A control method and system of a multi-channel ultra-high frequency non-inductive borrowing channel

Abstract

The application relates to the technical field of book borrowing, and particularly discloses a control method and system of a multi-channel super-high-frequency non-inductive borrowing channel, which is applied to a multi-channel control box body comprising multiple channels, and comprises the following steps: acquiring a historical book borrowing table of a borrower in each channel; acquiring label information of all books in each channel, and acquiring label time slot return information according to the label information; acquiring time slot position information of each label time slot return information, and judging whether the time slot position information corresponding to each label time slot return information is at the same position; the application not only realizes efficient book management and borrowing verification, but also solves various problems existing in traditional methods, such as label conflict, incomplete detection and data management disorder and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of book borrowing, and in particular to a control method and system of a multi-channel super-high-frequency non-inductive borrowing channel. BACKGROUND

[0002] The non-inductive borrowing channel is not only suitable for large public libraries, but also suitable for various library scenes such as colleges and enterprises. Its efficient and convenient characteristics enable the library to better serve readers and improve overall operational efficiency.

[0003] In the actual application of the non-inductive borrowing channel, readers may stack multiple books together to pass through the detection channel, which may cause mutual interference between RFID tags, resulting in identification errors and conflicts. Specifically, some tags may not be correctly read or multiple tags may return information in the same time slot. In the existing process of identifying conflicting tags through a mask mechanism, the processing time may be prolonged and the system complexity may be increased during the conflict processing adjustment process, causing the system to be unable to accurately distinguish the borrowing or returning state of each book. SUMMARY

[0004] The present application aims to provide a control method and system of a multi-channel super-high-frequency non-inductive borrowing channel to solve the technical problems raised in the background.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0006] A control method of a multi-channel super-high-frequency non-inductive borrowing channel, comprising:

[0007] A multi-channel control box body comprising multiple channels, comprising:

[0008] Obtaining a history book borrowing table of a borrower in each channel;

[0009] Obtaining tag information of all books in each channel, and obtaining tag time slot return information according to the tag information;

[0010] Obtaining time slot position information of each tag time slot return information, and determining whether the time slot position information corresponding to each tag time slot return information is in the same position;

[0011] If it is in the same position, the tag information in the same position is taken as conflict tag information, and a time slot serial number is generated according to the time slot position information corresponding to the conflict tag information;

[0012] If it is not in the same position, the tag information not in the same position is taken as first non-conflict tag information, all first non-conflict tag information is integrated, and a first identification tag list is obtained;

[0013] Identify the conflict tag information based on the time sequence number to obtain second non-conflict tag information, integrate all the second non-conflict tag information to obtain a second identification tag list;

[0014] According to the first identification tag list, the second identification tag list and the historical book borrowing table, a completion check table is obtained, and a real-time confidence of the borrower is obtained according to the historical book borrowing table and the completion check table;

[0015] Determine whether the real-time confidence of the borrower is less than a preset value;

[0016] If it is less than, it is determined that the borrower has not completed the verification, and a swing gate closing signal corresponding to the channel is generated;

[0017] If it is not less than, it is determined that the borrower has completed the verification, and a swing gate opening signal corresponding to the channel is generated.

[0018] Preferably, the step of obtaining the historical book borrowing table of the borrower in each channel comprises:

[0019] Obtain the face image information of the borrower through a face recognition all-in-one machine;

[0020] Obtain the identity information of the borrower from the database according to the face image information;

[0021] Obtain the historical borrowing book information from the database according to the identity information;

[0022] Obtain the book name information, the borrowing date information, the return date information and the book borrowing status information according to the historical borrowing book information;

[0023] Establish the historical book borrowing table according to the book name information, the borrowing date information, the return date information and the book borrowing status information.

[0024] Preferably, the step of obtaining the tag time slot return information according to the tag information comprises:

[0025] Obtain a preset time slot detection time interval;

[0026] Obtain a preset detection period for each of the tag information;

[0027] Divide the preset detection period according to the preset time slot detection time interval to obtain a plurality of tag detection time slots;

[0028] Number and sort the plurality of tag detection time slots corresponding to each of the tag information according to the division order to obtain a time slot group;

[0029] Send time slot detection information for each tag detection time slot in the time slot group;

[0030] If the first tag detection time slot in the time slot group does not generate a signal response when receiving the time slot detection information, the tag detection time slot is taken as a non-trigger time slot, and the time slot detection information is sent to the next tag detection time slot;

[0031] Until the subsequent tag detection time slot generates a signal response when receiving the time slot detection information, the tag detection time slot is taken as a tag time slot and the information is returned.

[0032] Preferably, the step of identifying the conflict tag information based on the time slot sequence number to obtain the second non-conflict tag information comprises:

[0033] Obtaining the sequence number length of the time slot sequence number;

[0034] Obtaining the refined sequence number information of each conflict tag information based on the sequence number length;

[0035] Judging whether the refined sequence number information corresponding to each conflict tag information is the same;

[0036] If there are multiple same refined sequence number information, increasing the sequence number length for all the same refined sequence number information, and returning the refined sequence number information with the increased sequence number length to the step of judging whether the refined sequence number information corresponding to each conflict tag information is the same;

[0037] If there are other different refined sequence number information, and the conflict tag information corresponding to the refined sequence number information is taken as the second non-conflict tag information.

[0038] Preferably, the step of obtaining the completed check table according to the first identified tag list, the second identified tag list and the historical book borrowing table comprises:

[0039] Obtaining multiple book names in the channel from the database based on the first identified tag list and the second identified tag list;

[0040] Establishing a book temporary list according to the multiple book names, wherein the book temporary list comprises book names and book borrowing and returning state information;

[0041] Obtaining book borrowing and returning operation information through a touch display screen;

[0042] Performing check and modification according to the book borrowing and returning operation information and the book borrowing and returning state information to obtain book check information;

[0043] Obtaining the completed check table according to the book check information and the corresponding book name.

[0044] Preferably, the step of obtaining the borrower real-time confidence of the borrower according to the historical book borrowing table and the completed check table comprises:

[0045] According to the historical book borrowing table, the number of borrowed successful books and the number of borrowed failed books are obtained;

[0046] According to the number of borrowed successful books and the number of borrowed failed books, a historical book borrowing success rate is obtained;

[0047] A first weight coefficient of the historical borrowing success rate is obtained;

[0048] According to the historical book borrowing table, the number of abnormal book borrowing times is obtained;

[0049] According to the number of abnormal book borrowing times, a second weight coefficient is obtained;

[0050] According to the completion check table, a current operation accuracy value is obtained;

[0051] According to the current operation accuracy value, a third weight coefficient is obtained;

[0052] According to the historical book borrowing success rate, the first weight coefficient, the number of abnormal book borrowing times, the second weight coefficient, the current operation accuracy value and the third weight coefficient, a borrower real-time confidence is obtained.

[0053] The application also discloses a control system of a multi-channel super-high-frequency non-inductive borrowing channel, which is applied to a multi-channel control box body comprising multiple channels, and characterized by comprising:

[0054] A first acquisition module is used to acquire a historical book borrowing table of a borrower in each channel;

[0055] A second acquisition module is used to acquire label information of all books in each channel, and return information of a label time slot is acquired according to the label information;

[0056] A first judgment module is used to acquire time slot position information of each label time slot return information, and judge whether the time slot position information corresponding to each label time slot return information is in the same position;

[0057] If yes, the label information in the same position is taken as conflict label information, and a time slot serial number is generated according to the time slot position information corresponding to the conflict label information;

[0058] If no, the label information not in the same position is taken as first non-conflict label information, and all first non-conflict label information is integrated to obtain a first identification label list;

[0059] A third acquisition module is used to identify the conflict label information based on the time slot serial number to obtain second non-conflict label information, and all second non-conflict label information is integrated to obtain a second identification label list;

[0060] a fourth obtaining module, configured to obtain a completed check table according to the first identification tag list, the second identification tag list and the historical book borrowing table, and obtain a real-time confidence of the borrower according to the historical book borrowing table and the completed check table;

[0061] a second judging module, configured to judge whether the real-time confidence of the borrower is less than a preset value;

[0062] if the real-time confidence is less than the preset value, it is determined that the borrower has not completed the verification, and a swing gate closing signal corresponding to the channel is generated;

[0063] if the real-time confidence is not less than the preset value, it is determined that the borrower has completed the verification, and a swing gate opening signal corresponding to the channel is generated.

[0064] Preferably, the second obtaining module comprises:

[0065] a first obtaining unit, configured to obtain a preset time interval for detection;

[0066] a second obtaining unit, configured to obtain a preset detection period for each of the tag information;

[0067] a third obtaining unit, configured to divide the preset detection period according to the preset time interval for detection, to obtain a plurality of tag detection time intervals;

[0068] a fourth obtaining unit, configured to number and sort the plurality of tag detection time intervals corresponding to each of the tag information according to the division order, to obtain a time interval group;

[0069] a first detecting unit, configured to send time interval detection information for each of the tag detection time intervals in the time interval group;

[0070] if the first tag detection time interval in the time interval group does not generate a signal response when receiving the time interval detection information, the tag detection time interval is regarded as a non-triggered time interval, and the time interval detection information is sent to the next tag detection time interval;

[0071] until the subsequent tag detection time interval generates a response when receiving the time interval detection information, the tag detection time interval is regarded as a tag time interval and the information is returned.

[0072] Preferably, the third obtaining module comprises:

[0073] a fifth obtaining unit, configured to obtain a sequence number length of the time interval sequence number;

[0074] a sixth obtaining unit, configured to obtain refined sequence number information of each of the conflict tag information based on the sequence number length;

[0075] a seventh obtaining unit, configured to judge whether the refined sequence number information corresponding to each of the conflict tag information is the same;

[0076] If there are multiple same refinement sequence number information, increase the sequence number length for all same refinement sequence number information, and return the refinement sequence number information with increased sequence number length to the step of judging whether the refinement sequence number information corresponding to each of the conflict label information pair is the same.

[0077] If there are other different refinement sequence number information, and the conflict label information corresponding to the refinement sequence number information is taken as the second conflict-free label information.

[0078] Preferably, the fourth acquisition module comprises:

[0079] An eighth acquisition unit is configured to acquire multiple book names in the channel from a database based on the first identification label list and the second identification label list.

[0080] A ninth acquisition unit is configured to establish a book temporary list according to the multiple book names, wherein the book temporary list comprises book names and book lending and returning state information.

[0081] A tenth acquisition unit is configured to acquire book lending and returning operation information through a touch display screen.

[0082] An eleventh acquisition unit is configured to check and modify according to the book lending and returning operation information and the book lending and returning state information to obtain book checking information.

[0083] A twelfth acquisition unit is configured to acquire a checking table according to the book checking information and the corresponding book name.

[0084] The present application has the following beneficial effects: the present application not only realizes efficient book management and borrowing verification, but also solves various problems existing in the traditional method, such as label conflict, incomplete detection and data management disorder and the like. Each step is closely connected and interlocked, and collectively constitutes an efficient, reliable and transparent book management system, which significantly improves the service quality and operation efficiency of the library. Through reasonable data extraction, checking and management, it is ensured that the state of each book can be accurately recorded and managed, and the trust degree and use experience of the user are greatly improved. BRIEF DESCRIPTION OF DRAWINGS

[0085] Figure 1 The method flowchart of an embodiment of the present application.

[0086] Figure 2 The system structure schematic diagram of an embodiment of the present application.

[0087] Figure 3 The multi-channel control box structure schematic diagram of the system application of an embodiment of the present application.

[0088] The implementation, functional features and advantages of the present application will be further illustrated in conjunction with the embodiments with reference to the drawings. DETAILED DESCRIPTION

[0089] It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

[0090] As shown in Figure 1 and Figure 3 The present application provides a control method for a multi-channel ultra-high frequency non-inductive borrowing channel, which is applied to a multi-channel control box a, an ultra-high frequency antenna b is arranged in each channel, a rotatable entrance swing gate c and an exit swing gate d are arranged in each channel, a touch display screen e corresponding to the channel, a face recognition all-in-one machine f and a sensing assembly are arranged on the control box, wherein the sensing assembly includes four sensors g, which include:

[0091] S1, obtaining the historical book borrowing table of the borrower in each channel;

[0092] S2, obtaining the tag information of all books in each channel, and obtaining the tag time slot return information according to the tag information;

[0093] S3, obtaining the time slot position information of each tag time slot return information, and judging whether the time slot position information corresponding to each tag time slot return information is in the same position;

[0094] If it is, the tag information in the same position is taken as the conflict tag information, and the time slot serial number is generated according to the time slot position information corresponding to the conflict tag information;

[0095] If not, the tag information not in the same position is taken as the first non-conflict tag information, and all the first non-conflict tag information is integrated to obtain a first identification tag list;

[0096] S4, identifying the conflict tag information based on the time slot serial number to obtain the second non-conflict tag information, and integrating all the second non-conflict tag information to obtain a second identification tag list;

[0097] S5, obtaining the completion check table according to the first identification tag list, the second identification tag list and the historical book borrowing table, and obtaining the real-time confidence of the borrower according to the historical book borrowing table and the completion check table;

[0098] S6, judging whether the real-time confidence of the borrower is less than a preset value;

[0099] If it is less than, it is determined that the borrower has not completed the verification, and a swing gate closing signal of the corresponding channel is generated;

[0100] If not less than, determine that the borrower completes the verification, and generate the corresponding channel of the swing gate opening signal.

[0101] As described in the above steps S1-S6, the conventional non-inductive borrowing channel mainly relies on face recognition to verify the identity of the borrower. When the borrower passes through the channel, the RFID tags on each book may emit signals due to the books being stacked together. These signals may reach the ultra-high frequency antenna at the same time within a short period of time, which is prone to mutual interference. For example, assuming that the borrower carries five books, and the tag signals of several books are read at the same time, it may not be possible to accurately distinguish the identity of each tag, resulting in partial tags not being correctly identified or repeatedly identified.

[0102] The application confirms the identity of the borrower by comparing the face photo of the borrower taken by the face recognition all-in-one machine with the user face information stored in the database. Then, according to the identity information of the borrower, the historical borrowing records of the borrower are extracted from the database, including the name of each book, the borrowing date, the return date, and the state, etc. For example, it is found that the borrower has borrowed "Book One" (ISBN: 978-0132350884, borrowing date: 2024-10-01, return date: 2024-10-15, state: returned) and "Design Patterns" (ISBN: 978-0201633610, borrowing date: 2024-10-05, return date: 2024-10-20, state: returned) in the past. Finally, a historical book borrowing table containing all the borrowing records of the borrower is generated. This step solves the problem of information dispersion, centrally manages the borrowing information, and facilitates the administrator and the borrower to check and correct, enhancing the security and reliability. Then, the tag information of all the books in each channel is obtained, and the tag time slot return information is obtained according to the tag information. Assuming that the borrower carries five books through the non-inductive borrowing channel, each book has an RFID tag. Set 10 milliseconds as a time slot, and divide the entire detection period into 16 time slots. The ultra-high frequency antenna sends detection commands to each time slot in turn, and judges the position and signal strength of each tag according to the response information. For example, tag A returns information in the 7th time slot (60-70 milliseconds), tag B returns information in the 9th time slot (80-90 milliseconds), and tag C returns information in the 11th time slot (100-110 milliseconds). In this way, the tag information of different arrangement positions and signal strengths is preliminarily screened out, reducing the complexity of subsequent processing and ensuring the accuracy and efficiency of tag identification. Then, the time slot position information of each tag time slot return information is obtained, and it is judged whether they are in the same position. For example, tag A returns information in the 7th time slot, tag B returns information in the 9th time slot, and tag C returns information in the 11th time slot. Because they are not in the same position, they are marked as the first non-conflict tag information and integrated into the first identified tag list. If multiple tags return information in the same time slot, they are marked as conflict tag information. For example, tag D and tag E both return information in the 5th time slot (40-50 milliseconds), which are marked as conflict tag information. This step separates the tags with normal return information from the tags with conflict, simplifies the subsequent processing process, and improves the reliability and accuracy; then, the conflict tag information is identified based on the time slot sequence number to obtain the second non-conflict tag information. For conflict tag information (such as tag D and tag E), the conflict time slot number is directly mapped to the initial detection sequence number (for example, the 5th time slot → initial detection sequence number = 1).The detection command with the initial detection sequence number 1 is sent to the fifth time slot, and it is found that there are still multiple tags returning information. At this time, the initial detection sequence number is increased to 2, and the detection command is sent again. Assuming that this time the detection successfully distinguishes two tags (tag D and tag E). Continue to refine the search range until all the conflict tags are uniquely confirmed and integrated into the second identification tag list. This step effectively solves the conflict problem caused by multiple tags responding at the same time, ensures that each tag can be uniquely confirmed and recorded, greatly improves the accuracy of tag identification and the ability to handle conflicts, and then obtains the completion check table according to the first identification tag list, the second identification tag list, and the historical book borrowing table, and obtains the real-time confidence of the borrower, merges the first identification tag list (tag A, tag B, tag C) and the second identification tag list (tag D, tag E) to form a book to be determined list, and compares it with the borrower's historical book borrowing table to generate a book temporary list. Then, the book information in the book temporary list is compared with the borrower's historical borrowing record one by one to generate a completion check table. For example, it is confirmed that the borrower returns “Book One” and borrows “Book Two”, and these information is updated to the completion check table. Finally, the real-time confidence of the borrower is calculated by comprehensively evaluating the borrower's historical borrowing behavior, current operation accuracy and other factors. Assuming that the borrower's historical borrowing success rate is high (94%), and the current operation accuracy value is 100%, the real-time confidence is set to 0.966. This step ensures that the status of all books is correctly recorded and checked, avoids errors or abnormal situations, and improves safety and reliability. Finally, it is judged whether the real-time confidence of the borrower is less than the preset value (for example, 0.9). Assuming that the real-time confidence of the borrower is 0.966, which is greater than the preset value, it is determined that the borrower has completed the verification, and an opening signal of the swing gate of the corresponding channel is generated to allow him to pass through the channel smoothly. On the contrary, if the real-time confidence is less than the preset value, it is determined that the borrower has not completed the verification, and a closing signal of the swing gate of the corresponding channel is generated to prompt reoperation or contact the administrator. This step timely discovers and handles abnormal behavior, ensures safety and reliability, prevents unauthorized personnel from entering or leaving the library, and improves user trust and use experience.

[0103] In one embodiment, the step of obtaining the historical book borrowing table of the borrower in each channel comprises:

[0104] S101, obtaining the face image information of the borrower through the face recognition all-in-one machine;

[0105] S102, obtaining the identity information of the borrower from the database according to the face image information;

[0106] S103, obtaining the historical borrowing book information from the database according to the identity information;

[0107] S104, obtaining book name information, borrowing date information, returning date information and book borrowing state information according to the historical borrowing book information;

[0108] S105, establishing a historical book borrowing table according to the book name information, the borrowing date information, the returning date information and the book borrowing state information.

[0109] As described in steps S101-S105, the present application quickly captures the borrower's facial photo through the facial recognition machine and compares it with the user's facial information stored in the database. For example, the borrower's facial photo is compared within a few seconds, confirming that he is a legal user. This process ensures that only authorized personnel can use the non-sensing borrowing channel, solving the security risks and efficiency problems that may arise from relying on cards or passwords in traditional methods. Facial recognition technology not only improves the accuracy and speed of borrower identity confirmation, but also reduces the inconvenience caused by lost cards or forgotten passwords, enhancing security and user trust. In this way, high precision and fast response characteristics are ensured, laying a solid foundation for subsequent operations and improving user experience. Then, the borrower's facial photo is matched with the records in the database, and his name, ID number, and other key data are quickly extracted. For example, after confirming the borrower's identity, his name "Zhang San" and ID number "123456789012345678" are immediately extracted. This process ensures the uniqueness and accuracy of the borrower's identity and provides necessary data support for subsequent operations. By matching the facial image information with the records in the database, the borrower's identity information is quickly extracted, solving the problem of scattered information that is difficult to manage and query. Then, according to the borrower's identity information, the historical borrowing book information is obtained from the database. The historical borrowing book information is obtained by querying the borrowing records in the database, and the specific information of all books is extracted from the database. These information is scattered in various fields in the database, and the historical book borrowing table is a structured table or report that integrates all the above information. For example, it is found that the borrower has borrowed "Book One" (ISBN: 978-0132350884) and "Design Patterns" (ISBN: 978-0201633610) in the past, including the ISBN number, book name, borrowing date, return date, and other detailed information of each book. This process provides detailed data support for subsequent book checking and status updating, ensuring that the status of each book can be accurately recorded and managed. By querying the borrower's historical borrowing records, the borrower's borrowing history can be fully understood, providing detailed data support for subsequent operations, ensuring that the status of each book can be accurately recorded and managed, avoiding omissions or repetitions, and ensuring the efficient operation of the non-sensing borrowing channel. Further refining data extraction, obtaining specific book name, borrowing date, return date, and book borrowing status information. For example, "Book One" is recorded as borrowed on October 1, 2024, returned on October 15, 2024, and the status is "returned". This process ensures that the status of each book can be accurately recorded and managed, and abnormal situations such as repeated borrowing or failure to return on time can be discovered and handled in a timely manner, improving the refinement and accuracy of book management.By further refining data extraction, the status of each book can be accurately recorded and managed, and abnormal situations such as repeated borrowing or overdue can be discovered and handled in a timely manner, improving the precision and accuracy of book management. This ensures that the status of all books is correctly recorded, avoiding omissions or repetitions. By integrating all extracted information, a complete historical book borrowing table is established. For example, a table containing all borrowing records of a borrower is generated, which intuitively displays the specific information of each book he borrows, such as "Book One" (ISBN: 978-0132350884, borrowing date: 2024-10-01, return date: 2024-10-15, status: returned) and "Design Patterns" (ISBN: 978-0201633610, borrowing date: 2024-10-05, return date: 2024-10-20, status: returned). This process centralizes the management of borrowing information, making it easy for administrators and borrowers to check and verify, solving the problem of scattered information, difficult management and query, and providing important basis for subsequent real-time confidence assessment, enhancing security and reliability. By integrating all extracted information, a historical book borrowing table is generated, which centralizes the management of borrowing information, making it easy for administrators and borrowers to check and verify, solving the problem of scattered information, difficult management and query, and providing important basis for subsequent real-time confidence assessment, enhancing security and reliability.

[0110] In one embodiment, the step of obtaining tag slot return information according to the tag information comprises:

[0111] S201, obtaining a preset time slot detection time interval;

[0112] S202, obtaining a preset detection period for each of the tag information;

[0113] S203, dividing the preset detection period according to the preset time slot detection time interval to obtain a plurality of tag detection time slots;

[0114] S204, numbering and sorting the plurality of tag detection time slots corresponding to each of the tag information according to the division order to obtain a time slot group;

[0115] S205, sending time slot detection information for each tag detection time slot in the time slot group;

[0116] If the first tag detection time slot in the time slot group does not produce a signal response when receiving the time slot detection information, the tag detection time slot is regarded as a non-triggered time slot, and the time slot detection information is sent to the next tag detection time slot;

[0117] S206, until the time slot detection information is received at the subsequent tag detection time slot, a response information is generated, and the tag detection time slot is returned as tag time slot return information.

[0118] As described in steps S201-S206 above, the present application sets a fixed time slot detection interval, for example 10 milliseconds. This time interval is determined in advance according to the characteristics of the ultra-high frequency RFID technology and the needs of the actual application scenario. For example, in the library non-inductive borrowing channel, in order to ensure that the tag information can be accurately read without conflict, 10 milliseconds is set as a time slot detection interval. In this way, multiple tags can be quickly detected in a short time, reducing the mutual interference of signals between tags, improving the overall response speed and accuracy. This process solves the conflict problem that may occur in a high-density tag environment, reduces the complexity caused by processing a large number of tags at the same time, and improves the reliability and stability. By setting the preset time slot detection interval, not only the response speed is improved, but also the conflict is reduced, ensuring that each tag has enough time window to return information, laying a solid foundation for subsequent operations, and then setting a preset detection period for each tag, that is, the time range that the tag needs to cover in the entire detection process. For example, assuming that the total detection period is 160 milliseconds, the entire period is divided into multiple time slots (such as 16 time slots, each time slot is 10 milliseconds), to ensure that each tag has enough time window to return information. This process solves the conflict problem that different tags may return information at the same time, ensuring that each tag can be identified individually. By reasonably dividing the detection period, it is ensured that each tag has enough time window to return information, avoiding omission and reducing the conflict caused by tags returning information at the same time. This step not only ensures comprehensive coverage, but also improves efficiency, providing protection for subsequent operations. By setting a reasonable preset detection period, multiple tags can be efficiently processed, improving overall efficiency and reliability, and then dividing the preset detection period (such as 160 milliseconds) according to the preset time slot detection interval (such as 10 milliseconds) to obtain multiple tag detection time slots. For example, the 160-millisecond detection period is divided into 16 time slots, each time slot is 10 milliseconds. Each time slot corresponds to a specific time window for receiving information from tags. This process solves the conflict problem that different tags may return information at the same time, ensuring that each tag can be identified individually. By dividing multiple time slots, the conflict caused by tags returning information at the same time is reduced, ensuring that each tag has an independent time window to return information, improving reliability and accuracy. The multiple tag detection time slots corresponding to the information of each tag are numbered and sorted in order to form an ordered time slot group. For example, the time slot corresponding to tag A may be the 7th time slot (60-70 milliseconds), and the time slot corresponding to tag B may be the 9th time slot (80-90 milliseconds). These time slots are numbered and sorted in order to form an ordered time slot group. This setting ensures the orderliness and controllability of the tag detection process, reduces the possibility of repeated detection or omission, simplifies the subsequent processing logic, and enhances the reliability and stability.By numbering and sorting the multiple tag detection time slots corresponding to each tag information, the orderliness and controllability of the tag detection process are ensured, the possibility of repeated detection or omission is reduced, the subsequent processing logic is simplified, the reliability and stability are enhanced, and the subsequent operation is guaranteed. The time slot detection information is sent to each time slot in turn, and a response is waited for. For example, the detection command is sent to the first time slot first. If the time slot does not produce a response, it is marked as an untriggered time slot, and the detection command is sent to the next time slot. Assuming that the first time slot does not produce a response, the detection command will be sent to the second time slot, and so on, until all time slots are detected. By detecting each time slot one by one, it is ensured that all tags can be correctly identified, the possibility of omission is reduced, and the accuracy and reliability of identification are improved. A reasonable detection order simplifies the subsequent processing logic, improves the reliability and stability, and provides a guarantee for the subsequent operation. The detection command is continuously sent to each time slot until a time slot receives the time slot detection information and produces an information response. For example, after sending the detection command to the seventh time slot, the response information of tag A is received, and the seventh time slot is returned as the tag time slot information at this time. This process ensures that all tags can be uniquely confirmed, reduces the possibility of omission, and improves the accuracy and reliability of identification. In this way, all tags can be efficiently processed to ensure that each tag is uniquely identified, improving the integrity and accuracy of tag detection, and enhancing flexibility and adaptability.

[0119] In one embodiment, the step of identifying the conflict tag information based on the time slot sequence number to obtain the second non-conflict tag information comprises:

[0120] S401, obtaining the sequence number length of the time slot sequence number;

[0121] S402, obtaining the refined sequence number information of each conflict tag information based on the sequence number length;

[0122] S403, judging whether the refined sequence number information corresponding to each conflict tag information is the same;

[0123] If there are multiple same refined sequence number information, the sequence number length of all same refined sequence number information is increased, and the refined sequence number information with increased sequence number length is returned to the step of judging whether the refined sequence number information corresponding to each conflict tag information is the same;

[0124] If there are other different refined sequence number information, the conflict tag information corresponding to the refined sequence number information is taken as the second non-conflict tag information.

[0125] As described in steps S401-S403, the application acquires the sequence number length of each conflict tag information corresponding time slot sequence number, to set the preliminary mask value. For example, in the initial detection, it is found that multiple tags return information in the 5th time slot (40-50 milliseconds), resulting in conflict. Record the conflict time slot number, and directly map the time slot number to the initial detection sequence number, set the initial detection sequence number to 3 bits. This process ensures that the conflict time slot can be assigned a preliminary mask value, so that the mask length is gradually increased to distinguish the tags more carefully. In this way, the tags can be distinguished more carefully in the process of gradually increasing the mask length, reducing the possibility of repeated conflict, simplifying the processing logic, and enhancing the reliability. For example, assuming that 5 conflict tag information (A, B, C, D and E) returns information in the 5th time slot, it is mapped to the initial detection sequence number (such as A: 000, B: 000, etc.), and then according to the set sequence number length, generate refined sequence number information for each conflict tag information. For example, the initial detection sequence number is 3 bits, and the refined sequence number information for each conflict tag information is generated, such as A: 000, B: 000, C: 000, D: 000 and E: 000. Then, send the detection command with the initial detection sequence number to the 5th time slot. The initial detection finds that multiple tags return information, indicating that the conflict still exists. At this time, return to the mapping step, increase the value of the initial detection sequence number (from 3 to 4), such as A: 0000, B: 0000, C: 0000, D: 0000 and E: 0000, and send the detection command again. By gradually increasing the initial detection sequence number, the search range can be gradually refined, and each tag can be successfully distinguished. For example, after the first refinement, A: 00010, B: 00001, C: 00000, D: 00000 and E: 00000, tag A and tag B are successfully identified; continue to increase the sequence number, C: 0000010, D: 0000001 and E: 0000000, tag C and tag D are also distinguished; finally, tag E is also successfully identified. Finally, it is judged whether the refined sequence number information corresponding to each conflict tag information is the same. If there are multiple same refined sequence number information, return to the mapping step, increase the value of the initial detection sequence number, and detect again; if there are refined sequence number information different from others, take these refined sequence number information corresponding conflict tag information as the second non-conflict tag information. For example, after the first refinement, A: 00010, B: 00001, C: 00000, D: 00000 and E: 00000, tag A and tag B are successfully identified; continue to increase the sequence number, C: 0000010, D: 0000001 and E: 0000000, tag C and tag D are also distinguished; finally, tag E is also successfully identified. This process ensures that all conflict tag information can be uniquely confirmed, solving the conflict problem caused by multiple tags returning information in the same time slot.By dynamically adjusting the mask length, the search range can be gradually refined, and the unique tag identity can be finally found, greatly improving the accuracy and reliability of tag identification.

[0126] In one embodiment, the step of obtaining a check table according to the first identification tag list, the second identification tag list, and the historical book borrowing table comprises:

[0127] S501, obtaining a plurality of book names in the channel from a database based on a first identification tag list and a second identification tag list;

[0128] S502, establishing a book temporary list according to a plurality of book names, wherein the book temporary list comprises book names and book borrowing status information;

[0129] S503, obtaining book borrowing operation information through a touch display screen;

[0130] S504, checking and modifying according to the book borrowing operation information and the book borrowing status information to obtain book checking information;

[0131] S505, obtaining a check table according to the book checking information and the corresponding book name.

[0132] As described in steps S501-S505 above, the present application integrates the first identification tag list (non-conflicting tags) and the second identification tag list (non-conflicting tags after refinement), and then obtains the names of multiple books in the channel from the database according to these tag information. For example, assuming that tags A, B, C are detected by the ultra-high frequency antenna, and tags D and E are successfully distinguished, the book names corresponding to these five tags are extracted from the database, such as "Book One", "Book Two", "Book Three", "Book Four", and "Book Five". This process solves the problem of scattered information, centrally manages the information of all books, provides necessary basic data support for subsequent operations, ensures that all book information can be accurately recorded and managed, avoids omission or repetition, and guarantees the efficient operation of the non-sensing borrowing channel. Then, according to the book names obtained from the database, a book temporary list is established, which not only contains the book names but also includes the borrowing and returning state information of the books. For example, in the book temporary list, the state of "Book One" is "borrowed out", the state of "Book Two" is "not borrowed", the state of "Book Three" is "returned", the state of "Book Four" is "borrowed out", and the state of "Book Five" is "not borrowed". This process solves the problem of scattered information, centrally manages the state information of all books, facilitates subsequent checking and state updating, ensures that the state of each book can be accurately recorded and managed, avoids omission or repetition, and then obtains the book borrowing and returning operation information of the borrower through the touch display screen. For example, when the borrower passes through the non-sensing borrowing channel, the touch display screen displays his current book list and allows him to select the books he needs to return or borrow. Assuming that the borrower chooses to return "Book One" and borrow "Book Two". This process solves the problem of inconvenient operation, provides an intuitive user interface, improves user experience and operation accuracy, and reduces the possibility of manual input errors. According to the book borrowing and returning operation information of the borrower and the borrowing and returning state information in the book temporary list, the checking and modification are carried out. For example, it is confirmed that the borrower chooses to return "Book One", and the state of the book is changed from "borrowed out" to "returned", and a successful mark is made in the checking table; at the same time, it is confirmed that he borrowed "Book Two", and the state of the book is changed from "not borrowed" to "borrowed out". This process solves the problem of inconsistent state caused by operation errors or abnormal situations, ensures the accuracy of book management, and timely discovers and handles abnormal situations. Finally, according to the book checking information and the corresponding book names, a completed checking table is generated. For example, a table containing all the borrowing and returning operation results of the borrower is generated, as follows: "Book One" (ISBN: 978-0132350884, original state: borrowed out, new state: returned, checking result: success); "Book Two" (ISBN: 978-0131103627, original state: not borrowed, new state: borrowed, checking result: success).This process solves the problem of information dispersion, difficulty in management and query, and can more efficiently carry out book checking and status updating through centralized data management, and facilitate administrators and readers to check and handle abnormal situations, thereby improving efficiency and transparency.

[0133] In one embodiment, the step of obtaining the real-time confidence of the borrower according to the historical book borrowing table and the completed checking table comprises:

[0134] S601, obtaining the number of borrowed successful books and the number of borrowed failed books according to the historical book borrowing table;

[0135] S602, obtaining the historical book borrowing success rate according to the number of borrowed successful books and the number of borrowed failed books;

[0136] S603, obtaining a first weight coefficient of the historical book borrowing success rate;

[0137] S604, obtaining the number of abnormal book borrowings according to the historical book borrowing table;

[0138] S605, obtaining a second weight coefficient according to the number of abnormal book borrowings;

[0139] S606, obtaining a current operation accuracy value according to the completed checking table;

[0140] S606, obtaining a third weight coefficient according to the current operation accuracy value;

[0141] S608, obtaining the real-time confidence of the borrower according to the historical book borrowing success rate, the first weight coefficient, the number of abnormal book borrowings, the second weight coefficient, the current operation accuracy value and the third weight coefficient.

[0142] As described in the above steps S601-S608, the present application obtains the number of successful and failed book borrowing from the historical book borrowing table (step S601). For example, assume that the borrower has successfully borrowed 50 books in the past year, but has failed to borrow 3 times. This step helps to comprehensively understand the borrowing behavior pattern of the borrower and identify whether there is a frequent borrowing failure situation. By quantifying the number of successful and failed times, the behavior stability of the borrower can be preliminarily evaluated. Next, based on the number of successful and failed borrowing, the historical book borrowing success rate is calculated (step S602). For example, according to the data of the borrower successfully borrowing 50 books and failing 3 times, the borrowing success rate is calculated to be 94%. This step not only quantifies the overall borrowing performance of the borrower, but also provides an important basis for the subsequent weight coefficient setting. By calculating the borrowing success rate, the historical behavior of the borrower can be more intuitively evaluated, potential risks or abnormal situations can be found, and the evaluation accuracy and reliability are improved. Then, the first weight coefficient is set for the historical borrowing success rate (step S603). For example, the weight coefficient of the historical borrowing success rate is set to 0.4, which means that this indicator has a greater impact on the final confidence. This step solves the problem of unreasonable weight distribution of different evaluation factors, ensuring the scientificity and rationality of the evaluation result. By reasonably setting the weight coefficient, multiple factors can be considered comprehensively, avoiding the dominance of a single indicator in the evaluation result, and improving the comprehensiveness and accuracy of the evaluation. The setting of the weight coefficient also makes the evaluation process more transparent and traceable, enhancing the trust of users. Further, the number of book abnormal borrowing is counted from the historical book borrowing table (step S604), such as repeated borrowing, not returning on time, etc. For example, it is found that the borrower has not returned the books on time for 2 times in the past year. This step helps to identify the abnormal behavior pattern of the borrower and timely find potential risks. By quantifying the number of abnormal borrowing, the credit status of the borrower can be more accurately evaluated, and the security and reliability of the system are improved. The number of abnormal borrowing as an important indicator helps to identify high-risk users and take corresponding preventive measures to ensure the safe operation of the no-touch borrowing channel. Next, the second weight coefficient is set for the number of book abnormal borrowing (step S605). For example, the weight coefficient of the number of book abnormal borrowing is set to 0.3, reflecting the importance of this indicator. This step solves the problem of unreasonable weight distribution of different evaluation factors, ensuring the scientificity and rationality of the evaluation result. By reasonably setting the weight coefficient, multiple factors can be considered comprehensively, avoiding the dominance of a single indicator in the evaluation result, and improving the comprehensiveness and accuracy of the evaluation. The setting of the weight coefficient also makes the evaluation process more transparent and traceable, enhancing the trust of users. Through the completion of the check table, the accurate value of the current operation is obtained (step S606). For example, according to all the book information of the borrower this time, it is confirmed that all the operations are accurate and correct, and the current operation accuracy value is 100%.This step ensures the authenticity and accuracy of each operation, solving the problem of evaluation deviation caused by operation errors or abnormalities. By quantifying the accuracy of the current operation, abnormal situations can be discovered and handled in a timely manner. The current operation accuracy value serves as an important indicator for real-time evaluation, ensuring that each borrowing and returning operation is accurately recorded and managed. Finally, a third weight coefficient is set for the current operation accuracy value (step S606). For example, the weight coefficient of the current operation accuracy value is set to 0.3, reflecting the importance of this indicator. This step addresses the problem of unreasonable weight distribution of different evaluation factors, ensuring the scientificity and rationality of the evaluation results. By reasonably setting the weight coefficient, multiple factors can be considered, avoiding the dominance of a single indicator in the evaluation results, and improving the comprehensiveness and accuracy of the evaluation. The setting of the weight coefficient also makes the evaluation process more transparent and traceable, enhancing the trust of users. Finally, the real-time confidence of the borrower is calculated by integrating the above indicators and their weight coefficients (step S608). For example, according to the borrower's historical borrowing success rate (94%, weight 0.4), the number of abnormal book borrowing (2 times, weight 0.3), and the current operation accuracy value (100%, weight 0.3), the calculation formula is. ; wherein, represents the real-time confidence, represents the first weight coefficient, represents the historical book borrowing success rate, represents the second weight coefficient, represents the number of abnormal book borrowing, represents the third weight coefficient, represents the current operation accuracy value, and the real-time confidence is calculated to be 0.966. The closer the real-time confidence is to 1, the better the borrower's credibility. This step solves the problem that a single indicator cannot fully reflect the borrower's behavior, and through multi-dimensional evaluation, it ensures the comprehensiveness and accuracy of the evaluation results. Real-time confidence not only improves the security and reliability of the system, but also enables timely detection and handling of abnormal behavior, ensuring the safe operation of the non-inductive borrowing channel. In addition, real-time confidence evaluation provides an important basis for administrators to make decisions. If the confidence exceeds the preset threshold, he can smoothly pass through the borrowing channel; otherwise, he is prompted to re-operate or contact the administrator.

[0143] As shown in Figure 2 , the present application also provides a control system for a multi-channel ultra-high frequency non-inductive borrowing channel, comprising:

[0144] A first acquisition module 1 is used to acquire the historical book borrowing table of the borrower in each channel;

[0145] A second acquisition module 2 is used to acquire the tag information of all books in each channel, and to acquire the tag time slot return information according to the tag information;

[0146] The first judging module 3 is configured to acquire time slot position information of each label time slot return information, and judge whether the time slot position information corresponding to each label time slot return information is at the same position;

[0147] If yes, the label information at the same position is taken as conflict label information, and a time slot serial number is generated according to the time slot position information corresponding to the conflict label information;

[0148] If no, the label information not at the same position is taken as first non-conflict label information, and all the first non-conflict label information is integrated to obtain a first identified label list;

[0149] The third acquiring module 4 is configured to identify the conflict label information based on the time slot serial number to obtain second non-conflict label information, and integrate all the second non-conflict label information to obtain a second identified label list;

[0150] The fourth acquiring module 5 is configured to acquire a completed check table according to the first identified label list, the second identified label list and a historical book borrowing table, and acquire a real-time confidence degree of a borrower according to the historical book borrowing table and the completed check table;

[0151] The second judging module 6 is configured to judge whether the real-time confidence degree of the borrower is less than a preset value;

[0152] If yes, it is determined that the borrower has not completed verification, and a swing gate closing signal corresponding to a channel is generated;

[0153] If no, it is determined that the borrower has completed verification, and a swing gate opening signal corresponding to the channel is generated.

[0154] In one embodiment, the second acquiring module 2 comprises:

[0155] The first acquiring unit is configured to acquire a preset time slot detection time interval;

[0156] The second acquiring unit is configured to acquire a preset detection period of each label information;

[0157] The third acquiring unit is configured to divide the preset detection period according to the preset time slot detection time interval to obtain a plurality of label detection time slots;

[0158] The fourth acquiring unit is configured to number and sort the plurality of label detection time slots corresponding to each label information according to the division order to obtain a time slot group;

[0159] The first detection unit is configured to send time slot detection information to each label detection time slot in the time slot group;

[0160] If the first tag detection time slot in the time slot group does not generate a signal response when the time slot detection information is received, the tag detection time slot is taken as a non-trigger time slot, and the time slot detection information is sent to the next tag detection time slot;

[0161] Until the subsequent tag detection time slot generates a signal response when the time slot detection information is received, the tag detection time slot is taken as a tag time slot and the information is returned.

[0162] In one embodiment, the third acquisition module 3 comprises:

[0163] The fifth acquisition unit is configured to acquire a sequence number length of the time slot sequence number;

[0164] The sixth acquisition unit is configured to acquire refined sequence number information of each conflict tag information based on the sequence number length;

[0165] The seventh acquisition unit is configured to determine whether the refined sequence number information corresponding to each of the conflict tag information is the same;

[0166] If there are multiple same refined sequence number information, the sequence number length of all the same refined sequence number information is increased, and the refined sequence number information with the increased sequence number length is returned to the step of determining whether the refined sequence number information corresponding to each of the conflict tag information is the same;

[0167] If there are other different refined sequence number information, the conflict tag information corresponding to the refined sequence number information is taken as the second non-conflict tag information.

[0168] In one embodiment, the fourth acquisition module 4 comprises:

[0169] The eighth acquisition unit is configured to acquire a plurality of book names in the channel from a database based on the first identified tag list and the second identified tag list;

[0170] The ninth acquisition unit is configured to establish a book temporary list according to the plurality of book names, wherein the book temporary list comprises book names and book borrowing and returning state information;

[0171] The tenth acquisition unit is configured to acquire book borrowing and returning operation information through a touch display screen;

[0172] The eleventh acquisition unit is configured to check and modify the book borrowing and returning operation information and the book borrowing and returning state information to obtain book checking information;

[0173] The twelfth acquisition unit is configured to acquire a completed checking table according to the book checking information and the corresponding book name.

[0174] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, storage, value library or other medium provided by the present application and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0175] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover a non-exclusive inclusion, so that a process, device, article or method that includes a list of elements not only includes those elements, but also includes other elements not expressly listed or inherent to such process, device, article or method. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, device, article or method that includes the element.

[0176] The above only describes the preferred embodiments of the present application, and does not limit the patent scope of the present application. Any equivalent result or equivalent process transformation obtained by using the content of the present application specification and drawings, or directly or indirectly applied to other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A control method for a multi-channel ultra-high frequency contactless borrowing channel, applied to a multi-channel control box including multiple channels, characterized in that, include: Obtain the historical book borrowing records of borrowers in each channel; Obtain the tag information of all books in each channel, and obtain the tag time slot return information based on the tag information; Obtain the time slot location information of each tag time slot return information, and determine whether the time slot location information corresponding to each tag time slot return information is in the same position; If they are in the same position, the tag information in the same position will be used as conflicting tag information, and a time slot sequence number will be generated based on the time slot position information corresponding to the conflicting tag information. If not, the label information that is not in the same position is taken as the first conflict-free label information. All the first conflict-free label information is integrated to obtain the first identification label list. Obtain the sequence number length of the time slot sequence number; Based on the serial number length, obtain the refined serial number information for each conflicting tag; Determine whether the refined sequence number information corresponding to each of the conflicting label information is the same; If multiple identical refined sequence number information exist, increase the sequence number length for all identical refined sequence number information, and return the refined sequence number information with the increased sequence number length to the step of determining whether the refined sequence number information corresponding to each conflicting label information is the same; If there is refined sequence information that is different from others, the conflicting label information corresponding to the refined sequence information is taken as the second conflict-free label information. All the second conflict-free label information is integrated to obtain the second identification label list. The completion verification table is obtained based on the first identification tag list, the second identification tag list, and the historical book borrowing table, and the real-time confidence level of the borrower is obtained based on the historical book borrowing table and the completion verification table. Determine whether the borrower's real-time confidence level is less than a preset value; If the value is less than the threshold, it is determined that the borrower has not completed the verification process, and a swing gate closing signal is generated for the corresponding channel. If the value is not less than the specified value, the borrower is deemed to have completed the verification process, and a swing gate opening signal for the corresponding channel is generated.

2. The control method for a multi-channel ultra-high frequency contactless borrowing channel according to claim 1, characterized in that, The step of obtaining the borrower's historical book borrowing list for each channel includes: The facial recognition system obtains the borrower's facial image information. The borrower's identity information is obtained from the database based on the facial image information; Based on the identity information, retrieve historical book borrowing information from the database; Based on the historical borrowing information, obtain the book name, borrowing date, return date, and borrowing / returning status information; A historical book borrowing table is created based on the book title information, borrowing date information, return date information, and book borrowing / returning status information.

3. The control method for a multi-channel ultra-high frequency contactless borrowing channel according to claim 1, characterized in that, The step of obtaining tag time slot return information based on the tag information includes: Obtain the preset time slot detection time interval; A preset detection period is used to obtain information about each of the aforementioned tags; The preset detection period is divided according to the preset time slot detection time interval to obtain multiple tag detection time slots; The multiple tag detection time slots corresponding to each tag information are numbered and sorted according to the division order to obtain a time slot group; For each tag detection time slot in the time slot group, time slot detection information is sent; If the first tag detection time slot in the time slot group does not generate a signal response when it receives the time slot detection information, then the tag detection time slot is regarded as a non-triggered time slot, and the time slot detection information is sent to the next tag detection time slot; The information response is generated when the subsequent tag detection time slot receives the time slot detection information, and the tag detection time slot is returned as the tag time slot information.

4. The control method for a multi-channel ultra-high frequency contactless borrowing channel according to claim 1, characterized in that, The step of obtaining the verification table based on the first identification tag list, the second identification tag list, and the historical book borrowing list includes: Multiple book names within the channel are retrieved from the database based on the first identification tag list and the second identification tag list; A temporary book list is created based on multiple book titles, wherein the temporary book list includes book titles and book borrowing / returning status information; Access book borrowing and returning information via the touchscreen display; The book borrowing and returning operation information and book borrowing and returning status information are checked and modified to obtain the book verification information; The verification table is obtained based on the book verification information and the corresponding book name.

5. The control method for a multi-channel ultra-high frequency contactless borrowing channel according to claim 1, characterized in that, The step of obtaining the borrower's real-time confidence level based on the historical book borrowing list and the completion verification list includes: The number of successfully borrowed books and the number of unborrowed books can be obtained from the historical book borrowing list. The historical book borrowing success rate is obtained based on the number of successfully borrowed books and the number of unsuccessfully borrowed books. The first weighting coefficient for obtaining historical borrowing success rates; The number of abnormal book borrowings is obtained from the historical book borrowing record. The second weighting coefficient is obtained based on the number of abnormal book borrowings. Obtain the accurate value of the current operation based on the completed checklist; The third weighting coefficient is obtained based on the current operation accuracy value; The borrower's real-time confidence level is obtained based on the historical book borrowing success rate, the first weight coefficient, the number of abnormal book borrowings, the second weight coefficient, the current operation accuracy value, and the third weight coefficient.

6. A control system for a multi-channel ultra-high frequency contactless borrowing channel, applied to a multi-channel control box including multiple channels, characterized in that, include: The first acquisition module is used to acquire the historical book borrowing records of borrowers in each channel; The second acquisition module is used to acquire the tag information of all books in each channel, and to acquire tag time slot return information based on the tag information; The first judgment module is used to obtain the time slot position information of each tag time slot return information and to determine whether the time slot position information corresponding to each tag time slot return information is in the same position. If they are in the same position, the tag information in the same position will be used as conflicting tag information, and a time slot sequence number will be generated based on the time slot position information corresponding to the conflicting tag information. If not, the label information that is not in the same position is taken as the first conflict-free label information. All the first conflict-free label information is integrated to obtain the first identification label list. The third acquisition module is used to identify the second conflict-free tag information based on the time slot sequence number conflict tag information, and integrate all the second conflict-free tag information to obtain the second identification tag list. The fourth acquisition module is used to acquire a completion verification table based on the first identification tag list, the second identification tag list, and the historical book borrowing table, and to acquire the borrower's real-time confidence level based on the historical book borrowing table and the completion verification table. The second judgment module is used to determine whether the borrower's real-time confidence level is less than a preset value; If the value is less than the threshold, it is determined that the borrower has not completed the verification process, and a swing gate closing signal is generated for the corresponding channel. If the value is not less than the minimum value, the borrower is deemed to have completed the verification process, and a swing gate opening signal for the corresponding channel is generated. The third acquisition module includes: The fifth acquisition unit is used to acquire the sequence number length of the time slot sequence number; The sixth acquisition unit is used to acquire refined sequence number information for each conflicting tag based on the sequence number length; The seventh acquisition unit is used to determine whether the refined sequence number information corresponding to each conflicting label information is the same; If multiple identical refined sequence number information exist, increase the sequence number length for all identical refined sequence number information, and return the refined sequence number information with the increased sequence number length to the step of determining whether the refined sequence number information corresponding to each conflicting label information is the same; If there is refined sequence information that is different from others, the conflicting label information corresponding to the refined sequence information shall be used as the second conflict-free label information.

7. The control system for a multi-channel ultra-high frequency contactless borrowing channel according to claim 6, characterized in that, The second acquisition module includes: The first acquisition unit is used to acquire a preset time slot detection time interval; The second acquisition unit is used to acquire a preset detection period for each of the label information; The third acquisition unit is used to divide the preset detection period according to the preset time slot detection time interval to obtain multiple tag detection time slots; The fourth acquisition unit is used to number and sort the multiple tag detection time slots corresponding to each tag information according to the division order to obtain a time slot group; The first detection unit is used to send time slot detection information for each tag detection time slot in the time slot group; If the first tag detection time slot in the time slot group does not generate a signal response when it receives the time slot detection information, then the tag detection time slot is regarded as a non-triggered time slot, and the time slot detection information is sent to the next tag detection time slot; The information response is generated when the subsequent tag detection time slot receives the time slot detection information, and the tag detection time slot is returned as the tag time slot information.

8. The control system for a multi-channel ultra-high frequency contactless borrowing channel according to claim 6, characterized in that, The fourth acquisition module includes: The eighth acquisition unit is used to acquire multiple book names from the database based on the first identification tag list and the second identification tag list; The ninth acquisition unit is used to establish a book temporary storage list based on multiple book names, wherein the book temporary storage list includes book names and book borrowing / returning status information; The tenth acquisition unit is used to acquire book borrowing and returning operation information through the touch screen; The eleventh acquisition unit is used to verify and modify the book borrowing and returning operation information and the book borrowing and returning status information to obtain the book verification information. The twelfth acquisition unit is used to acquire the completed verification table based on the book verification information and the corresponding book name.

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