A database for RFID collision identification and a construction method thereof, an RFID collision identification method and system

Abstract

The application provides a database for RFID collision identification and a construction method thereof, an RFID collision identification method and system. The construction method of the database for RFID collision identification comprises the following steps: S1, obtaining tag IDs and tag data of any two tags, wherein the tag ID comprises a binary sequence with a preset number of bits; S2, calculating superimposed data of the superimposed tag IDs of the two tags according to the overlapping range from one-bit overlap to complete overlap; S3, merging the superimposed data associated with the two tags into collision data and assigning a collision ID, wherein the collision ID is associated with the tag IDs and tag data of the two tags. Through retrieval from the database, the computational difficulty of directly analyzing the tag data from the collision data is avoided, thereby improving the efficiency and accuracy of the identification system in reading the RFID tags after data collision.

Description

Technical Field

[0001] This invention relates to the field of RFID tag identification technology, and in particular to a database for RFID collision identification and its construction method, as well as an RFID collision identification method and system. Background Technology

[0002] In a Radio Frequency Identification (RFID) system, the identification process involves a reader transmitting radio frequency signals to a tag via its antenna. This process consists of two phases: in the first phase, the tag sends a 16-bit random number (RN16); in the second phase, it sends an Electronic Product Code (EPC). After capturing this data, the reader interprets it according to a predetermined decoding protocol and displays the final reading result to the user.

[0003] In RFID systems, data exchange between RFID readers and electronic tags is accomplished wirelessly. Since all tags share the same communication channel, when multiple tags transmit data simultaneously, multiple data signals may overlap on the communication channel, leading to data collisions and transmission failures. To address this issue, two types of anti-collision algorithms have been developed: deterministic anti-collision algorithms and random competition-based anti-collision algorithms. The industry widely adopts random competition-based anti-collision algorithms (such as the ALOHA algorithm) to reduce the probability of data collisions and improve the reading efficiency and accuracy of RFID systems.

[0004] In practical applications such as libraries, supermarkets, and factories, RFID (Radio Frequency Identification) technology is widely used for item management, inventory counting, and product tracking. These scenarios often involve a large number of items with RFID tags, requiring readers to collect data in real time. However, because multiple tags may transmit data simultaneously, data collisions become an unavoidable problem. For example, on factory production lines, RFID technology is used to track product status in real time. The data collision problem is particularly prominent when a large number of tagged semi-finished or finished products are present on the production line simultaneously. This not only reduces reading efficiency but may also lead to inaccurate data collection on the production line, affecting product quality and production schedule. In these scenarios, where a large number of tags need to be read, data collisions are inevitable due to the possibility of multiple tags transmitting data simultaneously. Existing identification methods suffer from low efficiency and accuracy when reading RFID tags after data collisions occur. Therefore, a high-efficiency and accurate RFID tag identification system is needed to address collision scenarios. Summary of the Invention

[0005] This invention provides a database for RFID collision identification and its construction method, as well as an RFID collision identification method and system, to solve the problems of low efficiency and accuracy in reading RFID tags after a data collision.

[0006] In a first aspect, according to an embodiment of the present invention, a method for constructing a database for RFID collision identification is provided, comprising the following steps: S1, for any two tags, obtaining their tag IDs and tag data, wherein the tag ID includes a binary sequence of a preset number of bits; S2, for the tag IDs of the two tags, calculating the superimposed data of the two tag IDs respectively, based on the overlap range increasing from one bit overlap to complete overlap; S3, merging the superimposed data associated with the two tags into collision data and assigning a collision ID, wherein the collision ID is associated with the tag IDs and tag data of the two tags.

[0007] According to an embodiment of the present invention, the tag ID includes an electronic product code.

[0008] According to an embodiment of the present invention, the binary sequence with a preset number of bits is a 16-bit preamble.

[0009] According to an embodiment of the present invention, the tag data includes RN16 messages.

[0010] Secondly, according to another embodiment of the present invention, a database for RFID collision identification is provided, which is constructed using a database construction method for RFID collision identification as described in the first aspect.

[0011] Thirdly, according to another embodiment of the present invention, an RFID collision identification method is provided, comprising the following steps: T1, acquiring tag data to be identified and demodulating it into digital data; T2, comparing the digital data with collision data in a database for RFID collision identification as described in the second aspect; T3, returning the tag IDs and tag data of the two identified tags based on the similarity comparison result.

[0012] According to another embodiment of the present invention, the similarity is:

[0013] ,

[0014] in, This represents a vector composed of the label data to be identified. This represents a vector composed of collision data. and Representing vectors sum vector The Euclidean norm.

[0015] According to another embodiment of the present invention, the following formula is used for calculation:

[0016] ,

[0017] in, for[ ],and for[ ].

[0018] According to another embodiment of the present invention, the Euclidean norm of a vector is:

[0019] ,

[0020] .

[0021] Fourthly, according to another embodiment of the present invention, an RFID collision identification system is provided, comprising: a tag device for exchanging data with a reader; and a reader for acquiring tag data to be identified and identifying the tag data using an RFID collision identification method as described in the third aspect.

[0022] Compared with existing technologies, the present invention has the following advantages: by enumerating all possible data collision scenarios and constructing a corresponding database in advance, the data of the two parties involved in the data collision can be determined by searching and querying during the subsequent identification process. This avoids the computational difficulty of directly parsing the tag data from the collision data, thereby improving the efficiency and accuracy of the identification system in reading RFID tags after a data collision occurs. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating a method for constructing a database for RFID collision identification according to an embodiment of the present invention. Detailed Implementation

[0024] Before proceeding with the detailed description below, it may be advantageous to define certain words and phrases used throughout this patent document. The terms “coupled,” “connected,” and their derivatives refer to any direct or indirect communication or connection between two or more elements, regardless of whether those elements are physically in contact with each other. The terms “transmit,” “receive,” and “communicate,” and their derivatives cover both direct and indirect communication. The terms “comprise,” “include,” and their derivatives refer to, but are not limited to, those including, those including, those including, those including. The term “or” is inclusive, meaning and / or. The phrase “associated with,” and its derivatives refer to, including, being contained within, interconnected, containing, being included in, being connected or connected to, coupled or coupled to, communicating with, cooperating, intertwining, juxtaposed, proximate, bound or bound to, having, having attributes, having a relationship or being related to, etc. The term “controller” refers to any device, system, or part thereof that controls at least one operation. Such a controller may be implemented in hardware, or a combination of hardware and software and / or firmware. The functionality associated with any particular controller may be centralized or distributed, local or remote.

[0025] Definitions of other specific words and phrases are provided throughout this patent document. Those skilled in the art will understand that, in many, if not most, cases, such definitions apply to the prior and future use of the words and phrases thus defined.

[0026] In this patent document, the application combination of modules and the hierarchical division of sub-modules are for illustrative purposes only. Without departing from the scope of this disclosure, the application combination of modules and the hierarchical division of sub-modules can be in different ways.

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the invention.

[0028] The technical solutions of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0029] As described in the background section, existing identification methods suffer from low efficiency and accuracy when reading RFID tags after a data collision. To address this problem, as... Figure 1As shown in the embodiment of the present invention, a method for constructing a database for RFID collision identification is provided, comprising the following steps: S1, for any two tags, obtain their tag IDs and tag data, wherein the tag ID includes a binary sequence of a preset number of bits; S2, for the tag IDs of the two tags, calculate the superimposed data of the two tag IDs respectively, according to the overlap range increasing from one bit overlap to complete overlap; S3, merge the superimposed data associated with the two tags into collision data and assign a collision ID, wherein the collision ID is associated with the tag IDs and tag data of the two tags. By pre-enumerating all possible data collisions and constructing a corresponding database, the data of the two parties involved in the data collision can be determined by retrieval and query during the subsequent identification process, avoiding the computational difficulty of directly parsing the tag data from the collision data, thereby improving the efficiency and accuracy of the identification system in reading RFID tags after a data collision.

[0030] Furthermore, using two labels as an example serves two purposes: firstly, it allows for a simpler and clearer explanation of the invention; secondly, in actual experiments, collisions between two labels are the most common occurrence. Collisions between more than two labels are relatively rare, therefore, for efficiency reasons, collisions involving more than two labels can be discarded.

[0031] To ensure the uniqueness of each tag, according to embodiments of the present invention, the tag ID includes an electronic product code. Furthermore, the encoding methods for RFID electronic tags also include UID (Unique Identifier) ​​and custom encoding. The UID is a unique identification code inherent to the RFID tag at the factory, used to distinguish different tags; while the custom encoding is flexibly designed according to actual needs to meet the requirements of specific application scenarios.

[0032] To achieve data matching, the data and range involved in the collision are first determined. According to an embodiment of the invention, a binary sequence with a preset number of bits is a 16-bit preamble. The preamble can specifically indicate the tag device firstly, and secondly, it can indicate the range of the collision. For example, from a timing perspective, for the 16-bit preambles of two tags, the minimum overlap is one bit, meaning the last bit of the preceding sequence overlaps with the first bit of the following sequence. Furthermore, the maximum overlap is the entire length of the preamble, meaning every bit overlaps. In addition, from a symbol perspective, collisions can be categorized as 00 collisions, 01 collisions, 10 collisions, and 11 collisions. Moreover, in practical use, due to different locations, the voltage values ​​of the signals emitted by each tag device are likely to be different, thus distinguishing between 01 collisions and 10 collisions.

[0033] According to an embodiment of the present invention, the tag data includes an RN16 message. The RN16 message is a 16-bit random number. After capturing this data, the reader will interpret the data according to a predetermined decoding protocol and display the final reading result to the user. Furthermore, depending on the application scenario, the most basic content of an RFID electronic tag is the basic information of the item, including the item's unique identifier (such as an EPC code), name, specifications, production date, manufacturer, etc. This information helps construct the digital identity of each item, facilitating rapid identification and management in supply chain, inventory management, product traceability, and other stages. In addition to basic information, the electronic tag can also contain dynamic data, such as the cargo's transportation location, environmental parameters like temperature and humidity, as well as the inventory quantity and sales status of the goods. Real-time updates of this dynamic data enable enterprises to better understand the status of goods, adjust operational strategies in a timely manner, and improve efficiency and customer satisfaction.

[0034] According to another embodiment of the present invention, a database for RFID collision identification is provided, constructed using the aforementioned method for constructing a database for RFID collision identification. After the database is constructed, RFID identification can be performed through querying.

[0035] According to another embodiment of the present invention, an RFID collision identification method is provided, comprising the following steps: T1, acquiring tag data to be identified and demodulating it into digital data; T2, comparing the digital data with collision data in a database for RFID collision identification as described above; T3, returning the tag IDs and tag data of the two identified tags based on the similarity comparison result.

[0036] In order to perform data matching and comparison, according to another embodiment of the present invention, the similarity is:

[0037] ,

[0038] in, This represents a vector composed of the label data to be identified. This represents a vector composed of collision data. and Representing vectors sum vector The Euclidean norm. In addition to the cosine similarity comparison used in this invention, Euclidean distance can also be used. Euclidean distance is a commonly used definition of distance, referring to the true distance between two points in n-dimensional space. In two-dimensional and three-dimensional space, the Euclidean distance is the straight-line distance between two points. The Pearson correlation coefficient can also be used. The Pearson correlation coefficient is generally used to calculate the degree of connection between two fixed-distance vectors, and its value ranges from […]. The correlation coefficient is between 1 and +1. The larger the absolute value of the correlation coefficient, the higher the correlation between X and Y. When X and Y are linearly correlated, the correlation coefficient is 1 (positive linear correlation) or +1. 1 (Negative linear correlation).

[0039] According to another embodiment of the present invention, the following formula is used for calculation:

[0040] ,

[0041] in, for[ ],and for[ ].

[0042] According to another embodiment of the present invention, the Euclidean norm of a vector is:

[0043] ,

[0044] .

[0045] According to another embodiment of the present invention, an RFID collision identification system is provided, comprising: a tag device for exchanging data with a reader; and a reader for acquiring tag data to be identified and identifying the tag data using an RFID collision identification method as described above.

[0046] This invention can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of the invention.

[0047] Computer-readable storage media can be tangible devices that hold and store instructions for use by an instruction execution device. Computer-readable storage media can be, for example, including but not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof.

[0048] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for constructing a database for RFID collision identification, characterized in that, By pre-enumerating all possible data collision scenarios and constructing a corresponding database, the two data points involved in the collision can be identified through retrieval and querying during subsequent identification processes. The construction method includes the following steps: S1. For any two tags, obtain their tag ID and tag data, where the tag ID includes a binary sequence of a preset number of bits; S2. For the tag IDs of two tags, calculate the superimposed data of the two tag IDs after superimposing, based on the overlap range increasing from one bit overlap to complete overlap. S3. Merge the superimposed data associated with the two labels into collision data and assign a collision ID, wherein the collision ID is associated with the label ID and label data of the two labels.

2. The method for constructing a database for RFID collision identification according to claim 1, characterized in that, The tag ID includes the electronic product code.

3. The method for constructing a database for RFID collision identification according to claim 1, characterized in that, The default number of bits in the binary sequence is a 16-bit preamble.

4. The method for constructing a database for RFID collision identification according to claim 1, characterized in that, The tag data includes RN16 messages.

5. A database for RFID collision identification, characterized in that, The database for RFID collision identification is constructed using any one of the methods described in claims 1-4.

6. An RFID collision identification method, characterized in that, Includes the following steps: T1. Obtain the label data to be identified and demodulate it into digital data; T2. Compare the digital data with the collision data in a database for RFID collision identification as described in claim 5; T3. Based on the similarity comparison results, return the tag IDs and tag data of the two identified tags.

7. The RFID collision identification method according to claim 6, characterized in that, Similarity is: ， in, This represents a vector composed of the label data to be identified. This represents a vector composed of collision data. and Representing vectors sum vector The Euclidean norm.

8. The RFID collision identification method according to claim 7, characterized in that, Similarity calculation process Calculate using the following formula: ， in, for[ ],and for[ ].

9. The RFID collision identification method according to claim 8, characterized in that, The Euclidean norm of a vector is: ， 。 10. An RFID collision identification system, characterized in that, include: Tag devices used for exchanging data with readers; The reader acquires the tag data to be identified and uses an RFID collision identification method as described in any one of claims 6-9 to identify the tag data.

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