A full-link monitoring system for traditional Chinese medicine based on artificial intelligence

Abstract

The present invention relates to the technical field of link monitoring, and in particular to an artificial intelligence-based full-link monitoring system for traditional Chinese medicine, comprising: extracting a traditional Chinese medicine information set stored in a link monitoring platform; based on the traditional Chinese medicine information set stored in the link monitoring platform, analyzing each link of the traditional Chinese medicine from the dimension of information unit revision to obtain information confidence; comparing the information confidence with a preset information confidence to evaluate the traceability of each link of the traditional Chinese medicine; determining a calibration period of each information unit according to the frequency of each information unit in a monitoring period, and at the same time, determining a weight coefficient of the information unit according to the revision amplitude of the information unit, processing the calibration period of the information unit and the weight coefficient to obtain a monitoring period of each information unit; the present invention effectively ensures that data information involved in the full link of traditional Chinese medicine is more accurate, and effectively avoids the frequency of tampering with data information involved in the full link of traditional Chinese medicine.

Description

Technical Field

[0001] The present invention relates to the field of link monitoring technology, and in particular to an artificial intelligence-based full-link monitoring system for traditional Chinese medicine. Background Art

[0002] Consumers are paying more and more attention to the safety of Chinese herbal medicines and have put forward higher requirements for the quality, safety and effectiveness of Chinese herbal medicines. Now, by assigning a unique traceability code to each piece of Chinese herbal medicine, the entire process of production, circulation and consumption of Chinese herbal medicines can be traced;

[0003] In the existing technology, malicious access may occur in each link of the entire chain of Chinese medicinal materials, and the information of Chinese medicinal materials may be tampered with, resulting in the inability to quickly and accurately verify the data of Chinese medicinal materials. Summary of the Invention

[0004] The purpose of the present invention is to provide an artificial intelligence-based full-link monitoring system for Chinese medicinal materials to solve at least one of the above-mentioned problems in the prior art.

[0005] An AI-based full-link monitoring system for traditional Chinese medicine, including:

[0006] Information collection module: obtains the monitoring platforms involved in each link of Chinese medicinal materials and extracts the Chinese medicinal materials information set stored in the link monitoring platform;

[0007] Information analysis module: Based on the TCM information set stored in the link monitoring platform, analyze each link of TCM from the perspective of information unit revision to obtain information confidence; the information unit is the specific information included in the information set of the TCM production monitoring platform, circulation monitoring platform, and sales monitoring platform;

[0008] Information evaluation module: Based on the information confidence of each link of Chinese medicinal materials, the information confidence is compared with the preset information confidence to evaluate the traceability of each link of Chinese medicinal materials;

[0009] Monitoring and control module: Based on the signal that is difficult to trace, the calibration period of each information unit is determined according to the frequency of each information unit in the monitoring period. At the same time, the revision range of the information unit is obtained by comparing the information unit before revision with the information unit after revision. According to the revision range of the information unit, the weight coefficient of the information unit is determined. The calibration period of the information unit and the weight coefficient are processed to obtain the monitoring period of each information unit.

[0010] As a further technical solution of the present invention: the link monitoring platform includes a production monitoring platform for Chinese medicinal materials, a circulation monitoring platform for Chinese medicinal materials, and a sales monitoring platform for Chinese medicinal materials.

[0011] As a further technical solution of the present invention: in the information analysis module, during the monitoring period, for each link monitoring platform, relevant parameters for the revision of each information unit are obtained, and the relevant parameters include the number of information unit revisions and the time of information unit revisions; based on the relevant parameters of each revised information unit, the weight coefficient of each information unit is obtained.

[0012] As a further technical solution of the present invention: the process of obtaining the information confidence of each link is:

[0013] and obtaining the revision frequency of each information unit during the monitoring period, and calculating the product of the revision frequency of each information unit during the monitoring period and the weight coefficient to obtain the influence range of each information unit;

[0014] The influence ranges of all information units in each link monitoring platform are averaged to obtain the information confidence of each link.

[0015] As a further technical solution of the present invention: the specific process of obtaining the weight coefficient of each information unit is:

[0016] The weight coefficient of each information unit is calculated by the number of information unit revisions and the time of information unit revisions. The calculation formula is as follows:

[0017]

[0018] Where X represents the weight coefficient of each information unit, i=1,2,...,n, n represents the number of information unit revisions involved, N represents the number of all information units in the link monitoring platform, Ti represents the time of revision of the i-th information unit, and Tmax represents the maximum time of information unit revision.

[0019] As a further technical solution of the present invention: in the information evaluation module, if the information confidence is greater than or equal to a preset information confidence, a signal indicating that it is not convenient to trace back is generated.

[0020] As a further technical solution of the present invention: the process of obtaining the calibration period is:

[0021] Obtain the total number of revisions of the information unit during the monitoring period, as well as the time node corresponding to each revision; calculate the time interval between two adjacent revisions based on the time node corresponding to each revision, extract the minimum time interval between two adjacent revisions, and record it as the calibration period of the information unit.

[0022] As a further technical solution of the present invention: the process of obtaining the revision range is:

[0023] Obtain the number of characters of the information unit before revision, compare the revised information unit with the information unit before revision, extract the number of modified characters of the information unit, perform ratio processing on the number of modified characters of the information unit and the number of characters of the information unit before revision to obtain the revision range of the information unit.

[0024] As a further technical solution of the present invention: the process of obtaining the weight coefficient of the information unit is:

[0025]

[0026] Where K is the weight coefficient of the information unit, j=1,2,...,m, m represents the total number of revisions of the information unit during the monitoring period, and Dj represents the revision extent of the information unit at the jth revision.

[0027] As a further technical solution of the present invention, the specific process of processing the calibration period and the weight coefficient of the information unit is as follows:

[0028] The calibration period of the information unit is multiplied by the weight coefficient to obtain the monitoring period of each information unit.

[0029] Beneficial effects of the present invention:

[0030] The present invention obtains the monitoring platform involved in each link of Chinese medicinal materials, extracts the Chinese medicinal materials information set stored in the link monitoring platform; based on the Chinese medicinal materials information set stored in the link monitoring platform, each link of the Chinese medicinal materials is analyzed from the information unit revision dimension to obtain information confidence; based on the information confidence of each link of the Chinese medicinal materials, the information confidence is compared with the preset information confidence to evaluate the traceability of each link of the Chinese medicinal materials; the technical solution of the embodiment of the present invention: the information data in the monitoring platform connected to any link in the entire link of Chinese medicinal materials is analyzed from the revision mode, and the impact generated when the modification is performed is digitally evaluated, so that the information data involved in each link can be traced and evaluated, and the revision degree of the information data involved in each link can also be evaluated, that is, when the information data involved in the link is revised and modified, whether it is convenient to trace and search later.

[0031] The present invention is based on the fact that it is inconvenient to trace signals. According to the frequency of each information unit in the monitoring period, the calibration period of the information unit is determined. At the same time, the revision range of the information unit is obtained by comparing the information unit before revision with the information unit after revision. According to the revision range of the information unit, the weight coefficient of the information unit is determined. The calibration period and the weight coefficient of the information unit are processed to obtain the monitoring period of each information unit. The present invention identifies the monitoring period of each information unit based on the data analyzed in the monitoring period, so that the supervisor can promptly approve each information unit according to the analyzed period, which can effectively ensure that the data information involved in the whole chain of Chinese medicinal materials is more accurate, and effectively avoid the frequency of tampering with the data information involved in the whole chain of Chinese medicinal materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0033] Figure 1 This is a system block diagram of an artificial intelligence-based full-link monitoring system for traditional Chinese medicines according to the first embodiment of the present invention;

[0034] Figure 2 This is a system block diagram of an artificial intelligence-based full-link monitoring system for traditional Chinese medicines provided in Example 2 of the present invention;

[0035] Figure 3 This is a flowchart of a full-link monitoring method for Chinese medicinal materials based on artificial intelligence provided by the third embodiment of the present invention;

[0036] Figure 4 It is a structural diagram of the device provided in Example 4 of the present invention. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0038] Example 1

[0039] Figure 1This is a structural block diagram of an artificial intelligence-based full-link monitoring system for traditional Chinese medicines provided in the first embodiment of the present invention. This embodiment of the present invention is applicable to situations where malicious access occurs in each link of the full link of traditional Chinese medicines and the information of traditional Chinese medicines is tampered with, resulting in the inability to quickly and accurately verify the data of traditional Chinese medicines;

[0040] The relevant explanation about the whole chain of Chinese medicinal materials is: the whole chain of Chinese medicinal materials includes: the production, circulation, and sales chain of Chinese medicinal materials, etc.

[0041] like Figure 1 As shown, an embodiment of the present invention provides an artificial intelligence-based full-link monitoring system for traditional Chinese medicine, which specifically includes the following modules:

[0042] Information collection module: obtains the monitoring platforms involved in each link of Chinese medicinal materials and extracts the Chinese medicinal materials information set stored in the link monitoring platform;

[0043] Among them, the link monitoring platform includes the production monitoring platform of Chinese medicinal materials, the circulation monitoring platform of Chinese medicinal materials, and the sales monitoring platform of Chinese medicinal materials;

[0044] The information set of the production monitoring platform of Chinese herbal medicines includes: production batch number, production date, manufacturer, production equipment, production personnel, source of raw materials and other information of Chinese herbal medicines;

[0045] The information set of the circulation monitoring platform of Chinese medicinal materials includes: the transportation date, transportation method, transportation company, storage location, storage temperature, storage time and other information of Chinese medicinal materials;

[0046] The information set of the sales monitoring platform of Chinese medicinal materials includes: sales date, sales channel, sales quantity, sales price, sales area and other information of Chinese medicinal materials.

[0047] Information Analysis Module: Based on the TCM information set stored in the link monitoring platform, the module analyzes each link of the TCM from the perspective of information unit revision to obtain information confidence. The information unit is the specific information included in the information set of the TCM production monitoring platform, circulation monitoring platform, and sales monitoring platform, such as the production batch number, production date, transportation date, and sales date of the TCM.

[0048] Among them, from the perspective of information unit revision, the specific process of analyzing each Chinese medicinal material information set is as follows:

[0049] Setting a monitoring period. The length of the monitoring period can be preset by a person skilled in the art. Preferably, the monitoring period can be set to 1 hour.

[0050] During the monitoring cycle, for each link monitoring platform, relevant parameters of each information unit revision are obtained, including the number of information unit revisions and the time of the information unit revisions. Among them, information unit revision refers to modifying the original data of the information unit to different data from the previous data, for example, modifying the original production batch number of October 12, 2023, 8:52:18 to October 12, 2023, 8:59:18;

[0051] Obtaining a weight coefficient of each information unit according to relevant parameters of each revised information unit;

[0052] and obtaining the revision frequency of each information unit during the monitoring period, and calculating the product of the revision frequency of each information unit during the monitoring period and the weight coefficient to obtain the influence range of each information unit;

[0053] The influence range of all information units in each link monitoring platform is averaged to obtain the information confidence of each link;

[0054] First, specifically, the process of obtaining the weight coefficient of each information unit is as follows:

[0055] In a link monitoring platform, when any information unit in an information set is initially changed, the number of other information units that have also changed is counted, which is recorded as the number of information unit revisions involved. The time since the initial change of the other information units is counted, which is recorded as the information unit revision time.

[0056] The weight coefficient of each information unit is calculated by the number of information unit revisions and the time of information unit revisions. The calculation formula is as follows:

[0057]

[0058] Where X represents the weight coefficient of each information unit, i=1,2,...,n, n represents the number of information unit revisions involved, N represents the number of all information units in the link monitoring platform, T i Indicates the time when the i-th information unit is revised, T max The maximum value of the time when the information unit was revised;

[0059] Second, specifically, the process of obtaining the frequency of each information unit in the monitoring period is as follows:

[0060] Count the total number of revisions of the information unit during the monitoring period, and perform a ratio process on the total number of revisions and the monitoring period to obtain the frequency of each information unit during the monitoring period;

[0061] For example, during the monitoring period, for the production monitoring platform of Chinese medicinal materials, the number of revisions of the information units involved in the revision of the production batch number of the Chinese medicinal materials is obtained, which is recorded as a value A, and the time of the revision of the information units involved is recorded as a value B; and the frequency of revisions of the production batch number of the Chinese medicinal materials during the monitoring period is recorded as a value C, where the values of A, B, and C are based on actual statistics;

[0062] The weight coefficient of the production batch number of Chinese herbal medicine during revision is calculated using the following formula:

[0063] ;

[0064] Among them, X represents the weight coefficient of the production batch number of Chinese herbal medicine when it is revised, i=1,2,...,A, A represents the number of information units involved in the revision, N represents the number of all information units in the link monitoring platform, B A Indicates the time when the Ath information unit was revised, B max The maximum value of the time when the information unit was revised;

[0065] The revision frequency C of the production batch number of the Chinese herbal medicine in the monitoring period is multiplied by the weight coefficient X to obtain the influence range of each information unit;

[0066] Information evaluation module: Based on the information confidence of each link of Chinese medicinal materials, the information confidence is compared with the preset information confidence to evaluate the traceability of each link of Chinese medicinal materials;

[0067] The process of comparing the information confidence level with the preset information confidence level is as follows:

[0068] If the information confidence level is greater than or equal to the preset information confidence level, a signal indicating that it is not convenient for tracing is generated;

[0069] If the information confidence level is less than the preset information confidence level, a traceability signal is generated;

[0070] It should be explained that the meaning of the inconvenience of traceability signal is that when a specific information unit in a certain link of the Chinese medicinal materials analysis is tampered with in the monitoring platform involved in the link, it will cause a series of modifications to multiple other information units, with a large scope of triggering and related impacts. In addition, if the frequency of tampering with information units is high, the information data contained in the monitoring platform of the link will be tampered with, revised, and modified. In the subsequent verification process, it will be difficult to conduct verification and traceability to ensure the accuracy of the Chinese medicinal materials link data;

[0071] The meaning represented by the traceability signal is that: in one of the links analyzed by Chinese medicinal materials, when a specific information unit is tampered with in the monitoring platform involved in the link, it will not cause a series of modifications to multiple information units, and there will be a small triggering and associated impact range. In addition, the frequency of tampering with information units is low, which will make it easier to verify and trace the information data contained in the monitoring platform of the link if it is tampered with, revised, or modified. In this way, the accuracy of the Chinese medicinal materials link data can be guaranteed.

[0072] The technical solution of the embodiment of the present invention is as follows: obtaining the monitoring platform involved in each link of Chinese medicinal materials, extracting the Chinese medicinal materials information set stored in the link monitoring platform; based on the Chinese medicinal materials information set stored in the link monitoring platform, analyzing each link of the Chinese medicinal materials from the information unit revision dimension to obtain information confidence; based on the information confidence of each link of the Chinese medicinal materials, comparing the information confidence with the preset information confidence to evaluate the traceability of each link of the Chinese medicinal materials; the technical solution of the embodiment of the present invention is as follows: analyzing the information data in the monitoring platform connected to any link in the entire link of Chinese medicinal materials from the revision mode, and digitally evaluating the impact of the modification, so that the information data involved in each link can be traced and evaluated, and the revision degree of the information data involved in each link can also be evaluated, that is, when the information data involved in the link is revised or modified, whether it is convenient to trace and search later.

[0073] Example 2

[0074] Figure 2 This is a structural block diagram of a full-link monitoring system for Chinese medicinal materials based on artificial intelligence provided by the second embodiment of the present invention, such as Figure 2 As shown, an embodiment of the present invention provides an artificial intelligence-based full-link monitoring system for traditional Chinese medicine, which specifically includes the following modules:

[0075] Monitoring and control module: Based on the signal that is difficult to trace, the link corresponding to the signal that is difficult to trace is analyzed. According to the frequency of each information unit in the monitoring period, the calibration period of the information unit is determined. At the same time, the revision range of the information unit is obtained by comparing the information unit before and after the revision. According to the revision range of the information unit, the weight coefficient of the information unit is determined. The calibration period of the information unit and the weight coefficient are processed to obtain the monitoring period of each information unit.

[0076] First, specifically, according to the frequency of each information unit in the monitoring period, the specific process of determining the calibration period of the information unit is as follows:

[0077] Obtain the total number of revisions of the information unit during the monitoring period, as well as the time node corresponding to each revision; calculate the time interval between two adjacent revisions based on the time node corresponding to each revision, extract the minimum time interval between two adjacent revisions, and record it as the calibration period of the information unit;

[0078] Secondly, specifically, the specific process of obtaining the revision extent of the information unit by comparing the information unit before revision with the information unit after revision is as follows:

[0079] Obtaining the number of characters in the information unit before revision, comparing the revised information unit with the information unit before revision, extracting the number of characters modified in the information unit, performing ratio processing on the number of characters modified in the information unit and the number of characters in the information unit before revision to obtain the revision extent of the information unit;

[0080] Thirdly, specifically, according to the revision extent of the information unit, the specific process of determining the weight coefficient of the information unit is as follows:

[0081] Obtain the total number of revisions of the information unit during the monitoring period, as well as the revision range obtained by analyzing each revision of the information unit, and calculate the weight coefficient of the information unit through the formula, which is as follows:

[0082]

[0083] Where K is the weight coefficient of the information unit, j = 1, 2, ..., m, m represents the total number of revisions of the information unit during the monitoring period, D j Indicates the revision extent of the information unit at the jth revision;

[0084] Fourthly, specifically, the specific process of processing the calibration period and the weight coefficient of the information unit is as follows:

[0085] The calibration period of the information unit is multiplied by the weight coefficient to obtain the monitoring period of each information unit;

[0086] The technical solution of the embodiment of the present invention: based on the inconvenience of tracing signals, the calibration period of each information unit is determined according to the frequency of each information unit in the monitoring period. At the same time, the revision range of the information unit is obtained by comparing the information unit before revision with the information unit after revision. According to the revision range of the information unit, the weight coefficient of the information unit is determined, and the calibration period and weight coefficient of the information unit are processed to obtain the monitoring period of each information unit. The present invention identifies the monitoring period of each information unit based on the data analyzed in the monitoring period, so that the supervisor can promptly approve each information unit according to the analyzed period, which can effectively ensure that the data information involved in the whole chain of Chinese medicinal materials is more accurate, and effectively avoid the frequency of tampering with the data information involved in the whole chain of Chinese medicinal materials.

[0087] Example 3

[0088] Figure 3 This is a structural diagram of a full-link monitoring method for Chinese medicinal materials based on artificial intelligence provided in Example 2 of the present invention, such as Figure 2 As shown, an embodiment of the present invention provides an artificial intelligence-based full-link monitoring method for Chinese medicinal materials, which specifically includes the following steps:

[0089] Step 1: Obtain the monitoring platform involved in each link of Chinese medicinal materials and extract the Chinese medicinal materials information set stored in the link monitoring platform;

[0090] Step 2: Based on the TCM information set stored in the link monitoring platform, analyze each link of the TCM from the perspective of information unit revision to obtain information confidence; the information unit is the specific information included in the information set of the TCM production monitoring platform, circulation monitoring platform, and sales monitoring platform, such as the production batch number, production date, transportation date, and sales date of the TCM;

[0091] Step 3: Based on the information confidence of each link of the Chinese medicinal materials, the information confidence is compared with the preset information confidence to evaluate the traceability of each link of the Chinese medicinal materials;

[0092] Step 4. Based on the signal that is not easy to trace, determine the calibration period of each information unit according to the frequency of each information unit in the monitoring period. At the same time, compare the information unit before revision with the information unit after revision to obtain the revision range of the information unit. According to the revision range of the information unit, determine the weight coefficient of the information unit. Process the calibration period of the information unit and the weight coefficient to obtain the monitoring period of each information unit.

[0093] Example 4

[0094] Reference Figure 4An embodiment of the present invention further provides a computer device, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, a backlight module processing coating flatness monitoring method based on machine vision as described in any one of the above methods is implemented.

[0095] The computer device may be a desktop computer, a notebook computer, a PDA, a cloud server or other computing devices. The computer device may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will understand that Figure 3 The computer device is merely an example and does not constitute a limitation on the computer device. The computer device may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, etc.

[0096] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0097] In some embodiments, the memory 302 may be an internal storage unit of the computer device, such as a hard disk or memory of the computer device. In other embodiments, the memory 302 may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped with the computer device. Furthermore, the memory 302 may include both an internal storage unit of the computer device and an external storage device. The memory 302 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or is about to be output.

[0098] Example 5

[0099] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for monitoring the flatness of a backlight module coating based on machine vision as described in any one of the above methods is implemented.

[0100] In this embodiment, if the integrated unit is implemented as a software functional unit and sold or used as a standalone product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process steps in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a camera / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunication signals, and software distribution media. Examples include USB flash drives, removable hard drives, magnetic disks, or optical disks. In some jurisdictions, based on legislation and patent practice, computer-readable media cannot be electric carrier signals or telecommunication signals.

[0101] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0102] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0103] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0104] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0105] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A full-link monitoring system for Chinese medicinal materials based on artificial intelligence, characterized in that: include: Information collection module: obtains the monitoring platforms involved in each link of Chinese medicinal materials and extracts the Chinese medicinal materials information set stored in the link monitoring platform; Information analysis module: Based on the TCM information set stored in the link monitoring platform, each link of TCM is analyzed from the information unit revision dimension to obtain information confidence; The information unit is the specific information included in the information set of the production monitoring platform, circulation monitoring platform, and sales monitoring platform of traditional Chinese medicine; Information evaluation module: Based on the information confidence of each link of Chinese medicinal materials, the information confidence is compared with the preset information confidence to evaluate the traceability of each link of Chinese medicinal materials; Monitoring and control module: Based on the signal that is difficult to trace, the calibration period of each information unit is determined according to the frequency of each information unit in the monitoring period. At the same time, the revision range of the information unit is obtained by comparing the information unit before and after revision. According to the revision range of the information unit, the weight coefficient of the information unit is determined. The calibration period of the information unit and the weight coefficient are calculated to obtain the monitoring period of each information unit. The process of obtaining the revision range is as follows: obtaining the number of characters of the information unit before revision, comparing the revised information unit with the information unit before revision, extracting the number of modified characters of the information unit, performing ratio processing on the number of modified characters of the information unit and the number of characters of the information unit before revision to obtain the revision range of the information unit; The process of obtaining the weight coefficient of the information unit is as follows: ， Where K is the weight coefficient of the information unit, j = 1, 2, ..., m, m represents the total number of revisions of the information unit during the monitoring period, D j Indicates the revision extent of the information unit at the jth revision.

2. The artificial intelligence-based full-link monitoring system for Chinese medicinal materials according to claim 1 is characterized in that: The link monitoring platform includes the production monitoring platform of Chinese medicinal materials, the circulation monitoring platform of Chinese medicinal materials, and the sales monitoring platform of Chinese medicinal materials.

3. The artificial intelligence-based full-link monitoring system for Chinese medicinal materials according to claim 1 is characterized in that: In the information analysis module, during the monitoring cycle, for each link monitoring platform, the relevant parameters of each information unit revision are obtained, including the number of information unit revisions and the time of information unit revisions; based on the relevant parameters of each revised information unit, the weight coefficient of each information unit is obtained.

4. The artificial intelligence-based full-link monitoring system for Chinese medicinal materials according to claim 3 is characterized in that: The process of obtaining the information confidence of each link is as follows: Obtain the revision frequency of each information unit during the monitoring period, and calculate the product of the revision frequency of each information unit during the monitoring period and the weight coefficient to obtain the influence range of each information unit; The influence ranges of all information units in each link monitoring platform are averaged to obtain the information confidence of each link.

5. The artificial intelligence-based full-link monitoring system for Chinese medicinal materials according to claim 4 is characterized in that: The specific process of obtaining the weight coefficient of each information unit is as follows: The weight coefficient of each information unit is calculated by the number of information unit revisions and the time of information unit revisions. The calculation formula is as follows: ， Where X represents the weight coefficient of each information unit, i=1,2,...,n, n represents the number of information unit revisions involved, N represents the number of all information units in the link monitoring platform, T i Indicates the time when the i-th information unit is revised, T max Indicates the maximum value of the time when the information unit was revised.

6. The artificial intelligence-based full-link monitoring system for Chinese medicinal materials according to claim 1, characterized in that: In the information evaluation module, if the information confidence is greater than or equal to the preset information confidence, a signal indicating that it is not convenient to trace is generated.

7. The artificial intelligence-based full-link monitoring system for Chinese medicinal materials according to claim 6, characterized in that: The process of obtaining the calibration cycle is: Obtain the total number of revisions of the information unit during the monitoring period, as well as the time node corresponding to each revision; calculate the time interval between two adjacent revisions based on the time node corresponding to each revision, extract the minimum time interval between two adjacent revisions, and record it as the calibration period of the information unit.

8. The artificial intelligence-based full-link monitoring system for Chinese medicinal materials according to claim 1, characterized in that: The specific process of processing the calibration period and weight coefficient of the information unit is as follows: The calibration period of the information unit is multiplied by the weight coefficient to obtain the monitoring period of each information unit.

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