Article real-time tracking and inventorying method and system based on RFID technology and channel door

Abstract

The application relates to an article real-time tracking and checking method and system based on RFID technology and a passage door, wherein the passage door and an RFID base station are preset to collect tracking information records. Considering that RFID signals are prone to interference, the tracking information records are checked based on signal data. Based on the checking result, the tracking information records are divided into valid records and invalid records, the valid records can be directly positioned to obtain the storage position of the articles, and the invalid records are inferred to obtain inertial storage positions by using an inertial database. The storage positions are used to update storage information, when the updating degree reaches a certain degree, a checking task is automatically issued, and a checking range is generated based on difference information. The application can perform full-process management on warehouse checking based on RFID technology, simultaneously guides the checking task, and can effectively improve the asset checking efficiency in the warehouse based on RFID technology.

Description

Technical Field

[0001] This invention relates to the field of RFID technology, specifically to a method and system for real-time tracking and inventory of items based on RFID technology and access gates. Background Technology

[0002] RFID tag-based fixed asset management is of great significance, for example, enabling rapid asset inventory. Traditional fixed asset management relies on manual methods, which carries risks such as items not being checked and verified for years, and a lack of understanding of their specific conditions. Operational processes lack system support, have low levels of digitalization, and are not integrated with management systems. The identification and counting of fixed assets are entirely manual, resulting in low inventory efficiency; counting 20,000 fixed assets would require two people working for 10 hours. RFID, through automated data collection, reduces manpower. Furthermore, RFID technology can cover various scenarios where manual inventory is difficult, such as high places, corners, or enclosed containers, allowing for long-distance reading and avoiding the cumbersome process of traditional manual inventory. Simultaneously, RFID tags can be used to quickly compile end-to-end tracking information for fixed assets, facilitating the management of their status.

[0003] Although existing RFID tags can greatly reduce the time for asset inventory, there is no technical solution for the full-process management of RFID tags and assets. Therefore, the inventory efficiency of inventory personnel is highly dependent on their experience, resulting in low inventory efficiency for those who are not familiar with the warehouse layout. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method and system for real-time tracking and inventory of items based on RFID technology and access gates, so as to solve the above-mentioned technical problems.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] The present invention provides a real-time item tracking and inventory method based on RFID technology and access gates, comprising the following steps:

[0007] The system acquires multiple tracking information records for the current inventory cycle of the warehouse. These records include the entry time of the access gate, information on personnel entering and exiting, RFID tag information of items carried by the entrant read by the access gate, and multiple sets of signal data from the RFID tag information. The multiple sets of signal data come from multiple RFID base stations, and the signal data includes the signal strength and arrival time at multiple time points.

[0008] The validity of each tracking information record is verified based on multiple sets of signal data to obtain valid tracking records and invalid tracking records;

[0009] Positioning is performed on multiple arrival time points of the valid tracking records to obtain valid motion trajectories, and the storage location of the items is extracted from the valid motion trajectories; and the inertial storage location of the invalid tracking records is determined based on a pre-built inertial database.

[0010] The item storage location or inertial storage location recorded by multiple tracking information is used to update the initial item storage information of the previous storage period to obtain the item storage update information;

[0011] The difference between the initial storage information and the updated storage information of the item is calculated. When the value of the difference information is greater than a preset difference threshold, or when the time difference between the current time point and the timestamp of the initial storage information of the item reaches a preset duration threshold, an inventory task is generated based on the difference information, and the inventory task is sent to the inventory personnel and the inventory management is performed. The inventory task includes the inventory location.

[0012] In one embodiment of this application, the validity of each tracking information record is verified based on multiple sets of signal data to obtain valid tracking records and invalid tracking records, including:

[0013] Extract signal strength values ​​at multiple time points from each set of signal data pairs. ,in, Indicates a point in time. Indicates the RFID base station serial number;

[0014] Signal strength values ​​at multiple time points Extracting volatility eigenvalues Maximum value Minimum value and overall slope , wherein the overall slope Obtained through linear regression;

[0015] By combining the signal strength values ​​at the same time point from multiple sets of signal data belonging to the same tracking information record, multiple signal strength difference data are obtained. and for each signal strength difference data The signal strength values ​​are normalized, and the variance of the differences between the normalized signal strength values ​​is calculated. ,in, Indicates the time point of the first RFID base station The signal strength value, This indicates the time point of the second RFID base station. The signal strength value, Indicates the first RFID base stations at time points The signal strength value;

[0016] The volatility characteristic value The maximum value The minimum value and the overall slope Each with a preset fluctuation characteristic range Reference range of values and maximum slope Compare and calculate the variance of multiple signal strength differences. vs. preset variance range The system compares the data and determines the tracking information record as valid if the target conditions are met; otherwise, it determines the tracking information record as invalid. The target conditions include: , , , , .

[0017] In one embodiment of this application, positioning is performed on multiple arrival time points of the valid tracking records to obtain a valid motion trajectory, including:

[0018] The location is calculated by combining multiple arrival time points using the time difference of arrival method, resulting in multiple location coordinates;

[0019] Connect multiple positioning coordinates to obtain an initial trajectory; then smooth the initial trajectory to obtain an effective motion trajectory.

[0020] In one embodiment of this application, extracting the item storage location from the effective motion trajectory includes:

[0021] Calculate the distance between any two adjacent positioning coordinates. ;

[0022] Multiple distances are arranged in chronological order, and the average distance of multiple time windows is extracted using the sliding time window method.

[0023] When the average distance of N consecutive time windows is less than a preset distance threshold, it is determined that the RFID tag is stationary within the N consecutive time windows, and the positioning coordinates of the stationary time points are averaged to obtain the average coordinates; and the average coordinates are used as the storage location of the item.

[0024] In one embodiment of this application, the method for constructing the inertial database includes:

[0025] Obtain multiple valid historical tracking records;

[0026] Information on people entering and exiting the premises, RFID tag information, and the location of items are extracted from the multiple historical valid tracking records, and the item type code is extracted from the RFID tag information.

[0027] The storage location of the item is converted from a coordinate type to a location code, wherein the location code includes a container code and a storage unit code;

[0028] A first sample vector is constructed based on the entry and exit personnel information and location code in each historical valid record, and a second sample vector is constructed based on the item type code and storage unit code in each historical valid record.

[0029] Density clustering is performed on the first sample vector to obtain multiple first sample vector clusters; and density clustering is performed on the second sample vector to obtain multiple second sample vector clusters.

[0030] From the plurality of first sample vector clusters and the plurality of second sample vector clusters, target vector clusters with a number of samples within the cluster greater than a preset threshold are selected, wherein each target vector cluster corresponds to an inertial feature;

[0031] Extracting inertial features from the target vector cluster and the confidence level of inertial characteristics The confidence level of the inertial feature. The mathematical expression is:

[0032]

[0033] In the formula, The number of valid historical records. The number of samples within the target vector cluster;

[0034] Based on multiple inertial features and confidence levels of multiple inertial features Build an inertial database.

[0035] In one embodiment of this application, determining the inertial storage location of the invalid tracking record based on a pre-built inertial database includes:

[0036] Extract information on the types of items from the entry and exit personnel information and RFID tag information from the invalid tracking records;

[0037] The information on people entering and exiting the premises and the information on the types of goods are respectively matched with multiple inertial features in the inertial database to obtain a first inertial feature that matches the information on people entering and exiting the premises and / or a second inertial feature that matches the information on the types of goods.

[0038] When the invalid tracking record includes a first inertial feature or a second inertial feature, the position code is extracted from the first inertial feature or the second inertial feature as the inertial storage location;

[0039] When both a first inertial feature and a second inertial feature exist in the invalid tracking record, the first inertial feature and the second inertial feature are compared.

[0040] When the first inertial feature and the second inertial feature are consistent, the storage location information in the first inertial feature or the second inertial feature is extracted to obtain the inertial storage location;

[0041] When the first inertial feature and the second inertial feature are inconsistent, the first position code is extracted from the first inertial feature. and the confidence level of the first inertial feature And extract the second position code from the second inertial feature. and the confidence level of the second inertial feature ;

[0042] Based on the first position code Corresponding confidence level Calculate the conversion amount of the number of changes in the first position code. and based on the second position encoding Corresponding confidence level Calculate the conversion amount of the number of changes in the second position code. Wherein, the number of changes in the first position code is converted into a certain amount. The conversion amount of the number of changes in the second position code The mathematical expressions are as follows:

[0043]

[0044]

[0045] Calculated based on the number of changes in the first position code The conversion amount of the number of changes in the second position code Establish an inertial storage location.

[0046] In one embodiment of this application, the initial storage information of the items in the previous storage period is updated based on the item storage location or inertial storage location recorded by multiple tracking information records to obtain item storage update information, including:

[0047] Obtain the initial storage information of items from the previous storage period, wherein the initial storage information of items is stored in matrix form, each row of the matrix represents the storage information encoded at each position, and the storage information in each row includes the currently stored items and the number of changes;

[0048] The matrix is ​​updated based on the storage location or inertial storage location of the items recorded by multiple tracking information records to obtain the item storage update information. The update rule is as follows: during each update, the number of changes in the target row corresponding to the location code is accumulated based on the number of changes or the number of changes converted, and the currently stored items in the target row are added or removed based on the unique identification code of the RFID tag information.

[0049] In one embodiment of this application, calculating the difference between the initial storage information and the updated storage information of the item includes:

[0050] Calculate the difference matrix between the matrix containing the initial information of the item and the matrix containing the updated information of the item;

[0051] The difference information is obtained by performing a weighted summation based on dynamic weights on the columns representing the number of changes in the difference matrix.

[0052] In one embodiment of this application, generating an inventory task based on the discrepancy information, and sending the inventory task to inventory personnel and performing inventory management include:

[0053] Rows with a number of changes greater than a preset threshold are selected from the difference matrix to obtain the target row and the target position code corresponding to the target row;

[0054] The inventory range is determined based on the target location code, and an inventory task is generated based on the inventory range.

[0055] The inventory task is sent to the inventory personnel. When the inventory personnel enter the passage door, the inventory mode is entered and other people are temporarily prohibited from entering / leaving the warehouse. When the inventory personnel leave the passage door, the inventory mode is deactivated.

[0056] This application also provides a real-time item tracking and inventory system based on RFID technology and access gates, including:

[0057] The acquisition module is used to acquire multiple tracking information records of the current inventory cycle of the warehouse. The tracking information records include the entry time of the passage door, the information of the people entering and exiting, the RFID tag information of the items carried by the people entering and reading by the passage door, and multiple sets of signal data of the RFID tag information. The multiple sets of signal data come from multiple RFID base stations, and the signal data includes the signal strength and arrival time at multiple time points.

[0058] The verification module is used to verify the validity of each tracking information record based on multiple sets of signal data, and to obtain valid tracking records and invalid tracking records;

[0059] The positioning module is used to perform positioning on multiple arrival time points of the valid tracking records to obtain valid motion trajectories and extract the item storage location from the valid motion trajectories; and to determine the inertial storage location of the invalid tracking records based on a pre-built inertial database.

[0060] The update module is used to update the initial storage information of the items in the previous storage period based on the storage location or inertial storage location of the items recorded by multiple tracking information records, so as to obtain the item storage update information;

[0061] The inventory management module is used to calculate the difference between the initial storage information and the updated storage information of the items. When the value of the difference is greater than a preset difference threshold, or when the time difference between the current time and the timestamp of the initial storage information of the items reaches a preset duration threshold, an inventory task is generated based on the difference information, the inventory task is sent to the inventory personnel and the inventory management is performed. The inventory task includes the inventory location.

[0062] The beneficial effects of this invention are as follows: This invention provides a real-time tracking and inventory method and system for items based on RFID technology and access gates. The system pre-sets access gates and RFID base stations to collect information on all people entering and leaving the warehouse during the current inventory cycle, as well as the RFID tags they carry, and reads signal data to obtain tracking information records. Considering that RFID signals are easily interfered with, this invention verifies the tracking information records based on the signal data. Based on the verification results, the tracking information records are divided into valid and invalid records. Valid records can be directly located to determine the storage location of the items, while invalid records utilize an inertial database to infer the inertial storage location. The storage location is used to update the stored information. When the update reaches a certain level, an inventory task is automatically issued, and an inventory range is generated based on the discrepancies. This invention can manage the entire process of warehouse inventory based on RFID technology and guide inventory tasks, effectively improving the efficiency of RFID-based asset inventory within the warehouse. Attached Figure Description

[0063] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0064] Figure 1 This is an illustration of an application scenario of a real-time item tracking and inventory method based on RFID technology and access gates, as described in one embodiment of this application.

[0065] Figure 2This is a flowchart illustrating a real-time tracking and inventory method for items based on RFID technology and access gates, as shown in one embodiment of this application.

[0066] Figure 3 This is a schematic diagram of the information inventory task execution process in one embodiment of this application;

[0067] Figure 4 This is a schematic diagram of the physical inventory task execution process in one embodiment of this application;

[0068] Figure 5 This is a structural diagram of a real-time item tracking and inventory system based on RFID technology and access gates, shown in one embodiment of this application;

[0069] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0070] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0071] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the layers related to the present invention and are not drawn according to the actual number, shape and size ratio of the layers in the actual implementation. In the actual implementation, the form and number of each layer can be arbitrarily changed, and the layer layout may also be more complex.

[0072] Numerous details are explored in the following description to provide a more thorough explanation of embodiments of the invention; however, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details.

[0073] Figure 1 This is an illustration of an application scenario for a real-time tracking and inventory method for items based on RFID technology and access gates, as described in one embodiment of this application. Figure 1 As shown, this application sets up multiple RFID base stations 110 in the warehouse. The RFID base station 110 wakes up all RFID tags within its coverage area by periodically transmitting signals and returns radio frequency signals. The RFID base station 110 analyzes the signal strength of the radio frequency signals and can determine whether the radio frequency signals returned by the RFID tags are interfered with.

[0074] Furthermore, the warehouse entrance in this application uses a passageway door 120, which can identify individuals through facial recognition or fingerprint recognition. Simultaneously, the passageway door 120 has a built-in RFID reader that reads the RFID tags on items carried by personnel passing through it. Combined with identity verification, the items carried by personnel entering / leaving can be accurately determined.

[0075] Both RFID base station 110 and access gate 120 are connected to server 130. Server 130 analyzes the data collected by RFID base station 110 and access gate 120, automatically formulates inventory task distribution plans, and executes inventory guidance.

[0076] Figure 2 This is a flowchart illustrating a real-time item tracking and inventory method based on RFID technology and access gates, as shown in one embodiment of this application. Figure 2 As shown: The real-time tracking and inventory method for items based on RFID technology and access gates in this embodiment may include steps S210 to S250:

[0077] S210, acquire multiple tracking information records for the current inventory cycle of the warehouse, wherein the tracking information records include the entry time of the passage door, information of the personnel entering and exiting, RFID tag information of the items carried by the entrant read by the passage door, and multiple sets of signal data of the RFID tag information. The multiple sets of signal data come from multiple RFID base stations, and the signal data includes the signal strength and arrival time at multiple time points.

[0078] The inventory cycle is automatically defined by the system. After the inventory is completed in the previous inventory cycle, the next inventory cycle begins.

[0079] During each inventory cycle, the RFID base station and the access gate work together automatically to collect and record every tracking information.

[0080] The tracking information records include the unique identification code of the RFID tag at multiple time points, signal strength, collection time, personnel information, etc. This information is divided using the unique identification code to obtain the tracking information records corresponding to multiple RFID tags.

[0081] The system automatically filters out RFID tags that remain stationary on shelves for extended periods and does not generate corresponding tracking information records.

[0082] S220 verifies the validity of each tracking information record based on multiple sets of signal data to obtain valid tracking records and invalid tracking records;

[0083] Because RFID signals are susceptible to interference from metal, this embodiment uses anti-metal RFID tags. However, even so, the characteristics of RFID radio frequency signals cannot guarantee signal stability and reliability. Therefore, signal verification is necessary to determine the validity of the tracking information recording. This specifically includes:

[0084] S221, Extract signal strength values ​​at multiple time points from each set of signal data pairs. ,in, Indicates a point in time. Indicates the RFID base station serial number;

[0085] RFID signals are susceptible to interference from metals, electromagnetic interference, and environmental changes during transmission, resulting in dynamic variations in signal strength. By collecting signal strength values ​​from different RFID base stations (i) at multiple time points (t), the temporal variation characteristics of signal strength can be obtained. This is based on the electromagnetic field propagation principle of RFID technology—when electromagnetic waves encounter obstacles such as metal, they are reflected, absorbed, and scattered, leading to fluctuations in signal strength.

[0086] S222, signal strength values ​​at multiple time points Extracting volatility eigenvalues Maximum value Minimum value and overall slope , wherein the overall slope Obtained through linear regression;

[0087] Volatility eigenvalues: These quantify signal stability by calculating the standard deviation or variance of the signal strength time series. This is based on the principle in RFID technology that when electromagnetic waves encounter a spatial target, part of their energy is absorbed by the target, while the other part is scattered in various directions at different intensities. Volatility reflects the degree of interference to the signal.

[0088] Maximum and minimum values: These represent the extreme values ​​of signal strength and are used to determine whether there are abnormal signals.

[0089] Overall slope: By analyzing the trend of signal intensity over time through linear regression, we can determine whether the signal is stable, rising, or falling.

[0090] S223, combine the signal strength values ​​at the same time point from multiple sets of signal data belonging to the same tracking information record to obtain multiple signal strength difference data. and for each signal strength difference data The signal strength values ​​are normalized, and the variance of the differences between the normalized signal strength values ​​is calculated. ,in, Indicates the time point of the first RFID base station The signal strength value, This indicates the time point of the second RFID base station. The signal strength value, Indicates the first RFID base stations at time points The signal strength value;

[0091] S224, the volatility characteristic value The maximum value The minimum value and the overall slope Each with a preset fluctuation characteristic range Reference range of values and maximum slope Compare and calculate the variance of multiple signal strength differences. vs. preset variance range The system compares the data and determines the tracking information record as valid if the target conditions are met; otherwise, it determines the tracking information record as invalid. The target conditions include:

[0092]

[0093]

[0094]

[0095]

[0096]

[0097] In the above comparison of signals from a unified base station, the fluctuation characteristic values ​​are compared. The maximum value The minimum value Evaluate whether the fluctuations and values ​​of the signal strength are normal, and the overall slope. The comparison determines whether there is abnormal signal attenuation or abnormal enhancement.

[0098] Furthermore, by comparing signals from multiple base stations, it is possible to effectively detect local interference that a single base station may be affected by; normalization processing eliminates the impact of hardware differences between different base stations, making the comparison more equitable; variance values ​​can quantify the consistency of signals from multiple base stations, and the smaller the variance, the higher the consistency of signals measured by multiple base stations.

[0099] When the above conditions are met simultaneously, it indicates that the signal conditions are good, and the positioning data obtained by using the signal data of this group as the positioning reference is highly reliable.

[0100] S230, perform positioning on multiple arrival time points of the valid tracking records to obtain valid motion trajectories, and extract the item storage location from the valid motion trajectories; and determine the inertial storage location of the invalid tracking records based on a pre-built inertial database;

[0101] In this application, the time difference of arrival (TDOA) positioning method is used to perform positioning, including the following process:

[0102] S2301, based on the time difference of arrival method combined with multiple arrival time points, calculates positioning and obtains multiple positioning coordinates;

[0103] The location calculation based on the time difference of arrival method combined with multiple arrival time points is an existing technology, which will not be elaborated here.

[0104] S2302, connect multiple positioning coordinates to obtain an initial trajectory; and smooth the initial trajectory to obtain an effective motion trajectory.

[0105] The obtained positioning coordinates are smoothed using a sliding window averaging method.

[0106] After obtaining the valid movement trajectory, extract the starting storage location (for accepting the quest) or the ending storage location (for returning the quest) of the item from the valid movement trajectory. Specifically, this includes:

[0107] S2303, calculate the distance between any two adjacent positioning coordinates. ;

[0108] In the effective motion trajectory, each time point has corresponding positioning coordinates (x, y). The distance is obtained by calculating the Euclidean distance between adjacent coordinates. .

[0109] S2304, arrange multiple distances in chronological order, and use the sliding time window method to extract the average distance of multiple time windows;

[0110] S2305, when the average distance of N consecutive time windows is less than a preset distance threshold, it is determined that the RFID tag is stationary within the N consecutive time windows, and the positioning coordinates of the stationary time points are averaged to obtain the average coordinates; and the average coordinates are used as the storage location of the item.

[0111] By using a sliding time window and coordinate averaging, the reliability of storage location is significantly improved. This method enables RFID systems to more accurately identify the start and end locations of items, providing a reliable data foundation for applications such as item management and inventory tracking, effectively enhancing the value and practicality of RFID technology in real-world applications.

[0112] For invalid tracking records, since their location data is unreliable, an alternative method is used to infer the storage location of RFID items. This involves using big data analysis to build an inertial database, recording the inertial characteristics of the storage locations of different people and different types of items, and then using these inertial characteristics to perform the inference process.

[0113] The methods for constructing an inertial database include:

[0114] (1) Obtain multiple valid historical tracking records;

[0115] The valid historical tracking records are valid tracking records for multiple historical time periods obtained through the screening process described above.

[0116] (2) Extract the information of people entering and leaving, RFID tag information and the location of items from the multiple historical valid tracking records, and extract the item type code from the RFID tag information;

[0117] By extracting key feature information (personnel, items, location), a complete data feature set is constructed. The item type code in RFID tag information is a digital representation of item attributes, providing an important basis for subsequent cluster analysis. Features closely related to the storage location of items are extracted, providing necessary information for inertial feature analysis. The extraction of item type codes achieves a standardized representation of item attributes, facilitating systematic processing.

[0118] (3) The storage location of the item is converted from coordinate type to location code, wherein the location code includes container code and storage unit code;

[0119] Continuous coordinate locations are converted into discrete, identifiable location identifiers (container codes and storage unit codes). This conversion is based on the discretization of spatial locations, mapping physical locations to system-identifiable codes.

[0120] (4) Construct a first sample vector based on the entry and exit personnel information and location code in each historical valid record, and construct a second sample vector based on the item type code and storage unit code in each historical valid record;

[0121] The extracted feature information is converted into a vector form suitable for mathematical analysis. The first sample vector reflects the "person-location" association pattern, and the second sample vector reflects the "item-storage unit" association pattern. This provides a mathematical representation for subsequent clustering analysis.

[0122] (5) Perform density clustering on the first sample vector to obtain multiple first sample vector clusters; and perform density clustering on the second sample vector to obtain multiple second sample vector clusters;

[0123] Density clustering algorithms (such as DBSCAN) are used to identify natural clusters in data. Density clustering can discover clusters of arbitrary shapes and is particularly suitable for discovering habitual patterns in the storage of items.

[0124] Discover natural groupings in the data, identify common storage patterns, and identify stable storage patterns through cluster analysis.

[0125] (6) Select target vector clusters from the plurality of first sample vector clusters and the plurality of second sample vector clusters, wherein the number of samples within the cluster is greater than a preset threshold, wherein each target vector cluster corresponds to an inertial feature;

[0126] A preset threshold is set to ensure the reliability of the clustering results. Only when the number of samples within a cluster exceeds the threshold is the cluster considered to represent a reliable inertial feature.

[0127] Excluding small sample clustering improves the reliability of inertial features; avoids misjudgments caused by random events and ensures that inertial features are statistically significant.

[0128] (7) Extracting inertial features from the target vector cluster and the confidence level of inertial characteristics The confidence level of the inertial feature. The mathematical expression is:

[0129]

[0130] In the formula, The number of valid historical records. The number of samples within the target vector cluster;

[0131] The confidence metric quantifies the reliability of inertial features and provides a confidence reference for the inference process.

[0132] (8) Based on multiple inertial characteristics and confidence levels of multiple inertial features Build an inertial database.

[0133] In the above process, historical data analysis compensates for the unreliability of positioning data caused by RFID signal interference, enabling the system to provide reliable location inference services even in complex environments.

[0134] The process of determining the inertial storage location of the invalid tracking records based on the inertial database constructed according to the above process includes:

[0135] S2306, Extract the information on the types of items from the information on people entering and leaving the invalid tracking records and the information on the RFID tags;

[0136] This step extracts the identities of people entering and exiting (such as employee IDs or roles) and the item type codes (parsed from RFID tag information, such as "electronic components-001") from invalid records, transforming unstructured data into analyzable feature vectors.

[0137] S2307, the entry and exit personnel information and the item type information are respectively matched with multiple inertial features in the inertial database to obtain a first inertial feature matching the entry and exit personnel information, and / or a second inertial feature matching the item type information;

[0138] Multi-dimensional matching is performed based on feature vector clusters from an inertial database (constructed from historical valid records):

[0139] First inertial feature: Match personnel information with historical "personnel-location" association patterns (such as "Zhang San → Container in Area A");

[0140] Second inertial feature: Match the item type code with the historical "item-storage unit" association pattern (e.g., "electronic component → unit 3");

[0141] The matching process uses vector similarity calculation (such as cosine similarity). A match is determined when the cosine similarity is greater than a set similarity threshold.

[0142] S2308, when the invalid tracking record includes a first inertial feature or a second inertial feature, extract the position code from the first inertial feature or the second inertial feature as the inertial storage position;

[0143] When only the first inertial feature (personnel) or the second inertial feature (item type) is matched, the corresponding location code (such as container code + storage unit code) is directly extracted as the inertial storage location. This is based on the strong correlation between "feature-location" in the inertial database (such as 80% of "Zhang San's" operations are in area A), ensuring that the inference process is simple and reliable.

[0144] S2309, when both the first inertial feature and the second inertial feature exist in the invalid tracking record, the first inertial feature and the second inertial feature are compared.

[0145] S2310, when the first inertial feature and the second inertial feature are consistent, extract the storage location information from the first inertial feature or the second inertial feature to obtain the inertial storage location;

[0146] When both the first and second inertial features are matched simultaneously, first verify whether they are consistent (e.g., "Zhang San → Area A" and "Electronic Component → Area A Unit 3"). If they are consistent, it means that the inertial patterns of the personnel and the items point to the same location, and the location code is directly extracted.

[0147] S2311, when the first inertial feature and the second inertial feature are inconsistent, extract the first position code from the first inertial feature. and the confidence level of the first inertial feature And extract the second position code from the second inertial feature. and the confidence level of the second inertial feature ;

[0148] S2312, based on the first position code Corresponding confidence level Calculate the conversion amount of the number of changes in the first position code. and based on the second position encoding Corresponding confidence level Calculate the conversion amount of the number of changes in the second position code. Wherein, the number of changes in the first position code is converted into a certain amount. The conversion amount of the number of changes in the second position code The mathematical expressions are as follows:

[0149]

[0150] S2313, Calculate the number of changes based on the first position code. The conversion amount of the number of changes in the second position code Establish an inertial storage location.

[0151] In steps S2326-S2328, when the first inertial feature and the second inertial feature are inconsistent, a conversion logic is used to infer the possible inertial storage location. The above formula is used to quantify the location stability: the lower the confidence level (insufficient data support), the lower the conversion amount of the number of changes, indicating a lower risk of location change.

[0152] The above process scientifically quantifies uncertainty, transforming the confidence level into a calculable indicator by converting the number of changes into a variable, thus avoiding subjective judgment. Simultaneously, through mathematical conversion, positions with lower converted numbers of changes (i.e., positions with higher confidence) are prioritized, improving accuracy.

[0153] S240, based on the item storage location or inertial storage location recorded by multiple tracking information, update the item storage initial information of the previous storage period to obtain item storage update information;

[0154] The specific process includes:

[0155] S2401, Obtain the initial storage information of the items in the previous storage period, wherein the initial storage information of the items is stored in matrix form, each row of the matrix represents the storage information encoded at each position, and the storage information in each row includes the currently stored items and the number of changes.

[0156] The matrix expression for the initial information of the items is as follows:

[0157]

[0158] In the above formula, This indicates the location code of the first storage location. A unique identifier for the fixed asset in the first storage location. This indicates the current cumulative number of changes to the first storage location; Indicates the first The location code of each storage location. For the first A unique identifier for fixed assets at each storage location. Indicates the first The current cumulative number of changes to each storage location.

[0159] S2402, the matrix is ​​updated based on the item storage location or inertial storage location recorded by multiple tracking information records to obtain item storage update information. The update rule is as follows: during each update, the number of changes in the target row corresponding to the location code is accumulated based on the number of changes or the number of changes converted, and the currently stored items in the target row are added / reduced based on the unique identification code of the RFID tag information.

[0160] At each change, the number of changes in the target row corresponding to the location code is accumulated, and the currently stored items are updated based on the item change nature (addition / reduction) recorded in the tracking information.

[0161] S250, calculate the difference information between the initial storage information of the item and the updated storage information of the item. When the value of the difference information is greater than a preset difference threshold, or when the time difference between the current time point and the timestamp of the initial storage information of the item reaches a preset duration threshold, generate an inventory task based on the difference information, and send the inventory task to the inventory personnel and perform inventory management. The inventory task includes the inventory location.

[0162] This embodiment employs an automated inventory task distribution method. By calculating the changes, when the accumulated changes reach a certain level, an inventory task is automatically generated and distributed. The calculation of the changes includes:

[0163] S2501, Calculate the difference matrix between the matrix containing the initial information of the item and the matrix containing the updated information of the item;

[0164] The difference matrix reflects the difference between the storage information at the current time point and the initial storage information at the beginning of the current inventory cycle.

[0165] S2502, perform a weighted summation based on dynamic weights on the columns representing the number of changes in the difference matrix to obtain the value of the difference information.

[0166] The difference information is obtained by performing a weighted summation based on frequency decay for all the number of changes.

[0167]

[0168]

[0169] In the above formula, Indicates the total number of position codes. Indicates the first The difference in the number of changes to the storage location indicates the value of the first storage location. Dynamic weights for each storage location.

[0170] In the above calculation formula, dynamic weights Follow The increase is followed by a slow decline, among which, Satisfy: greater than 1 and follows The increase is slow (multiple changes at the same position are decayed to avoid the repeated changes at the same position affecting the overall change).

[0171] When the value of the discrepancy information exceeds the preset discrepancy threshold, it indicates that the changes in the integration have become significant, and an inventory check is required. Furthermore, the process of generating and issuing the inventory check task includes:

[0172] S2503, Filter out rows whose number of changes is greater than a preset threshold from the difference matrix to obtain the target row and the target position code corresponding to the target row;

[0173] By filtering areas with high frequency of changes, ineffective inventory checks are avoided on areas with slow changes (such as long-term stable storage units), and inventory resources are focused on actual problem areas (such as areas with high frequency of movement), improving inventory efficiency by more than 30%.

[0174] S2504, determine the inventory range based on the target location code, and generate an inventory task based on the inventory range;

[0175] The system automatically expands the inventory scope based on the target location code (such as "Container A-Unit 3").

[0176] S2505, the inventory task is sent to the inventory personnel. When the inventory personnel enter the passage door, the inventory mode is entered and other people are temporarily prohibited from entering / leaving the warehouse. When the inventory personnel leave the passage door, the inventory mode is deactivated.

[0177] During the inventory process, in order to avoid interference from other personnel, the warehouse needs to be sealed off through the access door (except for information inventory tasks).

[0178] Figure 3 This is a schematic diagram of the information inventory task execution process in one embodiment of this application, such as... Figure 3 As shown, the process of issuing and executing information inventory tasks in this application (the business process of the metering package management system - simplified information inventory of secondary metering packages) includes: formulating and issuing simplified flat inventory information inventory tasks - receiving information inventory tasks - starting to execute information inventory tasks - uploading information judgment data - receiving task information.

[0179] Figure 4 This is a schematic diagram of the physical inventory task execution process in one embodiment of this application, such as... Figure 4 As shown, the process of issuing and executing the physical inventory task in this application (the business process of the metering package management system - physical inventory of the simplified flat warehouse for secondary metering packages) includes: formulating and issuing the information inventory task for the simplified flat warehouse - receiving the physical inventory task - starting to execute the inventory task (while closing the passage door, not allowing other inbound and outbound tasks to be executed) - preparing the inventory equipment according to the inventory task - arriving at the passage door and logging into the system, clicking to open the door - pushing the equipment into the radio frequency door (passage door) - clicking to start scanning when reaching the target position - uploading the scan data after scanning is completed - pushing the inventoried equipment back to its original position and receiving and verifying the scan results - when all RFID information within the inventory range is included, the inventory is completed, and the inventory surplus and shortage information is confirmed. If the inventory task is not completed, return to pushing the equipment into the radio frequency door (passage door) and repeat the execution until it is completed.

[0180] This invention discloses a real-time tracking and inventory method for items based on RFID technology and access gates. The method involves pre-setting access gates and RFID base stations to collect information on all personnel entering and exiting the warehouse during the current inventory cycle, along with their RFID tags and signal data, to obtain tracking information records. Considering the susceptibility of RFID signals to interference, this invention verifies the tracking information records based on the signal data. Based on the verification results, the tracking information records are divided into valid and invalid records. Valid records can be directly located to determine the storage location of the items, while invalid records utilize an inertial database to infer the inertial storage location. The storage information is then updated using the storage location. When the update reaches a certain level, an inventory task is automatically issued, and an inventory range is generated based on the discrepancies. This invention enables full-process management of warehouse inventory based on RFID technology, while also guiding inventory tasks, effectively improving the efficiency of RFID-based asset inventory within the warehouse.

[0181] like Figure 5 As shown, this application also provides a real-time item tracking and inventory system based on RFID technology and access gates, including:

[0182] The acquisition module is used to acquire multiple tracking information records of the current inventory cycle of the warehouse. The tracking information records include the entry time of the passage door, the information of the people entering and exiting, the RFID tag information of the items carried by the people entering and reading by the passage door, and multiple sets of signal data of the RFID tag information. The multiple sets of signal data come from multiple RFID base stations, and the signal data includes the signal strength and arrival time at multiple time points.

[0183] The verification module is used to verify the validity of each tracking information record based on multiple sets of signal data, and to obtain valid tracking records and invalid tracking records;

[0184] The positioning module is used to perform positioning on multiple arrival time points of the valid tracking records to obtain valid motion trajectories and extract the item storage location from the valid motion trajectories; and to determine the inertial storage location of the invalid tracking records based on a pre-built inertial database.

[0185] The update module is used to update the initial storage information of the items in the previous storage period based on the storage location or inertial storage location of the items recorded by multiple tracking information records, so as to obtain the item storage update information;

[0186] The inventory management module is used to calculate the difference between the initial storage information and the updated storage information of the items. When the value of the difference is greater than a preset difference threshold, or when the time difference between the current time and the timestamp of the initial storage information of the items reaches a preset duration threshold, an inventory task is generated based on the difference information, the inventory task is sent to the inventory personnel and the inventory management is performed. The inventory task includes the inventory location.

[0187] This invention relates to a real-time inventory tracking system based on RFID technology and access gates. The system pre-sets access gates and RFID base stations to collect information on all personnel entering and exiting the warehouse during the current inventory cycle, along with their RFID tags and signal data, thus obtaining tracking information records. Considering the susceptibility of RFID signals to interference, this application verifies the tracking information records based on the signal data. Based on the verification results, the tracking information records are divided into valid and invalid records. Valid records can be directly located to determine the storage location of the items, while invalid records utilize an inertial database to infer the inertial storage location. The system then updates the stored information using the storage location. When the update reaches a certain level, an inventory task is automatically issued, and an inventory range is generated based on the discrepancies. This application enables full-process management of warehouse inventory based on RFID technology, while also guiding inventory tasks, effectively improving the efficiency of RFID-based asset inventory within the warehouse.

[0188] Figure 6 A schematic diagram of a computer system suitable for implementing the embodiments of this application is shown. It should be noted that... Figure 6 The computer system of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0189] like Figure 6 As shown, the computer system includes a Central Processing Unit (CPU) 601, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, based on programs stored in Read-Only Memory (ROM) 602 or programs loaded from storage portion 608 into Random Access Memory (RAM) 603. The RAM 603 also stores various programs and data required for system operation. The CPU 601, ROM 602, and RAM 603 are interconnected via a bus 604. An Input / Output (I / O) interface 605 is also connected to the bus 604.

[0190] The following components are connected to I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I / O interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 610 as needed so that computer programs read from it can be installed into storage section 608 as needed.

[0191] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and / or installed from removable medium 611. When the computer program is executed by central processing unit (CPU) 601, it performs various functions defined in the system of this application.

[0192] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0193] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0194] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0195] Another aspect of this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a computer's processor, causes the computer to perform the method as described above. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0196] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various embodiments described above.

[0197] The above embodiments are merely preferred embodiments provided to fully illustrate this application, and the scope of protection of this application is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on this application are all within the scope of protection of this application.

Claims

1. A real-time tracking and inventory method of items based on RFID technology and access gates, characterized in that, The method comprises the steps of: acquiring a plurality of tracking information records of a current inventory cycle of a warehouse, wherein the tracking information records comprise an entry time point of a channel door, entry personnel information, RFID tag information of an entry person's carried article read by the channel door, and a plurality of groups of signal data of the RFID tag information, the plurality of groups of signal data being from a plurality of RFID base stations, and the signal data comprising signal strength and arrival time points at a plurality of time points; The validity of each tracking information record is verified based on multiple sets of signal data to obtain valid and invalid tracking records. This verification process includes extracting signal strength values ​​at multiple time points from each set of signal data. ,in, Indicates a point in time. Indicates the RFID base station serial number; signal strength values ​​from multiple time points. Extracting volatility eigenvalues Maximum value Minimum value and overall slope , wherein the overall slope The signal strength values ​​at the same time point from multiple sets of signal data belonging to the same tracking information record were combined using linear regression to obtain multiple signal strength difference data. and for each signal strength difference data The signal strength values ​​are normalized, and the variance of the differences between the normalized signal strength values ​​is calculated. ,in, Indicates the time point of the first RFID base station The signal strength value, This indicates the time point of the second RFID base station. The signal strength value, Indicates the first RFID base stations at time points The signal strength value; the fluctuation characteristic value The maximum value The minimum value and the overall slope Each is different from the preset fluctuation characteristic range Reference range of values and maximum slope Compare and calculate the variance of multiple signal strength differences. vs. preset variance range The system compares the data and determines the tracking information record as valid if the target conditions are met; otherwise, it determines the tracking information record as invalid. The target conditions include: , , , , ; performing positioning on a plurality of arrival time points of the valid tracking records to obtain valid motion trajectories, and extracting article storage positions from the valid motion trajectories; and determining inertial storage positions of the invalid tracking records based on a pre-constructed inertia database; updating article storage initial information of a previous storage cycle based on the article storage positions or the inertial storage positions of the plurality of tracking information records to obtain article storage update information; calculating difference information of the article storage initial information and the article storage update information, generating an inventory task based on the difference information when a value of the difference information is greater than a preset difference threshold or a time difference between a current time point and a timestamp of the article storage initial information reaches a preset time length threshold, and sending the inventory task to an inventory person and performing inventory management, wherein the inventory task comprises an inventory location.

2. The RFID technology and portal gate based real-time tracking and inventory method of articles according to claim 1, characterized in that, performing positioning on a plurality of arrival time points of the valid tracking records to obtain valid motion trajectories, comprising: calculating positioning based on an arrival time difference method combined with a plurality of arrival time points to obtain a plurality of positioning coordinates; connecting the plurality of positioning coordinates to obtain an initial trajectory; and performing smoothing processing on the initial trajectory to obtain a valid motion trajectory.

3. The RFID technology and portal gate based real-time tracking and inventory method of articles according to claim 1, characterized in that, extracting article storage positions from the valid motion trajectories, comprising: calculating the distance of any two adjacent positioning coordinates ; arranging a plurality of distances in chronological order, and extracting average distances of a plurality of time windows by using a sliding time window method; when average distances of N continuous time windows are all less than a preset distance threshold, determining that the RFID tag is stationary in the N continuous time windows, and averaging positioning coordinates of stationary time points to obtain an average coordinate; and taking the average coordinate as an article storage position.

4. The RFID technology and portal gate based real-time tracking and inventory method of articles according to claim 1, characterized in that, The construction method of the inertia database comprises: acquiring a plurality of historical valid tracking records; extracting entry personnel information, RFID tag information, and article storage positions from the plurality of historical valid tracking records, and extracting article type codes from the RFID tag information; converting the article storage positions from coordinate types to position codes, wherein the position codes comprise cabinet codes and storage unit codes; constructing a first sample vector based on the entry personnel information and the position codes in each historical valid record, and constructing a second sample vector based on the article type codes and the storage unit codes of each historical valid record; performing density clustering on the first sample vector to obtain a plurality of first sample vector clusters; and performing density clustering on the second sample vector to obtain a plurality of second sample vector clusters; Filtering, from the plurality of first sample vector clusters and the plurality of second sample vector clusters, a target vector cluster with a number of intra-cluster samples greater than a preset number threshold, wherein each target vector cluster corresponds to an inertia feature; Extracting inertial features from a target vector cluster and a confidence of the inertial features wherein the confidence of the inertial features is mathematically expressed as: wherein, is the number of historical valid records, and c is the number of samples in the target vector cluster. Based on a plurality of inertial features And a confidence of the plurality of inertial features An inertial database is constructed.

5. The RFID technology and portal gate based real-time tracking and inventory method of articles according to claim 4, characterized in that, Determining, based on a pre-constructed inertia database, an inertia storage location of the invalid tracking record, comprising: Extracting, from the invalid tracking record, access personnel information and article category information in RFID tag information; Matching the access personnel information and the article category information with a plurality of inertia features in the inertia database respectively to obtain a first inertia feature matched with the access personnel information and / or a second inertia feature matched with the article category information; When the first inertia feature or the second inertia feature is included in the invalid tracking record, extracting a location code from the first inertia feature or the second inertia feature as the inertia storage location; When the first inertia feature and the second inertia feature exist in the invalid tracking record simultaneously, comparing the first inertia feature with the second inertia feature; When the first inertia feature and the second inertia feature are consistent, extracting storage location information in the first inertia feature or the second inertia feature to obtain the inertia storage location; extracting a first position encoding from the first inertial feature and a confidence of the first inertial feature and extracting a second position encoding from the second inertial feature and a confidence of the second inertial feature ; based on the first position encoding a corresponding confidence a number-of-variations conversion amount of the first position encoding , and based on the second position encoding a corresponding confidence a number-of-variations conversion amount of the second position encoding wherein the number-of-variations conversion amount of the first position encoding and the number-of-variations conversion amount of the second position encoding are respectively a conversion amount of a number of times of variation based on the first position code and a conversion amount of a number of times of variation based on the second position code constructing an inertial storage location.

6. The RFID technology and portal gate based real-time tracking and inventory method of articles according to claim 5, characterized in that, Updating article storage initial information of a previous storage period based on article storage locations or inertia storage locations of a plurality of tracking information records to obtain article storage update information, comprising: Obtaining article storage initial information of a previous storage period, wherein the article storage initial information is stored in a matrix form, each row of the matrix represents storage information of each location code, and the storage information of each row includes a current storage article and a number of changes; Updating the matrix based on article storage locations or inertia storage locations of a plurality of tracking information records to obtain article storage update information, wherein the update rule is that, at each update, the number of changes in a target row corresponding to a location code is accumulated based on the number of changes or a change conversion number, and the current storage article in the target row is updated based on a unique identification code of the RFID tag information.

7. The RFID technology and portal gate based real-time tracking and inventory method of articles according to claim 6, characterized in that, Calculating difference information of the article storage initial information and the article storage update information, comprising: Calculating a difference matrix of the matrix of the article storage initial information and the matrix of the article storage update information; Performing weighted summation based on dynamic weights on columns representing the number of changes in the difference matrix to obtain a value of the difference information.

8. The RFID technology and portal gate based real-time tracking and inventory method of claim 7, wherein, Generating an inventory task based on the difference information, and sending the inventory task to an inventory person and performing inventory management, comprising: Filtering, from the difference matrix, a row with a number of changes greater than a preset number threshold to obtain a target row and a target location code corresponding to the target row; Determining an inventory range based on the target location code, and generating an inventory task based on the inventory range; Sending the inventory task to the inventory person, entering an inventory mode when the inventory person enters a channel door, temporarily prohibiting other people from entering / leaving the warehouse, and exiting the inventory mode when the inventory person leaves the channel door.

9. An article real-time tracking and inventory system based on RFID technology and access gates, characterized in that, Comprising: An acquisition module is configured to acquire a plurality of tracking information records of a current inventory cycle of a warehouse, wherein the tracking information records include an entry time point of a channel door, entry personnel information, RFID tag information of an article carried by an entry person read by the channel door, and a plurality of groups of signal data of the RFID tag information, the plurality of groups of signal data are from a plurality of RFID base stations, and the signal data includes signal strength and an arrival time point at a plurality of time points; The verification module is used to verify the validity of each tracking information record based on multiple sets of signal data, obtaining valid and invalid tracking records. This verification process includes extracting signal strength values ​​at multiple time points from each set of signal data. ,in, Indicates a point in time. Indicates the RFID base station serial number; signal strength values ​​from multiple time points. Extracting volatility eigenvalues Maximum value Minimum value and overall slope , wherein the overall slope The signal strength values ​​at the same time point from multiple sets of signal data belonging to the same tracking information record were combined using linear regression to obtain multiple signal strength difference data. and for each signal strength difference data The signal strength values ​​are normalized, and the variance of the differences between the normalized signal strength values ​​is calculated. ,in, Indicates the time point of the first RFID base station The signal strength value, This indicates the time point of the second RFID base station. The signal strength value, Indicates the first RFID base stations at time points The signal strength value; the fluctuation characteristic value The maximum value The minimum value and the overall slope Each is different from the preset fluctuation characteristic range Reference range of values and maximum slope Compare and calculate the variance of multiple signal strength differences. vs. preset variance range The system compares the data and determines the tracking information record as valid if the target conditions are met; otherwise, it determines the tracking information record as invalid. The target conditions include: , , , , ; A positioning module is configured to perform positioning on a plurality of arrival time points of the valid tracking records, obtain an effective motion trajectory, and extract an article storage position from the effective motion trajectory; and determine an inertial storage position of the invalid tracking records based on a pre-constructed inertial database; An update module is configured to update article storage initial information of a previous storage cycle based on the article storage position or the inertial storage position of the plurality of tracking information records, and obtain article storage update information; An inventory management module is configured to calculate difference information of the article storage initial information and the article storage update information, generate an inventory task based on the difference information when a value of the difference information is greater than a preset difference threshold or a time difference between a current time point and a timestamp of the article storage initial information reaches a preset time length threshold, and send the inventory task to an inventory person and perform inventory management, wherein the inventory task includes an inventory location.

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