Intelligent warehousing material information data recognition method based on RFID technology

Abstract

This invention relates to the field of warehouse data processing technology, specifically to an intelligent warehouse material information data identification method based on RFID technology. The method includes: during the transportation of materials by transport equipment, determining, based on the expected movement trajectory and material transportation task, several tags that each reader is expected to read at future target times under the current power and after power reduction; determining the collision probability of the reader reading tags at the target time under the current power and after power reduction, based on the similarity between the tags and the difference in distance to the reader; calculating the collision probability difference between the reader under the current power and after power reduction; selecting the target reader at the target time based on the collision probability difference of each reader at the target time; and reducing the power of the target reader at the target time to avoid problems such as tag signal collision, misreading, and increased energy consumption.

Description

Technical Field

[0001] This invention relates to the field of warehouse data processing technology, and specifically to an intelligent warehouse material information data identification method based on RFID technology. Background Technology

[0002] Radio Frequency Identification (RFID) is a non-contact automatic identification technology that utilizes radio frequency signals and their spatial coupling transmission characteristics to automatically identify stationary or moving objects. An RFID system typically consists of a reader and an electronic tag. The reader emits radio waves of a specific frequency to the electronic tag, which in turn drives the tag's circuitry to read the internal ID code. Electronic tags can be affixed or installed on different items, allowing readers located at various geographical locations to read the data stored within the tags and achieve automatic item identification.

[0003] When using RFID technology to identify material information in a smart warehouse, the reader typically scans all tags within the area. Because material tags are often clustered in warehouse settings, multiple tags can be read simultaneously. Due to the limited propagation speed of electromagnetic waves, the reader can only receive the signal from one tag at a time. When multiple tags send signals simultaneously, these signals may interfere, overlap, or become confused, preventing the reader from correctly identifying the ID code of a particular tag and thus failing to obtain the correct information. Therefore, even when the target tag is known, using RFID technology to identify material information in a smart warehouse cannot avoid the repeated identification of irrelevant tags, leading to tag signal collisions, misreading, and increased energy consumption. Summary of the Invention

[0004] To address the technical problems of signal collisions, misreadings, and increased energy consumption associated with tag identification during intelligent warehousing material information data recognition, this invention aims to provide an intelligent warehousing material information data recognition method based on RFID technology. The specific technical solution adopted is as follows:

[0005] This invention provides a method for identifying intelligent warehouse material information data based on RFID technology, the method comprising:

[0006] During the transportation of tagged materials by the transportation equipment, based on the expected movement trajectory of the transportation equipment and the material transportation task, the number of tags that each reader is expected to read at each target time in the future under the current power and after the power is reduced is determined.

[0007] Based on the differences between the similarity between the tags and their distance from the reader, the collision probability of the reader reading tags at the target time is determined when the reader is at the current power and after the power is reduced.

[0008] The collision probability difference is obtained by calculating the difference between the collision probability of the reader at the target time under the current power and after reducing the power.

[0009] The target reader at the target time is selected based on the difference in collision probability among the readers at the target time.

[0010] The power of the target reader at the target time is reduced.

[0011] According to the intelligent warehouse material information data identification method based on RFID technology provided by the present invention, the step of determining the collision probability when the reader reads tags at the target time under the current power and after reducing the power, based on the difference between the similarity between the plurality of tags and the distance to the reader, includes:

[0012] For the current power and after reducing the power, the tags that the reader is expected to read at the target time are grouped into several tag pairs.

[0013] Calculate the similarity between the unique identifiers of the two tags in each tag pair and the difference between the distances of the two tags to the reader;

[0014] Based on the similarity between the unique identifiers of the two tags corresponding to each tag pair and the difference between the distances between the two tags and the reader, the collision probability of the reader reading the tag at the target time under the corresponding power is determined.

[0015] According to the intelligent warehousing material information data identification method based on RFID technology provided by the present invention, the step of determining a number of tags that each reader is expected to read at each target time under the current power and after reducing the power, based on the expected movement trajectory of the transportation equipment and the material transportation task, includes:

[0016] For each reader at each target time, the power of the reader at the target time is iteratively reduced in a simulated manner, without falling below the minimum reading range.

[0017] Based on the expected movement trajectory of the transportation equipment and the material transportation task, determine the number of tags that the reader is expected to read at the target time under the current power and after each power reduction.

[0018] The calculation of the collision probability difference between the reader at the target time under the current power and after reducing the power includes:

[0019] Calculate the difference between the collision probability of the reader at the target time under the current power and the collision probability after each power reduction, and select the largest difference as the collision probability difference of the reader at the target time.

[0020] According to the intelligent warehouse material information data identification method based on RFID technology provided by the present invention, the step of selecting the target reader at the target time based on the collision probability difference of each reader at the target time includes:

[0021] The reader with the largest difference in collision probability is selected as the target reader at the target time.

[0022] Alternatively, a preset number of readers can be selected as the target readers at the target time according to the order of collision probability differences from largest to smallest.

[0023] According to the intelligent warehouse material information data identification method based on RFID technology provided by the present invention, after reducing the power of the target reader at the target time, the method further includes:

[0024] The collision probability of the target reader when reading the tag at the target time after reducing the power is taken as the target collision probability of the target reader at the target time, and the collision probability of the other readers other than the target reader when reading the tag at the target time at the current power is taken as the target collision probability of the other readers at the target time.

[0025] The Q value of each reader at the target time is adjusted according to the target collision probability of each reader at the target time.

[0026] According to the intelligent warehouse material information data identification method based on RFID technology provided by the present invention, the step of adjusting the Q value of each reader at the target time according to the target collision probability of each reader at the target time includes:

[0027] Based on the target collision probability of each reader at the target time, determine the Q-value weighting coefficient of each reader at the target time;

[0028] Based on the weighting coefficients of the Q values ​​of each reader at the target time, the Q values ​​of each reader at the target time are weighted to obtain the adjusted Q values ​​of each reader at the target time.

[0029] According to the intelligent warehouse material information data identification method based on RFID technology provided by the present invention, after reducing the power of the target reader at the target time, the method further includes:

[0030] Obtain the actual signal strength of the tags read by each reader;

[0031] If the actual signal strength is less than or equal to a preset threshold, the power of the corresponding reader is increased, and the actual signal strength is reacquired until the actual signal strength is greater than the preset threshold.

[0032] According to the intelligent warehousing material information data identification method based on RFID technology provided by the present invention, if the actual signal strength is less than or equal to a preset threshold, the method further includes increasing the power of the corresponding reader and re-acquiring the actual signal strength until the actual signal strength is greater than the preset threshold.

[0033] The collision probability when the reader reads a tag is calculated based on the difference between the similarity between the tags actually read by the reader after the power is increased and the distance between the tags and the reader.

[0034] The current Q value of the reader is adjusted based on the collision probability when the reader reads a tag after the power is increased.

[0035] The intelligent warehousing material information data identification method based on RFID technology provided by the present invention further includes:

[0036] During the packaging process of materials, for each reader in the packaging area, the current parameter adjustment weight of the reader is determined based on the dispersion of the signal strength of the tag currently actually read by the reader, the similarity between the expected tag and the tag currently actually read, and the collision probability when reading the tag.

[0037] The weights are adjusted based on the current parameters to adjust the current power and Q value of the reader.

[0038] The intelligent warehousing material information data identification method based on RFID technology provided by the present invention further includes:

[0039] During the packaging process, the labels actually read by each reader in the packaging area are used to determine whether the materials in the packaging area match the order requirements.

[0040] If a match is found, a packaging label is generated, and the labels of the materials inside the package are silently processed.

[0041] This invention offers the following advantages: During the transportation of tagged materials by transport equipment, based on the expected movement trajectory of the transport equipment and the material transport task, several tags are predicted to be read by each reader at each target time under the current power and after power reduction. Then, based on the similarity between the tags and the difference in distance to the reader, the collision probability of the reader reading tags at the target time under the current power and after power reduction is determined. The difference in collision probability between the reader at the current power and after power reduction at the target time is calculated to obtain the collision probability difference. Based on the collision probability difference of each reader at the target time, the target reader is selected, and the power of the target reader at the target time is reduced. This achieves timely adjustment of the reader's working parameters by predicting the behavior of the tags in space. By reducing the reader's power, the reading range is narrowed, and reading can stop or proceed to the next stage after the target tag is read, avoiding repeated reading of a large number of irrelevant tags. Thus, the collision probability of tags is significantly reduced without tag loss, avoiding the problems of tag signal collision, misreading, and increased energy consumption during the intelligent warehousing material information data identification process. Attached Figure Description

[0042] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This invention provides a method for identifying intelligent warehouse material information data based on RFID technology, as one embodiment of the present invention.

[0044] Figure 2 A schematic diagram illustrating signal collisions when a reader reads multiple tags;

[0045] Figure 3 A diagram illustrating the overlapping reading ranges of different readers;

[0046] Figure 4 This is a schematic diagram illustrating a process for adjusting the reader's power based on the actual signal strength during transportation, as provided in one embodiment of the present invention.

[0047] Figure 5 This is a schematic diagram illustrating the process of adjusting the power and Q value of a reader during the packaging process, as provided in one embodiment of the present invention. Detailed Implementation

[0048] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an intelligent warehousing material information data identification method based on RFID technology proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0050] The following description, in conjunction with the accompanying drawings, details a specific scheme for an intelligent warehousing material information data identification method based on RFID technology provided by the present invention.

[0051] Please see Figure 1 The diagram illustrates a flowchart of an intelligent warehousing material information data identification method based on RFID technology according to an embodiment of the present invention, including the following steps:

[0052] Step 101: During the transportation of tagged materials by the transportation equipment, based on the expected movement trajectory of the transportation equipment and the material transportation task, determine the number of tags that each reader is expected to read at each target time in the future, both at the current power and after the power is reduced.

[0053] In smart warehousing, transportation equipment refers to devices used for transporting materials. Examples include AGVs (Automated Guided Vehicles) or AGV intelligent handling robots. Tags refer to electronic tags in Radio Frequency Identification (RFID) systems. Tag data storage follows the physical characteristics of integrated circuits; its essence is a binary code, converted into electromagnetic signals using voltage transitions (rising edge = "1", falling edge = "1"). A reader refers to the reader in an RFID system. A reader can read all responding tags within its reading range. The data read by the reader includes the tag's unique identifier (ID), signal strength (RSSI, Received Signal Strength Indication), and response timestamp. Readers are installed on shelves to perform static inventory checks by reading the tags on the materials on the shelves. Readers are also installed on transportation equipment to identify the target materials to be transported by reading the tags on the materials on the shelves. The warehousing environment is equipped with readers to read the tags of materials on transport equipment during transport to monitor the process, and also to read the tags on the transport equipment itself to determine its location. Readers are also installed in the packing area to read the tags of materials there to determine if the materials match the order requirements. A material transport task refers to which materials the transport equipment needs to transport.

[0054] In one embodiment, a warehouse management system (WMS) or manufacturing execution system (MES) obtains a task list (i.e., material transportation tasks) based on order requirements, and then automatically retrieves the target material information corresponding to the task list. The target material information may include a unique identifier (ID) for the label, a material type field (full case / bulk / mixed), the coordinates of the material's location on the shelf, the order number to which the material belongs, and the customer number. A target label database is formed based on the target material information. The target materials are then retrieved from the shelf according to the target label database and transported to the packing area for packaging.

[0055] It's understandable that label reading involves multiple stages: on the shelf, during transportation, to the packing area, and during the packing process. On the shelf, labels are relatively clustered and stable; therefore, traditional methods can be used to directly read the labels of materials on the shelf using readers on the transportation equipment, without adjusting the reader's operating parameters. However, during transportation and packing, the spatial distribution of labels is more complex, and the types of labels are also diverse, such as... Figure 2 As shown, multiple tags can be read by the reader simultaneously. When multiple tags are read at the same time, due to the limited propagation speed of electromagnetic waves, the reader can only receive the signal from one tag at a time. When multiple tags send signals simultaneously, these signals may interfere with, superimpose, or become confused, resulting in tag signal collisions. This can cause the reader to fail to correctly identify the ID code of a particular tag, thus failing to obtain the correct information. Therefore, it is necessary to optimize the reader's operating parameters (power and Q value) to avoid signal collisions, misreading, and increased energy consumption.

[0056] In one embodiment, during the transportation of tagged materials by the transport equipment, the transport equipment performs path planning. A reader in the warehousing environment can read the tags on the transport equipment to determine its location. Based on the location of the transport equipment and the path planning results, the expected movement trajectory of the transport equipment is determined. Thus, the adjustment of the reader's working parameters can be predicted in advance based on the expected movement trajectory of the transport equipment and the material transportation task.

[0057] In one embodiment, the location of the transport equipment at each future target time can be determined based on its projected movement trajectory. The tags of the target materials transported by the transport equipment can be determined based on the material transport task. Based on the location of the transport equipment and the tags of the transported target materials at each future target time, the location of the tags of the target materials at each future target time can be determined. The reading range of the reader can be determined by its power. Based on the reading range of each reader at different power levels, the location of each reader, and the location of the tags of the target materials at each future target time, the number of tags that each reader is expected to read at each future target time under different power levels can be determined.

[0058] In one embodiment, the interval between target moments can be set according to the actual situation. For example, one second can be considered as one target moment.

[0059] In one embodiment, steps 101 to 105 can be performed for each target time point within the entire period of future transportation task completion to predict the reading situation and adjust the power of each target time point. In another embodiment, steps 101 to 105 can be performed for each target time point within a future time interval at preset intervals to predict the reading situation and adjust the power of each target time point. For example, every hour, predictions can be made for each target time point within the next hour.

[0060] Step 102: Based on the similarity between several tags and the difference in distance from the reader, determine the collision probability when the reader reads tags at the target time under the current power and after reducing the power.

[0061] The collision probability is used to measure the likelihood of a tag signal collision when the reader is reading a tag.

[0062] It's understandable that if the similarity of tag unique identifiers is used in the reader's selection or grouping strategy, then the greater the similarity of the tag unique identifiers, the greater the overlap of logical activations, leading to a higher collision probability. For example, assuming the unique identifiers of tags A and B are each n bits long, and the reader's current selection command mask is m bits long, and assuming the first m bits are used for matching: if A and B are completely identical in the first m bits, they will be activated simultaneously, thus increasing the collision probability; if they differ in the first m bits (i.e., at least one bit is different), they will not be activated by the same command, resulting in a lower collision probability. The spatial response time of the tags must also be considered; differences in response time can also prevent collisions. Therefore, the more similar the tag unique identifiers, the more likely collisions are to occur. The smaller the difference in distance between the tags and the reader, the more likely collisions are to occur. Thus, the collision probability when the reader reads tags at the target time is positively correlated with the similarity of the unique identifiers of the tags the reader expects to read at the target time, and negatively correlated with the difference in distance between the tags the reader expects to read at the target time and the reader itself.

[0063] Step 103: Calculate the difference in collision probability between the reader at the current power and after reducing the power at the target time.

[0064] In one embodiment, the maximum value among the differences between the collision probability of the reader at the current power and the collision probability after each power reduction is taken as the collision probability difference.

[0065] Step 104: Select the target reader at the target time based on the difference in collision probability among the readers at the target time.

[0066] It's understandable that the greater the difference in collision probabilities between the readers, the more effectively the reader can reduce the collision probability by lowering its power. Therefore, the greater the difference in collision probabilities, the more likely that reader will be selected as the target reader for power reduction.

[0067] Step 105: Reduce the power of the target reader at the target time.

[0068] like Figure 3 As shown, the reading ranges of different readers overlap to avoid signal loss during data handover in the reading areas. Therefore, during the tag reading process, a single tag may be read by multiple readers. Thus, reducing the reader's power to narrow its reading range can significantly reduce the probability of collisions while ensuring that tag reading is not lost.

[0069] In one embodiment, the target power can be the power corresponding to the maximum value of the difference between the collision probability of the reader at the current power and the collision probability after each power reduction, and the power of the target reader at the target time can be reduced to the target power.

[0070] In one embodiment, PID (proportional-integral-derivative) control can be performed by setting the reader's reading range to reduce the power to the target power.

[0071] The aforementioned intelligent warehousing material information data identification method based on RFID technology, during the transportation of tagged materials by transport equipment, determines several tags that each reader is expected to read at various target times under both current power and reduced power, based on the predicted movement trajectory of the transport equipment and the material transportation task. Then, based on the similarity between the tags and the differences in their distance from the readers, the collision probability of the readers reading tags at the target times under both current power and reduced power is determined. The difference in collision probability between the current power and reduced power at the target times is calculated to obtain the collision probability difference. Based on the collision probability difference of each reader at the target times, the target reader is selected, and its power is reduced. This achieves timely adjustment of the reader's operating parameters by predicting the behavior of the tags in space. By reducing the reader's power, the reading range is narrowed, and reading can stop or proceed to the next stage after the target tag is read, avoiding repeated reading of a large number of irrelevant tags. This significantly reduces the tag collision probability without losing tags, avoiding problems such as tag signal collisions, misreading, and increased energy consumption during intelligent warehousing material information data identification, and also improving identification efficiency.

[0072] In one embodiment, determining the collision probability of the reader reading tags at a target time under the current power and after reducing the power, based on the similarity between several tags and the difference between their distances to the reader, includes: forming several tag pairs from several tags that the reader is expected to read at the target time, respectively, under the current power and after reducing the power; calculating the similarity between the unique identifiers of the two tags in each tag pair and the difference between the distances between the two tags and the reader; and determining the collision probability of the reader reading tags at the corresponding power at the target time based on the similarity between the unique identifiers of the two tags corresponding to each tag pair and the difference between the distances between the two tags and the reader.

[0073] In one embodiment, the unique identifiers of the two tags in a tag pair can be compared bit by bit. The difference between the two tags' unique identifiers is determined based on the number of bits that are inconsistent, and the similarity is determined by the reciprocal of the difference. The more bits that are inconsistent, the smaller the difference and the greater the similarity; conversely, the more bits that are inconsistent, the greater the difference and the smaller the similarity. For example, if the unique identifiers of two tags are 1111 and 0000, and all bits are inconsistent (i.e., 4 bits are inconsistent), then the difference is the greatest, and the similarity can be the reciprocal of the difference. If the unique identifiers of two tags are 1111 and 1000, and the number of bits that are inconsistent is 3, then the difference can be 3, and the similarity can be the reciprocal of the difference. When the unique identifiers of two tags are completely consistent, the number of inconsistent bits is 0, and the difference is 0. However, since there is no case where the unique identifiers of two tags are completely consistent, the difference value can never be 0.

[0074] The collision probability when the reader reads a tag at the target time is positively correlated with the similarity of the unique identifiers of the two tags in each tag pair among the several tags that the reader expects to read at the target time, and negatively correlated with the difference between the distances between the two tags in each tag pair among the several tags that the reader expects to read at the target time and the reader.

[0075] In one embodiment, the collision probability when the reader reads the tag at the target time can be determined according to the following formula:

[0076]

[0077] in, Indicates the first The reader in the first The collision probability when reading the tag at each target time. Indicates the first The difference between the unique identifiers of the two tags in a tag pair. Indicates the first The similarity between the unique identifiers of two tags in a tag pair. Indicates the first The difference between the distances of the two tags in a tag pair to the reader can be specifically represented using the absolute value of the difference in this embodiment of the invention. Indicates the first The absolute value of the difference between the distances of the two tags in a tag pair and the reader. This represents an exponential function with the natural constant as its base. Indicates the first The reader in the first The number of tag pairs consisting of several tags expected to be read at each target time.

[0078] In the above embodiments, since the more similar the unique identifiers of the tags are, the more likely a collision will occur, and the smaller the difference between the distances between the tags and the reader, the more likely a collision will occur. Therefore, by calculating the similarity between the unique identifiers of the two tags in each tag pair and the difference between the distances between the two tags and the reader, the collision probability when the reader reads the tags at the target time can be accurately determined based on the similarity between the unique identifiers of the two tags corresponding to each tag pair and the difference between the distances between the two tags and the reader.

[0079] In one embodiment, based on the expected movement trajectory of the transportation equipment and the material transportation task, a number of tags that each reader is expected to read at each target time under the current power and after power reduction are determined. This includes: for each reader at each target time, simulating iteratively reducing the power of the reader at the target time without falling below the minimum reading range; and determining the number of tags that the reader is expected to read at the target time under the current power and after each power reduction, based on the expected movement trajectory of the transportation equipment and the material transportation task. The collision probability difference is calculated by determining the difference between the collision probability of the reader at the target time under the current power and after power reduction, and selecting the largest difference as the collision probability difference of the reader at the target time.

[0080] The minimum reading range is the minimum value that the reader's reading range cannot be lower than.

[0081] In one embodiment, without falling below the minimum reading range, the reader's power is iteratively reduced based on the location of the transport equipment, so that the reader's reading range can cover the transport equipment after each power reduction.

[0082] In the above embodiments, for each reader at each target time, the power of the reader at the target time is simulated and iteratively reduced without falling below the minimum reading range. Based on the expected movement trajectory of the transportation equipment and the material transportation task, the number of tags that the reader is expected to read at the target time under the current power and after each power reduction is determined. This allows the collision probability of the reader reading tags at the target time under the current power and after each power reduction to be determined. Then, the difference between the collision probability of the reader at the target time under the current power and the collision probability after each power reduction is calculated. The largest difference is selected as the collision probability difference of the reader at the target time, which can accurately determine how much the reader can reduce the collision probability at the target time by reducing the power.

[0083] In one embodiment, selecting the target reader at the target time based on the collision probability difference of each reader at the target time includes: selecting the reader with the largest collision probability difference as the target reader at the target time; or, selecting a preset number of readers as the target readers at the target time in descending order of collision probability difference.

[0084] It's understandable that the greater the difference in collision probabilities, the more likely that reader will be selected as the target reader for power reduction. Therefore, the reader with the largest difference in collision probabilities is selected as the target reader at the target time. Alternatively, a preset number of readers can be selected as the target readers at the target time, in descending order of collision probability differences. For example, the preset number could be 2 or 3.

[0085] In the above embodiments, the reader with the largest collision probability difference is selected as the target reader at the target time, or a preset number of readers are selected as the target readers at the target time in descending order of collision probability difference to reduce power. This can significantly reduce the collision probability of tags without losing tag readings, avoiding the problems of tag signal collision, misreading, and increased energy consumption during the intelligent warehousing material information data identification process.

[0086] In one embodiment, after reducing the power of the target reader at the target time, the method further includes: using the collision probability of the target reader when reading a tag at the target time after reducing the power as the target collision probability of the target reader at the target time; using the collision probability of the other readers (excluding the target reader) when reading a tag at the target time at the current power as the target collision probability of the other readers at the target time; and adjusting the Q value of each reader at the target time according to the target collision probability of each reader at the target time.

[0087] The Q-value refers to the parameter Q in the anti-collision algorithm. The anti-collision algorithm is the core technology for resolving multi-tag signal collisions in RFID systems. This algorithm controls the length of the next identification frame by statistically analyzing the number of idle and collision slots within the identification frame, enabling the system to maintain good identification performance across different tag counts. The Q-value determines the number of slots within a single identification frame. A higher collision probability requires a larger Q-value to increase the number of slots within a single identification frame, thus reducing the collision probability. Therefore, the reader's Q-value at the target time is positively correlated with the target collision probability at that time. For example, a preset Q-value of 3 can be used, and then the Q-value can be gradually adjusted during transportation.

[0088] In the above embodiments, since a higher collision probability requires a larger Q value to increase the number of time slots in a single recognition frame and reduce the collision probability, the Q value of each reader at the target time can be accurately adjusted according to the target collision probability of each reader at the target time to avoid the problem of tag signal collision.

[0089] In one embodiment, adjusting the Q-value of each reader at the target time based on the target collision probability of each reader at the target time includes: determining the weighting coefficient of the Q-value of each reader at the target time based on the target collision probability of each reader at the target time; and weighting the Q-value of each reader at the target time based on the weighting coefficient of the Q-value of each reader at the target time to obtain the adjusted Q-value of each reader at the target time.

[0090] In one embodiment, the adjusted Q value of the reader at the target time can be determined according to the following formula:

[0091]

[0092] in, This represents the adjusted Q value. This represents the probability of a target collision. This represents the weighting coefficient. This represents the Q value before adjustment.

[0093] In the above embodiments, based on the target collision probability of each reader at the target time, a weighting coefficient for the Q value of each reader at the target time is determined. The Q value of each reader at the target time is weighted according to the weighting coefficient to obtain the adjusted Q value of each reader at the target time. This achieves the goal of setting a larger Q value when the target collision probability is higher, so as to avoid the problem of tag signal collision.

[0094] Conversely, in other embodiments of the present invention, when the target collision probability Below the baseline value (e.g.) , Setting a threshold for the historical average collision probability or the system can reduce the Q value.

[0095]

[0096] In the formula, This represents the minimum Q value allowed by the system (e.g., Q=1) to ensure recognition stability, while max represents the function that takes the maximum value.

[0097] That is to say, in some other embodiments of the present invention, the target collision probability is determined. When the value is lower than the preset baseline, a process of reducing the Q value can be performed, thereby achieving adaptive adjustment of the Q value.

[0098] The specific values ​​(e.g., 1.5) for the system-set thresholds given in this embodiment of the invention are empirical values ​​obtained under typical hardware configurations and test scenarios, intended to facilitate understanding of the invention. In practical applications, those skilled in the art can adjust, calibrate, or optimize these parameters according to specific hardware performance, scenario complexity, and data characteristics, which does not constitute a limitation of the invention.

[0099] In one embodiment, see Figure 4 After reducing the power of the target reader at the target time, the method further includes:

[0100] Step 401: Obtain the actual signal strength of the tag read by each reader.

[0101] The actual signal strength refers to the signal strength (RSSI, Received Signal Strength Indication) of the tag signal actually read by the reader.

[0102] Step 402: If the actual signal strength is less than or equal to a preset threshold, increase the power of the corresponding reader and reacquire the actual signal strength until the actual signal strength is greater than the preset threshold.

[0103] For example, the preset threshold can be set to -60dBM.

[0104] It is understandable that during actual transportation, the actual arrival time of the transportation equipment at each location may deviate from the expected arrival time. Therefore, the collision probability determined based on the tag information expected to be read by the reader may deviate from the actual situation. Thus, after adjusting the power based on the predicted collision probability, the power can be further adjusted according to the actual situation. When the actual signal strength is less than or equal to the preset threshold, the power of the corresponding reader is increased until the actual signal strength is greater than the preset threshold, thereby avoiding tag signal loss.

[0105] If the actual signal strength at the target time is greater than the preset threshold, the power at the target time, which is determined in advance based on the prediction results, will remain unchanged and no adjustment is required.

[0106] In the above embodiments, if the actual signal strength is less than or equal to a preset threshold, the power of the corresponding reader is increased, and the actual signal strength is reacquired until the actual signal strength is greater than the preset threshold, which can prevent the tag signal from being lost.

[0107] In one embodiment, if the actual signal strength is less than or equal to a preset threshold, the power of the corresponding reader is increased, and the actual signal strength is reacquired until the actual signal strength is greater than the preset threshold. The method further includes: calculating the collision probability when the reader reads a tag after increasing the power based on the difference between the similarity between the tags actually read by the reader after increasing the power and the distance between the tags and the reader; and adjusting the current Q value of the reader based on the collision probability when the reader reads a tag after increasing the power.

[0108] In the above embodiments, after adjusting the reader's power according to the actual signal strength, the collision probability is recalculated, and the Q value is adjusted according to the collision probability, which can adjust the Q value more accurately according to the actual situation.

[0109] In one embodiment, see Figure 5 The method also includes:

[0110] Step 501: During the packaging process of materials, for each reader in the packaging area, the current parameter adjustment weight of the reader is determined based on the dispersion of the signal strength of the tag currently actually read by the reader, the similarity between the expected tag and the tag currently actually read, and the collision probability when reading the tag.

[0111] The dispersion of the signal strength of the tag actually read by the reader can be measured by variance or standard deviation.

[0112] It is understandable that during the packaging process, as transport equipment continuously delivers materials to the packaging area, the accumulation of materials gradually increases. With this accumulation, signal strength fluctuations become more pronounced, requiring higher power for reading. Furthermore, the closer the actual acquired material is to the expected acquired material, the less significant the impact of material changes, leading to a higher risk of collisions. A higher collision probability during tag reading necessitates increasing the reader's operating parameters. Therefore, the current parameter adjustment weights of the reader are positively correlated with the dispersion of the signal strength of the currently read tag, the similarity between the expected and actual read tags, and the collision probability during tag reading.

[0113] In one embodiment, the current parameter adjustment weights of the reader can be determined according to the following formula:

[0114]

[0115] in, This indicates the current parameter adjustment weights for the reader. This indicates the signal strength of the tag that the reader is currently actually reading. This indicates the degree of dispersion in the signal strength of the tag that the reader is currently actually reading. Indicates the label to be read The unique identifier and the tag currently being read The differences between unique identifiers. Indicates the label to be read The unique identifier and the tag currently being read Similarity between unique identifiers. This indicates the collision probability when reading the current tag. This represents the minimum value, used to avoid the denominator being 0. Specifically, it can be 0.1, and its value should be chosen within the allowable range of the overall error.

[0116] Step 502: Adjust the weights according to the current parameters, and adjust the current power and Q value of the reader.

[0117] In one embodiment, it can be achieved by The reader's current power and Q value are weighted. This indicates the current parameter adjustment weights for the reader.

[0118] In one embodiment, the frequency of executing steps 501 to 502 during the packaging process can be set according to actual conditions. For example, steps 501 to 502 can be executed once every second.

[0119] In the above embodiments, during the packaging process of materials, for each reader in the packaging area, the current parameter adjustment weight of the reader is determined based on the dispersion of the signal strength of the tag currently actually read by the reader, the similarity between the expected tag and the tag currently actually read, and the collision probability when reading the tag. Based on the current parameter adjustment weight, the current power and Q value of the reader are adjusted, so as to accurately adjust the power and Q value of the reader in the scenario of tag aggregation during the packaging process and avoid tag signal collision.

[0120] In one embodiment, the method further includes: during the packaging process, determining whether the materials in the packaging area match the order requirements based on the labels actually read by each reader in the packaging area; if they match, generating packaging labels and silently processing the labels of the materials inside the packaging area.

[0121] In one embodiment, after integrating and deduplicating the tags actually read by each reader in the packaging area, it is determined whether the materials in the packaging area match the order requirements. If they match, a packaging tag is generated, and the tags of the materials inside the package are silently processed; if they do not match, the mismatched materials are processed.

[0122] In the above embodiments, during the packaging process, the system determines whether the materials in the packaging area match the order requirements based on the labels actually read by each reader in the packaging area. If they match, a packaging label is generated, and the labels of the materials inside the package are silently processed, thus completing the process from loose goods to packaged goods. In subsequent analysis, only the packaging labels need to be read, and the internal information does not need to be read.

[0123] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0124] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] The above-described embodiments are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

[0126] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0127] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for identifying intelligent warehouse material information data based on RFID technology, characterized in that, The method includes: During the transportation of tagged materials by the transportation equipment, based on the expected movement trajectory of the transportation equipment and the material transportation task, the number of tags that each reader is expected to read at each target time in the future under the current power and after the power is reduced is determined. Based on the differences between the similarity between the tags and their distance from the reader, the collision probability of the reader reading tags at the target time is determined when the reader is at the current power and after the power is reduced. The collision probability difference is obtained by calculating the difference between the collision probability of the reader at the target time under the current power and after reducing the power. The target reader at the target time is selected based on the difference in collision probability among the readers at the target time. The power of the target reader at the target time is reduced; The method for determining the collision probability includes: For the current power and after reducing the power, the tags that the reader is expected to read at the target time are grouped into several tag pairs. Calculate the similarity between the unique identifiers of the two tags in each tag pair and the difference between the distances of the two tags to the reader; Based on the similarity between the unique identifiers of the two tags corresponding to each tag pair and the difference between the distances between the two tags and the reader, the collision probability of the reader reading the tag at the target time under the corresponding power is determined; Methods for selecting a target reader include: The reader with the largest difference in collision probability is selected as the target reader at the target time. Alternatively, a preset number of readers can be selected as the target readers at the target time according to the order of collision probability differences from largest to smallest.

2. The intelligent warehousing material information data identification method based on RFID technology according to claim 1, characterized in that, Based on the expected movement trajectory of the transportation equipment and the material transportation task, the system determines several tags that each reader is expected to read at each target time in the future, both under the current power and after reducing the power. These tags include: For each reader at each target time, the power of the reader at the target time is iteratively reduced in a simulated manner, without falling below the minimum reading range. Based on the expected movement trajectory of the transportation equipment and the material transportation task, determine the number of tags that the reader is expected to read at the target time under the current power and after each power reduction. The calculation of the collision probability difference between the reader at the target time under the current power and after reducing the power includes: Calculate the difference between the collision probability of the reader at the target time under the current power and the collision probability after each power reduction, and select the largest difference as the collision probability difference of the reader at the target time.

3. The intelligent warehousing material information data identification method based on RFID technology according to claim 1, characterized in that, After reducing the power of the target reader at the target time, the method further includes: The collision probability of the target reader when reading the tag at the target time after reducing the power is taken as the target collision probability of the target reader at the target time, and the collision probability of the other readers other than the target reader when reading the tag at the target time at the current power is taken as the target collision probability of the other readers at the target time. Based on the target collision probability of each reader at the target time, the Q value of each reader at the target time is adjusted, wherein the Q value is the value of parameter Q in the anti-collision algorithm.

4. The intelligent warehousing material information data identification method based on RFID technology according to claim 3, characterized in that, The step of adjusting the Q value of each reader at the target time based on the target collision probability of each reader at the target time includes: Based on the target collision probability of each reader at the target time, determine the Q-value weighting coefficient of each reader at the target time; Based on the weighting coefficients of the Q values ​​of each reader at the target time, the Q values ​​of each reader at the target time are weighted to obtain the adjusted Q values ​​of each reader at the target time.

5. The intelligent warehousing material information data identification method based on RFID technology according to claim 1, characterized in that, After reducing the power of the target reader at the target time, the method further includes: Obtain the actual signal strength of the tags read by each reader; If the actual signal strength is less than or equal to a preset threshold, the power of the corresponding reader is increased, and the actual signal strength is reacquired until the actual signal strength is greater than the preset threshold.

6. The intelligent warehousing material information data identification method based on RFID technology according to claim 5, characterized in that, If the actual signal strength is less than or equal to a preset threshold, the power of the corresponding reader is increased, and the actual signal strength is reacquired until the actual signal strength is greater than the preset threshold. The method further includes: The collision probability when the reader reads a tag is calculated based on the difference between the similarity between the tags actually read by the reader after the power is increased and the distance between the tags and the reader. The current Q value of the reader is adjusted based on the collision probability when the reader reads a tag after the power is increased.

7. The intelligent warehousing material information data identification method based on RFID technology according to claim 1, characterized in that, The method further includes: During the packaging process of materials, for each reader in the packaging area, the current parameter adjustment weight of the reader is determined based on the dispersion of the signal strength of the tag currently actually read by the reader, the similarity between the expected tag and the tag currently actually read, and the collision probability when reading the tag. The weights are adjusted based on the current parameters to adjust the current power and Q value of the reader.

8. The intelligent warehousing material information data identification method based on RFID technology according to any one of claims 1 to 7, characterized in that, The method further includes: During the packaging process, the labels actually read by each reader in the packaging area are used to determine whether the materials in the packaging area match the order requirements. If a match is found, a packaging label is generated, and the labels of the materials inside the package are silently processed.

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