RFID-based intelligent traceable hazardous waste management system

Abstract

The application discloses an intelligent traceable hazardous waste management system based on RFID, and particularly relates to the technical field of intelligent supervision of hazardous waste, and is used for solving the problems of unreliable data collection, missed reading and reading errors and state updating delay caused by signal interference of the existing RFID system in the high-density hazardous waste storage scene; the warehouse sub-area is dynamically divided and the unique grouping identification code is distributed, the signal crosstalk is avoided by combining the directional antenna array partition scanning technology; the label recognition rate in the complex electromagnetic environment is improved by dynamically identifying the main interference frequency band and switching the communication frequency by using the covariance decomposition algorithm through analyzing the multipath phase fluctuation rate and the polarization direction offset; the target sub-area scanning process is dispatched based on the warehouse-in and warehouse-out instructions, the label state and the actual position are synchronously checked, the operation link space-time graph is generated, the cross-area time logical contradiction is actively traced and the full scanning is triggered; the precise tracing of the hazardous waste container in the whole process and the complete data management and control in the high-density scene are realized.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology for hazardous waste, and more specifically, to an RFID-based intelligent traceable hazardous waste management system. Background Technology

[0002] In the field of hazardous waste management, RFID-based tracking systems have been widely used for the identification and process monitoring of hazardous waste containers. Existing technologies utilize RFID tags deployed on hazardous waste containers, combined with fixed or handheld readers, to automate the collection of basic information such as the type, weight, and location of hazardous waste. Such systems can replace traditional manual recording methods, meeting the basic requirements of regulatory authorities for the traceability of hazardous waste data, and are particularly suitable for routine scenarios from the generation to temporary storage of hazardous waste.

[0003] However, in real-world scenarios involving high-density centralized storage of hazardous waste, the reliability of data acquisition by existing RFID systems is significantly reduced. Due to the dense stacking of numerous hazardous waste containers, tag signals are subject to combined interference from metal materials, liquid media, and spatial obstructions, causing reading and writing devices to be unable to reliably identify all tags. Simultaneously, the dynamic entry and exit operations of hazardous waste containers further exacerbate signal conflicts, resulting in missed reads, misreads, and delays in status updates. This problem directly undermines the integrity and real-time nature of hazardous waste data, making it difficult for regulatory authorities to verify the actual inventory and operational compliance of the storage process. Summary of the Invention

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

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

[0006] The RFID-based intelligent traceable hazardous waste management system includes the following modules:

[0007] Zone division module: Divide the hazardous waste containers into multiple signal read / write sub-zones based on their storage location and warehouse space parameters, and assign a unique group identifier code to each sub-zone;

[0008] Read / write control module: Based on the group identification code, the RFID reader is controlled to activate the directional antenna array of the corresponding sub-area and scan the RFID tags of hazardous waste containers in the sub-area;

[0009] Frequency band optimization module: When multiple RFID tag signals are detected to overlap in the same sub-region, the interference frequency band is determined by covariance decomposition based on multipath phase fluctuation rate and polarization direction offset, and then switched and scanned again;

[0010] Command scheduling module: Extracts target group identification code based on hazardous waste container entry and exit instructions, activates directional antenna array in target sub-region and pauses scanning process in non-target sub-region;

[0011] 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.

[0012] The graph alarm module extracts state change records from the synchronization log and physical operation time nodes to construct a spatiotemporal graph of the operation link. When there is a time logic contradiction across regions, a full scan is triggered and a path alarm is sent.

[0013] In a preferred embodiment, dividing multiple signal read / write sub-regions includes the following steps:

[0014] Based on the storage location coordinates of hazardous waste containers and the shelf height and spacing in the warehouse space parameters, the storage area is divided into multiple cuboid sub-areas, and each sub-area is assigned a group identification code containing the warehouse location code and the number of shelf layers.

[0015] In a preferred embodiment, 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 numerical 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 group identifier, the multi-beam directional antenna of the reader is controlled to activate the target sub-region with a preset elevation angle and radiation power. The elevation angle is dynamically adjusted according to the number of shelf layers, and the radiation power is set as a gradient value according to the area of ​​the sub-region. A dynamic frame time slot polling mechanism is used to scan the RFID tags of 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 variability 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 covariance matrix eigenvalue decomposition;

[0020] The multipath phase ripple rate is the phase standard deviation of adjacent signal periods, and the polarization direction offset is the change in the angle between the polarization direction of the tag antenna and the reader antenna.

[0021] Select frequency bands with frequency band correlation below a preset threshold as target interference frequency bands for switching.

[0022] In a preferred embodiment, activating the directional antenna array in the target sub-region includes the following steps:

[0023] The system analyzes the target shelf layer and location code in the hazardous waste container entry / exit instructions, matches the corresponding group identification code, and controls the reader to activate the directional antenna of the target sub-area with maximum radiation power, while simultaneously turning off the antenna power of non-target sub-areas.

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

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

[0026] In a preferred embodiment, updating the database and generating synchronization logs includes the following steps:

[0027] When the RFID tag of a hazardous waste container records an operation stage of "outbound" but the actual storage location has not left the warehouse, the tag status is overwritten and updated to "pending outbound," and the status change time and operator identifier 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 identifier is extracted from the inbound / outbound instructions.

[0028] In a preferred embodiment, constructing the spatiotemporal map of the operational links includes the following steps:

[0029] Extract the outbound timestamp and inbound timestamp of hazardous waste containers from the synchronization log. When the outbound time is later than the inbound time of the same container, it is marked as a cross-region time logic contradiction and a full scan is triggered. The inbound timestamp is extracted from the reader scan log of the receiving location. The full scan covers all hazardous 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 dynamic partitioning and multi-dimensional signal optimization mechanisms, the reliability of data acquisition in high-density hazardous waste storage scenarios is significantly improved; the partitioning control strategy based on group identification codes, combined with the precise scanning of directional antenna arrays, effectively avoids the problem of signal crosstalk between adjacent areas, ensuring that the reader only activates the target sub-area, and greatly reduces multipath reflection and signal attenuation caused by the stacking of metal containers; by analyzing the multipath phase fluctuation rate and polarization direction offset in real time, the main interference frequency band is dynamically identified and frequency band switching is implemented, breaking through the environmental adaptability limitations of traditional single-band anti-collision algorithms, enabling stable acquisition of tag data even in complex electromagnetic interference environments, and solving the problems of missed reading and misreading caused by dense stacking of hazardous waste containers;

[0032] 2. Through an intelligent scheduling mechanism driven by operation commands, refined management and control of the hazardous waste transfer process is achieved; the reverse traceability function based on spatiotemporal maps deeply associates physical operation nodes with database change records, proactively identifies cross-regional time logic contradictions, triggers targeted full-scale scanning, and makes up for the shortcomings of traditional traceability systems that rely solely on single-point data verification; the data synchronization module forcibly updates the label status and storage location, ensuring data consistency of hazardous waste containers during dynamic entry and exit processes, avoiding false inventory reports caused by human error or equipment misreading, and providing full-cycle, highly reliable data support for hazardous waste supervision. Attached Figure Description

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

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

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

[0036] Zone division module: Divide the hazardous waste containers into multiple signal read / write sub-zones based on their storage location and warehouse space parameters, and assign a unique group identifier code to each sub-zone;

[0037] Read / write control module: Based on the group identification code, the RFID reader is controlled to activate the directional antenna array of the corresponding sub-area and scan the RFID tags of hazardous waste containers in the sub-area;

[0038] Frequency band optimization module: When multiple RFID tag signals are detected to overlap in the same sub-region, the interference frequency band is determined by covariance decomposition based on multipath phase fluctuation rate and polarization direction offset, and then switched and scanned again;

[0039] Command scheduling module: Extracts target group identification code based on hazardous waste container entry and exit instructions, activates directional antenna array in target sub-region and pauses scanning process in non-target sub-region;

[0040] 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.

[0041] The graph alarm module extracts state change records from the synchronization log and physical operation time nodes to construct a spatiotemporal graph of the operation link. When there is a time logic contradiction across regions, a full scan is triggered and a path alarm is sent.

[0042] The storage location coordinates of hazardous waste containers and the shelf height and spacing in the warehouse space parameters are used to divide multiple cuboid sub-areas. The storage location coordinates are the X, Y, and Z axis coordinates of the hazardous waste containers in the warehouse's three-dimensional coordinate system. The three-dimensional coordinate system has its origin at the warehouse entrance on the ground floor. The X-axis extends along the length of the warehouse, the Y-axis extends along the width, and the Z-axis extends vertically upwards. The coordinate values ​​are calculated using the RFID reader to scan the tag signal strength and arrival time difference. Warehouse space parameters include shelf height and shelf spacing. Shelf height is the vertical distance from bottom to top of a single shelf, obtained from warehouse design drawings or manually measured and input into the system. Shelf spacing is the horizontal distance between adjacent shelves, set according to the width of the hazardous waste container transport aisle, for example, set to 3 meters to meet forklift access requirements. The warehouse space is divided vertically into several layers based on the shelf height, with each layer having the same height as the shelf. For example, if the shelf height is 2 meters, each 2-meter section is a layer vertically. Horizontally, each layer is divided into several columns based on the shelf spacing, with each column having the same width as the shelf spacing. For example, if the shelf spacing is 3 meters, each 3-meter section is a column horizontally, ultimately forming multiple cuboid sub-areas. The side length of each cuboid sub-area is a three-dimensional combination of the shelf spacing, shelf height, and shelf spacing, for example, 3 meters (length) × 3 meters (width) × 2 meters (height).

[0043] Each rectangular sub-region is assigned a unique group identifier, which includes the warehouse location code and the shelf layer number. The warehouse location code is generated based on the sub-region's position in the warehouse's planar grid. The planar grid establishes a two-dimensional coordinate system with the warehouse entrance as the origin. The X-axis and Y-axis correspond to the warehouse's length and width, respectively. Each grid cell corresponds to a column of horizontally divided sub-regions. The location code is represented by a combination of letters and numbers. The letters represent the X-axis number, ordered from left to right as A, B, C, etc., and the numbers represent the Y-axis number, ordered from entrance to interior as 1, 2, 3, etc. For example, a sub-region 6 meters from the entrance (3rd column in the X-axis direction) and 9 meters wide (3rd row in the Y-axis direction) has the location code C3. The shelf layer numbers increase from bottom to top according to the vertical cutting order, with the bottom layer being layer 01, and layers 02, 03, etc., fixed at two digits to ensure a consistent coding format. The group identification code consists of a location code and a shelf level number connected by a hyphen. For example, the group identification code for a sub-area with location code C3 and shelf level 02 is C3-02. The group identification code is linked to the warehouse's electronic map via a database. Each sub-area's 3D coordinate range on the electronic map corresponds one-to-one with the group identification code. The coordinate range includes the start and end values ​​for the X-axis, Y-axis, and Z-axis. For example, the coordinate range for group 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 a sub-area is determined by the shelf height. The vertical boundary value is the bottom and top height of the layer containing the sub-area. For example, when the shelf height is 2 meters, the vertical boundary of layer 01 is 0-2 meters, and that of layer 02 is 2-4 meters. The horizontal boundary is determined by the shelf spacing. The horizontal boundary value is the start and end coordinates of the column containing the sub-area. For example, when the shelf spacing is 3 meters, location code C3 corresponds to 6-9 meters on the X-axis and 9-12 meters on the Y-axis. The warehouse management system stores the boundary coordinates of all sub-areas on an electronic map and automatically matches the group identification code of the sub-area to which the container belongs when it enters the warehouse, based on its storage location 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-area of ​​group identification code C3-02 (X-axis 6-9 meters, Y-axis 9-12 meters, Z-axis 2-4 meters) and writes this group identification code into the storage field of the container's RFID tag.

[0045] When the dense stacking of hazardous waste containers causes the tag density in a sub-region to exceed a preset threshold, the system recalculates the sub-region division parameters based on the current storage location coordinates, dynamically increasing the number of vertical or horizontal cutting layers. The tag density threshold is set according to the reader's performance, for example, 10 containers per square meter. When the system detects that the tag density in a sub-region exceeds this threshold, it triggers a dynamic adjustment mechanism. During adjustment, the atomic region is first cut into smaller sub-regions along the vertical direction, for example, a sub-region with a height of 2 meters is cut into two sub-regions with a height of 1 meter. If the density requirement is still not met after vertical cutting, it is further cut along the horizontal direction. The adjusted sub-regions are reassigned 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 dynamically adjusted group identification codes and coordinate information 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 rules for group identification codes are automatically executed by the configuration function of the warehouse management system. When warehouse space parameters change, the system re-divides and reassigns 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 to 3 (total width 15 meters ÷ 4 meters ≈ 3.75, rounded to 3 columns). The system automatically updates the group identification codes and electronic map coordinates of all sub-areas, and the original group identification code C3-02 changes to B2-02 (the second column on the X-axis corresponds to 4-8 meters, and the second row on the Y-axis corresponds to 4-8 meters). When hazardous waste containers are removed from the warehouse, the system quickly locates the sub-area to which they belong based on the group identification code stored in their RFID tags and dispatches readers for directional scanning. For example, when a container with group identification code C3-02 is removed from the warehouse, the reader only activates the directional antenna of the C3-02 sub-area to avoid interfering with other sub-areas.

[0047] The location code in the group identifier is used to control the reader's multi-beam directional antenna to activate the target sub-region with a preset elevation angle and radiation power. For example, location code C3 represents the sub-region in the 3rd column of the X-axis and the 3rd row of the Y-axis in the warehouse planar grid. The reader matches the target sub-region's coordinate range on the electronic map based on the location code; for example, location code C3 corresponds to sub-region coordinates of 6-9 meters on the X-axis and 9-12 meters on the Y-axis. The reader's multi-beam directional antenna adjusts its beam pointing angle to align the antenna's main lobe with the center point of the target sub-region's coordinate range, for example, at 7.5 meters on the X-axis and 10.5 meters on the Y-axis. The beam pointing angle is controlled by the reader's motor drive unit. After receiving control commands, the motor drive unit rotates the antenna to the target angle, for example, adjusting the horizontal azimuth angle to 30 degrees to cover the 6-9 meter range on the X-axis.

[0048] The elevation angle is dynamically adjusted based on the number of shelf layers, which is determined by a two-digit code in the group identifier. For example, "02" in group identifier C3-02 indicates the 2nd layer. The reader has a pre-stored mapping table between shelf layers and elevation angles. For example, layer 01 corresponds to an elevation angle of 0 degrees (horizontal direction), layer 02 corresponds to an elevation angle of 30 degrees, and layer 03 corresponds to an elevation angle of 45 degrees. The reader queries the mapping table based on the layer code in the current group identifier and drives the antenna elevation mechanism to adjust to the target elevation angle. For example, when the group identifier is C3-02, the elevation angle is adjusted to 30 degrees, so that the antenna main lobe covers a vertical range of 2-4 meters along the Z-axis. The radiated power is set as a gradient value based on the sub-area area. The sub-area area is calculated from the coordinate range in the warehouse electronic map. For example, 6-9 meters (3 meters long) along the X-axis and 9-12 meters (3 meters wide) along the Y-axis, with an area of ​​9 square meters. The reader pre-stores a gradient mapping rule between area and radiated power. For example, the power is set to 20dBm for an area less than 5 square meters, 25dBm for 5-10 square meters, and 30dBm for more than 10 square meters. When the target sub-area area is 9 square meters, the radiated power is set to 25dBm. The radiated power is dynamically adjusted by the reader's power amplifier to ensure that the signal strength adapts to the sub-area size.

[0049] A dynamic frame time-slot polling mechanism is used to scan the RFID tags of hazardous waste containers within the corresponding sub-region. This mechanism employs an existing anti-collision algorithm, with the initial frame length adaptively adjusted based on the tag density within the sub-region. Tag density is obtained through statistical analysis of historical scan data; for example, if an average of 15 tags were identified in the target sub-region during the last 10 scans, the tag density is 15 tags per scan cycle. The initial frame length is set to twice the tag density; for example, with a density of 15, the initial frame length is 30 time slots. At the start of scanning, the reader broadcasts a query command containing the initial frame length. Tags randomly select time slots to respond. If a conflict occurs (multiple tags responding in the same time slot), the frame length is extended using a binary tree splitting algorithm, and the scan is re-attempted. The polling cycle is inversely proportional to the tag density within the sub-region and is controlled by the reader's timer; 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 polling cycle adjustment logic is as follows: for every 5 units / square meter increase in density, the cycle shortens by 10 milliseconds, with a minimum cycle of 30 milliseconds and a maximum cycle of 200 milliseconds. For example, when the target sub-region density is 15 units / square meter, the cycle is calculated as 100 milliseconds - (15-10) / 5 × 10 milliseconds = 90 milliseconds.

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

[0051] During scanning, the reader continuously monitors the signal quality of the target sub-region. If the signal strength is lower than a preset threshold (e.g., -70dBm), it triggers a radiated power increase. The signal strength threshold is set based on the reader's sensitivity; for example, if the sensitivity is -80dBm, the threshold is set to -70dBm to retain a 10dB margin. The radiated power increase increment is 2dBm per cycle until the signal strength reaches the threshold or the maximum power limit (e.g., 30dBm). For example, if the current power is 25dBm and the signal strength is -75dBm, the power is increased to 27dBm, and the signal strength is checked again. If it is still lower than the threshold, it is increased to 29dBm. The power adjustment is recorded in the log for reference in subsequent scanning cycles. After the target sub-region scanning is completed, the reader turns off the directional antenna power, releases resources, and waits for the next instruction, such as reactivating the target sub-region upon receiving an in / out instruction.

[0052] Extract the multipath phase fluctuation rate and polarization direction offset of RFID tag signals within the same sub-region. Multipath phase fluctuation rate is defined as the phase standard deviation of adjacent signal periods. An adjacent signal period is the continuous scanning cycle of the same tag by the reader at fixed time intervals, such as one scan every 100 milliseconds. The phase value is measured by the reader's phase detection unit. For example, if 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 to be 15 degrees. Polarization direction offset is defined as the change in the angle between the tag antenna polarization direction and the reader antenna. The tag antenna polarization direction is determined by the tag design parameters, such as linear or circular polarization. The reader antenna polarization direction is fixed to vertical polarization through its hardware configuration. The angle change is measured by the reader's polarization detection module. For example, if the angle measured in the first scan is 5 degrees, and the second is 8 degrees, the offset is 3 degrees.

[0053] The frequency band correlation of the main interference path is calculated through eigenvalue decomposition of the covariance matrix. The covariance matrix is ​​constructed from the multipath phase variability 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 (865MHz, 868MHz, and 915MHz) within the sub-region, the covariance matrix is ​​a 3×3 matrix, and the element C(1,2) represents the covariance value between the 865MHz and 868MHz frequency bands. 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 865MHz frequency band. The frequency band correlation is calculated after normalizing the eigenvalues. For example, if the largest eigenvalue accounts for 80% of the total sum of eigenvalues, then the frequency band correlation is 80%.

[0054] Frequency bands with a correlation lower than a preset threshold are selected as target interference bands for switching. The preset threshold is set based on historical interference data. For example, experimental statistics show that when the correlation is below 30%, the signal collision probability drops to below 5%, so the threshold is set to 30%. If the calculated correlation results are 865MHz (80%), 868MHz (15%), and 915MHz (5%), then 868MHz and 915MHz are selected as target interference bands. The reader switches to the corresponding communication frequency according to the target frequency band, for example, switching from 865MHz to 868MHz, and rescans the hazardous waste container tag in the switched frequency band. During switching, the reader sends a frequency band switching command to the tag, and the tag adjusts the resonant circuit frequency to match the new frequency band according to the command. For example, if the tag's original resonant frequency is 865MHz, it is adjusted to 868MHz after switching.

[0055] After a frequency band switch, the reader records the switching time and 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 868MHz is set to 10 minutes; after the timeout, it automatically switches back to the initial frequency band to avoid frequency occupancy conflicts. If signal conflicts still exist in the switched frequency band (e.g., the conflict time slot ratio exceeds 30%), a secondary frequency band selection process is triggered. For example, the sub-frequency band with the lowest correlation (e.g., 915.2MHz to 915.8MHz) is selected from the 915MHz band for fine-tuning. The range of sub-frequency bands selected in the secondary selection is determined based on the reader's frequency tuning accuracy; for example, when the tuning accuracy is 0.1MHz, the sub-frequency band interval is set to 0.2MHz.

[0056] During frequency band switching, the reader monitors signal quality metrics (such as signal-to-noise ratio and bit error rate). If the signal quality falls below a preset threshold (e.g., signal-to-noise ratio below 10dB), a frequency band fallback mechanism is triggered. The signal-to-noise ratio threshold is set based on the tag sensitivity; for example, if the tag sensitivity is -80dBm, the threshold is set to 10dB to retain communication margin. During frequency band fallback, the reader switches to the previous available frequency band and rescans, for example, falling back from 868MHz to 865MHz, while simultaneously recording the fallback event for future frequency band optimization reference.

[0057] By extracting multipath phase volatility and polarization direction offset, and combining this with covariance matrix eigenvalue decomposition, the main interference frequency band in densely stacked hazardous waste containers can be accurately identified. Multipath phase volatility quantifies the stability of signal phase changes with the path, while polarization direction offset reflects the degree of polarization mismatch between the tag and reader antenna. Together, these two factors can distinguish between signals reflected from metal containers and signals from the actual tags. Compared to existing technologies that rely solely on signal strength or single-band switching, this approach utilizes multi-physics parameters (phase, polarization) to construct a covariance matrix, locates the interference source frequency band through eigenvalue decomposition, and dynamically switches to a low-correlation frequency band, significantly reducing signal attenuation and multipath interference caused by metal containers. By combining electromagnetic wave propagation characteristics (multipath effect, polarization matching) with statistical analysis methods, this approach overcomes the limitations of single signal indicators, making it particularly suitable for high-density hazardous waste storage scenarios. It solves the problem of unreliable data acquisition caused by material interference and signal overlap in existing technologies, ensuring the integrity and real-time nature of hazardous waste operation traceability.

[0058] The system parses the target shelf layer number and location code in the hazardous waste container inbound / outbound instructions and matches them with the corresponding group identifier codes. The inbound / outbound instructions are generated by the warehouse management system and contain information about the target storage or removal location of the hazardous waste containers. For example, the instruction format is "Outbound - Shelf Layer Number 02 - Location Code C3". The target shelf layer number is a two-digit code, for example, "02" represents the 2nd layer vertically; the location code is 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's planar grid. After parsing the instructions, the reader extracts the target shelf layer number "02" and the location code "C3" and matches them with a pre-stored list of group identifier codes. For example, if the matching group identifier code C3-02 corresponds to the sub-area coordinates of 6-9 meters on the X-axis, 9-12 meters on the Y-axis, and 2-4 meters on the Z-axis.

[0059] The reader activates the directional antenna of the target sub-region at maximum radiated power. The maximum radiated power dynamically increases based on the proportion of metal containers in the target sub-region, which is obtained through historical scan data. The metal container proportion is the ratio of the number of metal hazardous waste containers in the sub-region to the total number of containers. For example, if the scan records from the last 30 days show that there are 20 metal containers in target sub-region C3-02 out of a total of 50 containers, the proportion is 40%. The reader pre-stores a mapping rule between the metal container proportion and the radiated power; for example, the power is set to 25dBm when the proportion is ≤30%, 30dBm for 30%-60%, and 35dBm for ≥60%. Since the metal container proportion in target sub-region C3-02 is 40%, the radiated power is set to 30dBm. The reader's power amplifier adjusts its output power according to this value to ensure signal attenuation compensation caused by the metal containers.

[0060] Simultaneously, the antenna power supply for non-target sub-regions is turned off. Non-target sub-regions are all sub-regions not covered by the current inbound / outbound command, such as other group identifiers besides C3-02 (e.g., B2-01, D4-03). The reader / writer uses a relay control circuit to cut off the power supply circuit of the directional antennas in the non-target sub-regions; for example, turning off the power supply to the antenna corresponding to group identifier B2-01, causing it to stop transmitting signals. After the power is turned off, the reader / writer's resources are concentrated on scanning the target sub-region, avoiding signal interference and energy waste.

[0061] The specific steps for calculating the proportion of metal containers include: the reader records the material type of containers in each sub-area during the historical scanning cycle. The material type is obtained through the extended storage field of the RFID tag, for example, the "material" field value in the tag's memory is "metal" or "non-metal". During the statistics, the system filters all scan records of the target sub-area and calculates the ratio of the number of metal containers to the total number. For example, if sub-area C3-02 identifies 200 containers in the most recent 100 scans, and 80 of these tags have a "material" field value of "metal", then the proportion is 40%. The statistical results are stored in the database for use when adjusting radiation power.

[0062] The logic for dynamically increasing radiated power includes: triggering a power increase when the proportion of metal containers exceeds the threshold of the previous statistical period. For example, if the proportion was 35% in the previous period and 40% in the current period, exceeding the threshold by 5%, the radiated power will increase from 25dBm to 30dBm. The power adjustment step size is set according to the gradient of the proportion change; for example, for every 10% increase in proportion, the power increases by 5dBm, with a maximum not exceeding 35dBm supported by the reader hardware. After power adjustment, the reader performs signal strength calibration, such as sending a test signal to the target sub-area and checking whether the feedback signal strength reaches the expected value (e.g., -60dBm). If it does not meet the standard, the power is further fine-tuned.

[0063] After scanning the target sub-region, the reader restores the antenna power to the non-target sub-regions and resets the radiated power to the default value. For example, after an inbound / outbound operation is completed, the reader reactivates the antennas for group identifiers B2-01 and D4-03 and restores the power to 25dBm. This reset logic ensures fairness and energy balance in subsequent scanning operations. If the same target sub-region triggers power increases multiple times consecutively (e.g., the proportion is ≥40% in three consecutive scanning cycles), the system permanently adjusts the default power of that sub-region to 30dBm until the proportion falls below the threshold.

[0064] When the RFID tag of a hazardous waste container records an operation stage of "outbound" but the actual storage location has not left the warehouse, the tag status is overwritten and updated to "pending outbound". The operation stage is defined by the operation type field of the inbound / outbound instruction. For example, if the "operation type" field value in the instruction is "outbound", the tag status is marked as "outbound". The actual storage location is confirmed by comparing the reader scan result with the coordinates of the warehouse's electronic map. The warehouse electronic map is a digital map that includes the three-dimensional coordinate range of the warehouse. For example, the warehouse boundary is defined as X-axis 0-30 meters, Y-axis 0-20 meters, and Z-axis 0-10 meters. The reader scan result includes the real-time coordinates of the tag (e.g., 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 container has not left the warehouse. For example, when the tag coordinates X=31 meters (30 meters beyond the warehouse X-axis boundary), it is determined that the container has left the warehouse; if X=25 meters (within the boundary), it is determined that the container has not left the warehouse.

[0065] The synchronization log records the status change time and operator ID. The status change time is the current timestamp when the system detects a tag status conflict (operation stage: outbound but location not yet left), for example, "2023-10-05 14:30:00". The operator ID is extracted from the "Operator" field of the inbound / outbound command. For example, if the command contains "Operator: Zhang San", the ID will be "Zhang San". The fields in the synchronization log include tag ID, original status (outbound), new status (pending outbound), change time, and operator ID. For example, the log record is "Tag ID: 001, Original status: Outbound, New status: Pending outbound, Time: 2023-10-05 14:30:00, Operator: Zhang San". The log data is written to the "Status Change Record" table in the database, and data integrity is ensured through transaction locking mechanisms, such as using the ACID properties of database transactions to prevent concurrent write conflicts.

[0066] The logic for confirming the actual storage location includes: after the reader scans the tag, it compares its coordinates one by one with the boundary coordinates of the warehouse electronic map. The boundary coordinates of the warehouse electronic map are generated from warehouse survey data; for example, after the survey 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 0-30 meters, the Y value is between 0-20 meters, and the Z value is between 0-10 meters. If all conditions are met, it is determined that the tag has not left the warehouse. For example, if the tag coordinates 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 30 meters on the X axis), it is determined that the tag has left the warehouse.

[0067] The steps for extracting the operator identifier include: parsing the message structure of the inbound / outbound command. The message is in JSON format and contains fields such as "Operation Type," "Target Location," and "Operator." For example, if the command content is {"Operation Type":"Outbound","Target Location":"C3-02","Operator":"Zhang San"}, the system uses a JSON parser to extract the value "Zhang San" from the "Operator" field as the identifier. If the command format is XML, the corresponding node value is extracted using an XPath parser. The operator identifier is then verified against the employee information table in the database. For example, it checks whether "Zhang San" exists in the "Name" field of the "Employee Table." If it does not exist, it is recorded as "Unknown Operator."

[0068] The fault-tolerance mechanism for status overwrite updates includes the following: When a tag's status rolls back from "outbound" to "pending outbound," the system checks whether the tag is in the subsequent inbound / outbound queue. For example, if the tag has already been included in the next outbound plan (scheduled for 2023-10-06 09:00:00), 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, overwrite updates are allowed, and the fields in the RFID tag's memory are rewritten, for example, changing the "status" field in the tag's memory from "outbound" to "pending outbound," ensuring that the tag's physical status is consistent with the database.

[0069] Optimizations to the storage and retrieval of synchronized logs include: partitioning logs by time, such as by month (e.g., "log_202310"), to improve query efficiency; adding indexed fields (such as tag ID, operator, and time range) to 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 results using the tag ID index and the operator hash table; and periodically backing up log data to off-site storage nodes, such as synchronizing to a backup server via the Rsync protocol, to prevent data loss.

[0070] Extract the outbound and receiving timestamps of hazardous waste containers from the synchronization log. The synchronization log contains records of hazardous waste container status changes, such as the log entry "Label ID: 001, Original Status: Outbound, New Status: Pending 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 is marked as outbound at "2023-10-05 14:30:00". The receiving timestamp is extracted from the scan log of the receiving reader. The receiving reader log format is consistent with the warehouse system. For example, the log entry "Label ID: 001, Operation Type: Inbound, Time: 2023-10-05 14:00:00" has an inbound timestamp of "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-regional time logic contradiction. Time comparison uses the absolute values ​​of the timestamps. For example, the outbound timestamp "2023-10-05 14:30:00" corresponds to the Unix timestamp 1696494600, while the inbound timestamp "2023-10-05 14:00:00" corresponds to 1696492800. The former value is greater than the latter, so it is determined that the outbound is later than the inbound. The system adds a tag field to the database for the contradictory event. For example, it inserts a record into the "Abnormal Events Table" with the tag ID: 001, contradiction type: time logic contradiction, outbound time: 1696494600, inbound time: 1696492800.

[0072] A full scan is triggered, covering 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 discrepancy belongs. For example, the container with tag ID 001 has a group identifier of C3-02, and its target sub-region is C3-02. Adjacent sub-regions are determined based on the coordinate boundaries of the target sub-region on the warehouse electronic map. For example, C3-02 has an X-axis range of 6-9 meters and a Y-axis range of 9-12 meters. Its adjacent sub-regions include B3-02 (3-6 meters) and D3-02 (9-12 meters) adjacent on the X-axis, and C2-02 (9-12 meters) and C4-02 (12-15 meters) adjacent on the Y-axis. The reader sequentially activates the directional antenna arrays of the target sub-region and its adjacent sub-regions, scanning all container tags at maximum radiated power. For example, the radiated power of C3-02, B3-02, D3-02, C2-02, and C4-02 is set to 30dBm to ensure signal penetration through metal containers.

[0073] The steps for extracting the entry timestamp include: After the receiving site reader scans the hazardous waste container, it writes the entry timestamp to a local log file and synchronizes it to the warehouse system via a network protocol. The warehouse system parses the "time" field of the receiving site log file, for example, extracting the "time" value "2023-10-05 14:00:00" from the JSON format log {"tag ID":"001","operation type":"entry","time":"2023-10-05 14:00:00"}. If the receiving site log is in CSV format, the timestamp is extracted by column index, for example, the third column contains time data. The extracted timestamp and the local exit timestamp are stored in the same database table for use in spatiotemporal mapping.

[0074] The execution logic of the full scan includes: the reader activates antennas according to sub-region priority, with priority set based on the urgency of time-contradictory events. For example, sub-regions with time-contradictory events have the highest priority, and adjacent sub-regions have the second highest priority. During scanning, the reader uses a dynamic frame slot anti-collision algorithm. The initial frame length is adaptively adjusted according to the tag density of the sub-region. For example, if the tag density of C3-02 is 20 tags / square meter, the initial frame length is set to 40 slots. If an unregistered tag is detected during the scan (e.g., the tag ID does not exist in the database), an alarm is triggered and recorded in the anomaly log, for example, "Unregistered tag ID detected: 999, Location: C3-02".

[0075] The full scan result processing includes: comparing the scanned tag data with pre-stored information in the database; if a mismatch is found between location and status (e.g., a 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's memory, for example, rewriting the "status" field of tag ID 001 from "outbound" to "pending outbound," and updating the location coordinates and operation stage in the database. After synchronization is complete, the system regenerates the spatiotemporal map, for example, displaying the inbound / outbound path discrepancies of tag ID 001 in a timeline format on the warehouse management interface.

[0076] The construction and visualization of the spatiotemporal graph includes associating the full scan results with temporal contradiction markers to generate a topology graph containing timestamps, geographical locations, and container status. For example, graph nodes represent hazardous waste containers (e.g., node 001), edges represent operation links (e.g., "outbound → inbound"), and node colors indicate contradiction status (red indicates temporal contradictions). Graph data is stored in a graph database format (e.g., Neo4j), supporting path queries and anomaly tracing, such as querying "the operation path of tag ID 001 on 2023-10-05".

[0077] The calculations in the embodiments are all dimensionless and numerical calculations. The calculation formulas involved are obtained by software simulation based on a large amount of data to get the formula closest to the real situation. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0078] It should be noted that this invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting 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 thereof. 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 skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and inventive constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

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

[0082] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0083] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0084] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An RFID-based intelligent traceable hazardous waste management system, characterized in that, Includes the following modules: Region Division Module: The system is divided into multiple signal reading and writing sub-regions based on the storage location of hazardous waste containers and warehouse space parameters, and each sub-region is assigned a unique group identification code. The reading and writing control module controls the RFID reader to activate the directional antenna array of the corresponding sub-region based on the group identification code, and scans the RFID tags of hazardous waste containers in the sub-region. Controlling an RFID reader to activate the directional antenna array in the corresponding sub-region includes the following steps: Based on the location code in the group identifier, the multi-beam directional antenna of the reader is controlled to activate the target sub-region with a preset elevation angle and radiation power. The elevation angle is dynamically adjusted according to the number of shelf layers, and the radiation power is set as a gradient value according to the area of ​​the sub-region. A dynamic frame time slot polling mechanism is used to scan the RFID tags of hazardous waste containers in the corresponding sub-region. The polling period is inversely proportional to the tag density in the sub-region. Frequency band optimization module: When multiple RFID tag signals are detected to overlap in the same sub-region, the interference frequency band is determined by covariance decomposition based on multipath phase fluctuation rate and polarization direction offset, and then switched and scanned again; Command scheduling module: Extracts target group identification code based on hazardous waste container entry and exit instructions, activates directional antenna array in target sub-region and pauses scanning process in non-target sub-region; 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. The graph alarm module extracts state change records from the synchronization log and physical operation time nodes to construct a spatiotemporal graph of the operation link. When there is a time logic contradiction across regions, a full scan is triggered and a path alarm is sent. Determining the interference frequency band includes the following steps: extracting the multipath phase fluctuation rate and polarization direction offset of each RFID tag signal in the same sub-region, and calculating the frequency band correlation of the main interference path through covariance matrix eigenvalue decomposition; The multipath phase ripple rate is the phase standard deviation of adjacent signal periods, and the polarization direction offset is the change in the angle between the polarization direction of the tag antenna and the reader antenna. Select frequency bands with frequency band correlation below a preset threshold as target interference frequency bands for switching; Activating the directional antenna array in the target sub-region includes the following steps: parsing the target shelf layer number and location code in the hazardous waste container entry and exit instructions, matching the corresponding group identification code, and controlling the reader to activate the directional antenna in the target sub-region with maximum radiation power, while turning off the antenna power in non-target sub-regions; Updating the database and generating a synchronization log includes the following steps: When the RFID tag of a hazardous waste container records the operation stage as "outbound" but the actual storage location has not left the warehouse, the tag status is overwritten and updated to "pending outbound". The status change time and operator identifier 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 identifier is extracted from the inbound and outbound instructions. Constructing the spatiotemporal graph of the operation link includes the following steps: extracting the outbound timestamp and the inbound timestamp of the hazardous waste container from 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 a full scan is triggered. The inbound timestamp is extracted from the reader scan log of the receiving location. The full scan covers all hazardous waste containers in the target sub-region and its adjacent sub-regions.

2. The RFID-based intelligent traceable hazardous waste management system according to claim 1, characterized in that, Dividing the signal into multiple read / write sub-regions includes the following steps: Based on the storage location coordinates of hazardous waste containers and the shelf height and spacing in the warehouse space parameters, the storage area is divided into multiple cuboid 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, 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 a combination of letters and numbers, and the number of shelf layers is represented by a numerical code.

4. The RFID-based intelligent traceable hazardous waste management system according to claim 3, characterized in that, The maximum radiation power is dynamically increased based on the proportion of metal containers in the target sub-region.

5. The RFID-based intelligent traceable hazardous waste management system according to claim 3, characterized in that, The percentage of metal containers was obtained through statistical analysis of historical scan data.

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