Intelligent article tracking and identification method and system based on RFID technology

Abstract

The invention discloses an intelligent article tracking and identification method and system based on an RFID technology, and the method comprises the steps: collecting an environment noise intensity value, and carrying out the statistics of the number of tags in an effective identification range through a tag response signal; inputting the environmental noise intensity value and the tag number into a power regulation and control model, outputting reader-writer transmitting power, and generating a reader-writer transmitting power instruction; counting a collision time slot number, a successful time slot number and an idle time slot number of the label response signal in a preset time window; dynamically adjusting a frame time slot number Q value according to a proportional relation among the collision time slot number, the success time slot number and the free time slot number; and extracting the EPC code of the successfully identified tag, and deleting the predefined fixed bit field data in the EPC code. According to the method, an environment-data-communication three-in-one optimization system is constructed, the dynamic adaptability, the data transmission efficiency and the data reliability are improved, and the recognition success rate in a high-noise scene is improved.

Description

Technical Field

[0001] This application belongs to the technical field of intelligent item tracking, and particularly relates to an intelligent item tracking and identification method and system based on RFID technology. Background Art

[0002] With the rapid development of Internet of Things technology, RFID technology is increasingly widely used in fields such as logistics, warehousing, and retail.

[0003] The existing Chinese patent with the publication number CN112258133B discloses a luggage tracking and identification system based on RFID technology, including a conveying mechanism, a logic control system, a luggage position detection device, and an RFID identification system. The conveying mechanism is used to convey luggage with RFID tags; the logic control system is used to drive the conveying mechanism to convey luggage, receive the position information obtained by the luggage position detection device, perform tracking control on the luggage, communicate with the RFID identification system in real time, and realize automatic identification of luggage barcode information; the luggage position detection device is used to detect the position information of the luggage on the conveying mechanism and send the position information to the logic control system; the RFID identification system is used to receive the luggage tracking signal transmitted by the logic control system, scan the RFID tags on the luggage, and complete the marking of the luggage tag information. This invention improves the luggage recognition rate and realizes the accurate binding of luggage tag data and luggage information.

[0004] However, in the process of implementing the related technical solutions, it is found that there are at least the following technical problems:

[0005] The above-mentioned technology is based on the emission power adjustment method based on the number of tags (such as the linear correlation between the number of tags N and the power P), but does not consider the dynamic influence of environmental noise. In high-noise scenarios such as metal shelves, its recognition success rate will drop significantly compared with the theoretical value. Moreover, the above-mentioned technology uses a static EPC compression method (such as fixedly deleting 8-bit header files), which will lead to the inability to adapt to dynamic service requirements (such as embedding temperature and humidity data in the cold chain), with poor compatibility and increased channel load. Summary of the Invention

[0006] In order to solve the above problems, an embodiment of the present invention provides an intelligent item tracking and identification method based on RFID technology. The method includes:

[0007] Collect the environmental noise intensity value, and count the number of tags within the effective recognition range through the tag response signal;

[0008] Input the environmental noise intensity value and the number of tags into the power regulation model, output the reader emission power, and generate a reader emission power instruction;

[0009] Count the number of collision time slots, successful time slots, and idle time slots of the tag response signal within a preset time window;

[0010] Dynamically adjust the Q value of the frame time slots according to the proportional relationship among the number of collision time slots, the number of successful time slots, and the number of idle time slots;

[0011] Extract the EPC code of the successfully recognized tag, and delete the predefined fixed-bit segment data in the EPC code;

[0012] Perform variable-length coding conversion on the remaining EPC code after deleting the fixed-bit segment data, and output the coded data;

[0013] Encapsulate the coded data and the spatio-temporal coordinate information into a transmission data packet, and send it to the server through a narrowband communication channel.

[0014] Furthermore, the power regulation model calculates the transmission power P through the following rules, and the calculation method includes:

[0015]

[0016] Wherein, N tag is the current number of tags, N base is the preset reference number of tags, K(N tog ) is a piecewise increasing exponential function based on the number of tags, f(S noise ) is a non-linear mapping function of the environmental noise intensity, and α and β are preset weighting factors.

[0017] Furthermore, the method for dynamically adjusting the Q value of the frame time slots includes:

[0018] If the proportion of collision time slots exceeds the preset upper threshold, then according to the formula Q new =Q current ×γ up increase the Q value, where γ up >1 is the upward adjustment coefficient;

[0019] If the proportion of idle time slots exceeds the preset lower threshold, then according to the formula Q new =Q current ÷γ up decrease the Q value, where γ down >1 is the downward adjustment coefficient.

[0020] Furthermore, the predefined fixed-bit segment data includes the protocol version identifier in the EPC code header and the cyclic redundancy check code segment in the EPC code tail;

[0021] The fixed rules of the protocol version identifier include:

[0022] Extract the protocol version identifier from the EPC encoding header as a fixed bit field. The protocol version identifier is located at a preset position in the encoding structure, and its bit length corresponds to what is predefined in the protocol version mapping table. At the decoding end, load the corresponding decoding rule set according to the protocol version identifier;

[0023] The retention rules for the cyclic redundancy check code segment include:

[0024] Extract the original cyclic redundancy check code segment from the EPC encoding tail as a fixed bit field, and insert a secondary dynamic check code into the compressed variable-length encoded data to form a dual-check mechanism; The generation algorithm of the secondary dynamic check code is independent of the original cyclic redundancy check code, and its check range covers the compressed encoded data and the protocol version identifier.

[0025] Furthermore, the variable-length encoding conversion method includes:

[0026] Generate a dynamic dictionary table based on the statistical data of the reader historical data, and define the screening rules for frequently occurring encoding segments; perform bit mask matching on the original encoding. The bit mask matching includes: if there is a dictionary table entry whose different bits from the original encoding are less than or equal to the preset bit mask threshold, then output the corresponding entry index and the different bit mask, otherwise output the original encoding.

[0027] Furthermore, the spatio-temporal coordinate information generation method includes:

[0028] Compress the geographical location data output by the GNSS module into a binary field with a preset bit width;

[0029] Truncate the high-precision time stamp generated by the clock circuit into a field with a preset bit width, and splice it with the geographical location field to form a spatio-temporal label, which is embedded into the reserved bits of the EPC encoding.

[0030] Furthermore, the generation method of the dynamic check sequence includes:

[0031] According to the preset data volume interval to which the compressed encoded data volume belongs, match the corresponding check bit length from the predefined check bit length mapping table; among them, the data volume interval and the check bit length in the mapping table have an inverse correlation relationship; according to the Q value segmentation interval to which the current frame time slot number Q value belongs, match the corresponding check polynomial from the predefined check strategy mapping table; among them, the Q value segmentation interval and the error correction strength of the check polynomial in the mapping table have an inverse correlation relationship; based on the matched check bit length and check polynomial, perform redundancy calculation on the compressed encoded data, generate a dynamic check sequence and insert it into the transmission data packet.

[0032] An intelligent item tracking and identification system based on RFID technology, the system includes:

[0033] The acquisition and recognition module is used to collect the environmental noise intensity value and count the number of tags within the effective recognition range through the tag response signal;

[0034] The power control module is used to input the environmental noise intensity value and the number of tags into the power regulation model, output the reader transmitter power, and generate the reader transmitter power instruction;

[0035] The statistics module is used to count the number of collision time slots, successful time slots, and idle time slots of the tag response signal within a preset time window;

[0036] The frame time slot number adjustment module is used to dynamically adjust the frame time slot number Q value according to the proportional relationship of the number of collision time slots, successful time slots, and idle time slots;

[0037] The deletion and modification module is used to extract the EPC code of the successfully recognized tag and delete the predefined fixed bit segment data in the EPC code;

[0038] The encoding conversion module is used to perform variable-length encoding conversion on the remaining EPC code after deleting the fixed bit segment data and output the encoded data;

[0039] The transmission module is used to encapsulate the encoded data and the spatio-temporal coordinate information into a transmission data packet and send it to the server through a narrowband communication channel.

[0040] The technical effects and advantages of an intelligent item tracking and recognition method and system based on RFID technology provided by the present invention:

[0041] The present invention constructs an optimized system of "environment - data - communication" trinity, improves the dynamic adaptability, data transmission efficiency, and data reliability, improves the recognition success rate in high-noise scenarios, and significantly enhances the comprehensive performance of the system through multi-dimensional parameter linkage regulation and intelligent coding compression, providing a highly robust solution for large-scale Internet of Things deployment. The present invention is based on a dual-factor power regulation model of environmental noise intensity and tag density, dynamically adjusts the frame length in combination with the slot collision rate, and realizes precise resource allocation in complex scenarios; significantly reduces the data volume through dynamic deletion of EPC fixed redundant fields, variable-length coding compression, and spatio-temporal tag embedding; dynamically selects the verification strategy according to the data volume size and channel state, constructs a dual verification mechanism, and avoids resource waste caused by excessive redundancy; realizes flexible adaptation of the coding rule through the protocol version identifier and dynamic dictionary table design. Description of the Drawings

[0042] Figure 1 It is a flowchart of an intelligent item tracking and recognition method based on RFID technology in Embodiment 1;

[0043] Figure 2 It is a flowchart of the method for dynamically adjusting the Q value of the frame time slot number in Embodiment 1;

[0044] Figure 3 It is a schematic connection diagram of an intelligent item tracking and identification system based on RFID technology in Embodiment 2. Specific implementation manners

[0045] 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.

[0046] Embodiment 1:

[0047] Please refer to Figure 1 As shown, a method for tracking and identifying intelligent items based on RFID technology in this embodiment includes:

[0048] Collect the environmental noise intensity value, and count the number of tags within the effective identification range through the tag response signal;

[0049] Input the environmental noise intensity value and the number of tags into the power control model, output the transmitter power of the reader, and generate a transmitter power command for the reader;

[0050] Count the number of collision time slots, successful time slots, and idle time slots of the tag response signal within a preset time window;

[0051] Dynamically adjust the Q value of the frame time slot number according to the proportional relationship of the number of collision time slots, successful time slots, and idle time slots;

[0052] Extract the EPC code of the successfully identified tag, and delete the predefined fixed-bit segment data in the EPC code;

[0053] Perform variable-length coding conversion on the remaining EPC code after deleting the fixed-bit segment data, and output the coded data;

[0054] Encapsulate the coded data and the spatio-temporal coordinate information into a transmission data packet, and send it to the server through a narrowband communication channel.

[0055] The environmental noise intensity value is collected in real time through a radio frequency noise sensor built in the reader, with the unit of decibel milliwatt (dBm), which is the intensity of the radio frequency interference signal in the environment where the reader is located, usually generated by other co-located wireless devices (such as Wi-Fi, Bluetooth) or electromagnetic noise sources.

[0056] The statistical method for tag response signal statistics includes:

[0057] The reader sends a query command containing a Q value (the Q value determines the number of frame time slots);

[0058] The tag responds in a randomly selected time slot;

[0059] The reader detects the signal strength of each time slot. If only one tag responds in a certain time slot, it is counted as a successful time slot, otherwise it is marked as a collision time slot;

[0060] Estimate the number of tags based on the number of successful time slots (e.g., using the Schoute algorithm: T≈2.39×number of collision time slots).

[0061] Exemplary:

[0062] When Q = 16, the number of successful time slots counted = 10, the number of collision time slots = 3, and the estimated number of tags ≈10 + 2.39×3≈17.

[0063] The effective identification range is the maximum distance at which the reader antenna can reliably read tags, and it is affected by the transmit power, antenna gain, tag sensitivity, and environmental attenuation.

[0064] The power regulation model is a mathematical model for dynamically adjusting the transmit power according to the environmental noise and the number of tags, used to balance the identification success rate and energy consumption. The transmit power P is calculated through the following rules, and the calculation method includes:

[0065]

[0066] Among them, N tag is the current number of tags, N base is the preset reference number of tags, K(N tog ) is a piecewise increasing exponential function based on the number of tags, f(S noise ) is a non-linear mapping function of the environmental noise intensity, and α and β are preset weighting factors.

[0067] Through the design of weighting factors and functions, while ensuring the identification rate, the power consumption is minimized to achieve the optimal balance between performance and energy efficiency.

[0068] Please refer to Figure 2 As shown, the method for dynamically adjusting the Q value of the number of frame time slots includes:

[0069] If the proportion of collision time slots exceeds the preset upper threshold, then according to the formula Q new = Q current ×γ up increase the Q value, where γ up > 1 is the upward adjustment coefficient;

[0070] If the proportion of idle time slots exceeds the preset lower threshold, then according to the formula Q new = Q current ÷γ up decrease the Q value, where γ down > 1 is the downward adjustment coefficient.

[0071] Exemplary:

[0072] Initial parameter setting:

[0073] Current Q value: Q = 5 → number of frame time slots = 2 5 = 32 time slots.

[0074] Observation window: K = 8 time slots (for simplified calculation).

[0075] The preset upper threshold is 30%, and the preset lower threshold ratio is 40%.

[0076] The upward and downward adjustment coefficient γ = 1.5.

[0077] The first stage (high collision scenario);

[0078] Monitoring data:

[0079] Number of collision time slots C = 3 (collisions occur in time slots 2, 5, 7).

[0080] Number of idle time slots I = 1 (no response in time slot 4).

[0081] Number of successful time slots S = 4 (successfully identified in time slots 1, 3, 6, 8).

[0082] Ratio calculation:

[0083] Collision ratio = 3 / 8 = 37.5% (> 30%).

[0084] Idle ratio = 1 / 8 = 12.5% (< 40%).

[0085] Q value adjustment: 5 × 1.5 ≈ 9 → number of frame time slots = 2 8 = 256 time slots.

[0086] In the second stage (high idle scenario), after adjusting Q = 8 and running for a period of time: Monitoring data:

[0087] Number of collision time slots C = 1 (collision in time slot 128).

[0088] Number of idle time slots I = 5 (time slots 32, 64, 96, 160, 224 are idle). Number of successful time slots S = 2 (success in time slots 16, 192).

[0089] Ratio calculation:

[0090] Idle ratio = 5 / 8 = 62.5% (> 40%).

[0091] Collision ratio = 1 / 8 = 12.5% (< 30%).

[0092] Q value adjustment: 8 / 1.5 ≈ 5 → Number of frame time slots = 2 5 = 32 time slots.

[0093] In the third stage (stable scenario), after adjustment, Q runs at 5:

[0094] Monitoring data:

[0095] Number of collision time slots C = 2 (time slots 8 and 24 collide).

[0096] Number of idle time slots I = 3 (time slots 4, 16, and 28 are idle).

[0097] Number of successful time slots S = 3 (time slots 12, 20, and 30 are successful).

[0098] Ratio calculation:

[0099] Idle ratio = 25% (< 30%), collision ratio = 37.5% (< 40%). Adjustment result: → Q value remains 5 unchanged.

[0100] Automatically expand the capacity when high collisions are detected, contract resources when there are a large number of idle time slots, and finally converge to a stable state, improving the throughput.

[0101] The predefined fixed bit segment data includes the protocol version identifier in the EPC encoding header and the cyclic redundancy check code segment in the EPC encoding tail;

[0102] The EPC encoding consists of a string of numbers or letters and contains information such as the category of the item, the manufacturer, and the production date. The EPC encoding rules may be different for different versions. The protocol version identifier can tell the decoder which version of the rules should be used to read the data; the cyclic redundancy check code segment is generated through calculation. If the data is tampered with or damaged during transmission (such as signal interference), the cyclic redundancy check code will not match, thus detecting errors.

[0103] The fixed rules for the protocol version identifier include:

[0104] Extract the protocol version identifier from the EPC encoding header as a fixed bit segment. The protocol version identifier is located at a preset position in the encoding structure, and its bit length corresponds to the predefined mapping in the protocol version mapping table. At the decoding end, load the corresponding decoding rule set according to the protocol version identifier; the decoding rule set is equivalent to a version dictionary table, and the corresponding decoding rules can be found based on the protocol version identifier. This approach enables even old devices that do not support the new version to identify whether an upgrade is required based on the version number, and when a new version is added, only the "version dictionary table" needs to be updated, without rewriting the entire system.

[0105] The retention rules for the cyclic redundancy check code segment include:

[0106] Extract the original cyclic redundancy check code segment from the EPC encoding tail as a fixed bit segment, and insert a secondary dynamic check code into the compressed variable-length encoded data to form a dual verification mechanism. The first lock (cyclic redundancy check code) checks for basic errors, and the second lock (dynamic check code) prevents malicious tampering; the generation algorithm of the secondary dynamic check code is independent of the original cyclic redundancy check code, and its verification scope covers the compressed encoded data and the protocol version identifier. Dual verification can further enhance data storage security.

[0107] Exemplarily, the generation process of the EPC encoding:

[0108] Version identifier:

[0109] Use the "2023 Logistics Coding Rule", corresponding to the identifier 011.

[0110] Original data:

[0111] Contains the recipient address, package weight, and shipping route: Pudong, Shanghai, 5kg, Beijing - Jinan - Shanghai.

[0112] First-layer verification (cyclic redundancy check code):

[0113] Generate the check code 2F4A and append it to the end of the data.

[0114] Compress the data

[0115] Compress the data into a short string: SHPD5kg - BJ - JN - SH.

[0116] Second-layer verification (dynamic code):

[0117] Mix the version number 011 and the compressed data to generate the dynamic code 9E3C.

[0118] Final encoding:

[0119] 011SHPD5kg - BJ - JN - SH 2F4A 9E3C.

[0120] The variable-length coding conversion method includes:

[0121] Generate a dynamic dictionary table based on the statistical analysis of the reader's historical data, and define the screening rules for frequently occurring coding segments; the dynamic dictionary table records the frequently occurring coding segments and their corresponding short indexes, which are automatically generated by analyzing historical data, and the more frequently used segments are assigned shorter indexes.

[0122] Exemplarily:

[0123] Data statistics:

[0124] The system automatically analyzes all coding data of the reader in the past month.

[0125] Example: It is found that the coding segment 01001101 appears 100,000 times (accounting for 8% of the total data volume), exceeding the threshold of 5%.

[0126] Screening of high-frequency segments:

[0127] Add the segments with a frequency of occurrence > 5% to the dictionary table.

[0128] Dictionary table structure:

[0129] Index Coding segment Frequency of occurrence

[0130] 01 01001101 8%

[0131] 02 11000011 6%

[0132] Allocation of short indexes:

[0133] Replace the 8-bit high-frequency segments with 2-bit codes (such as 01, 02), and the compression ratio = 2 / 8 = 25%.

[0134] Perform bitmask matching on the original coding. The bitmask matching includes: if there is a dictionary table entry with the number of different bits from the original coding less than or equal to the preset bitmask threshold, output the corresponding entry index and the different bitmask; otherwise, output the original coding.

[0135] Exemplarily:

[0136] Preprocessing the original coding:

[0137] Split the 64-bit coding to be sent into 8 8-bit segments:

[0138] [Segment 1][Segment 2][Segment 3][Segment 4][Segment 5][Segment 6][Segment 7][Segment 8];

[0139] Detection of different bits:

[0140] For each segment, find the most similar entry in the dictionary table.

[0141] Matching rule: allow at most 1 bit difference (bitmask threshold = 1).

[0142] Example:

[0143] Original fragment: 01001101.

[0144] Dictionary entry: 01001001 (the difference is in the 7th position).

[0145] Difference bitmask: 10000000 (binary marks difference positions).

[0146] Encoding conversion:

[0147] If a similar entry is found, output the index + mask; otherwise output the original fragment.

[0148] Conversion results:

[0149] 01(index)+10000000(mask)(total length=2+8=10 bits).

[0150] Doing so can improve compression efficiency, saving resources and improving reliability, reducing scanning error alarms and improving inventory efficiency.

[0151] The method for generating space-time coordinate information includes:

[0152] Compress the geographic location data output by the GNSS module into a binary field with a preset bit width (e.g. 34052→100001010100);

[0153] The high-precision timestamp generated by the clock circuit is truncated into a preset bit width field, for example:

[0154] Base time: 2020-01-01 00:00:00 (Unix timestamp 1577836800)

[0155] Calculate the time difference:

[0156] Target timestamp: 2023-10-05 14:30:45.678 → Unix time 1696523445.678;

[0157] Difference in seconds: 1696523445.678-1577836800=118686645.678 seconds;

[0158] Maximum representable value: 2 15 -1 = 32767 seconds (about 9.1 hours) → needs to be stored in different levels;

[0159] Actual solution: Store the number of milliseconds of the day (0 to 86399999);

[0160] Time of the day: 14h × 3600 + 30m × 60 + 45.678s = 52245.678 seconds;

[0161] Converted to milliseconds: 52245678 ms;

[0162] Binary truncation:

[0163] 52245678 → Binary 110001110111001111101110 (24 bits);

[0164] Take the higher 15 bits: 110001110111001 (decimal 25,305);

[0165] And splice it with the geographical location field to form a spatio-temporal tag, which is embedded in the reserved bits of the EPC code.

[0166] The dynamic check sequence can dynamically generate check codes according to data characteristics, taking into account both transmission efficiency and reliability.

[0167] The generation method of the dynamic check sequence includes:

[0168] According to the preset data volume interval to which the compressed encoded data volume belongs, match the corresponding check bit length from the predefined check bit length mapping table; wherein, the data volume interval and the check bit length in the mapping table have an inverse correlation relationship; according to the Q-value segmented interval to which the current frame time slot number Q value belongs, match the corresponding check polynomial from the predefined check strategy mapping table; for example, CRC-8 (weak error correction): x 8 + x 2 + x + 1; CRC-16 (medium error correction strength): x 16 + x 15 + x 2 + 1; wherein, the Q-value segmented interval and the error correction strength of the check polynomial in the mapping table have an inverse correlation relationship; based on the matched check bit length and check polynomial, perform redundancy calculation on the compressed encoded data to generate a dynamic check sequence and insert it into the transmission data packet.

[0169] Exemplary:

[0170] Count the number of bytes of the compressed data, for example, the temperature and humidity data reported by the sensor is compressed to 185 bytes.

[0171] According to the mapping table, 185 bytes belong to the 128 - 512 interval → Select a 16-bit check code.

[0172] Large data blocks (> 512B) inherently have statistical redundancy, and short check codes are used to save space; small data (< 128B) requires stronger protection.

[0173] Obtain the current Q value: Q = 75 (medium congestion).

[0174] Check the policy mapping table:

[0175] Q value range, verification policy, error correction ability

[0176] 0 - 50, Reed - Solomon, can repair 2 - bit errors

[0177] 51 - 100, CRC - 16, detect 3 - bit errors

[0178] >100, CRC - 8, detect 1 - bit errors.

[0179] Matching result: Q = 75 → Select the CRC - 16 polynomial.

[0180] Redundancy calculation (taking CRC - 16 as an example):

[0181] Regard the data as a binary stream, such as 1011001100101101...

[0182] CRC - 16 polynomial x 16 +x 15 +x 2 +1 → binary 11000000000000101.

[0183] Modulo - 2 division operation:

[0184] Append 16 zeros at the end of the data → 10110011...0000.

[0185] Perform binary division with the polynomial and retain the remainder.

[0186] The remainder is the 16 - bit check code, such as 1100101011001101.

[0187] Doing so can not only flexibly adapt to environmental changes, but also accurately provide the required protection level without wasting resources.

[0188] Embodiment 2:

[0189] As Figure 3 shown, based on the same inventive concept as the intelligent item tracking and identification method based on RFID technology in the foregoing embodiment, this application provides an intelligent item tracking and identification system based on RFID technology. The system in the embodiment of this application and the method embodiment are based on the same inventive concept. Among them, the system includes:

[0190] An acquisition and identification module, which is used to acquire the environmental noise intensity value and count the number of tags within the effective identification range through the tag response signal;

[0191] A power control module, which is used to input the environmental noise intensity value and the number of tags into a power regulation model, output the transmitting power of the reader-writer, and generate a transmitting power instruction for the reader-writer;

[0192] A statistics module, which is used to count the number of collision time slots, successful time slots, and idle time slots of the tag response signals within a preset time window;

[0193] A frame time slot number adjustment module, which is used to dynamically adjust the Q value of the frame time slot number according to the proportional relationship of the number of collision time slots, successful time slots, and idle time slots;

[0194] A deletion and modification module, which is used to extract the EPC code of the successfully identified tags and delete the predefined fixed-bit segment data in the EPC code;

[0195] An encoding conversion module, which is used to perform variable-length encoding conversion on the remaining EPC code after deleting the fixed-bit segment data and output the encoded data;

[0196] A transmission module, which is used to encapsulate the encoded data and spatio-temporal coordinate information into a transmission data packet and send it to the server through a narrowband communication channel.

[0197] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

[0198] The above-mentioned are only the preferred specific implementation manners of the embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application, according to the technical solution and its concept of the present application, makes equivalent substitutions or changes, and all should be covered by the protection scope of the present application.

Claims

1. A smart item tracking and identification method based on RFID technology, characterized in that: Methods include: Collect the environmental noise intensity value and count the number of tags within the effective identification range through the tag response signal; Input the environmental noise intensity value and the number of tags into the power control model, output the reader transmit power, and generate a reader transmit power instruction; Counting the number of collision time slots, successful time slots and idle time slots of tag response signals within a preset time window; Dynamically adjust the frame time slot number Q value according to the ratio of the number of collision time slots, the number of successful time slots and the number of idle time slots; Extract the EPC code of the successfully identified tag and delete the predefined fixed bit segment data in the EPC code; Perform variable length coding conversion on the remaining EPC code after deleting the fixed bit segment data, and output the coded data; The encoded data and the space-time coordinate information are encapsulated into a transmission data packet and sent to the server through a narrowband communication channel.

2. The method according to claim 1, characterized in that The power control model calculates the transmit power P according to the following rules, and the calculation method includes: Among them, Ntag is the current number of tags, N base The number of preset benchmark tags, K(Ntog) is a piecewise increasing exponential function based on the number of tags, and f(S noise ) is a nonlinear mapping function of the ambient noise intensity, and α and β are preset weighting factors.

3. The method according to claim 1, characterized in that: The method for dynamically adjusting the frame time slot number Q value comprises: If the collision time slot ratio exceeds the preset upper limit threshold, then according to the formula Q new =Q current ×γ up Increase the Q value, where γ up >1 is an upward adjustment coefficient; If the idle time slot ratio exceeds the preset lower limit, the formula Q new =Q current ÷γ up Reduce the Q value, where γ down >1 is a downward adjustment factor.

4. The method according to claim 1, characterized in that: The predefined fixed bit segment data includes a protocol version identifier in the EPC coding header and a cyclic check code segment in the EPC coding tail; The fixed rules for protocol version identifiers are: Extracting a protocol version identifier from the EPC encoding header as a fixed bit segment, the protocol version identifier is located at a preset position of the encoding structure, and its bit length corresponds to a predefined protocol version mapping table, and at the decoding end, loading a corresponding decoding rule set according to the protocol version identifier; The retention rules for the cyclic check code segment include: The original cyclic check code segment is extracted from the tail of the EPC code as a fixed bit segment, and a secondary dynamic check code is inserted into the compressed variable-length coded data to form a double check mechanism; the generation algorithm of the secondary dynamic check code is independent of the original cyclic check code, and its check range covers the compressed coded data and the protocol version identifier.

5. The method according to claim 1, characterized in that The variable length coding conversion method comprises: Generate a dynamic dictionary table based on the historical data statistics of the reader / writer, and define the screening rules for frequently appearing code fragments; perform bit mask matching on the original code, and the bit mask matching includes: if the difference between the dictionary table entry and the original code is less than or equal to the preset bit mask threshold, output the corresponding entry index and difference bit mask, otherwise output the original code.

6. The method according to claim 1, characterized in that The method for generating space-time coordinate information comprises: Compressing the geographic location data output by the GNSS module into a binary field of a preset bit width; The high-precision timestamp generated by the clock circuit is truncated into a preset bit width field, and is spliced ​​with the geographic location field into a time-space label, which is embedded in the reserved bit of the EPC code.

7. The method according to claim 1, characterized in that The method for generating the dynamic verification sequence includes: According to the preset data volume interval to which the compressed coded data volume belongs, the corresponding check bit length is matched from a predefined check bit length mapping table; wherein the data volume interval in the mapping table is inversely correlated with the check bit length; according to the Q value segmentation interval to which the current frame time slot number Q value belongs, the corresponding check polynomial is matched from a predefined check strategy mapping table; wherein the Q value segmentation interval in the mapping table is inversely correlated with the error correction strength of the check polynomial; based on the matched check bit length and check polynomial, redundant calculation is performed on the compressed coded data, and a dynamic check sequence is generated and inserted into a transmission data packet.

8. An intelligent item tracking and identification system based on RFID technology, characterized in that: The system includes: The acquisition and identification module is used to collect the environmental noise intensity value and count the number of tags within the effective identification range through the tag response signal; The power control module is used to input the environmental noise intensity value and the number of tags into the power control model, output the reader transmit power, and generate the reader transmit power instruction; A statistics module, which is used to count the number of collision time slots, successful time slots and idle time slots of the tag response signal within a preset time window; A frame time slot number adjustment module, which is used to dynamically adjust the frame time slot number Q value according to the proportional relationship between the collision time slot number, the success time slot number and the idle time slot number; The deletion and modification module is used to extract the EPC code of the successfully identified tag and delete the predefined fixed bit segment data in the EPC code; A coding conversion module, which is used to perform variable-length coding conversion on the remaining EPC codes after deleting the fixed bit segment data, and output the coded data; The transmission module is used to encapsulate the coded data and the space-time coordinate information into a transmission data packet, and send it to the server through a narrowband communication channel.

Images