Intelligent traceable hazardous waste management system based on RFID

Abstract

The invention discloses an intelligent traceable hazardous waste management system based on RFID, particularly relates to the technical field of hazardous waste intelligent supervision, and is used for solving the problems of unreliable data acquisition, misreading and misreading and state updating delay caused by signal interference of an existing RFID system in a high-density hazardous waste storage scene. The method comprises the following steps: dynamically dividing warehouse sub-regions, distributing a unique grouping identification code, and combining a directional antenna array partition scanning technology to avoid signal crosstalk; by analyzing the multi-path phase fluctuation rate and the polarization direction offset, a main interference frequency band is dynamically identified by using a covariance decomposition algorithm, and the communication frequency is switched, so that the tag identification rate in a complex electromagnetic environment is improved; scheduling a target sub-region scanning process based on a warehouse-in and warehouse-out instruction, synchronously verifying a label state and an actual position, generating an operation link space-time atlas, actively tracing cross-region time logic contradictions and triggering full-disk scanning; and full-process accurate tracing of the hazardous waste container and complete data management and control in a high-density scene are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent supervision of hazardous waste. More specifically, the present invention relates to an intelligent traceable hazardous waste management system based on RFID. Background Art

[0002] In the field of hazardous waste management, tracking systems based on RFID technology have been widely used for the identification of hazardous waste containers and process monitoring. The prior art realizes the automatic collection of basic information such as the type, weight, and location of hazardous waste by deploying RFID tags on hazardous waste containers and combining fixed or handheld reading and writing devices. Such systems can replace the traditional manual recording method and meet the basic requirements of regulatory authorities for the traceability of hazardous waste data, especially suitable for conventional scenarios from the generation end to the temporary storage end of hazardous waste.

[0003] However, in the actual scenario of high-density centralized storage of hazardous waste, the reliability of data collection of the existing RFID system is significantly reduced. Due to the dense stacking of a large number of hazardous waste containers, the label signals are subject to the combined interference of metal materials, liquid media, and space occlusion, resulting in the inability of the reading and writing device to stably identify all labels. At the same time, the dynamic inbound and outbound operations of hazardous waste containers further exacerbate signal conflicts, causing missed readings, misreadings, and delays in status updates. This problem directly destroys the integrity and real-time nature of hazardous waste data, making it difficult for regulatory authorities to verify the true inventory and operation compliance in the storage link. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent traceable hazardous waste management system based on RFID to solve the problems proposed in the above background art.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] An intelligent traceable hazardous waste management system based on RFID, comprising the following modules:

[0007] Region division module: Divide multiple signal reading and writing sub-regions according to the storage location of hazardous waste containers and the warehouse space parameters, and assign a unique group identification code to each sub-region;

[0008] Reading and writing control module: Based on the group identification code, control the RFID reader to activate the directional antenna array corresponding to the sub-region and scan the RFID tags of hazardous waste containers in the sub-region;

[0009] Frequency band optimization module: When detecting that there are multiple overlapping RFID tag signals in the same sub-region, determine the interference frequency band through covariance decomposition based on the multipath phase volatility and polarization direction offset, and switch and perform a secondary scan;

[0010] Instruction Scheduling Module: Extract the target grouping identification code according to the inbound and outbound instructions of the hazardous waste container, activate the directional antenna array of the target sub-region, and pause the scanning process of the non-target sub-region;

[0011] Data Synchronization Module: Compare the recognized RFID tag data with the pre-stored information in the database. If the tag status is inconsistent with the actual storage location or operation stage, update the database and generate a synchronization log;

[0012] Spectrum Alarm Module: Extract the status change records in the synchronization log and the physical operation time nodes to construct a spatio-temporal spectrum of the operation link. When there are cross-regional time logic contradictions, trigger a full scan and send a path alarm.

[0013] In a preferred embodiment, dividing multiple signal reading and writing sub-regions includes the following steps:

[0014] According to the storage location coordinates of the hazardous waste container and the shelf height and spacing in the warehouse space parameters, divide the storage area into multiple cuboid-shaped sub-regions, and assign a grouping identification code including the warehouse location code and the shelf layer number to each sub-region.

[0015] In a preferred embodiment, the shelf height and spacing are used to determine the vertical and horizontal boundaries of the sub-region. The warehouse location code is a combination of letters and numbers, and the shelf layer number is represented by a digital code.

[0016] In a preferred embodiment, controlling the RFID reader to activate the directional antenna array of the corresponding sub-region includes the following steps:

[0017] Based on the location code in the grouping identification code, control the multi-beam directional antenna of the reader to activate the target sub-region at a preset elevation angle and radiation power. The elevation angle is dynamically adjusted according to the shelf layer number, the radiation power is set as a gradient value according to the sub-region area, and the dynamic frame time slot polling mechanism is used to scan the RFID tags of the hazardous waste containers in the corresponding sub-region. The polling period is inversely proportional to the tag density in the sub-region.

[0018] In a preferred embodiment, determining the interference frequency band includes the following steps:

[0019] Extract the multipath phase volatility and polarization direction offset of each RFID tag signal in the same sub-region, and calculate the frequency band correlation of the main interference path through the eigenvalue decomposition of the covariance matrix;

[0020] The multipath phase volatility is the phase standard deviation of adjacent signal cycles, and the polarization direction offset is the change amount of the included angle between the polarization direction of the tag antenna and the antenna of the reader;

[0021] Select the frequency band with a frequency band correlation lower than the preset threshold as the target interference frequency band for switching.

[0022] In a preferred embodiment, the steps for activating the directional antenna array of the target sub-region are as follows:

[0023] Analyze the target shelf layer number and location code in the waste container in-out warehouse instruction, match the corresponding grouping identification code, and control the reader-writer to activate the directional antenna of the target sub-region with the maximum radiation power, while turning off the antenna power supply of the non-target sub-region.

[0024] In a preferred embodiment, the maximum radiation power is dynamically increased according to the proportion of metal containers in the target sub-region.

[0025] In a preferred embodiment, the proportion of metal containers is obtained by statistical analysis of historical scanning data.

[0026] In a preferred embodiment, the steps for updating the database and generating a synchronization log are as follows:

[0027] When the operation stage recorded by the RFID tag of the waste container is "out of the warehouse" but the actual storage location has not left the warehouse, overwrite and update the tag status to "pending out of the warehouse", and record the status change time and operator identification in the synchronization log, where the actual storage location is confirmed by comparing the reader-writer scanning result with the coordinates of the warehouse electronic map, and the operator identification is extracted from the in-out warehouse instruction.

[0028] In a preferred embodiment, the steps for constructing the spatio-temporal map of the operation link are as follows:

[0029] Extract the outbound timestamp and inbound timestamp at the receiving location of the waste container from the synchronization log. When the outbound time is later than the inbound time of the same container, mark it as a cross-region time logic contradiction and trigger a full scan, where the inbound timestamp is extracted from the reader-writer scanning log at the receiving location, and the full scan covers all waste containers in the target sub-region and its adjacent sub-regions.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. Through the dynamic partitioning and multi-dimensional signal optimization mechanism, the reliability of data acquisition in high-density waste storage scenarios is significantly improved; based on the partition control strategy of the grouping identification code, combined with the precise scanning of the directional antenna array, the problem of signal crosstalk in adjacent regions is effectively avoided, ensuring that the reader-writer only activates the target sub-region, and greatly reducing the multipath reflection and signal attenuation caused by the stacking of metal containers; by real-time analyzing the multipath phase volatility and polarization direction offset, dynamically identifying the main interference frequency band and implementing frequency band switching, the environmental adaptability limitation of the traditional single-frequency anti-collision algorithm is broken through, enabling stable acquisition of tag data in a complex electromagnetic interference environment and solving the problems of missed reading and misreading caused by the dense stacking of waste containers;

[0032] 2. The intelligent scheduling mechanism driven by operation instructions realizes the refined control of the hazardous waste transfer link; the reverse tracing function based on the spatio-temporal map deeply associates the physical operation nodes with the database change records, actively identifies the cross-regional time logic contradictions, triggers the directional full-scale scan, and makes up for the defect that the traditional tracing system only relies on single-point data verification; the data synchronization module forcibly updates the label status and storage location to ensure the data consistency of the hazardous waste containers during the dynamic inbound and outbound processes, avoids the inventory misreporting caused by manual operation errors or equipment missed readings, and provides full-cycle and highly reliable data support for hazardous waste supervision. Brief Description of the Drawings

[0033] Figure 1 It is a schematic structural diagram of the RFID-based intelligent traceable hazardous waste management system of the present invention. Detailed Embodiments

[0034] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0035] Embodiment: Figure 1 A schematic structural diagram of the RFID-based intelligent traceable hazardous waste management system of the present invention is given. The RFID-based intelligent traceable hazardous waste management system includes the following modules:

[0036] Region Division Module: Divide multiple signal reading and writing sub-regions according to the storage location of the hazardous waste containers and the warehouse space parameters, and assign a unique group identification code to each sub-region;

[0037] Reading and Writing Control Module: Based on the group identification code, control the RFID reader to activate the directional antenna array of the corresponding sub-region and scan the RFID tags of the hazardous waste containers in the sub-region;

[0038] Frequency Band Optimization Module: When it is detected that there are multiple RFID tag signals overlapping in the same sub-region, determine the interference frequency band through covariance decomposition based on the multipath phase volatility and polarization direction offset, and switch and perform a secondary scan;

[0039] Instruction Scheduling Module: Extract the target group identification code according to the inbound and outbound instructions of the hazardous waste containers, activate the directional antenna array of the target sub-region and pause the scanning process of the non-target sub-regions;

[0040] Data Synchronization Module: Compare the identified RFID tag data with the pre-stored information in the database. If the label status is inconsistent with the actual storage location or operation stage, update the database and generate a synchronization log;

[0041] Spectrum Alarm Module: Extract the status change records and physical operation time nodes in the synchronization log to construct a spatio-temporal graph of the operation link. When there are cross-regional time logic contradictions, trigger a full scan and send a path alarm.

[0042] The storage location coordinates of the hazardous waste container and the shelf height and spacing in the warehouse space parameters are used to divide the warehouse into multiple cuboid-shaped sub-regions. The storage location coordinates are the X-axis, Y-axis, and Z-axis coordinate values of the hazardous waste container in the three-dimensional coordinate system of the warehouse. The three-dimensional coordinate system takes the warehouse ground entrance as the origin, the X-axis extends along the length direction of the warehouse, the Y-axis extends along the width direction of the warehouse, and the Z-axis extends vertically upward. The coordinate values are obtained by calculating the signal strength and time difference of arrival of the RFID reader scanning the label. The warehouse space parameters include the shelf height and the shelf spacing between shelves. The shelf height is the vertical distance from the bottom to the top of a single shelf, which is obtained from the warehouse design drawings or manually measured and input into the system; the shelf spacing is the horizontal interval distance between adjacent shelves, which is set according to the width of the hazardous waste container transportation channel. For example, it is set to 3 meters to meet the forklift passage requirements. Vertically, the warehouse space is cut into several layers based on the shelf height, and the height of each layer is equal to the shelf height. For example, when the shelf height is 2 meters, each 2 meters in the vertical direction is divided into a layer; horizontally, each layer is cut into several columns based on the shelf spacing, and the width of each column is equal to the shelf spacing. For example, when the shelf spacing is 3 meters, each 3 meters in the horizontal direction is divided into a column, and finally multiple cuboid-shaped sub-regions are formed. The side lengths of the cuboid-shaped sub-regions are a three-dimensional combination of the shelf spacing, shelf height, and shelf spacing, such as 3 meters (length) × 3 meters (width) × 2 meters (height).

[0043] Each cuboid-shaped sub-region is assigned a unique grouping identification code, which contains the warehouse location code and the shelf layer number. The warehouse location code is generated based on the position of the sub-region in the warehouse floor grid. A two-dimensional coordinate system is established with the warehouse entrance as the origin for the floor grid. The X-axis and Y-axis correspond to the length and width directions of the warehouse respectively. Each grid cell corresponds to a horizontally cut sub-region. The location code is represented by a combination of letters and numbers. The letters represent the X-axis direction number, which are A, B, C, etc. in sequence from left to right, and the numbers represent the Y-axis direction number, which are 1, 2, 3, etc. in sequence from the entrance to the interior. For example, for a sub-region that is 6 meters from the entrance (the 3rd column in the X-axis direction) and 9 meters in the width direction (the 3rd row in the Y-axis direction), its location code is C3. The shelf layer numbers are incrementally numbered from bottom to top according to the vertical cutting order. The bottom layer is the 01st layer, and upwards are the 02nd layer, 03rd layer, etc. The numbers are fixed as two digits to ensure a unified coding format. The grouping identification code is composed of the location code and the shelf layer number connected by a short dash. For example, for a sub-region with a location code of C3 and a shelf layer number of 02, its grouping identification code is C3-02. The grouping identification code is bound to the warehouse electronic map through a database. The three-dimensional coordinate range of each sub-region in the electronic map corresponds one-to-one with the grouping identification code. The coordinate range includes the starting and ending values of the X-axis, the starting and ending values of the Y-axis, and the starting and ending values of the Z-axis. For example, the coordinate range of the grouping identification code C3-02 is 6 - 9 meters for the X-axis, 9 - 12 meters for the Y-axis, and 2 - 4 meters for the Z-axis.

[0044] The vertical boundary of the sub-region is determined by the shelf height. The vertical boundary value is the bottom and top heights of the layer where the sub-region is located. For example, when the shelf height is 2 meters, the vertical boundary of the 01st layer is 0 - 2 meters, and that of the 02nd layer is 2 - 4 meters. The horizontal boundary is determined by the shelf spacing. The horizontal boundary value is the starting and ending coordinates of the column where the sub-region is located. For example, when the shelf spacing is 3 meters, the location code C3 corresponds to 6 - 9 meters for the X-axis and 9 - 12 meters for the Y-axis. The warehouse management system stores the boundary coordinates of all sub-regions through the electronic map and, when a hazardous waste container is put into storage, automatically matches the grouping identification code of the sub-region to which it belongs according to its storage position coordinates. For example, if the coordinates of a hazardous waste container are X = 7.5 meters, Y = 10.5 meters, and Z = 3 meters, the system determines that it falls into the sub-region with the grouping identification code C3-02 (6 - 9 meters for the X-axis, 9 - 12 meters for the Y-axis, and 2 - 4 meters for the Z-axis), and writes this grouping identification code into the storage field of the container RFID tag.

[0045] When the hazardous waste containers are densely stacked, resulting in the label density in a certain sub-region exceeding the preset threshold, the system recalculates the sub-region division parameters based on the current storage location coordinates and dynamically increases the number of vertical or horizontal cutting layers. The label density threshold is set according to the performance of the reader, for example, set to 10 containers per square meter. When the system detects that the label density in a certain sub-region exceeds this threshold, the dynamic adjustment mechanism is triggered. During adjustment, the original sub-region is preferentially cut into smaller sub-regions in the vertical direction. For example, a sub-region with an original height of 2 meters is cut into two sub-regions of 1 meter each. If the density requirement still cannot be met after vertical cutting, further cutting is performed in the horizontal direction. The adjusted sub-regions are re-allocated with group identification codes. For example, the original group identification code C3-02 is adjusted to C3-02-1 and C3-02-2, and the coordinate range in the electronic map is updated. The group identification codes and coordinate information after dynamic adjustment are synchronized to the read-write control module in real time to ensure that subsequent scanning operations are performed based on the latest partition.

[0046] The generation rule of the group identification code is automatically executed by the configuration function of the warehouse management system. When the warehouse space parameters change, the system re-divides and allocates the group identification codes. For example, when the shelf spacing is adjusted from 3 meters to 4 meters, the number of horizontal cutting columns changes from 5 columns to 3 columns (total width 15 meters ÷ 4 meters ≈ 3.75, rounded down to 3 columns). The system automatically updates the group identification codes and electronic map coordinates of all sub-regions. The original group identification code C3-02 is changed to B2-02 (the 2nd column on the X-axis corresponds to 4 - 8 meters, and the 2nd row on the Y-axis corresponds to 4 - 8 meters). When a hazardous waste container is taken out of the warehouse, the system quickly locates the sub-region to which it belongs based on the group identification code stored in its RFID tag, and schedules the reader to perform directional scanning. For example, when a container with the group identification code C3-02 is taken out of the warehouse, the reader only activates the directional antenna in the C3-02 sub-region to avoid interfering with other sub-regions.

[0047] The location code in the group identification code is used to control the multi-beam directional antenna of the reader to activate the target sub-region at a preset elevation angle and radiation power. The generation method of the group identification code is, for example, the location code C3 represents the sub-region in the X-axis 3rd column and Y-axis 3rd row of the warehouse floor grid. The reader matches the coordinate range of the target sub-region in the electronic map according to the location code. For example, the coordinate range of the sub-region corresponding to the location code C3 is 6 - 9 meters on the X-axis and 9 - 12 meters on the Y-axis. The multi-beam directional antenna of the reader adjusts the beam pointing angle to align the main lobe of the antenna with the center point of the target sub-region coordinate range, for example, the position of 7.5 meters on the X-axis and 10.5 meters on the Y-axis. The beam pointing angle is controlled by the motor drive device of the reader. After receiving the control instruction, the motor drive device rotates the antenna to the target angle, for example, adjusting the horizontal azimuth angle to 30 degrees to cover the range of 6 - 9 meters on the X-axis.

[0048] The elevation angle is dynamically adjusted according to the number of shelves. The number of shelves is determined by the two-digit code in the grouping identification code. For example, "02" in the grouping identification code C3-02 represents the second layer. The reader stores a mapping table of the number of shelves and the elevation angle in advance. For example, the elevation angle corresponding to the first layer is 0 degrees (horizontal direction), the second layer corresponds to an elevation angle of 30 degrees, and the third layer corresponds to an elevation angle of 45 degrees. The reader queries the mapping table according to the layer code in the current grouping identification code and drives the antenna pitching mechanism to adjust to the target elevation angle. For example, when the grouping identification code is C3-02, the elevation angle is adjusted to 30 degrees, so that the main lobe of the antenna covers the vertical range of 2-4 meters on the Z-axis. The radiation power is set as a gradient value according to the sub-region area. The sub-region area is calculated from the coordinate range in the warehouse electronic map. For example, the X-axis is 6-9 meters (length 3 meters), the Y-axis is 9-12 meters (width 3 meters), and the area is 9 square meters. The reader stores the gradient mapping rule of the area and the radiation power in advance. For example, when the area is less than 5 square meters, the power is set to 20 dBm, 5-10 square meters is set to 25 dBm, and above 10 square meters is set to 30 dBm. When the target sub-region area is 9 square meters, the radiation power is set to 25 dBm. The radiation power is dynamically adjusted through the power amplifier of the reader to ensure that the signal strength adapts to the sub-region size.

[0049] The dynamic frame-slotted polling mechanism is used to scan the RFID tags of hazardous waste containers in the corresponding sub-region. The dynamic frame-slotted polling mechanism is an anti-collision algorithm in the prior art, and its initial frame length is adaptively adjusted according to the tag density in the sub-region. The tag density is obtained by counting historical scan data. For example, in the recent 10 scans, an average of 15 tags are identified in the target sub-region, then the tag density is 15 tags / scan cycle. The rule for setting the initial frame length is twice the tag density. For example, when the density is 15, the initial frame length is 30 time slots. The reader broadcasts a query instruction containing the initial frame length at the start of the scan. The tags randomly select time slots to respond. If a collision occurs (multiple tags respond in the same time slot), the frame length is extended according to the binary tree splitting algorithm and the scan is restarted. The polling cycle is inversely proportional to the tag density in the sub-region. The polling cycle is controlled by the timer of the reader. For example, when the tag density is 20 tags per square meter, the polling cycle is set to 50 milliseconds; when the density is 10 tags per square meter, the cycle is set to 100 milliseconds. The adjustment logic of the polling cycle is: for every 5 tags per square meter increase in density, the cycle is shortened by 10 milliseconds, the minimum cycle is 30 milliseconds, and the maximum cycle is 200 milliseconds. For example, when the density of the target sub-region is 15 tags per square meter, the cycle is calculated as 100 milliseconds - (15 - 10) / 5×10 milliseconds = 90 milliseconds.

[0050] During the scanning process, the reader continuously calculates the proportion of collision time slots in real time. If the proportion of collision time slots exceeds a preset threshold (e.g., 30%), dynamic frame length adjustment is triggered. The proportion of collision time slots is the ratio of the number of collision time slots to the total number of time slots. For example, if there are 10 collision time slots out of 30 total time slots, the proportion is 33.3%. The adjustment rule is as follows: when the collision proportion exceeds 30%, the frame length increases by 50%; when the collision proportion is lower than 10%, the frame length decreases by 25%. For example, if the initial frame length is 30 time slots and the collision proportion is 35%, the frame length is adjusted to 45 time slots; when the collision proportion is 8%, the frame length is adjusted to 22.5 time slots (rounded up to 23 time slots). The adjusted frame length is applied to the next scanning cycle until the collision proportion stabilizes within the range of 10% - 30%. After the scanning is completed, the reader uploads the identified tag data (such as tag ID, signal strength, response time) to the database and compares it with the pre-stored information. For example, it verifies whether the tag ID exists in the hazardous waste container registration list in the database.

[0051] The reader continuously monitors the signal quality of the target sub-region during scanning. If the signal strength is lower than a preset threshold (e.g., -70 dBm), radiation power increase is triggered. The signal strength threshold is set according to the reader's sensitivity. For example, when the sensitivity is -80 dBm, the threshold is set to -70 dBm to reserve a 10 dB margin. The radiation power increases by 2 dBm per cycle until the signal strength reaches the threshold or the maximum power limit (e.g., 30 dBm). For example, when the current power is 25 dBm and the signal strength is -75 dBm, the power is increased to 27 dBm, and the signal strength is detected again. If it is still lower than the threshold, it is continued to be increased to 29 dBm. The power adjustment record is written into the log for reference in subsequent scanning cycles. After the scanning of the target sub-region is completed, the reader turns off the power of the directional antenna, releases resources, and waits for the next instruction. For example, it reactivates the target sub-region after receiving the inbound / outbound instruction.

[0052] Extract the multipath phase volatility and polarization direction offset of each RFID tag signal within the same sub-region. The multipath phase volatility is defined as the phase standard deviation of adjacent signal cycles. Adjacent signal cycles are consecutive scanning cycles of the same tag by the reader at fixed time intervals. For example, scanning is performed every 100 milliseconds. The phase value is measured by the phase detection unit of the reader. For example, the phase measured in the first scan is 30 degrees, the second is 45 degrees, and the third is 60 degrees. The phase standard deviation is calculated as 15 degrees. The polarization direction offset is defined as the change in the angle between the polarization direction of the tag antenna and the reader antenna. The polarization direction of the tag antenna is determined by the tag design parameters, such as linear polarization or circular polarization. The polarization direction of the reader antenna is fixed as vertical polarization through its hardware configuration. The change in the angle is measured by the polarization detection module of the reader. For example, the angle measured in the first scan is 5 degrees, the second is 8 degrees, and the offset is 3 degrees.

[0053] Calculate the frequency band correlation of the main interference path through the eigenvalue decomposition of the covariance matrix. The covariance matrix is constructed from the multipath phase volatility and polarization direction offset of all RFID tag signals within the same sub-region. The row and column elements of the matrix represent the statistical correlation of signals in different frequency bands. For example, if there are three frequency bands (865 MHz, 868 MHz, 915 MHz) in the sub-region, the covariance matrix is a 3×3 matrix, and the element C(1,2) represents the covariance value between the 865 MHz and 868 MHz frequency bands. The eigenvalue decomposition decomposes the matrix into eigenvalues and eigenvectors. The eigenvector corresponding to the largest eigenvalue indicates the frequency band distribution of the main interference path. For example, the eigenvector [0.8, 0.2, 0.1] indicates that the main interference path is concentrated in the 865 MHz frequency band. The frequency band correlation is calculated after normalizing the eigenvalues. For example, if the largest eigenvalue accounts for 80% of the sum of all eigenvalues, the frequency band correlation is 80%.

[0054] Select the frequency bands with a frequency band correlation lower than the preset threshold as the target interference frequency bands for switching. The preset threshold is set according to historical interference data. For example, through experimental statistics, it is found that when the frequency band correlation is lower than 30%, the signal conflict probability drops to less than 5%. Therefore, the threshold is set to 30%. If the calculated frequency band correlations are 865 MHz (80%), 868 MHz (15%), and 915 MHz (5%), then select 868 MHz and 915 MHz as the target interference frequency bands. The reader switches to the corresponding communication frequency according to the target frequency band, for example, switches from 865 MHz to 868 MHz, and re-scans the hazardous waste container tags within the switched frequency band. During the switch, the reader sends a frequency band switch command to the tag, and the tag adjusts the resonance circuit frequency according to the command to match the new frequency band. For example, if the original resonance frequency of the tag is 865 MHz, it is adjusted to 868 MHz after the switch.

[0055] After the frequency band switch, the reader records the switch time and the target frequency band parameters, and updates the frequency band usage record in the database. For example, the continuous usage time of the target frequency band 868 MHz is set to 10 minutes, and it automatically switches back to the initial frequency band after the timeout to avoid frequency occupancy conflicts. If there are still signal conflicts in the switched frequency band (for example, the conflict time slot ratio exceeds 30%), then trigger the secondary frequency band selection process, for example, select the sub-frequency band with the lowest correlation (such as 915.2 MHz to 915.8 MHz) from the 915 MHz frequency band for fine-tuning. The range of the sub-frequency bands selected for the second time is determined according to the frequency tuning accuracy of the reader. For example, when the tuning accuracy is 0.1 MHz, the sub-frequency band interval is set to 0.2 MHz.

[0056] During the frequency band switching process, the reader monitors signal quality metrics (such as signal-to-noise ratio, bit error rate). If the signal quality is below a preset threshold (for example, the signal-to-noise ratio is below 10 dB), the frequency band fallback mechanism is triggered. The signal-to-noise ratio threshold is set according to the tag sensitivity. For example, when the tag sensitivity is -80 dBm, the threshold is set to 10 dB to reserve communication margin. During frequency band fallback, the reader switches to the previous available frequency band and rescans. For example, it falls back from 868 MHz to 865 MHz, and at the same time records the fallback event for subsequent frequency band optimization reference.

[0057] By extracting the multipath phase volatility and polarization direction offset, and combining with the eigenvalue decomposition of the covariance matrix, the main interference frequency band in the densely stacked scenario of hazardous waste containers is accurately identified. The multipath phase volatility quantifies the stability of the signal phase with the path change, and the polarization direction offset reflects the polarization mismatch degree between the tag and the reader antenna. The two work together to distinguish the metal container reflection signal from the real tag signal. Compared with the existing technology that only relies on signal strength or single frequency band switching, using multi-physical field parameters (phase, polarization) to construct a covariance matrix, and locating the interference source frequency band through eigenvalue decomposition, and dynamically switching to a low-correlation frequency band, significantly reduces the signal attenuation and multipath interference caused by metal containers. Combining the electromagnetic wave propagation characteristics (multipath effect, polarization matching) with statistical analysis methods, breaking through the limitation of a single signal index, especially suitable for the high-density storage scenario of hazardous waste, solves the problem of unreliable data collection caused by material interference and signal overlap in the existing technology, and ensures the integrity and real-time of the traceability of the hazardous waste operation link.

[0058] Parse the target shelf layer number and location code in the hazardous waste container inbound and outbound instruction, and match the corresponding group identification code. The inbound and outbound instruction is generated by the warehouse management system and contains the target storage or removal location information of the hazardous waste container. For example, the instruction format is "Outbound - Shelf Layer 02 - Location Code C3". The target shelf layer number is a two-digit code. For example, "02" represents the 2nd layer in the vertical direction; the location code is represented by a combination of letters and numbers. For example, "C3" represents the 3rd column on the X-axis and the 3rd row on the Y-axis in the warehouse plane grid. After the reader parses the instruction, it extracts the target shelf layer number "02" and the location code "C3", and matches them with the pre-stored list of group identification codes. For example, it matches that the sub-region coordinates corresponding to the group identification code C3-02 are 6-9 meters on the X-axis, 9-12 meters on the Y-axis, and 2-4 meters on the Z-axis.

[0059] Control the reader to activate the directional antenna of the target sub-region with the maximum radiation power. The maximum radiation power is dynamically increased according to the proportion of metal containers in the target sub-region, and the proportion of metal containers is obtained by statistical analysis of historical scan data. The proportion of metal containers is the ratio of the number of hazardous waste containers made of metal in the sub-region to the total number of containers. For example, the scan records in the last 30 days show that there are 20 metal containers and 50 total containers in the target sub-region C3-02, with a proportion of 40%. The reader pre-stores the mapping rule between the proportion of metal containers and the radiation power. For example, when the proportion ≤ 30%, the power is set to 25 dBm; when 30% - 60%, it is set to 30 dBm; when ≥ 60%, it is set to 35 dBm. Since the proportion of metal containers in the target sub-region C3-02 is 40%, the radiation power is set to 30 dBm. The power amplifier of the reader adjusts the output power according to this value to ensure compensation for the attenuation caused by the signal penetrating the metal container.

[0060] At the same time, turn off the antenna power supply of the non-target sub-regions. The non-target sub-regions are all sub-regions not involved in the current inbound and outbound instructions. For example, other grouping identification codes (such as B2-01, D4-03) except C3-02. The reader cuts off the power supply circuit of the directional antenna in the non-target sub-region through a relay control circuit. For example, turn off the antenna power corresponding to the grouping identification code B2-01 to stop it from transmitting signals. After the power is turned off, the reader resources are concentrated on scanning the target sub-region to avoid signal interference and energy consumption waste.

[0061] The specific steps for statistics of the proportion of metal containers include: The reader records the container material type of each sub-region during the historical scan cycle. The material type is obtained through the extended storage field of the RFID tag. For example, the value of the "material" field in the tag memory is "metal" or "non-metal". During statistics, the system filters all scan records of the target sub-region and calculates the ratio of the number of metal containers to the total number. For example, in the last 100 scans of the sub-region C3-02, 200 containers are identified, and among them, 80 tags have the "material" field as "metal", so the proportion is 40%. The statistical result is stored in the database for use when adjusting the radiation power.

[0062] The logic for dynamically increasing the radiation power includes: When the proportion of metal containers exceeds the threshold of the previous statistical cycle, trigger an increase in power. For example, the proportion in the previous cycle was 35% and the current cycle is 40%, exceeding the threshold by 5%, then the radiation power is increased from 25 dBm to 30 dBm. The power adjustment step size is set according to the change gradient of the proportion. For example, for every 10% increase in the proportion, the power is increased by 5 dBm, with a maximum not exceeding 35 dBm supported by the reader hardware. After the power is adjusted, the reader performs signal strength calibration. For example, send a test signal to the target sub-region to detect whether the feedback signal strength reaches the expected value (such as -60 dBm). If not, further fine-tune the power.

[0063] After the target sub-region scan is completed, the reader resumes the antenna power of the non-target sub-region and resets the radiation power to the default value. For example, after the inbound and outbound operation is completed, the reader reactivates the antennas of grouping identification codes B2-01 and D4-03 and restores the power to 25 dBm. The reset logic ensures the fairness and energy consumption balance of subsequent scan operations. If the power increase is triggered continuously for the same target sub-region (e.g., the proportion is ≥40% in three consecutive scan cycles), the system will permanently adjust the default power of this sub-region to 30 dBm until the proportion drops below the threshold.

[0064] When the operation stage recorded by the RFID tag of the hazardous waste container is "out of warehouse" but the actual storage location has not left the warehouse, the overwrite update the tag status to "pending outbound". The operation stage is defined by the operation type field of the inbound and outbound instruction. For example, if the value of the "operation type" field in the instruction is "outbound", the tag status is marked as "out of warehouse". The actual storage location is confirmed by comparing the reader scan result with the coordinates of the warehouse electronic map. The warehouse electronic map is a digital map containing the three-dimensional coordinate range of the warehouse. For example, the warehouse boundary is defined as 0-30 meters on the X-axis, 0-20 meters on the Y-axis, and 0-10 meters on the Z-axis. The reader scan result includes the real-time coordinates of the tag (such as X = 25 meters, Y = 18 meters, Z = 5 meters). The system determines whether the coordinates are within the range of the warehouse electronic map. If they are within the range, it is determined that the item has not left the warehouse. For example, when the tag coordinate X = 31 meters (exceeding the warehouse X-axis boundary of 30 meters), it is determined that the item has left the warehouse; if X = 25 meters (within the boundary), it is determined that the item has not left the warehouse.

[0065] Record the status change time and operator identification in the synchronization log. The status change time is the current timestamp when the system detects a tag status conflict (the operation stage is "out of warehouse" but the location has not left), such as "2023-10-05 14:30:00". The operator identification is extracted from the "operator" field of the inbound and outbound instruction. For example, if the instruction contains "operator: Zhang San", the identification is "Zhang San". The fields of the synchronization log include tag ID, original status ("out of warehouse"), new status ("pending outbound"), change time, and operator identification. For example, the log record is "tag ID: 001, original status: out of warehouse, new status: pending outbound, time: 2023-10-05 14:30:00, operator: Zhang San". The log data is written into the "status change record" table of the database, and the data integrity is ensured through the transaction lock mechanism. For example, the ACID characteristics of the database transaction are used to prevent concurrent write conflicts.

[0066] The confirmation logic for the actual storage location includes: after the reader scans the tag, its coordinates are compared one by one with the boundary coordinates of the warehouse electronic map. The boundary coordinates of the warehouse electronic map are generated from the warehouse surveying and mapping data. For example, after the surveying and mapping data is imported into the system, it is automatically converted into the maximum and minimum values of the X, Y, and Z axes. During the comparison, the system checks whether the X value of the tag coordinates is between 0 and 30 meters, the Y value is between 0 and 20 meters, and the Z value is between 0 and 10 meters. If all are satisfied, it is determined that the tag has not left. For example, when the tag coordinates are X = 28 meters, Y = 19 meters, and Z = 9 meters, it is determined that the tag is inside the warehouse; if X = 32 meters (exceeding the maximum value of the X axis, 30 meters), it is determined that the tag has left.

[0067] The extraction steps for the operator identification include: parsing the message structure of the inbound and outbound instructions. The message adopts the JSON format and contains fields such as "operation type", "target location", and "operator". For example, if the instruction content is {"operation type": "outbound", "target location": "C3-02", "operator": "Zhang San"}, the system extracts the value of the "operator" field, "Zhang San", as the identification through the JSON parser. If the instruction format is XML, the corresponding node value is extracted through the XPath parser. The operator identification is verified with the employee information table in the database. For example, it is checked whether "Zhang San" exists in the "name" field of the "employee table". If not, it is recorded as "unknown operator".

[0068] The fault tolerance mechanism for status overwrite update includes: when the tag status rolls back from "outbound" to "pending outbound", the system checks whether the tag is in the subsequent inbound and outbound queue. For example, if the tag has been included in the next outbound plan (the planned time is 2023-10-06 09:00:00), the status rollback is prohibited and an alarm event is generated. The alarm event is recorded in the "abnormal operation log" and the administrator is notified for verification. If the tag has no subsequent plan, the overwrite update is allowed, and the field rewrite of the RFID tag memory is triggered. For example, the "status" field in the tag memory is modified from "outbound" to "pending outbound" to ensure that the physical status of the tag is consistent with the database.

[0069] The optimization of the storage and retrieval of synchronization logs includes: the logs are stored by time partition. For example, they are partitioned by month (such as "log_202310") to improve the query efficiency. Index fields (such as tag ID, operator, time range) are added to the log entries to support fast retrieval. For example, when querying "all status change records of operator Zhang San in October 2023", the system quickly returns the results through the tag ID index and the operator hash table. The log data is regularly backed up to off-site storage nodes. For example, it is synchronized to the backup server through the Rsync protocol to prevent data loss.

[0070] Extract the outbound timestamp of the hazardous waste container and the inbound timestamp at the receiving location from the synchronization log. The synchronization log contains the status change records of the hazardous waste container. For example, the log entry "Label ID: 001, Original Status: Outbound, New Status: To be Outbound, Time: 2023-10-05 14:30:00, Operator: Zhang San". The outbound timestamp is extracted from the "Change Time" field of the log. For example, the container with label ID 001 was marked as outbound at "2023-10-05 14:30:00". The inbound timestamp at the receiving location is extracted from the scan log of the receiving location's reader. The log format of the receiving location's reader is consistent with the warehouse system. For example, the log entry "Label ID: 001, Operation Type: Inbound, Time: 2023-10-05 14:00:00", and the inbound timestamp is "2023-10-05 14:00:00".

[0071] When the outbound time is later than the inbound time of the same container, it is marked as a cross-region time logic contradiction. The time comparison uses the absolute numerical value comparison of timestamps. For example, the outbound timestamp "2023-10-05 14:30:00" corresponds to the Unix timestamp 1696494600, and the inbound timestamp "2023-10-05 14:00:00" corresponds to 1696492800. Since the former numerical value is greater than the latter, it is determined that the outbound is later than the inbound. The system adds a flag field for the contradictory event in the database. For example, insert a record in the "Abnormal Event Table": "Label ID: 001, Contradiction Type: Time Logic Contradiction, Outbound Time: 1696494600, Inbound Time: 1696492800".

[0072] Trigger a full scan. The full scan covers all hazardous waste containers in the target sub-region and its adjacent sub-regions. The target sub-region is the sub-region to which the container with the current time contradiction belongs. For example, the container grouping identification code of the container with label ID 001 is C3-02, and the target sub-region is C3-02. The adjacent sub-regions are determined according to the coordinate boundaries of the target sub-region in the warehouse electronic map. For example, the X-axis range of C3-02 is 6-9 meters and the Y-axis range is 9-12 meters. Its adjacent sub-regions include B3-02 (3-6 meters) and D3-02 (9-12 meters) adjacent to the X-axis, and C2-02 (9-12 meters) and C4-02 (12-15 meters) adjacent to the Y-axis. The reader sequentially activates the directional antenna arrays in the target sub-region and its adjacent sub-regions, and scans all container labels with the maximum radiation power. For example, the radiation power of C3-02, B3-02, D3-02, C2-02, and C4-02 is set to 30 dBm to ensure the signal can penetrate metal containers.

[0073] The steps for extracting the warehousing timestamp include: After the reader at the receiving location scans the hazardous waste container, it writes the warehousing timestamp into the local log file and synchronizes it to the warehouse system via a network protocol. The warehouse system parses the "time" field in the receiving location log file. For example, it extracts the "time" value "2023-10-05 14:00:00" from the JSON-formatted log {"tag ID":"001","operation type":"warehousing","time":"2023-10-05 14:00:00"}. If the receiving location log is in CSV format, the timestamp is extracted according to the column index. For example, the third column is the time data. The extracted timestamp and the local outbound timestamp are stored in the same database table for use in constructing the spatio-temporal map.

[0074] The execution logic for full-scale scanning includes: The reader activates the antennas in the order of sub-region priorities. The priorities are set according to the urgency of time conflict events. For example, the sub-region with a time conflict has the highest priority, and the adjacent sub-region has the second-highest priority. During scanning, the reader uses the dynamic frame slotted anti-collision algorithm, and the initial frame length is adaptively adjusted according to the tag density in the sub-region. For example, when the tag density of C3-02 is 20 tags per square meter, the initial frame length is set to 40 time slots. If an unregistered tag is detected during scanning (such as the tag ID does not exist in the database), an alarm is triggered and recorded in the exception log. For example, "Unregistered tag ID: 999 detected, location: C3-02".

[0075] The processing of full-scale scanning results includes: Comparing the tag data obtained from scanning with the pre-stored information in the database. If a mismatch in location and status is found (such as the container with tag ID 001 is scanned in C3-02 but its database status is "outbound"), a forced synchronization protocol is triggered. The forced synchronization protocol overwrites and updates the status field in the tag memory. For example, it rewrites the "status" field of tag ID 001 from "outbound" to "awaiting outbound", and updates the location coordinates and operation stage in the database. After synchronization is completed, the system regenerates the spatio-temporal map. For example, it shows the inbound and outbound path conflict points of tag ID 001 in the form of a timeline in the warehouse management interface.

[0076] The construction and visualization of the spatio-temporal map include: Associating the full-scale scanning results with time conflict markers to generate a topological map containing timestamps, geographical locations, and container statuses. For example, the map nodes represent hazardous waste containers (such as node 001), the edges represent operation links (such as "outbound → inbound"), and the node colors mark the conflict status (red indicates a time conflict). The map data is stored in a graph database format (such as Neo4j), which supports path queries and exception tracing. For example, querying "the operation path of tag ID 001 on 2023-10-05".

[0077] The calculations in the embodiments are all dimensionless numerical calculations. The calculation formulas involved are obtained by collecting a large amount of data for software simulation to obtain a formula that is closest to the actual situation. The preset parameters and threshold selection in the formula are set by those skilled in the art according to the actual situation.

[0078] It should be noted that the present invention can be deployed on the device itself to achieve an embedded application, or can also run on a PC or other terminal with a user interface, so as to meet various hardware environments and usage requirements.

[0079] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0080] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and the inventive constraints of the technical solution. Skilled professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0081] In addition, in each embodiment of the present application, the various functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0082] In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there can be other division methods. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces, and the indirect coupling or communication connection of the devices or modules can be in an electrical, mechanical or other form.

[0083] As described above, only the specific implementation manners of the present application are provided, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application, and all should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0084] Finally, the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. The intelligent traceable hazardous waste management system based on RFID is characterized by: Includes the following modules: Area division module: divides multiple signal reading and writing sub-areas according to the storage location of hazardous waste containers and warehouse space parameters, and assigns a unique group identification code to each sub-area; Read-write control module: controls the RFID reader to activate the directional antenna array of the corresponding sub-area based on the group identification code, and scans the RFID tags of the hazardous waste containers in the sub-area; Frequency band optimization module: When multiple RFID tag signals overlap in the same sub-area, the interference frequency band is determined by covariance decomposition based on the multipath phase fluctuation rate and polarization direction offset, and then switched and scanned again; Instruction dispatching module: extracts the target group identification code according to the entry and exit instructions of hazardous waste containers, activates the directional antenna array of the target sub-area and suspends the scanning process of the non-target sub-area; Data synchronization module: compares the identified RFID tag data with the pre-stored information in the database. If the tag status is inconsistent with the actual storage location or operation stage, the database is updated and a synchronization log is generated; Graph alarm module: extracts the status change records and physical operation time nodes in the synchronization log to build a spatiotemporal graph of the operation link. When there is a cross-regional time logic contradiction, a full disk scan is triggered and a path alarm is sent.

2. The RFID-based intelligent traceable hazardous waste management system according to claim 1 is characterized in that: Dividing multiple signal read and write sub-areas includes the following steps: According to the storage location coordinates of the hazardous waste containers and the shelf height and spacing in the warehouse space parameters, the storage area is divided into multiple rectangular sub-areas, and each sub-area is assigned a group identification code containing the warehouse location code and the number of shelf layers.

3. The RFID-based intelligent traceable hazardous waste management system according to claim 2 is characterized in that: The shelf height and spacing are used to determine the vertical and horizontal boundaries of the sub-area. The warehouse location code is an alphanumeric combination, and the number of shelf layers is represented by a digital code.

4. The RFID-based intelligent traceable hazardous waste management system according to claim 1 is characterized in that: Controlling the RFID reader to activate the directional antenna array of the corresponding sub-area includes the following steps: Based on the location code in the group identification code, the multi-beam directional antenna of the reader is controlled to activate the target sub-area with a preset elevation angle and radiation power, where the elevation angle is dynamically adjusted according to the number of shelf layers, and the radiation power is set to a gradient value according to the area of ​​the sub-area. A dynamic frame time slot polling mechanism is used to scan the RFID tags of hazardous waste containers in the corresponding sub-area, and the polling period is inversely proportional to the tag density in the sub-area.

5. The RFID-based intelligent traceable hazardous waste management system according to claim 1 is characterized in that: Determining the interference frequency band includes the following steps: The multipath phase fluctuation rate and polarization direction offset of each RFID tag signal in the same sub-area are extracted, and the frequency band correlation of the main interference path is calculated by eigenvalue decomposition of the covariance matrix; The multipath phase fluctuation rate is the phase standard deviation of adjacent signal cycles, and the polarization direction offset is the change in the angle between the tag antenna polarization direction and the reader antenna. A frequency band whose frequency band correlation is lower than a preset threshold is selected as a target interference frequency band for switching.

6. The RFID-based intelligent traceable hazardous waste management system according to claim 1 is characterized in that: Activating the directional antenna array of the target sub-area includes the following steps: Parse the target shelf layer number and location code in the hazardous waste container entry and exit instructions, match the corresponding group identification code, and control the reader to activate the directional antenna of the target sub-area with maximum radiation power, while turning off the antenna power of the non-target sub-area.

7. The RFID-based intelligent traceable hazardous waste management system according to claim 6 is characterized in that: The maximum radiation power is dynamically increased according to the proportion of metal containers in the target sub-area.

8. The RFID-based intelligent traceable hazardous waste management system according to claim 6 is characterized in that: The proportion of metal containers is obtained through historical scanning data statistics.

9. The RFID-based intelligent traceable hazardous waste management system according to claim 1 is characterized in that: Updating the database and generating a synchronization log includes the following steps: When the operation stage recorded on the RFID tag of the hazardous waste container is "out of warehouse" but the actual storage location has not left the warehouse, the tag status is overwritten and updated to "to be out of warehouse", and the status change time and operator ID are recorded in the synchronization log. The actual storage location is confirmed by comparing the reader scan results with the warehouse electronic map coordinates, and the operator ID is extracted from the entry and exit instructions.

10. The RFID-based intelligent traceable hazardous waste management system according to claim 1 is characterized in that: Building the spatiotemporal graph of the operation link includes the following steps: Extract the outbound timestamp and inbound timestamp of hazardous waste containers in the synchronization log. When the outbound time is later than the inbound time of the same container, it is marked as a cross-regional time logic contradiction and triggers a full scan. The inbound timestamp is extracted from the scanning log of the reader / writer at the receiving location. The full scan covers all hazardous waste containers in the target sub-area and its adjacent sub-areas.

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