Book positioning method

Abstract

The application provides a book positioning method, comprising: a book classification method configured to divide books into two categories by the thickness of the book spine, if the thickness of the book spine exceeds a first threshold value, the book is divided into an image barcode category, otherwise the book is divided into an RFID category; a mark generation method configured to generate different marks for different types of books, forming an image barcode mark on the spine of the image barcode category book, and placing an RFID mark in the RFID category book; a first positioning module configured to identify the book according to the image barcode mark on the image barcode category book; and a second positioning module configured to identify the book according to the RFID mark on the RFID category book.

Description

Technical Field

[0001] This invention relates to the field of information technology for library management, and in particular to a method for locating books. Background Technology

[0002] Libraries commonly face the challenge of locating and shelving books in their daily operations. Due to the unpredictable nature of readers' reading habits, returning books to their proper places after reading is extremely difficult. Many books are carelessly placed on shelves far from designated locations, making them hard to find and locate, thus affecting subsequent readers' access to the books. Existing book location methods can be broadly categorized into two types: spine tags and RFID tags. Spine tags use cameras to capture images and image analysis software to read the book's identification information; RFID tags use dedicated readers to read the book's identification information. However, spine tags are incomplete on thinner books, making them difficult to read; RFID tags also face limitations in the number that can be used per unit space, otherwise, severe collisions will occur, rendering them unusable. Summary of the Invention

[0003] The purpose of this invention is to provide a book location method to solve the problem of books being difficult to find and locate due to readers placing them haphazardly. The basic idea is to divide books into two categories: thick and thin, and use different location methods for each. Thick books have ample space on their spines, allowing for complete label display and easy reading using image technology; thin books are equipped with RFID tags. This compensates for the difficulty in tag reading due to insufficient spine thickness, and the relatively low proportion of thin books significantly reduces the risk of RFID collisions, thus improving work efficiency.

[0004] To solve the above-mentioned technical problems, the present invention provides a book positioning system, comprising:

[0005] The book classification method is configured to classify books based on their spine thickness. If the thickness exceeds a first threshold, the book is classified as an image barcode book; otherwise, the book is classified as an RFID book.

[0006] The tag generation method is configured to form image barcode tags on the spine of image barcode books and place RFID tags in RFID books;

[0007] The first positioning module is configured to identify books based on the image barcode markings on image barcode books, and obtain the image identification code of the image barcode books; and

[0008] The second positioning module is configured to identify books based on RFID tags on RFID-enabled books, and obtain the information about the RFID-enabled books.

[0009] RFID identification code.

[0010] Optionally, the book positioning system may also include:

[0011] The integrated decision-making module is configured to fuse and make a comprehensive judgment on the image identification code information of the book obtained by the first positioning module and the RFID identification code information obtained by the second positioning module;

[0012] Optionally, the book positioning system may also include:

[0013] The anti-collision module is configured to implement a dynamic frame ALOHA anti-collision strategy to avoid collisions between multiple RFID-enabled books.

[0014] The RFID tag is experiencing a collision.

[0015] The dynamic frame ALOHA anti-collision strategy includes adjusting the first threshold of the book counting and barcode extraction modules based on the estimated number of RFID-enabled books on the bookshelf.

[0016] Optionally, in the book positioning system, the book counting and barcode extraction module includes: a shooting module configured to take pictures of the books on the bookshelf using a camera installed on the bookshelf;

[0017] The analysis module is configured to analyze the images obtained by the imaging module, and use image processing algorithms to locate book stacks, segment books, extract spines, estimate thickness, and count books, thereby completing the classification and statistics of image barcode books and RFID books.

[0018] Optionally, in the book positioning system, the first positioning module is an image tag recognition module, wherein:

[0019] The analysis module provides the extracted image barcode markings from the spine of the books to the image label recognition module, so that the image label recognition module can identify the unique image recognition code corresponding to the book.

[0020] The analysis module provides the quantity estimate of RFID-class books to the anti-collision module for dynamic time slot configuration.

[0021] Optionally, in the book positioning system, the anti-collision module uses the received estimated number of RFID books as a rough estimate of the number of tags on each bookshelf, and configures dynamic time slot frames accordingly. The frame length is reasonably adjusted based on the number of tags to be identified, thereby optimizing the execution efficiency of tag detection and maximizing the anti-collision performance of RFID.

[0022] The integrated decision-making module obtains the barcode and RFID information of books on each bookshelf through the network, and obtains the unique ID information of each book, so that the book positioning system can form a comprehensive and seamless coverage of the library's collection, and make the accuracy and efficiency of book positioning meet the requirements of practical application.

[0023] Optionally, the book positioning system may also include:

[0024] The image preprocessing module is used to perform noise reduction preprocessing on the images input by the imaging module, in preparation for image processing by the subsequent analysis module;

[0025] The book stack localization module is used to divide the bookshelves in the image into layers through spatial multi-object detection and classification, and find the location of the books stacked on each layer. It uses deep network technology to realize the localization and bounding of the book stacks on each layer of the bookshelf in the field of view. The book segmentation and conversion module is used to further process the book stacks bounded by the book stack localization module through line detection and local correction, segmenting the vertically or horizontally arranged books in the stack into independent objects, and defining each book with standard geometric shapes.

[0026] The spine extraction module extracts rectangular images from the book segmentation results to form a spine image, which is then further standardized to facilitate thickness estimation.

[0027] The thickness estimation module estimates the thickness of books using spine images and uses a statistical averaging method to reduce thickness errors; the book counting module counts books with image barcodes and RFID using spine images respectively.

[0028] Optionally, in the book positioning system, the second positioning module is an RFID reader, the RFID tag is an RFID marker, and the book positioning system further includes:

[0029] The initialization module is used to read the estimated number of RFID books provided by the book counting module and use it as a rough estimate of the number of RFID tags within the range of the RFID reader. It also configures the parameters of the dynamic frame ALOHA anti-collision strategy and assigns an initial value to the dynamic frame length.

[0030] The time slot dynamic allocation module is used to allocate time slot resources to RFID tags within the range of the RFID reader using a pseudo-randomization method;

[0031] The time slot detection module is used to confirm the existence of RFID tags by broadcasting identification commands to the RFID tags and analyzing the ID information returned by the RFID tags. The confirmation strategy includes: detecting the number of successful time slots, the number of idle time slots, and the number of collision time slots in the ID information, repeating the process multiple times, and statistically analyzing the results.

[0032] The tag identification module is used to analyze the number of various time slots to determine which RFID tags have been identified and which have not.

[0033] The RFID tag has not yet been identified;

[0034] The frame length dynamic adjustment module is used to reset a reasonable frame length based on the identification status of RFID tags;

[0035] The initial number of RFID tags within the RFID reader's range is greater than the second threshold to ensure no collisions occur. Adjustments are made using a frame length dynamic adjustment module based on the time slot usage.

[0036] The inventors of this invention discovered through research that while existing technologies have proposed some solutions to address the problem of locating books throughout a library, their effectiveness is unsatisfactory. For example, some methods use image analysis, attaching graphic markers with book identification to the spine of books and installing cameras on the bookshelves to identify these markers and thus locate the books. However, when the thickness of the books does not meet a certain standard, attaching the markers to the spine is difficult, the exposed identifiable portion is too small, and the recognition rate is low, failing to meet the requirements. Other methods use RFID technology, placing RFID tags inside the books and installing RFID readers on the bookshelves to obtain the location of the books to be detected by reading the tag information within the effective range. However, due to the large number of books on the shelves, RFID suffers from severe collision problems, making it difficult to obtain accurate detection results, and therefore, it cannot be put into practical use.

[0037] Based on the above insights, this invention provides a book location method that combines image barcode recognition and RFID detection, utilizing book classification to leverage the strengths of both methods while avoiding their weaknesses. This overcomes the shortcomings of existing methods, resulting in a practical hybrid library book location system that improves the informatization of library management.

[0038] level.

[0039] This invention classifies books based on their spine thickness. Books exceeding a threshold are categorized as image barcode books; otherwise, they are classified as RFID books. A tag generation method creates image barcodes on the spines of image barcode books and places RFID tags on RFID books. A first positioning module identifies books based on the image barcodes, while a second positioning module identifies books based on the RFID tags. This provides a practical hybrid library book positioning system. Unlike existing systems, this invention uses a hybrid strategy, combining image barcode and RFID technologies. Its core principle is categorizing books into thick and thin books based on their thickness. Thick books have clear, complete barcodes on their spines, which can be identified using a camera, while thin books have RFID tags. Note that this invention only places RFID tags on thin books. Since the number of thin books in a library is limited, and even fewer are on each shelf, the collision problem of RFID tags is effectively overcome. This invention also uses image analysis technology to obtain an accurate estimate of the number of thin books on the bookshelf, and adjusts the key parameters of the RFID subsystem online accordingly to minimize RFID collision problems. Attached Figure Description

[0040] Figure 1 is a schematic diagram of the module of a book positioning system according to an embodiment of the present invention, which determines the thickness of books on a bookshelf and counts them respectively.

[0041] Figure 2 is a flowchart illustrating the anti-collision module for reading RFID information in a thin book in a book positioning system according to an embodiment of the present invention.

[0042] Figure 3 is a schematic diagram of the module flow of a book positioning system according to an embodiment of the present invention, which integrates book barcode information and RFID information and makes a comprehensive judgment and decision. Detailed Implementation

[0043] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0044] It should be noted that the components in the various figures may be shown exaggeratedly for illustrative purposes and are not necessarily to scale. In each figure, the same reference numerals are used for components that are identical or have the same function.

[0045] In this invention, unless otherwise specified, "arranged on," "arranged above," and "arranged on" do not exclude the possibility of an intermediate element between them. Furthermore, "arranged on or above" merely indicates the relative positional relationship between two components, and in certain cases, such as when the product orientation is reversed, it can also be converted to "arranged below or under," and vice versa.

[0046] In this invention, the various embodiments are merely intended to illustrate the solutions of the invention and should not be construed as limiting.

[0047] In this invention, unless otherwise specified, the quantifiers “a” and “one” do not exclude scenarios involving multiple elements.

[0048] It should also be noted that, in the embodiments of the present invention, only a portion of the components or parts may be shown for clarity and simplicity. However, those skilled in the art will understand that, under the teachings of the present invention, necessary components or parts can be added as needed for specific scenarios. Furthermore, unless otherwise stated, features in different embodiments of the present invention can be combined with each other. For example, a feature in the second embodiment can replace a corresponding or functionally identical or similar feature in the first embodiment, and the resulting embodiment will also fall within the scope of disclosure or description of this application.

[0049] It should also be noted that, within the scope of this invention, the terms "same," "equal," and "equal to" do not imply that the two values ​​are absolutely equal, but rather allow for a certain reasonable margin of error. In other words, the terms also encompass "substantially the same," "substantially equal," and "substantially equal to." Similarly, in this invention, the directional terms "perpendicular to," "parallel to," etc., also encompass the meanings of "substantially perpendicular to" and "substantially parallel to."

[0050] Furthermore, the numbering of the steps in the methods of the present invention does not limit the execution order of the method steps. Unless otherwise specified, the method steps may be executed in different orders.

[0051] The book positioning method proposed in this invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of this invention will become clearer from the following description and claims. It should be noted that the drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of this invention.

[0052] The purpose of this invention is to provide a book location method to solve the problem that existing books are difficult to find and locate because they are placed randomly by readers.

[0053] To achieve the above objectives, the present invention provides a book positioning method, comprising: a book classification method configured to classify books according to their spine thickness, wherein if the thickness exceeds a first threshold, the book is classified as an image barcode book, otherwise the book is classified as an RFID book; a tag generation method configured to form an image barcode tag on the spine of the image barcode book and place an RFID tag in the RFID book; a first positioning module configured to identify the book based on the image barcode tag on the image barcode book; and a second positioning module configured to identify the book based on the RFID tag on the RFID book.

[0054] This invention proposes a hybrid library book location method, which includes a module for determining the thickness of books on a bookshelf and counting them separately, an anti-collision module for reading RFID information from thin books (RFID-type books), and a module for fusing book barcode information with RFID information and making a comprehensive judgment decision. By classifying library collections according to book thickness, different location methods are used to handle thick and thin books respectively.

[0055] In one embodiment of the invention, a camera and an RFID reader are installed on each bookshelf. Image tags are affixed to the spines of thick books (image barcode books) for identification and positioning; RFID tags are placed in thin books for detection and positioning using RFID technology. Since thin books (RFID books) constitute only a small portion of the entire collection, the number of thin books on each bookshelf is very limited. Therefore, placing RFID tags only in thin books can...

[0056] To minimize the impact of RFID collisions on identification, since the spine of a thick book has ample space, attaching image tags to the spine ensures the integrity and readability of the tags, enabling image recognition to meet practical requirements.

[0057] In one embodiment of the present invention, the approximate number of thin books on the bookshelf is determined by image analysis and provided to an anti-collision module based on the ALOHA principle for the adjustment and setting of dynamic time slot frames.

[0058] Referring to Figure 1, which is a simplified structural diagram of a module used to determine the thickness of books on a bookshelf and count them, the module includes:

[0059] Module 100 is an image preprocessing module, used to perform routine preprocessing operations such as noise reduction on the input image to prepare it for subsequent image analysis.

[0060] Module 101 is the book stack localization module, used to divide the bookshelf in the image into layers and find the location of the books stacked on each layer. The key to this step lies in the detection and classification of multiple objects in space. Relatively mature deep network technology can be used to localize and define the bounding box of the books stack on each layer of the bookshelf in the field of view.

[0061] Module 102 is a book segmentation and conversion module, used to further process the book pile defined by the book pile positioning module. Books in the pile, whether arranged vertically or horizontally, are segmented into independent objects, with each book defined by a standard geometric shape (e.g., a rectangle). Book segmentation falls under relatively regular image recognition and localization, and can be accomplished using standard and mature methods such as line detection, with local corrections.

[0062] Module 103 is the spine extraction module, which extracts the image of the spine from the results of book segmentation. This is typically a long, narrow rectangular image. The spine extraction step requires further normalization of the spine image to facilitate thickness estimation.

[0063] Module 104 is the thickness estimation module, which uses spine images to estimate the book's thickness. Since the thickness displayed on the spine image may not be uniform, a statistical averaging method is used to reduce error. If the book's thickness meets a certain standard, i.e., it is classified as a thick book, an image tag will be affixed to the spine, which can be identified using the recognition module. If the book's thickness does not meet the standard, i.e., it is classified as a thin book, there will be no tag on the spine, and no processing is required. Thin books contain RFID tags, which can be detected using RFID technology.

[0064] Module 105 is a book counting module that uses spine images to classify and count thick and thin books. The counting granularity is at the bookshelf level, aiming to provide the RFID anti-collision module with a rough estimate of the number of tags, facilitating its optimization of dynamic configuration parameters and maximizing the effectiveness of anti-collision.

[0065] Referring to Figure 2, which is a simplified flowchart of the anti-collision module for reading RFID information in thin books, it includes:

[0066] Module 201 is an initialization module used to read the number of thin books given by the book counting module and use it as a rough estimate of the number of RFID tags within the range of the RFID reader, configure the parameters of the ALOHA algorithm, and assign an initial value to the dynamic frame length.

[0067] Module 202 is a time slot dynamic allocation module that uses a pseudo-randomization method to allocate time slot resources to RFID tags within the range of the RFID reader.

[0068] Module 203 is a time slot detection module. It confirms the existence of a tag by broadcasting an identification command to the tag and analyzing the ID information returned by the tag. The specific confirmation strategy involves detecting the number of time slots of various types, such as successful, idle, and collision, in the returned signal. To improve robustness, a similar process can be repeated multiple times, and the results can be statistically analyzed.

[0069] Module 204 is a tag recognition module. By analyzing the number of various time slots, it can determine which tags have been recognized and which tags have not yet been recognized.

[0070] Module 205 is a frame length dynamic adjustment module that resets a reasonable frame length based on the identification of tags.

[0071] It should be emphasized that, in order to ensure that no collisions occur, the initial number of tags within the RFID reader's effective range should be sufficiently large, and then adjusted using the frame length dynamic adjustment module according to the usage of time slots.

[0072] Figure 3 shows a simplified flowchart of the information fusion and comprehensive judgment decision module (ID in the figure is an abbreviation for identification code): Module 301 is the identification code aggregation module, which aggregates the thick book image identification code information transmitted by the camera and the thin book RFID identification code information transmitted by the RFID reader into two different identification code pools.

[0073] Module 302 is the identifier code query module. It first reads records from the library's catalogue to obtain book identifier codes and thickness information. Then, based on the thickness information, it checks the identifier code pool to see if the identifier code exists. If it exists, a record is made in the catalogue, and the corresponding identifier code is deleted from the identifier code pool; if it does not exist, the record in the catalogue is skipped, and the next record is processed directly. This process is repeated until all records in the catalogue have been processed.

[0074] It is worth noting that the results retrieved from the identifier pool may not be unique. If more than one result is found, the identifier that most closely matches the corresponding entry in the collection catalog will be deleted, based on the identifier's auxiliary information (such as bookshelf origin, book classification number, etc.).

[0075] Module 303 is the identifier relocation module, used to resolve issues where the query module fails to process data correctly. (If the collection...)

[0076] If there are unprocessed entries in the catalog, these entries are first compared with the remaining undeletable identifiers in the identifier pool. Next, the identifier and thickness information of the book associated with that entry are sent to the module that determines the thickness of books on the bookshelf and counts them individually. Using camera and RFID information, further targeted searches are performed.

[0077] The purpose of this invention is to provide a practical hybrid library book positioning system. Unlike existing systems, the library book positioning solution presented in this invention uses a hybrid strategy, utilizing both image barcode technology and RFID technology. Its core lies in classifying library collections into thick and thin books based on their thickness. Thick books have complete and clear barcodes affixed to their spines, which can be identified using a camera, while thin books are tagged with RFID tags. Note that this invention only places RFID tags on thin books. Since the number of thin books in a library is limited, and even more so on each bookshelf, the RFID collision problem can be effectively overcome. This invention also utilizes a dynamic frame ALOHA anti-collision strategy, adjusting the internal parameters of the RFID based on an estimated number of thin books on the shelf to improve system performance.

[0078] The present invention provides a hybrid library book location method, comprising: determining the number of books on a bookshelf.

[0079] The system includes a module for counting thick and thin books separately; an anti-collision module for reading RFID information from thin books; and a module for fusing book barcode information with RFID information and making a comprehensive judgment. It should be noted that the image tag reading module and RFID information acquisition module, which play important roles in the book positioning system described in this invention, are mature technologies and are not related to the innovation of this invention, so they will not be described in detail.

[0080] The module for determining and counting the thickness of books on a bookshelf uses a camera mounted on the bookshelf to photograph the books. The acquired images are then analyzed, and through a series of steps including stack location, book segmentation, spine extraction, thickness estimation, and book counting, the thick and thin books are classified and counted. The extracted spines of the thick books are then passed to an image tag recognition module to identify image tag information. The number of thin books is passed to an anti-collision module for dynamic time slot configuration.

[0081] The anti-collision module for reading RFID information for thin books uses the received number of thin books as a rough estimate of the number of tags on the bookshelf, and configures dynamic time slot frames accordingly. The frame length is reasonably adjusted based on the number of tags to be identified, thereby optimizing the execution efficiency of tag detection and maximizing the anti-collision performance of RFID.

[0082] The module for integrating book barcode information with RFID information and making comprehensive judgments and decisions obtains information on thick and thin books on each bookshelf through the network, and obtains the unique ID of each book. This enables the book positioning system to achieve all-round, no-dead-angle coverage of the library's collection, and makes the accuracy and efficiency of book positioning meet the requirements for practical application.

[0083] In summary, the above embodiments have provided detailed descriptions of different configurations of the book positioning method. Of course, this invention includes, but is not limited to, the configurations listed in the above embodiments. Any modifications made based on the configurations provided in the above embodiments are within the scope of protection of this invention. Those skilled in the art can apply the principles to other situations based on the content of the above embodiments.

[0084] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0085] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the present invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure shall fall within the protection scope of the claims.

Claims

1. A method for locating books, characterized in that, include: The book classification method is configured to divide books into two categories based on the thickness of the spine. If the thickness exceeds a first threshold, the book is classified as an image barcode book; otherwise, the book is classified as an RFID book. The logo generation method is configured to generate different logos for different types of books; Image barcode marks are formed on the spine of image barcode books, and each image barcode mark corresponds to a unique image identification code for image barcode books; RFID tags are placed in RFID books, and each RFID tag stores a unique RFID identification code for the RFID book. The book counting and barcode extraction module consists of three sub-modules: spine extraction, thickness estimation, and book counting. It is communicatively coupled to the first positioning module and the second positioning module. It performs thickness identification and classification counting of books on the bookshelf, outputs the image barcode mark on the spine of the image barcode books on the bookshelf to the first positioning module, and outputs the estimated value of the number of RFID books on the bookshelf to the second positioning module. The first positioning module, which is communicatively coupled to the book counting and barcode extraction module and the comprehensive decision module, is configured to identify the image barcode mark of the image barcode book received from the book counting and barcode extraction module, obtain the unique image identification code of the image barcode book, and send the image identification code to the comprehensive decision module. The second positioning module, which is communicatively coupled to the book counting and barcode extraction module and the comprehensive decision module, is configured to configure the parameters of the RFID reader based on the estimated number of RFID books received from the book counting and barcode extraction module, obtain the RFID identification code of the book by identifying the RFID tags on the RFID books on the bookshelf, and send the RFID identification code to the comprehensive decision module. The feature is that the book counting and barcode extraction module includes: The camera module is configured to take pictures of the books on the bookshelf using a camera mounted on the bookshelf; The analysis module is configured to analyze the images obtained by the imaging module, and use image processing algorithms to locate book stacks, segment books, extract book spines, estimate thickness, and count books, thereby completing the classification and statistics of image barcode books and RFID books. The analysis module is characterized in that it further includes: The image preprocessing module is used to perform noise reduction preprocessing on the images input by the imaging module, in preparation for image processing by the subsequent analysis module; The book stack localization module is used to divide the bookshelves in the image into layers through spatial multi-target detection and classification, and find the location of the books stacked on each layer. It uses deep network technology to realize the localization and range definition of the books stack on each layer of the bookshelf in the field of view. The book segmentation and transfer module is used to further process the book stack defined by the book stack positioning module through line detection and local correction, and to segment the vertically or horizontally arranged books in the book stack into independent objects, and to define each book with a standard geometric shape. The spine extraction module extracts rectangular images from the book segmentation results to form a spine image, which is then further standardized to facilitate thickness estimation. The thickness estimation module estimates the thickness of books using spine images and uses a statistical averaging method to reduce thickness errors; the book counting module counts books with image barcodes and RFID using spine images respectively.

2. The book positioning method as described in claim 1, characterized in that, Also includes: The integrated decision-making module, which is communicatively coupled to the first positioning module and the second positioning module, is configured to receive image identification codes of image barcode books from the first positioning module and RFID identification codes of RFID books from the second positioning module, and to make a comprehensive judgment on the location of the target book based on the image identification code and RFID identification code information. The integrated decision-making module obtains image identification code information or RFID identification code information of books on each bookshelf through the network, so that the book positioning method can form a comprehensive and seamless coverage of the library's collection, and make the accuracy and efficiency of book positioning meet the requirements for practical application.

3. The book positioning method as described in claim 1, characterized in that, The first positioning module includes an image label recognition module, wherein: The image label recognition module provides the extracted spine and / or image barcode mark and / or book barcode information of the image barcode-type books to the image label recognition module, so that the image label recognition module can identify the book corresponding to the book barcode information, or identify the book barcode information corresponding to the book.

4. The book positioning method as described in claim 1, characterized in that, The second positioning module includes an anti-collision module, wherein: The anti-collision module is configured as a sub-module of the second positioning module to execute the dynamic frame ALOHA anti-collision strategy and avoid collisions between RFID tags of multiple RFID books within the range of the second positioning module. The dynamic frame ALOHA anti-collision strategy includes: using the estimated number of received RFID books as a rough estimate of the number of tags on each bookshelf, configuring dynamic time slot frames accordingly, and adjusting the frame length reasonably based on the number of tags to be identified, thereby optimizing the execution efficiency of tag detection and maximizing the anti-collision performance of RFID.

5. The book location method as described in claim 1, characterized in that, The second positioning module includes an RFID reader, the RFID tag being the RFID marker, and also includes: The time slot dynamic allocation module is used to allocate time slot resources to RFID tags within the range of the RFID reader using a pseudo-randomization method; The time slot detection module is used to confirm the existence of RFID tags by broadcasting identification commands to the RFID tags and analyzing the ID information returned by the RFID tags. The confirmation strategy includes: detecting the number of successful time slots, the number of idle time slots, and the number of collision time slots in the ID information, repeating the process multiple times, and statistically analyzing the results. The tag identification module is used to analyze the number of various time slots to determine which RFID tags have been identified and which RFID tags have not yet been identified. The frame length dynamic adjustment module is used to reset a reasonable frame length based on the identification status of RFID tags. The initial value of the number of RFID tags within the range of the RFID reader is greater than the second threshold to ensure that no collisions occur. The frame length dynamic adjustment module makes adjustments based on the usage of time slots.

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