement, the method also includes:

[0040] When it is detected that there is at least one identical RFID tag number between the batch number of the N+1th batch of medical fabrics and the batch number of the Nth batch of medical fabrics, the identical RFID tag number is taken as the target RFID tag number and removed from the batch number of the Nth batch of medical fabrics.

[0041] The batch of RFID tag numbers corresponding to the Nth batch of medical fabrics, after removing the target RFID tag number, are bound together with the actual fabric data of that batch of medical fabrics.

[0042] On the other hand, the present invention also provides a medical fabric information input device, the device including a camera, a photoelectric sensor, a reader, a memory, a processor, and a computer program stored in the memory, the processor executing the computer program to implement the steps of the above method.

[0043] Beneficial Effects: The medical fabric information input method and apparatus provided by this invention can analyze the target image based on an image recognition algorithm and provide recommended fabric data for a batch of medical fabrics placed in the target area. This allows inexperienced operators to receive prompts, reducing the error rate of information input. Furthermore, since the content of the corresponding field in the actual fabric data of the batch of medical fabrics is generated based on the content of the field corresponding to the selected control, if the operator verifies that the recommended data is correct, they only need to select the corresponding control to complete the information input, eliminating the need for manual searching or input, thus improving input efficiency. Attached Figure Description

[0044] To make the technical problems solved by this invention, the technical means adopted, and the technical effects achieved clearer, specific embodiments of this invention will be described in detail below with reference to the accompanying drawings. However, it should be noted that the drawings described below are merely drawings of exemplary embodiments of this invention. Those skilled in the art can obtain drawings of other embodiments based on these drawings without any creative effort.

[0045] Figure 1 is a schematic diagram of the application environment of the medical fabric information input method provided in an embodiment of the present invention;

[0046] Figure 2 is a schematic diagram of the structure of a medical fabric information input device provided in an embodiment of the present invention;

[0047] Figure 3 is a schematic diagram of the operation interface of the medical fabric information input device provided in an embodiment of the present invention;

[0048] Figure 4 is a schematic diagram of the principle of the triplet corresponding to the compressed batch of unsorted RFID tag numbers in Example 1.

[0049] Figure 5 is a schematic diagram of the principle of the triplet corresponding to the compressed batch of sorted RFID tag numbers in Example 1.

[0050] Figure 6 is a schematic diagram of the principle of the window's position before sliding in Embodiment 1;

[0051] Figure 7 is a schematic diagram of the principle of the position of the window after sliding in Embodiment 1;

[0052] Figure 8 is a flowchart illustrating a method for inputting medical fabric information according to an embodiment of the present invention;

[0053] Figure 9 is a flowchart illustrating a method for inputting medical fabric information according to an embodiment of the present invention.

[0054] Figure 10 is a flowchart illustrating a method for inputting medical fabric information according to an embodiment of the present invention;

[0055] Figure 11 is a schematic diagram of the principle of the binary tuples corresponding to the compressed numbers of a batch of unsorted RFID tags in Example 2;

[0056] Figure 12 is a schematic diagram of the principle of the binary tuples corresponding to the compressed numbers of a batch of sorted RFID tags in Example 2.

[0057] Figure 13 is a schematic diagram of the principle of the window's position before sliding in Embodiment 2;

[0058] Figure 14 is a schematic diagram of the position of the window after sliding in Example 2. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] Figure 1 is a schematic diagram of the application environment of a medical fabric information entry method provided in an embodiment of the present invention. The medical fabric information entry method provided in this embodiment is applied to a medical fabric information entry system, which includes a server 3 and a medical fabric information entry device that communicates with the server 3 via the Internet. The medical fabric information entry device includes a terminal 1 and an imaging device 12, a reader 14, a photoelectric sensor 13, and a touch screen 11 connected to the terminal 1. The terminal 1 includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the medical fabric information entry method provided in this embodiment of the present invention. The imaging device 12 can be a camera or a video camera, the reader 14 can be an RFID reader 14 or an RFID reader / writer, the photoelectric sensor 13 is a light curtain sensor, and the touch screen 11 can be a capacitive or resistive touch screen 11. Server 3 has a database installed, which is an SQL database in this example. Terminal 1 packages the RFID tag numbers of a batch of medical fabrics read by reader 14 together with the actual fabric data of the batch of medical fabrics selected by the user on touch screen 11 into a file and sends it to server 3 after compression. After receiving the compressed package, server 3 decompresses it and automatically enters the RFID tag numbers and actual fabric data of the batch of medical fabrics into the SQL database through a pre-set script.

[0061] In existing technologies, when entering medical fabric information into an electronic information management system, operators often need to visually identify the fabric information and then select from multiple selection buttons corresponding to different fabric types (e.g., multiple selection buttons are displayed on the interface, each corresponding to one of the fabric types, patterns, colors, etc.) on the system's interface before the information can be entered. This method of entering medical fabric information is time-consuming, as operators need to manually judge the various fabric information items. Inexperienced operators are prone to errors, leading to a high error rate. Furthermore, the process of selecting from multiple selection buttons corresponding to the fabric information of the current medical fabric is inefficient.

[0062] In response, embodiments of the present invention provide a method and apparatus for inputting medical fabric information, which can reduce the error rate of inputting fabric information and improve the efficiency of inputting fabric information.

[0063] The following will describe in detail the specific implementation of the medical fabric information entry method and device provided in this application through multiple embodiments and accompanying drawings.

[0064] As shown in Figure 2, one embodiment provides a medical fabric information input device. This device includes a camera, a light curtain sensor, an RFID reader 14, a memory, a processor, and a computer program stored in the memory. When the processor executes the computer program, it can analyze the target image based on an image recognition algorithm and provide recommended fabric data for a batch of medical fabrics placed in the target area. This provides guidance to inexperienced operators and reduces the error rate of information input. Simultaneously, since the content of the corresponding field in the actual fabric data of the batch of medical fabrics is generated based on the content of the field corresponding to the selected control, once the recommended data is verified as correct, the corresponding fabric information can be directly input by selecting the corresponding control. This eliminates the need for manual searching through a large amount of fabric information or manually inputting large amounts of information, thus improving input efficiency.

[0065] The medical fabric information input device provided in this embodiment also includes a main body. Specifically, as shown in Figure 2, the top surface of a hexahedral metal box 10 is removed, leaving the other five faces, thus forming the main body. The space inside the main body constitutes the target area mentioned above. Specifically, in this example, since the main body is formed by removing the top surface of the hexahedral metal box 10, the space inside the main body is hexahedral, so the target area is a hexahedral spatial area. It should be noted that if the top surface of a metal cylinder is removed to form the main body, the target area is a cylindrical spatial area. The range of the target area is constrained by the spatial shape of the main body, and this application does not limit the specific shape of the target area. The reader 14 is set on the bottom surface of the metal box 10. In use, the main body is placed on an operating table at a certain height from the ground. Medical fabrics that have not yet been entered into the main body are placed on a storage cart below the operating table or on the ground. The operator places each batch of medical fabrics (i.e., each bundle of medical fabrics) into the target area in batches to enter the medical fabric information. Since the reader 14 is located on the bottom surface of the metal housing 10, and the medical fabrics that have not yet been registered are placed on the storage cart under the operating table or on the ground, the shielding effect of the metal on radio frequency signals can be used to avoid interference from the medical fabrics that have not yet been registered with the reader 14 in reading RFID tags during the registration process. As shown in Figure 2, the imaging device 12 is located on the inner wall of the metal housing 10 and is in the target area, used to photograph the medical fabrics placed at the bottom of the metal housing 10. A light curtain sensor is installed at the opening at the top of the metal housing 10. The light curtain sensor is located outside the target area. When an object enters or exits the target area, the light curtain sensor will be triggered. The touch screen 11 is located outside the target area and is connected to the main body via a bracket. The touch screen 11 is used to display the software interface of the terminal 1, facilitating interactive operation by the operator.

[0066] As shown in Figure 8, an example provides a method for inputting medical fabric information, the method including:

[0067] In step S202, terminal 1 obtains the RFID tag numbers corresponding to a batch of medical fabrics in the target area, which are read by reader 14.

[0068] Specifically, communication between reader 14 and terminal 1 is established through the low-level reader protocol LLRP. Reader 14 reports to terminal 1 every time it reads a tag and notifies terminal 1 when the reading task is completed. Therefore, terminal 1 can know that reader 14 has completed the reading task.

[0069] Step S204: Terminal 1 acquires target images of a batch of medical fabrics in the target area collected by imaging device 12.

[0070] In some examples, the imaging device 12 acquires video by continuously recording the target area and then uses the video frames as the target image. In other examples, to save storage space required to store the video, the imaging device 12 takes a picture as the target image only after receiving a trigger signal. For example, when the terminal 1 receives the RFID tag number sent by the reader 14, it triggers the taking of a picture.

[0071] Step S206: Terminal 1 analyzes the target image based on an image recognition algorithm to determine the recommended fabric data of the batch of medical fabrics; wherein, the recommended fabric data consists of a preset number of fields, and the content of each field is used to identify a recommended fabric information.

[0072] In one example, the image recognition algorithm uses a neural network model. Specifically, this neural network model is trained using multiple sets of data through machine learning. Each set of data includes a photograph and a label identifying a batch of recommended fabric data for medical textiles in that photograph. For example, the recommended fabric data has three fields: product name, color, and material. Let's denote the product name as surgical gown (1), the color as green (2), and the material as polyester fiber (3). This results in a one-dimensional vector [1,2,3] representing the recommended fabric data for that batch of medical textiles. Therefore, during training, the label for that batch of medical textiles is a one-dimensional vector of three elements [1,2,3]. This process is repeated to obtain the labels for each batch of medical textiles, which are then used to train the neural network model. The output of the subsequently trained neural network model is also a one-dimensional vector of three elements. For example, if the one-dimensional vector output by the neural network model is [1,2,3], then the product name of that batch of medical textiles is surgical gown, the color is green, and the material is polyester fiber. The specific training process and the method of calling the trained neural network model are mature technologies in this field and will not be elaborated here. In another example, template matching can also be used to identify fabrics. The principle is to extract features from the input image, compare them one by one with features in a template library, and select the most similar template as the recognition result. Template matching is also a mature technology in this field and will not be elaborated upon here.

[0073] In step S208, terminal 1 displays multiple controls on the software interface that correspond one-to-one with each field of the recommended fabric data; each control displays the content of the corresponding field.

[0074] Step S210: Terminal 1 receives the user's selection operation on any one or more of the multiple controls, and generates the content of the corresponding field in the real fabric data of the batch of medical fabrics based on the content of the field corresponding to the selected control; wherein, the real fabric data consists of a preset number of fields, and each field is used to identify a piece of real fabric information.

[0075] As shown in Figure 3, in one example, the lower half of the software interface, area 22, is used to display recommended fabric data. For example, in this example, the recommended fabric data has four fields, and the content displayed on the control 22 corresponding to each field comes from the recognition results of the image recognition algorithm. Furthermore, the upper half of the software interface, area 21, is used to display actual fabric data. In this example, the actual fabric data is the same as the recommended fabric data, also having four fields. Each field corresponds to a drop-down list 24. The content displayed in the drop-down list 24 can be manually selected, or the operator can click the control 23 corresponding to the field in the lower half of the software interface, which will automatically input the content of that field into the drop-down list 24 corresponding to the corresponding field in the actual fabric data. For example, when an operator clicks the control corresponding to the product name in the lower half of the software interface (area 22), since the field content corresponding to the product name is "surgical gown," terminal 1 automatically extracts the three characters "surgical gown" and inputs them into the drop-down list 24 corresponding to the product name in the upper half of the software interface (area 21), thus selecting the "surgical gown" option in the drop-down list 24. In other words, in this embodiment, the content of the corresponding field in the actual fabric data of the batch of medical fabrics can be generated based on the content of the field corresponding to the selected control.

[0076] In step S212, when terminal 1 detects that the preset conditions are met, it binds the batch RFID tag number corresponding to the batch of medical fabrics and the actual fabric data of the batch of medical fabrics.

[0077] As shown in Figure 3, in one example, when the operator clicks the "Complete" button in the upper part 21 of the software interface, it is considered that the preset conditions are met. At this time, the batch RFID tag numbers corresponding to a batch of medical fabrics and the actual fabric data of that batch of medical fabrics are bound together. It should be noted that in this example, binding means associating two sets of data, that is, associating the batch RFID tag numbers corresponding to a batch of medical fabrics and the actual fabric data of that batch of medical fabrics. The association method can be to record the batch RFID tag numbers corresponding to a batch of medical fabrics and the actual fabric data of that batch of medical fabrics into a database. However, when the database is deployed on server 3, the batch RFID tag numbers corresponding to a batch of medical fabrics and the actual fabric data of that batch of medical fabrics need to be transmitted to server 3 first, and then server 3 records them into the database. In one example, when there is a network failure or offline operation, the batch RFID tag numbers corresponding to a batch of medical fabrics and the actual fabric data of that batch of medical fabrics can be written together into a file and saved to local storage to achieve binding.

[0078] In summary, this embodiment analyzes the target image based on an image recognition algorithm to provide recommended fabric data for a batch of medical fabrics to be placed in the target area. This provides guidance to inexperienced operators and reduces the error rate of data entry. Furthermore, since the content of the corresponding field in the actual fabric data of the batch of medical fabrics is generated based on the content of the field corresponding to the selected control, once the operator verifies that the recommended data is correct, they can directly enter the corresponding fabric information by selecting the corresponding control. This eliminates the need for manual searching through a large amount of fabric information or manually inputting large amounts of data, thus improving entry efficiency.

[0079] In one embodiment, the batch of RFID tag numbers corresponding to the batch of medical fabrics are bound to the actual fabric data of the batch of medical fabrics, specifically including:

[0080] Write the batch of RFID tag numbers corresponding to the batch of medical fabrics and the actual fabric data of the batch of medical fabrics into the same target file;

[0081] The writing process includes: first, writing all the RFID tag numbers corresponding to the batch of medical fabrics into the target file, and then appending the actual fabric data of the batch of medical fabrics to the end of the target file to obtain the target file after writing.

[0082] Specifically, in this example, during the writing process to the target file, only the RFID tag number and a single copy of the actual fabric data for the same batch of medical fabrics are stored. This eliminates the need to store a corresponding copy of the actual fabric data for each RFID tag number as in existing table-based storage methods, achieving a degree of compression and saving storage space. For example, if a batch contains 100 RFID tag numbers, the existing table-based storage method would require storing 100 corresponding copies of the actual fabric data. However, since the actual fabric data corresponding to each RFID tag number in this application is identical within the same target file, only one copy of the corresponding actual fabric data can be written to the target file, saving storage space.

[0083] As shown in Figure 9, in one embodiment, a photoelectric sensor 13 is disposed at the edge of the target area. The photoelectric sensor 13 emits a first signal when it is unobstructed and emits a second signal when it is obstructed. The method further includes:

[0084] In step S302, when terminal 1 detects that the number of RFID tags read by reader 14 changes from zero to non-zero, it monitors the change in the signal emitted by photoelectric sensor 13.

[0085] In step S304, when the change in the signal emitted by the photoelectric sensor 13 is detected as a change from the second signal to the first signal, the terminal 1 triggers the imaging device 12 to acquire target images of a batch of medical fabrics in the target area.

[0086] It should be noted that while reader 14 can identify RFID tags located within the target area, when an operator transports a batch of medical fabrics from outside the target area near the opening at the top of the metal housing 10, reader 14 may identify RFID tags outside the target area. In this case, terminal 1 detects that the number of RFID tags read by reader 14 changes from zero to non-zero. Therefore, when the number of RFID tags read by reader 14 changes from zero to non-zero, it indicates that the operator is placing a batch of medical fabrics into the target area. It is understood that the height of the metal housing 10 is greater than the maximum size of a batch of medical fabrics, allowing the batch of medical fabrics to be completely within the target area. Simultaneously, the height of imaging device 12 from the bottom of the target area is also greater than the maximum size of a batch of medical fabrics. When the user places a batch of medical fabrics into the target area, the medical fabrics and the operator's hand enter the target area, thus blocking the light curtain sensor. At this time, photoelectric sensor 13 is in a blocked state and emits a second signal. After a batch of medical fabrics is placed at the bottom of the metal box 10, the operator removes their hand from the target area, leaving the light curtain sensor unobstructed and emitting a first signal. That is, when terminal 1 detects a change in the signal emitted by photoelectric sensor 13 from a second signal to a first signal, terminal 1 triggers imaging device 12 to acquire a target image of the batch of medical fabrics in the target area. In this embodiment, only one target image needs to be captured for image recognition of the batch of medical fabrics, eliminating the need for continuous video recording to obtain video frames containing the batch of medical fabrics for image recognition, thus saving storage space. Furthermore, since the image is captured only after the operator's hand has been removed from the target area, it ensures that the medical fabrics are not obstructed by the operator's hand, guaranteeing the quality of the captured target image and improving the accuracy of image recognition.

[0087] In some scenarios, operators may directly throw a batch of medical fabrics from outside the target area into the target area, without actually touching it with their hands. Therefore, when the signal emitted by the photoelectric sensor 13 changes from a second signal to a first signal, it actually indicates the moment the batch of medical fabrics has completely entered the target area. It should be noted that if the batch of medical fabrics has not completely reached the bottom of the target area at this moment, but is still falling within the target area, the captured image of the medical fabrics will be in motion, potentially resulting in a blurry target image. To address this, the method in this embodiment further includes:

[0088] In step S31, when terminal 1 detects that the number of RFID tags read by reader 14 changes from zero to non-zero, it monitors the change in the signal emitted by photoelectric sensor 13.

[0089] Step S32: When terminal 1 detects that the signal emitted by photoelectric sensor 13 has changed from the first signal to the second signal, the current time is recorded as the first time point.

[0090] Step S33: When terminal 1 detects that the signal emitted by photoelectric sensor 13 has changed from the second signal to the first signal, the current time is recorded as the second time point.

[0091] Step S34: When terminal 1 detects that it is at the second time point, it determines whether the elapsed time between the second time point and the first time point is not less than the target time T. If so, it triggers imaging device 12 to acquire target images of a batch of medical fabrics in the target area. If not, it waits until the third time point and then triggers imaging device 12 to acquire target images of a batch of medical fabrics in the target area. The elapsed time between the third time point and the first time point is not less than the target time T, which is determined by the following formula:

[0092] Formula 1: ;

[0093] Wherein, the target duration T is in seconds, and L is the distance between the top and bottom of the target area.

[0094] Therefore, in this embodiment, it is also necessary to determine whether the elapsed time between the second time point and the first time point is not less than the target time T. Only when the elapsed time between the second time point and the first time point is not less than the target time T will the imaging device 12 be triggered to acquire the target image of a batch of medical fabrics in the target area. Steps S31 to S34 can ensure that a batch of medical fabrics entering the target area has fallen to the bottom of the target area before the image is taken, thereby improving the clarity of the captured target image and improving the accuracy of the image recognition algorithm.

[0095] As shown in Figure 10, in one embodiment, the method further includes:

[0096] Step S402, terminal 1 obtains the target length; wherein, the target length is the length of the batch RFID tag number corresponding to the Nth batch of medical fabrics in the target area read by reader 14.

[0097] In one example, the RFID tag number can be 12 bytes long. In another example, the RFID tag number can be 32 bytes long. RFID tags in the same batch of medical fabrics are all sewn by the same fabric manufacturer, therefore the RFID tag numbers in the same batch of medical fabrics are all the same length, and the RFID tag numbers in the same batch of medical fabrics are generally similar or consecutive. This is because before sewing, the fabric manufacturer usually makes the RFID chips into rolls or sheets (e.g., 500 tags in one roll). The EPC area of ​​this batch of RFID tags may have been pre-written with consecutive numbers when it leaves the factory, or a serial number may have been written inside the factory. During the sewing process, the tags are often taken from the roll one by one, and workers tear the tags from the roll and sew them onto the garments. This results in the tag numbers on the same batch of garments being basically consecutive.

[0098] Step S404: Terminal 1 sets the target compression parameters corresponding to the Nth target file based on the target length; where N is a positive integer, and the Nth target file is the target file obtained by binding the batch RFID tag number corresponding to the Nth batch of medical fabrics and the actual fabric data of the batch of medical fabrics; the target compression parameters include the target search buffer length and the target advance buffer length, both of which are equal to the target length.

[0099] In step S406, terminal 1 calls the LZ77 compression algorithm corresponding to the target compression parameters to compress the Nth target file to obtain the Nth target compressed package.

[0100] In step S408, terminal 1 sends the Nth target compressed package to server 3.

[0101] For example, according to the fabric manufacturer's specifications, each batch of medical fabrics includes 100 pieces of fabric of the same specification for easy packaging and counting. However, due to oversights in manual packaging, the first batch of medical fabrics contains only 98 pieces. The target file for the first batch of medical fabrics includes 98 RFID tag numbers and data at the end of the target file used to record the actual fabric data corresponding to this batch of medical fabrics. In this example, each RFID number is 32 bytes. The actual fabric data has three fields: product name, color, and material. Each field is numbered using 4-character digits, meaning each field can represent 40 different specifications. For example, in the product name field, 0000 represents surgical gowns; in the color field, 0001 represents white; in the material field, 0002 represents pure cotton, and so on. Therefore, the actual fabric data has three fields: product name, color, and material, corresponding to a total of 12 numbers. For example, 000000010002 indicates that the product name is surgical gown, the color is white, and the material is pure cotton. After receiving the target compressed package, server 3 decompresses it using step S410. Then, based on the length of each field of the actual fabric data (4 bytes), it segments the decompressed target file backward from the end to obtain the content of each field of the actual fabric data. When all fields of the actual fabric data are obtained (3 fields in this example), it continues to segment backward according to the RFID tag number to obtain the RFID tag number, until the target file is completely segmented. By segmenting backward, server 3 can accurately obtain the RFID tag number and actual fabric data of each batch of medical fabrics, even when the quantity of fabrics in each batch varies.

[0102] It is understandable that the existing LZ77 compression algorithm faces the following technical difficulties: on the one hand, the lengths of both the search buffer and the lookahead buffer should be large to allow for the search of longer matching segments, thereby improving the compression ratio; on the other hand, the lengths of both the search buffer and the lookahead buffer should be small to reduce the resources used in matching calculations, thus reducing the resource overhead of the compression algorithm. In this embodiment, to address these technical difficulties, in step S404, both the search buffer length and the lookahead buffer length are set equal to the target length. That is, when the RFID number is 32 bytes, both the search buffer length and the lookahead buffer length in the LZ77 compression algorithm used to compress the target file are set to 32 bytes. Since the target file starts from the beginning, forming repeating units within a 32-byte range, this embodiment, by setting both the search buffer length and the lookahead buffer length to the target length, achieves optimal compression ratio and resource overhead simultaneously.

[0103] It should be noted that since compression software based on the LZ77 algorithm cannot adjust the search buffer length and lookahead buffer length, multiple compression software programs based on the LZ77 algorithm with different search buffer length and lookahead buffer length specifications are configured on terminal 1. For example, two corresponding compression software programs based on the LZ77 algorithm are configured for the two rules of RFID tag number 32 and RFID tag number 12. Terminal 1 can determine the appropriate compression software to call for compression only by specifying the length of the RFID tag number of the current batch of medical fabrics to be compressed. This embodiment uses compression software with different window parameters to compress different target files, thereby achieving optimal compression ratio and resource consumption. Furthermore, the optimal window parameters (including search buffer length and lookahead buffer length) can be determined before the file to be compressed is obtained and its content is analyzed, thus enabling the corresponding compression software to be called in advance. In this embodiment, compression can be triggered as soon as the file to be compressed is obtained. Specifically, in this embodiment, the length of the RFID tag number is obtained first, and then the target file is generated. Once the target file is generated, compression can be performed without waiting, which can speed up the compression process. In existing technologies, to obtain the most suitable window parameters for a file to be compressed, the window parameters must be determined after obtaining the file and analyzing its contents. In other words, the solution in this embodiment does not require computer analysis of the file's contents, does not require computer resources for file content analysis, and can obtain parameters more quickly, determine which compression software to use, and perform compression faster, thus accelerating the compression process.

[0104] In one embodiment, the method further includes:

[0105] Step S410: Server 3 decompresses the received target compressed packages of different types using the same LZ77 compression algorithm with preset compression parameters to obtain the decompressed target files.

[0106] Among them, different types of target compressed packages are obtained by compressing different target files using the LZ77 compression algorithm with different target compression parameters. The preset compression parameters include a preset search buffer length and a preset lookup buffer length. The preset search buffer length is not less than the maximum value of the target search buffer length among the different target compression parameters, and the preset lookup buffer length is not less than the maximum value of the target lookup buffer length among the different target compression parameters.

[0107] For example, medical fabrics from different fabric factories may have RFID tag numbers of different lengths. For instance, the RFID tag number from factory A is 32 bytes long, while the RFID tag number from factory B is 12 bytes long. In this case, after terminal 1 identifies the RFID tag number length corresponding to the current batch of medical fabrics, it compresses the data using steps S402 to S408. Meanwhile, server 3 decompresses the received target compressed packages of different types using step S410, which uses compression software based on the same LZ77 compression algorithm with preset compression parameters, to obtain the decompressed target file. This greatly optimizes the decompression process of server 3, eliminates the need to call multiple decompression algorithms, saves server 3 overhead, and speeds up the decompression process.

[0108] In one embodiment, the method further includes:

[0109] In step S412, after receiving the target compressed package, the server 3 decompresses the target compressed package to obtain the decompressed target file.

[0110] In step S412, server 3 generates an SQL entry script based on the decompressed target file; wherein, the SQL entry script is used to enter the RFID tag number and the corresponding real medical fabric data into the SQL database.

[0111] In this embodiment, after the compressed file is decompressed, the generated script is automatically written to the SQL database, which reduces the manual cost of data entry and improves data entry efficiency.

[0112] Specifically, the following provides two implementation examples of the LZ77 compression algorithm mentioned above, including the compression and decompression processes.

[0113] Example 1:

[0114] The compression process includes:

[0115] Step 1: For the string in the window's lookahead buffer starting from the current compression position, search for the longest matching string in the window's search buffer. If found, proceed to Step 2; otherwise, proceed to Step 3.

[0116] Step 2: Output the triplet (off, len, c), then slide the window forward len+1 characters and jump to Step 1; where off is the offset of the start position of the lookahead buffer relative to the start position of the longest matching string in the search buffer, len is the length of the match, and c is the next character of the longest matching string in the lookahead buffer.

[0117] Step 3: Output the triplet (0, 0, c), then slide the window back one character and jump to step 1.

[0118] The decompression process includes:

[0119] Step 4: Determine if the 'off' and 'len' fields in the triplet (off, len, c) at the current decompression location in the compressed file are both 0. If not, proceed to step 5; otherwise, proceed to step 6.

[0120] Step 5: Starting from the position in the search buffer of the window with an offset of -off relative to the start position of the lookup buffer, copy the target string of length len to the start position of the lookup buffer of the window, and copy the c field to the position after the target string. Then slide the window forward len+1 characters, and move the decompression position in the compressed package to the next triplet, and jump to step 4.

[0121] Step 6: Copy field c to the beginning of the window's lookahead buffer, slide the window back one character, move the decompression location in the compressed file to the next triplet, and jump to step 4.

[0122] Referring to Figures 6 and 7, the compression process is illustrated with an example. As shown in Figure 6, before the window slides, the content in the search buffer is 'C00000000022'. The current compression position is the character 'C' in the lookahead buffer. Obviously, the longest matching string 'C0000000002' can be found in the window's search buffer. At this time, the length of the match len = 11. The offset of the starting position of the lookahead buffer relative to the starting position of the longest matching string in the search buffer is off = 12. The next character of the longest matching string in the lookahead buffer is c = '3', that is, the output triplet is (12, 11, 3). And after the window slides 12 bytes, as shown in Figure 7.

[0123] In one embodiment, writing all the RFID tag numbers corresponding to the batch of medical fabrics into the target file specifically includes:

[0124] Step S502: Sort the batch of RFID tag numbers corresponding to the batch of medical fabrics according to a preset sorting rule; wherein, the preset sorting rule includes ascending sorting or descending sorting.

[0125] Step S504: Based on the sorted order, write the RFID tag numbers into the target file sequentially.

[0126] It should be noted that the order of the RFID tag numbers in a batch of medical fabrics read by reader 14 is random. Therefore, the order of the RFID tag numbers in a batch of medical fabrics received by terminal 1 is also random. In this embodiment, the differences in compression will be revealed when writing all the RFID tag numbers corresponding to a batch of medical fabrics into the target file under two conditions: random order and according to the sorting rules of this embodiment.

[0127] Referring to Figure 4, which provides a comparative example, the RFID tag numbers corresponding to a batch of medical fabrics are not sorted and are directly written into the target file. Therefore, when compressing the three sets of RFID tag numbers 'C00000000022', 'C00000000031', and 'C00000000023' in the target file, six triples will be generated, namely triple 1, triple 2, triple 3, triple 4, triple 5, and triple 6 in Figure 4. Referring to Figure 5, which shows the target file obtained after performing steps S502 to S504 in this embodiment. As shown in Figure 5, when compressing the three sets of RFID tag numbers 'C00000000022', 'C00000000023', and 'C00000000024' in the target file, three triplets are generated, namely triplet 7, triplet 8, and triplet 9 in Figure 4. It can be seen that, by writing all the RFID tag numbers corresponding to a batch of medical fabrics into the target file according to the method of this embodiment, compared to the target file generated without sorting, the number of triplets generated during compression is reduced, resulting in a higher compression ratio.

[0128] Example 2

[0129] The compression process includes:

[0130] Step 1: For the string in the window's lookahead buffer starting from the current compression position, search for the longest matching string in the window's search buffer. If found, proceed to Step 2; otherwise, proceed to Step 3.

[0131] Step 2: Output the tuple (len, c), then slide the window forward len+1 characters and jump to Step 1; where len is the length of the match and c is the next character of the longest match string in the lookahead buffer.

[0132] Step 3: Output the tuple (0, c), then slide the window back one character and jump to step 1.

[0133] The decompression process includes:

[0134] Step 4: Determine if the len field in the tuple (len, c) at the current decompression position in the compressed file is 0. If not, proceed to step 5; otherwise, proceed to step 6.

[0135] Step 5: Starting from the position in the search buffer of the window with an offset of -Q relative to the start position of the lookahead buffer, copy the target string of length len to the start position of the lookahead buffer of the window, and copy the c field to the position after the target string. Then slide the window forward len+1 characters, and move the decompression position in the compressed package to the next tuple, and jump to step 4; where Q is the length of the search buffer.

[0136] Step 6: Copy field c to the beginning of the window's lookahead buffer, slide the window back one character, move the decompression location in the compressed file to the next tuple, and jump to step 4.

[0137] In Example 2, binary tuples are used instead of triples, further improving the compression ratio. It should be noted that, based on the characteristics of the RFID tag numbers of a batch of medical fabrics—that is, the RFID tag numbers of a batch of medical fabrics are consecutive, with only the last few digits differing—when the len field in the triple (off, len, c) is not 0, its corresponding triple is (Q, len, c), where Q is the length of the search buffer. Therefore, in Example 2, binary tuples are directly used instead of triples.

[0138] Step 6: Copy field c to the beginning of the window's lookahead buffer, slide the window back one character, move the decompression location in the compressed file to the next triplet, and jump to step 4.

[0139] Referring to Figures 13 and 14, the compression process is illustrated with an example. As shown in Figure 13, before the window slides, the content in the search buffer is 'C00000000022'. The current compression position is the character 'C' in the lookahead buffer. Obviously, the longest matching string 'C0000000002' can be found in the window's search buffer. At this time, the length of the match is len=11. The offset of the starting position of the lookahead buffer relative to the starting position of the longest matching string in the search buffer is off=Q, which is the length of the search buffer. In this embodiment, it does not need to be recorded. The next character of the longest matching string in the lookahead buffer is c='3', that is, the output triplet is (11,3). And after the window slides 12 bytes, as shown in Figure 14.

[0140] Similarly, the compression and decompression processes implemented using Embodiment 2 are still applicable to steps S502 to S504. Specifically, referring to Figure 11, which provides a comparative example, a batch of RFID tag numbers corresponding to a batch of medical fabrics are not sorted and are directly written into the target file. Therefore, when compressing the three sets of RFID tag numbers 'C00000000022', 'C00000000031', and 'C00000000023' in the target file, six tuples will be generated, namely tuple 1, tuple 2, tuple 3, tuple 4, tuple 5, and tuple 6 in Figure 11. Referring to Figure 12, which shows the target file obtained after executing steps S502 to S504 in this embodiment. As shown in Figure 12, when compressing the three sets of RFID tag numbers 'C00000000022', 'C00000000023', and 'C00000000024' in the target file, three tuples are generated, namely tuple 7, tuple 8, and tuple 9 in Figure 12. It can be seen that, by writing all the RFID tag numbers corresponding to a batch of medical fabrics into the target file according to the method of this embodiment, compared to the target file generated without sorting, the number of tuples generated during compression is reduced, resulting in a higher compression ratio.

[0141] In one embodiment, sorting the batch of RFID tag numbers corresponding to the batch of medical fabrics according to a preset sorting rule specifically includes:

[0142] Step S5021: Extract a preset segment of the RFID tag number corresponding to the batch of medical fabrics; wherein the preset segment is the last few digits of the RFID tag number.

[0143] Step S5022: Sort the batch of RFID tag numbers corresponding to the batch of medical fabrics according to the preset sorting rules based on the preset bit segment.

[0144] For example, a batch of medical fabrics corresponds to a batch of 100 RFID tag numbers, each consisting of 32 characters. Since these RFID tag numbers are adjacent, only the last three digits of the RFID tag number need to be compared. In this case, the preset segment is the last three digits of the RFID tag number. In this embodiment, when sorting a batch of RFID tag numbers, only the last few digits are sorted, which reduces the computational cost of sorting.

[0145] In one embodiment, when a preset condition is met, the batch RFID tag number corresponding to the batch of medical fabrics is bound to the actual fabric data of the batch of medical fabrics, specifically including:

[0146] Step S602: When it is detected that the batch RFID tag number corresponding to the N+1th batch of medical fabrics does not have the same RFID tag number as the batch RFID tag number corresponding to the Nth batch of medical fabrics, the batch RFID tag number corresponding to the Nth batch of medical fabrics is bound to the actual fabric data of that batch of medical fabrics.

[0147] The method further includes:

[0148] Step S604: When it is detected that there is at least one identical RFID tag number between the batch number of the N+1th batch of medical fabrics and the batch number of the Nth batch of medical fabrics, the identical RFID tag number is taken as the target RFID tag number and removed from the batch number of the Nth batch of medical fabrics.

[0149] Step S606: Bind the batch RFID tag number corresponding to the Nth batch of medical fabrics (after removing the target RFID tag number) and the actual fabric data of that batch of medical fabrics.

[0150] In one scenario, a textile factory might accidentally mix hospital gowns into a batch of medical fabric intended for surgical gowns due to operator error. This results in a mix of two types of medical fabrics within a single batch. When this batch of medical fabrics is placed in the target area, it might be mistakenly identified as surgical gowns, leading to the recommended fabric data being classified as such. Upon discovering the hospital gowns mixed in, the operator removes the entire batch of medical fabrics from the target area, then removes the hospital gowns from this batch and places them separately in the target area for identification. This will cause terminal 1 to detect the same RFID tag number for these hospital gowns in two adjacent batches.

[0151] However, if a batch of medical fabrics contains only one type of fabric, after the operator removes that batch from the target area, they will place the next batch of medical fabrics into the target area. Terminal 1 will not detect the same RFID tag number in two adjacent batches. In this case, the RFID tag number corresponding to the previous batch of medical fabrics will be directly bound to the actual fabric data of that batch of medical fabrics.

[0152] For example, in a batch of 100 medical fabric garments, 97 are surgical gowns, and 3 are hospital gowns. The image recognition algorithm recommends that the first batch of medical fabrics correspond to surgical gowns. The operator uses touchscreen 11 to confirm the actual fabric data corresponding to the first batch of medical fabrics. At this point, terminal 1 does not immediately bind the RFID tag number of the first batch of medical fabrics to the actual fabric data; instead, it waits for the detection results of the RFID tag number of the second batch of medical fabrics before performing the binding operation. Specifically, after the operator confirms the actual fabric data corresponding to the first batch of medical fabrics on touchscreen 11, they remove the first batch of medical fabrics from the target area and discover that 3 hospital gowns are mixed in. These 3 hospital gowns are then removed from the first batch of medical fabrics and placed into the target area. For terminal 1, these 3 hospital gowns are the second batch of medical fabrics. Obviously, terminal 1 will find that the RFID tag number of the second batch of medical fabrics is the same as that of the first batch of medical fabrics. At this time, the same RFID tag number is taken as the target RFID tag number and removed from the batch of RFID tag numbers corresponding to the first batch of medical fabrics. The batch of RFID tag numbers corresponding to the first batch of medical fabrics after the target RFID tag number has been removed is bound to the actual fabric data of the first batch of medical fabrics.

[0153] If the first batch of medical fabrics does not contain any other types of clothing, that is, if the batch RFID tag number corresponding to the second batch of medical fabrics is different from that of the first batch, the batch RFID tag number corresponding to the second batch of medical fabrics and the actual fabric data of that batch of medical fabrics will be bound together.

[0154] This embodiment enables correction when different types of clothing are mixed into a batch of medical fabrics, improving the efficiency of information entry. In this embodiment, the timing of binding the batch of RFID tag numbers corresponding to a batch of medical fabrics with the actual fabric data of that batch ensures that the target file does not require modification after generation, even if the image recognition algorithm cannot identify the mixed clothing. This improves information entry efficiency and reduces the resource overhead required to modify the file.

[0155] Understandably, if operators discover mixed-in clothing before placing a batch of medical textiles into the target area, they will remove these mixed-in garments from the batch beforehand, ensuring that all medical textiles placed into the target area are of a single type. Operators are not permitted to remove any other types of mixed-in clothing while a batch of medical textiles is being placed in the target area.

[0156] On the other hand, in one embodiment, a medical fabric information input device is provided, the device including a camera, a photoelectric sensor 13, a reader 14, a memory, a processor, and a computer program stored in the memory, the processor executing the computer program to implement the steps of the above-described medical fabric information input method.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for inputting information about medical fabrics, characterized in that, The method includes: acquiring a batch of RFID tag numbers corresponding to a batch of medical fabrics in a target area read by a reader; acquiring a target image of a batch of medical fabrics in the target area captured by an imaging device; analyzing the target image based on an image recognition algorithm to determine recommended fabric data for the batch of medical fabrics; wherein the recommended fabric data consists of a preset number of fields, and the content of each field is used to identify a recommended fabric information; displaying multiple controls on a software interface that correspond one-to-one with each field of the recommended fabric data; wherein each control displays the content of the corresponding field; receiving a user's selection operation on any one or more of the multiple controls, and generating the content of the corresponding field in the actual fabric data of the batch of medical fabrics based on the content of the corresponding field of the selected control; wherein the actual fabric data consists of a preset number of fields, and each field is used to identify an actual fabric information; and when a preset condition is detected, binding the batch of RFID tag numbers corresponding to the batch of medical fabrics and the actual fabric data of the batch of medical fabrics.

2. The method for inputting medical fabric information according to claim 1, characterized in that, A photoelectric sensor is installed at the edge of the target area. The photoelectric sensor emits a first signal when it is unobstructed and emits a second signal when it is obstructed. The method further includes: monitoring the change in the signal emitted by the photoelectric sensor when the number of RFID tags read by the reader changes from zero to non-zero; and triggering an imaging device to acquire a target image of a batch of medical fabrics in the target area when the change in the signal emitted by the photoelectric sensor is detected to be a change from the second signal to the first signal.

3. The method for inputting medical fabric information according to claim 1, characterized in that, The binding of the batch of RFID tag numbers corresponding to the batch of medical fabrics and the actual fabric data of the batch of medical fabrics specifically includes: writing the batch of RFID tag numbers corresponding to the batch of medical fabrics and the actual fabric data of the batch of medical fabrics into the same target file; wherein, the writing process includes: first writing all the batch of RFID tag numbers corresponding to the batch of medical fabrics into the target file, and then appending the actual fabric data of the batch of medical fabrics to the end of the target file to obtain the target file after writing.

4. The method for inputting medical fabric information according to claim 3, characterized in that, The method further includes: obtaining a target length; wherein the target length is the length of a batch of RFID tag numbers corresponding to the Nth batch of medical fabrics in the target area read by the reader; setting target compression parameters corresponding to the Nth target file based on the target length; wherein N is a positive integer, and the Nth target file is a target file obtained by binding the batch of RFID tag numbers corresponding to the Nth batch of medical fabrics and the actual fabric data of the batch of medical fabrics; the target compression parameters include a target search buffer length and a target pre-buffer length, both of which are equal to the target length; calling the LZ77 compression algorithm corresponding to the target compression parameters to compress the Nth target file to obtain the Nth target compressed package; and sending the Nth target compressed package to the server.

5. The method for inputting medical fabric information according to claim 4, characterized in that, The step of writing all the RFID tag numbers corresponding to the batch of medical fabrics into the target file specifically includes: sorting the RFID tag numbers corresponding to the batch of medical fabrics according to a preset sorting rule; wherein, the preset sorting rule includes ascending sorting or descending sorting; and writing each RFID tag number into the target file in sequence based on the sorted order.

6. The method for inputting medical fabric information according to claim 5, characterized in that, The step of sorting the batch of RFID tag numbers corresponding to the batch of medical fabrics according to a preset sorting rule specifically includes: extracting a preset segment of the batch of RFID tag numbers corresponding to the batch of medical fabrics; wherein, the preset segment is the last few digits of the RFID tag number; and sorting the batch of RFID tag numbers corresponding to the batch of medical fabrics according to the preset sorting rule based on the preset segment.

7. The method for inputting medical fabric information according to claim 4, characterized in that, The LZ77 compression algorithm includes a compression process and a decompression process. The compression process includes: Step 1, for the string starting from the current compression position in the window's lookup buffer, searching for the longest matching string in the window's search buffer. If found, proceed to Step 2; otherwise, proceed to Step 3. Step 2, output the tuple (len, c), then slide the window forward len+1 characters and proceed to Step 1; where len is the length of the match, and c is the next character of the longest matching string in the lookup buffer. Step 3, output the tuple (0, c), then slide the window forward 1 character and proceed to Step 1. The decompression process includes: Step 4, determining the tuple (len, c) at the current decompression position in the compressed file. If the len field in the search buffer is 0, proceed to step 5; otherwise, proceed to step 6. Step 5: Copy the target string of length len from the position offset by -Q from the start position of the search buffer relative to the start position of the lookahead buffer in the window to the start position of the lookahead buffer in the window, and copy the c field to the position after the target string. Then slide the window forward len+1 characters and move the decompression position in the compressed package to the next tuple, and proceed to step 4. Here, Q is the length of the search buffer. Step 6: Copy the c field to the start position of the lookahead buffer in the window, slide the window forward 1 character, and move the decompression position in the compressed package to the next tuple, and proceed to step 4.

8. The method for inputting medical fabric information according to claim 1, characterized in that, When the preset conditions are met, the batch RFID tag number corresponding to the batch of medical fabrics and the actual fabric data of the batch of medical fabrics are bound together. Specifically, when it is detected that the batch RFID tag number corresponding to the N+1th batch of medical fabrics read does not have the same RFID tag number as the batch RFID tag number corresponding to the Nth batch of medical fabrics read, the batch RFID tag number corresponding to the Nth batch of medical fabrics and the actual fabric data of the batch of medical fabrics are bound together.

9. A method for inputting medical fabric information according to claim 8, characterized in that, The method further includes: when it is detected that at least one RFID tag number is the same as the RFID tag number of the N+1th batch of medical fabrics, the same RFID tag number is taken as the target RFID tag number and removed from the RFID tag number of the Nth batch of medical fabrics; and the RFID tag number of the Nth batch of medical fabrics after the target RFID tag number has been removed is bound to the actual fabric data of the batch of medical fabrics.

10. A medical fabric information input device, characterized in that, The device includes a camera, a photoelectric sensor, a reader, a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the medical fabric information input method according to any one of claims 1 to 9.

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