Data touch all-in-one machine management system and method based on artificial intelligence

Abstract

The invention discloses a datamation touch all-in-one machine management system and method based on artificial intelligence, and relates to the technical field of artificial intelligence datamation, and the regulation and control method comprises the following steps: collecting the specific use condition of a touch all-in-one machine when a user uses the touch all-in-one machine; the method comprises the following steps of: establishing an evaluation coefficient by using a plurality of acquired parameters of the touch all-in-one machine by a user through a formula, and comparing the evaluation coefficient with a gradient threshold value to obtain an actual experience effect of the user on the touch all-in-one machine; considering that the performance of the touch all-in-one machine and the area where the touch all-in-one machine is located can affect the experience effect of a user on the touch all-in-one machine, the quality coefficient of the touch all-in-one machine is obtained in real time through the monitoring module, and management on the touch all-in-one machine is enhanced by comparing the quality coefficient with a standard threshold value, so that the user experience is improved. The touch all-in-one machine can be put into use conveniently, and meanwhile human resources are saved.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence data technology, specifically to an artificial intelligence-based data-driven touch screen all-in-one machine management system and method. Background Technology

[0002] With the continuous development of science and technology, touch screen all-in-one machines are used in many situations. Direct operation through the touchscreen makes the interaction between the user and the device more intuitive and natural. The high-definition display of the touch screen all-in-one machine can display rich images, videos, text, and other content. Users can directly physically interact with the screen using their fingers, styluses, etc., achieving more precise and free operation and providing a richer interactive experience.

[0003] Artificial intelligence-based data-driven touch screen all-in-one machine management systems and methods typically include components such as smart displays, cameras, computers, and software. Among them, the camera is responsible for capturing the user's appearance, and the computer recognizes the captured images to provide different operation pages for different users. The computer technology uses the data analysis results to make intelligent decisions and optimizations, and finally provides comprehensive and effective services to users based on their actual feedback.

[0004] The existing technology has the following shortcomings:

[0005] In real life, touch screen all-in-one machines have become widespread in various industries, such as administration, commerce, finance, and management, and can usually bring users fast and efficient services. However, in actual use, due to the lagging management methods of managers, touch screen all-in-one machines have not been widely used by a large number of users. Summary of the Invention

[0006] The purpose of this invention is to provide a data-driven touch screen all-in-one machine management system and method based on artificial intelligence, so as to solve the shortcomings of the prior art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a data-driven touch screen all-in-one machine management method based on artificial intelligence, the management method comprising the following steps:

[0008] S1: Collect multiple parameters when users use the touch screen all-in-one machine, and establish an evaluation coefficient for the user's evaluation of the touch screen all-in-one machine's performance through a formula;

[0009] S2: Based on the comparison results of the evaluation coefficient and the gradient threshold, generate the user's experience level of the touch screen all-in-one machine;

[0010] S3: Monitor the user's evaluation of touch all-in-one machines as "average" in the user experience rating;

[0011] S4: By monitoring the performance changes of touch all-in-one machines with mediocre user experience, a quality coefficient is established for the performance status of the touch all-in-one machines.

[0012] S5: Compare the quality coefficient with the standard threshold, and based on the comparison results, further manage the touch screen all-in-one machine.

[0013] In a preferred embodiment: In S1, establishing the evaluation coefficients includes the following steps:

[0014] The collected parameters include user frequency of use of the touch screen all-in-one machine, click-through rate in hotspot areas, churn rate due to pain points, and operation time. These parameters are used to establish an evaluation coefficient for the user's evaluation of the touch screen all-in-one machine's effectiveness. The expression is as follows:

[0015]

[0016] In the formula, dk i My rating is a coefficient used by users to evaluate the effectiveness of using the touch screen all-in-one machine. j Pain point loss level value, lk j Based on the frequency of user use of touch screen all-in-one machines, ty z For click-through rates in hot areas, su k The operation time is represented by a1, a2, a3, and a4, which are the weighting factor coefficients of the pain point loss level, the user's frequency of use of the touch screen all-in-one machine, the click rate of hot spots, and the operation time, respectively, and a2>a3>a1>a4>0.

[0017] In a preferred embodiment, establishing the evaluation coefficients includes the following steps:

[0018] S1.1: The expression for calculating the pain point loss level is: my j =100log 10 (m1 / m2), where m1 is the number of users experiencing pain points and m2 is the total number of users. The total number of users refers to the total number of users who use the touch all-in-one machine within a single day.

[0019] S1.2: The formula for calculating the frequency of user use of the touch screen all-in-one machine is: lk j =yg i / (yh i +1), yg i The number of times a touch screen all-in-one machine is used refers to the total number of times the touch screen all-in-one machine is used within a single day; yh i This represents the total number of users of the touch screen all-in-one machine;

[0020] S1.3: The logic for obtaining the click-through rate of hot spots is as follows: By setting some hot spots on the touch screen all-in-one machine, the ratio of the number of clicks on the hot spots to the total number of times the hot spots are displayed or appear on the touch screen all-in-one machine is the click-through rate of the hot spots.

[0021] S1.4: The logic for obtaining the user's operation time on the touch screen all-in-one machine is to record the specific time from when the user initiates the operation to when the application interface opens and until the application interface is closed.

[0022] In a preferred embodiment: S2, comparing the user's evaluation coefficient of the touch screen all-in-one machine's performance with a gradient threshold includes the following steps:

[0023] S2.1 After obtaining the evaluation coefficients of the user's feedback on the use of the touch screen all-in-one machine, the gradient threshold includes the first threshold yu. m Second threshold yu n And the first threshold yu m <Second threshold yu n The evaluation coefficients are compared with the first threshold yu. m Second threshold yu n Compare;

[0024] S2.2 If the evaluation coefficient ≤ the first threshold yu m The system outputs a level one warning signal;

[0025] S2.3 When the first threshold yu m <Evaluation coefficient<Second threshold yu n The system outputs a level-two warning signal;

[0026] S2.4 If the evaluation coefficient ≥ the second threshold yu n The system does not issue a warning signal;

[0027] In a preferred embodiment: In S4, the quality coefficient of the touch screen all-in-one machine is established, including the following steps:

[0028] During the monitoring process, multiple performance parameters of each touch screen all-in-one machine were collected. These parameters included the interference level of the wireless network signal, the lag level of the touch screen all-in-one machine, and the sampling rate of the touch screen. A quality coefficient was established using a formula based on these parameters, expressed as follows:

[0029]

[0030] In the formula, ct i For the quality coefficient of the touch screen all-in-one machine, LG z This is a lag level value for the touch screen all-in-one machine. z This represents the interference level of the wireless network signal, mj xβ1, β2, and β3 are the sampling rate of the touch screen, the interference value of the wireless network signal, and the lag value of the touch screen all-in-one machine, respectively, with β1>β2>β3>0.

[0031] In a preferred embodiment, the comparison of the quality coefficient with a standard threshold includes the following steps:

[0032] After obtaining the quality score of a touch screen all-in-one machine with a mediocre user experience, the quality score is compared with a standard threshold:

[0033] If the quality coefficient is greater than the standard threshold, the system will issue a regional survey signal;

[0034] If the quality coefficient is less than or equal to the standard threshold, the system will not issue a regional survey signal.

[0035] The present invention also provides an artificial intelligence-based data-driven touch screen all-in-one machine management system, including a data acquisition module, a comparison module, an early warning module, a monitoring module, a processing module, and a management module;

[0036] The data acquisition module collects multiple parameters of the user's use of the touch screen all-in-one machine and establishes evaluation coefficients through formulas. The comparison module compares the evaluation coefficients with the gradient threshold. The early warning module issues early warning information based on the comparison results. Considering that the performance of the touch screen all-in-one machine itself and the area where the touch screen all-in-one machine is located will also affect the user's experience, the monitoring module obtains the quality coefficient of the touch screen all-in-one machine in real time. The processing module compares the quality coefficient with the standard threshold. The management module strengthens the management of the touch screen all-in-one machine based on the comparison results.

[0037] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0038] 1. This invention collects user data on the operation panel of a touch screen all-in-one machine when the user starts using it. It establishes evaluation coefficients based on multiple parameters of the user collected, including the user's frequency of use of the touch screen all-in-one machine, the click rate of hot spots, the degree of loss due to pain points, and the operation time. Based on the comparison between the evaluation coefficients and the gradient threshold, the actual usage effect of the touch screen all-in-one machine is obtained, and the touch screen all-in-one machine is managed.

[0039] 2. This invention manages touch screen all-in-one machines with mediocre user experience. Considering that the performance of the touch screen all-in-one machine and its location also affect the user experience, it is necessary to collect data on the machine's performance. Multiple performance parameters are then combined to establish a quality coefficient. This quality coefficient is then compared with a standard threshold to further manage the touch screen all-in-one machine. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0041] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Example 1

[0044] This invention collects data on user experience when using a touchscreen all-in-one machine. Multiple parameters of the collected data are used to establish evaluation coefficients. By comparing these evaluation coefficients with a gradient threshold, the actual user experience of the touchscreen all-in-one machine is obtained. Considering that the performance of the touchscreen all-in-one machine itself and the area where it is located both affect the user experience, a monitoring module obtains the quality coefficient of the touchscreen all-in-one machine in real time. By comparing the quality coefficient with a standard threshold, the management of the touchscreen all-in-one machine is strengthened.

[0045] To better illustrate this embodiment, the evaluation coefficients are established by collecting multiple parameters from the user when using the touch screen all-in-one machine, including the following steps:

[0046] The collected parameters include user frequency of use of the touch screen all-in-one machine, click-through rate in hotspot areas, churn rate due to pain points, and operation time. These parameters are used to establish an evaluation coefficient for the user's evaluation of the touch screen all-in-one machine's effectiveness. The expression is as follows:

[0047]

[0048] In the formula, dk i My rating is a coefficient used by users to evaluate the effectiveness of using the touch screen all-in-one machine. j Pain point loss level value, lk j Based on the frequency of user use of touch screen all-in-one machines, ty z For click-through rates in hot areas, su kThe operation time is represented by a1, a2, a3, and a4, which are the pain point loss level value, the user's frequency of use of the touch screen all-in-one machine, the click rate of hot spots, and the weight factor coefficients of the operation time. The specific values ​​of the weight factor coefficients a1, a2, a3, and a4 are set by those skilled in the art based on the actual collected production information, and are not limited here.

[0049] The expression for calculating the pain point loss level is: my j =100log 10 (m1 / m2), where m1 is the number of users who churned due to pain points, which refers to the number of users who left during the use of the touch screen all-in-one machine; and m2 is the total number of users, which refers to the total number of users who used the touch screen all-in-one machine in a single day.

[0050] The logic for acquiring users who churn due to pain points is: the number of users who leave the purchase process midway through use, abandon a certain function, or stop using the touch all-in-one machine. The specific number of users is collected and recorded by the camera.

[0051] The formula for calculating the frequency of user usage of a touch screen all-in-one machine is: lk j =yg i / (yh i +1), yg i The number of times a touch screen all-in-one machine is used refers to the total number of times the touch screen all-in-one machine is used within a single day; yh i The total number of touch screen all-in-one users refers to the total number of users who use the touch screen all-in-one device in a single day; the higher the frequency of use of the touch screen all-in-one device, the better the user experience.

[0052] The logic for obtaining the click-through rate of hotspot areas is as follows: by setting some hotspot areas on the touch screen all-in-one machine, the ratio of the number of clicks on the hotspot areas to the total number of times the hotspot areas are displayed or appear on the touch screen all-in-one machine is the click-through rate of the hotspot areas. A higher click-through rate usually indicates that users pay more attention to the hotspot areas, while a lower click-through rate may mean that the hotspot areas are less attractive or that there is an opportunity for improvement.

[0053] It should be noted that the hot spots of a touch screen all-in-one machine refer to the areas on the screen that users touch, click or operate most frequently, such as menus, icons and buttons on the main screen.

[0054] The logic for obtaining the user's operation time on the touch screen all-in-one machine is as follows: Record the specific time from when the user initiates an operation to when the application interface opens and closes. For example, when the user starts an operation, record the current timestamp, which is the start time of the operation. Wait for the user to complete the operation, such as clicking a button or swiping the screen. After the user completes the operation, record the current timestamp again, which is the end time of the operation. Subtract the start time of the operation from the end time to get the time difference of the operation. This time difference is the user's operation time on the touch screen all-in-one machine. A shorter operation time usually means that the user can complete the task quickly, while a longer operation time means that more time is needed or there are difficulties in operation.

[0055] It should be noted that this embodiment is a continuous operation process under normal circumstances. There is no operation that starts and then restarts after a period of time. If this happens, it will still be calculated as a restart.

[0056] Obtain the user evaluation coefficient dk for the effectiveness of using the touch screen all-in-one machine. i Subsequently, the gradient threshold in this application includes a first threshold yu. m Second threshold yu n And the first threshold yu m <Second threshold yu n The evaluation coefficient dk i respectively with the first threshold yu m Second threshold yu n Comparison:

[0057] If the evaluation coefficient dk i ≤First threshold yu m The user experience is very poor. The system outputs a level one warning signal. When the maintenance personnel receive the warning signal, they will shut down the machine for improvement.

[0058] When the first threshold yu m <Evaluation coefficient dk i <Second threshold yu n The user experience is average. The system outputs a level 2 warning signal. When maintenance personnel receive the level 2 warning signal, they can directly perform simple maintenance on the touch screen all-in-one machine.

[0059] If the evaluation coefficient dk i ≥ Second threshold yu n This indicates that users have an excellent experience with the touch screen all-in-one machine and will retain it.

[0060] Specifically, the importance of a Level 1 warning is greater than that of a Level 2 warning. When the system issues a warning, maintenance personnel can directly perform simple maintenance on the touch screen all-in-one machine upon receiving a Level 2 warning signal. Touch screen all-in-one machines that issue a Level 1 warning signal should be shut down for improvement, while those that do not issue a warning signal should be retained.

[0061] Example 2

[0062] In Embodiment 1 above, an evaluation coefficient for user experience with the touchscreen all-in-one machine was established. To objectively quantify user experience, the user experience was categorized into three types: good, average, and poor. Furthermore, the quality of the touchscreen all-in-one machine itself needs to be monitored to determine whether the performance of the machine itself or the location of the machine affects the user experience. This allows for more accurate identification and resolution of potential user experience issues, enabling targeted improvements and ultimately enhancing the overall user experience.

[0063] A quality coefficient is established by combining multiple parameters of the collected touch screen all-in-one machine's performance into a single formula. The quality coefficient is then compared with a standard threshold to further manage the touch screen all-in-one machine.

[0064] This invention establishes a quality coefficient by monitoring changes in the performance of the touch screen all-in-one machine and combining multiple parameters, including the following steps:

[0065] The monitoring module monitors multiple performance parameters of each touch screen all-in-one machine. These parameters include the interference level of the wireless network signal, the lag level of the touch screen all-in-one machine, and the sampling rate of the touch screen. A quality coefficient is established using a formula based on these parameters, expressed as follows:

[0066]

[0067] In the formula, ct i For the quality coefficient of the touch screen all-in-one machine, LG z This is a lag level value for the touch screen all-in-one machine. z This represents the interference level of the wireless network signal, mj x β1, β2, and β3 are the sampling rate of the touch screen, the interference value of the wireless network signal, and the lag value of the touch screen all-in-one machine. The specific values ​​of the weighting factor coefficients β1, β2, and β3 are set by those skilled in the art based on the actual production information collected, and are not limited here.

[0068] The logic for obtaining the lag level value of a touch screen all-in-one machine is as follows: The lag level of a touch screen all-in-one machine can be achieved by measuring the average response time of the application. The average response time refers to the average time taken to perform a specific operation or open an application within a certain period of time. A longer average response time indicates a higher degree of lag, and vice versa. For example, first determine the application that the user operates on, and the scenario in which the user performs these operations or opens the application. Record the response time of each execution, add up the response times of all test results, and then divide by the number of tests to obtain the average response time. Generally speaking, when the average response time of the touch screen all-in-one machine exceeds about 300 milliseconds (ms), it is considered to be lagging.

[0069] The logic for obtaining the interference level of a wireless network signal is as follows: the signal strength is usually used to obtain the interference level of the wireless network signal. The signal strength refers to the strength of the received signal, usually expressed in decibels (dBm). The larger the value, the stronger the signal and the lower the interference level.

[0070] Signal strength is usually measured using a spectrum analyzer installed on the touch screen all-in-one machine. The spectrum analyzer scans the signals within the frequency range set by the touch screen all-in-one machine, converts the collected signal data into a spectrum graph, and displays it on the screen. The spectrum graph is usually plotted with frequency on the horizontal axis and signal strength on the vertical axis. By obtaining the values ​​on the coordinate axes, the signal strength value is obtained.

[0071] Touchscreen sampling rate mj x The acquisition logic is as follows: When a user is using a touch screen all-in-one machine and a specific option is involved, the touch screen analyzer measures the number of times the user's finger presses the screen within one second. The more touches collected, the higher the sampling rate, and the higher the frequency of touch input collection by the touch screen. A high sampling rate means that the touch screen detects touch input more frequently, thus it can more accurately capture the position and action of the touch point and provide a more sensitive touch response.

[0072] The quality coefficient (ct) of the touch all-in-one machine with a mediocre user experience was obtained. i Subsequently, the standard threshold in this application is bz. i The quality coefficient ct i Compared with the standard threshold bz i The comparison includes the following steps:

[0073] If the quality coefficient ct i Standard threshold bz i The performance and quality of the touch screen all-in-one machines are good. The system sends out a regional survey signal. After receiving the regional survey signal, the staff will conduct a survey on all the touch screen all-in-one machines in the region.

[0074] If the quality coefficient ct i ≤Standard threshold bz i The performance and quality of the touch screen all-in-one machines are poor. The system does not send out regional survey signals, and managers do not conduct surveys on the touch screen all-in-one machines in the area after not receiving the regional survey signals.

[0075] Example 3

[0076] The AI-based data-driven touchscreen all-in-one machine management system described in this embodiment includes a data acquisition module, a comparison module, an early warning module, a monitoring module, a processing module, and an adjustment module.

[0077] in,

[0078] Data acquisition module: Used to collect various parameters of the user's experience with the touch screen all-in-one machine and establish evaluation coefficients through formulas;

[0079] Comparison module: Compares the evaluation coefficients with the gradient threshold;

[0080] Early warning module: Determines whether to issue an early warning signal based on the comparison results;

[0081] Monitoring module: Monitors touch screen all-in-one machines with mediocre user experience, collects multiple parameters to establish a quality coefficient;

[0082] Processing module: compares the quality coefficient with a standard threshold;

[0083] Management module: Manages the touch screen all-in-one machine in real time based on whether the system issues a regional survey signal.

[0084] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0085] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0086] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0087] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0088] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0089] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art 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.

[0090] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0092] The units described as separate components may or may not be physically separate. 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 the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0093] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0094] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0095] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A data-driven touch screen all-in-one machine management method based on artificial intelligence, characterized in that: The method includes the following steps: S1: Collect multiple parameters when users use the touch screen all-in-one machine, and establish an evaluation coefficient for the user's evaluation of the touch screen all-in-one machine's performance through a formula; S2: Based on the comparison results of the evaluation coefficient and the gradient threshold, generate the user's experience level of the touch screen all-in-one machine; S3: Monitor the user's evaluation of touch all-in-one machines as "average" in the user experience rating; S4: By monitoring the performance changes of touch all-in-one machines with mediocre user experience, a quality coefficient is established for the performance status of the touch all-in-one machines. S5: Compare the quality coefficient with the standard threshold, and based on the comparison results, further manage the touch screen all-in-one machine.

2. The data-driven touch screen all-in-one machine management method based on artificial intelligence according to claim 1, characterized in that: In S1, establishing the evaluation coefficients includes the following steps: The collected parameters include user frequency of use of the touch screen all-in-one machine, click-through rate in hotspot areas, churn rate due to pain points, and operation time. These parameters are used to establish an evaluation coefficient for the user's evaluation of the touch screen all-in-one machine's effectiveness. The expression is as follows: In the formula, dk i My rating is a coefficient used by users to evaluate the effectiveness of using the touch screen all-in-one machine. j Pain point loss level value, lk j Based on the frequency of user use of touch screen all-in-one machines, ty z For click-through rates in hot areas, su k The operation time is represented by a1, a2, a3, and a4, which are the weighting factor coefficients of the pain point loss level, the user's frequency of use of the touch screen all-in-one machine, the click rate of hot spots, and the operation time, respectively, and a2>a3>a1>a4>0.

3. The data-driven touch screen all-in-one machine management method based on artificial intelligence according to claim 2, comprising the following steps: S1.1: The expression for calculating the pain point loss level is: my j =100log 10 (m1 / m2), where m1 is the number of users experiencing pain points and m2 is the total number of users. The total number of users refers to the total number of users who use the touch all-in-one machine within a single day. S1.2: The formula for calculating the frequency of user use of the touch screen all-in-one machine is: lk j =yg i / (yh i +1), ygi is the total number of times the touch screen all-in-one machine was used within a single day, yh i This represents the total number of users of the touch screen all-in-one machine; S1.3: The logic for obtaining the click-through rate of hot spots is as follows: by setting hot spots on the touch screen all-in-one machine, the ratio of the number of clicks on the hot spots to the total number of times the hot spots are displayed or appear on the touch screen all-in-one machine is the click-through rate of the hot spots. S1.4: The logic for obtaining the user's operation time on the touch screen all-in-one machine is to record the specific time from when the user initiates the operation to when the application interface opens and until the application interface is closed.

4. The data-driven touch screen all-in-one machine management method based on artificial intelligence according to claim 1, characterized in that: In S2, the comparison between the user's evaluation coefficient of the touch screen all-in-one machine's performance and the gradient threshold includes the following steps: S2.1 After obtaining the evaluation coefficients of the user's feedback on the use of the touch screen all-in-one machine, the gradient threshold includes the first threshold yu. m Second threshold yu n And the first threshold yu m <Second threshold yu n The evaluation coefficients are compared with the first threshold yu. m Second threshold yu n Compare; S2.2 If the evaluation coefficient ≤ the first threshold yu m The system outputs a level one warning signal; S2.3 When the first threshold yu m <Evaluation coefficient<Second threshold yu n The system outputs a level-two warning signal; S2.4 If the evaluation coefficient ≥ the second threshold yu n The system does not issue a warning signal.

5. The data-driven touch screen all-in-one machine management method based on artificial intelligence according to claim 1, characterized in that: In S4, the quality coefficient of the touch screen all-in-one machine is established, including the following steps: During the monitoring process, multiple performance parameters of each touch screen all-in-one machine were collected. These parameters included the interference level of the wireless network signal, the lag level of the touch screen all-in-one machine, and the sampling rate of the touch screen. A quality coefficient was established using a formula based on these parameters, expressed as follows: In the formula, ct i For the quality coefficient of the touch screen all-in-one machine, LG z This is a lag level value for the touch screen all-in-one machine. z This represents the interference level of the wireless network signal, mj x β1, β2, and β3 are the sampling rate of the touch screen, the interference value of the wireless network signal, and the lag value of the touch screen all-in-one machine, respectively, with β1>β2>β3>0.

6. The data-driven touch screen all-in-one machine management method based on artificial intelligence according to claim 1, characterized in that: In S5, the comparison of the quality coefficient with the standard threshold includes the following steps: After obtaining the quality score of a touch screen all-in-one machine with a mediocre user experience, the quality score is compared with a standard threshold: If the quality coefficient is greater than the standard threshold, the system will issue a regional survey signal; If the quality coefficient is less than or equal to the standard threshold, the system will not issue a regional survey signal.

7. A data-driven touch screen all-in-one machine management system based on artificial intelligence, used to implement any one of the management methods in claims 1-6, characterized in that: It includes a data acquisition module, a comparison module, an early warning module, a monitoring module, a processing module, and a management module; The data acquisition module collects multiple parameters of the user's use of the touch screen all-in-one machine and establishes evaluation coefficients through formulas. The comparison module compares the evaluation coefficients with the gradient threshold. The early warning module issues early warning information based on the comparison results. Considering that the performance of the touch screen all-in-one machine itself and the area where the touch screen all-in-one machine is located will also affect the user's experience, the monitoring module obtains the quality coefficient of the touch screen all-in-one machine in real time. The processing module compares the quality coefficient with the standard threshold. The management module strengthens the management of the touch screen all-in-one machine based on the comparison results.

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