A touch interference jump point self-check reporting method and system, and an electronic device

Abstract

This application relates to the field of communication technology and discloses a method, system, and electronic device for self-testing and reporting touch interference jump points. The method includes: real-time monitoring of touch events, obtaining the coordinate information of touch points, and determining whether the touch points are located within the coordinate range of non-operating areas; real-time acquisition of electromagnetic interference detection data by calling the underlying interface of the touch chip, and calculating the electromagnetic interference intensity index within a set time window; if, within the set time window, the abnormal touch frequency in the non-operating area exceeds a first preset threshold, and the electromagnetic interference intensity index exceeds a second preset threshold, then an interference jump point event is determined to have occurred in the non-operating area; based on the electromagnetic interference intensity index and the abnormal touch frequency, the interference jump point event is classified into levels, an interference report is generated, and reported to a cloud server. This application establishes a correspondence between touch behavior and electromagnetic interference signal strength to achieve graded judgment and health trend analysis of interference events.

Description

Technical Field

[0001] This application relates to the field of communication technology, and more specifically, to a method, system, and electronic device for self-testing and reporting touch interference jump points. Background Technology

[0002] With the rapid development of mobile payment and smart retail, POS devices equipped with capacitive touchscreens are widely used. Capacitive touch technology is widely adopted due to its advantages such as high responsiveness, support for multi-touch, and intuitive user experience. However, the working principle of capacitive touchscreens is to locate the touch point by detecting minute changes in capacitance caused by human touch. This makes its signal very fragile and easily affected by various interference sources in the environment, such as broadband electromagnetic radiation from dense electrical equipment in the POS area; electrostatic discharge accumulated by the human body or equipment; conducted noise introduced by the power adapter; and capacitance baseline drift caused by drastic changes in ambient temperature and humidity. These interference sources, mixed with the touch sensor signal, cause disordered jumps in the touch point, a phenomenon known as "jumping points."

[0003] In high-precision, high-reliability transaction scenarios such as point-of-sale (POS), point skipping not only degrades the user experience but can also lead to serious problems such as accidental triggering of interface elements, incorrect amount input, and incorrect order submission, directly affecting transaction security and operational efficiency. The consequences are particularly pronounced in unattended scenarios. Summary of the Invention

[0004] To address the aforementioned technical issues, this application discloses a touch interference jump point self-testing and reporting method, system, and electronic device. By monitoring and judging touch events in non-operational areas at the software level, and introducing an electromagnetic interference detection mechanism, a correspondence between touch behavior and electromagnetic interference signal strength is established, thereby realizing the graded judgment of interference events and health trend analysis.

[0005] Specifically, the technical solution of this application is as follows: Firstly, this application discloses a method for self-testing and reporting touch interference jump points, comprising the following steps: Real-time monitoring of touch events, acquisition of the coordinate information of the touch point, and determination of whether the touch point is located within the coordinate range of the non-operation area; Electromagnetic interference detection data is collected in real time by calling the underlying interface of the touch chip, and the electromagnetic interference intensity index within a set time window is calculated. If, within the set time window, the frequency of abnormal touches in the non-operation area exceeds a first preset threshold and the electromagnetic interference intensity index exceeds a second preset threshold, then it is determined that an interference jump event has occurred in the non-operation area. Based on the electromagnetic interference intensity index and the abnormal touch frequency, the interference jump point events are classified into levels, interference reports are generated and reported to the cloud server.

[0006] In some embodiments, the touch interference jump point self-test reporting method further includes: pre-defining the coordinate range of the operating area and the non-operating area of ​​the touch screen interface at the system layer; The operating area is the coordinate range of a predefined button, slider, or input box; the non-operating area is all areas of the touchscreen interface other than the operating area.

[0007] In some implementations, the method of collecting electromagnetic interference detection data in real time by calling the underlying interface of the touch chip and calculating the electromagnetic interference intensity index within a set time window specifically includes: The touch chip driver layer registers are called through the underlying interface; the electromagnetic interference detection data is collected in real time; the electromagnetic interference detection data includes one or more of the following: capacitor signal noise power, capacitance change amplitude, interference count, and voltage noise threshold. Within the set time window, the preprocessed electromagnetic interference detection data is statistically analyzed to obtain the electromagnetic interference intensity index.

[0008] In some embodiments, the touch interference jump point self-test reporting method further includes: treating the touch event in the non-operation area as an abnormal touch event; Within the set time window, abnormal touch events are counted and timestamped; the ratio of the accumulated abnormal touch events to the duration of the set time window is calculated to obtain the touch abnormality frequency.

[0009] In some embodiments, the touch interference jump point self-test reporting method further includes: The coordinate sequence of the touch points within the set time window is statistically analyzed to obtain the movement trajectory characteristics. Based on the movement trajectory characteristics, the touch anomaly frequency, and the electromagnetic interference intensity index, the interference jump event is determined.

[0010] In some implementations, the determination of the interference jump event based on the movement trajectory characteristics, the abnormal touch frequency, and the electromagnetic interference intensity index specifically includes: If the movement trajectory features meet the preset random scatter distribution or disordered jump conditions, and the touch abnormality frequency exceeds the first preset threshold, and the electromagnetic interference intensity index exceeds the second preset threshold, then it is determined that an interference jump event has occurred in the non-operation area. The movement trajectory features include the scattered distribution features of the touch points and / or the statistical features of jump distances.

[0011] In other embodiments, the step of classifying the interference jump event into levels based on the electromagnetic interference intensity index and the abnormal touch frequency, generating an interference report, and uploading it to the cloud server specifically includes: Based on the electromagnetic interference intensity index and the touch abnormality frequency, the interference jump point event is classified into at least three levels: mild, moderate and severe. Simultaneously, record and obtain relevant information about the interference jump event, including one or more of the following: device identifier, timestamp, interference duration, non-operation area touch point coordinate sequence, and electromagnetic interference intensity value; The grading results and related information are compiled to obtain the interference report, which is then uploaded to the cloud server.

[0012] In some embodiments, the touch interference jump point self-test reporting method further includes: the cloud server is adapted to receive interference reports from multiple devices, calculate the average electromagnetic interference level and jump point trend of each device in its operating cycle by utilizing the distribution of interference jump point event levels of each device, construct a device health model based on the average electromagnetic interference level and the jump point trend, the device health model is adapted to generate dynamically adjusted interference judgment thresholds for each device, the interference judgment thresholds include a first preset threshold and a second preset threshold; The method further includes: Receive the interference determination threshold generated by the cloud server; The first preset threshold and the second preset threshold set on the device are updated according to the interference determination threshold.

[0013] Secondly, this application also discloses a touch interference jump point self-test reporting system, the system being used to implement the touch interference jump point self-test reporting method described in any of the above embodiments, including: The touch monitoring module is used to monitor touch events in real time, obtain the coordinate information of the touch point, and determine whether the touch point is located within the coordinate range of the non-operation area. The electromagnetic detection module is used to collect electromagnetic interference detection data in real time by calling the underlying interface of the touch chip, and to calculate the electromagnetic interference intensity index within a set time window. An interference determination module is used to determine that an interference jump event has occurred in the non-operation area if, within the set time window, the frequency of abnormal touches in the non-operation area exceeds a first preset threshold and the electromagnetic interference intensity index exceeds a second preset threshold. The hierarchical processing module is used to classify the interference jump point event into levels based on the electromagnetic interference intensity index and the touch abnormality frequency. The data reporting module generates an interference report and uploads it to the cloud server.

[0014] In some embodiments, the touch interference jump point self-test reporting system further includes: a region definition module, used to predefine the coordinate range of the operating area and the non-operating area of ​​the touch screen interface at the system layer; The operation area is a predefined coordinate range of a button, slider, or input box; the non-operation area is all areas of the touchscreen interface other than the operation area.

[0015] Thirdly, this application also discloses an electronic terminal device, which includes the touch interference jump point self-test reporting system described in any of the above embodiments.

[0016] Compared with the prior art, this application has at least one of the following beneficial effects: 1. The core advantage of this application lies in realizing a paradigm shift from passive anti-interference to proactive intelligent health management. This application introduces a dual-source data fusion judgment mechanism of "touch behavior-electromagnetic signal," constructing a highly reliable interference identification and tracing capability at the software level. It not only relies on the spatial and frequency characteristics of the touch point but also combines direct electromagnetic interference intensity indicators, thereby significantly improving the accuracy of interference jump point event judgment and the ability to resist false alarms in complex field environments. This solves the problem of missed judgments or false judgments caused by existing technologies relying on a single data source.

[0017] 2. This application establishes a structured hierarchical model based on multidimensional quantitative indicators, which classifies interference events into different levels such as mild, moderate and severe, and realizes a refined assessment of abnormal equipment status, providing a clear basis for differentiated response and priority handling for backend operation and maintenance.

[0018] 3. This application constructs a complete health management system that integrates terminal perception, cloud analysis, and closed-loop optimization. Through continuously reported structured interference data, it builds a device health trend model in the cloud, realizes long-term interference situation analysis, potential risk prediction, and adaptive optimization of judgment parameters, and ultimately upgrades the device operation and maintenance mode from reactive post-event maintenance to pre-event early warning and predictive maintenance, thereby improving the operational reliability, service continuity, and intelligent level of the entire life cycle management of the device. Attached Figure Description

[0019] The preferred embodiments will now be described in a clear and easy-to-understand manner, in conjunction with the accompanying drawings, to further explain the above-mentioned characteristics, technical features, advantages, and implementation methods of this application.

[0020] Figure 1 This is a flowchart illustrating the steps of an embodiment of a touch interference jump point self-test reporting method according to this application; Figure 2 This is a flowchart illustrating the steps of another embodiment of the touch interference jump point self-test reporting method of this application; Figure 3 This is a flowchart illustrating a sub-step of step S4 in another embodiment of the touch interference jump point self-test reporting method of this application; Figure 4 This is a structural block diagram of an embodiment of a touch interference jump point self-test reporting system of this application. Detailed Implementation

[0021] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0022] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or sets.

[0023] To keep the drawings concise, each figure only schematically shows the parts relevant to the invention, and these do not represent the actual structure of the product. Furthermore, to facilitate understanding, in some figures, only one of components with the same structure or function is schematically depicted, or only one is labeled. In this document, "one" not only means "only one," but can also mean "more than one."

[0024] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] In this document, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0026] Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the specific implementation methods of this application will be described below with reference to the accompanying drawings. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without creative effort.

[0028] In the prior art, in order to deal with the jumping point phenomenon mentioned in the background art, the most mainstream technology mainly relies on the anti-interference design at the hardware level of the touch chip to achieve automatic frequency hopping. Its basic principle is: the controller continuously monitors the signal noise level of the current working frequency band. When the noise intensity is detected to exceed a certain threshold, it automatically and seamlessly switches to another preset "clean" frequency band to continue working, thereby avoiding continuous interference at specific frequency points.

[0029] However, existing passive defense systems based on hardware frequency hopping have significant technical blind spots and management shortcomings. First, the system lacks the ability to perceive and record data on interference events themselves. The frequency hopping process is completed automatically at the chip level, and the device operating system and upper-layer applications typically cannot know whether interference has occurred, its frequency, its duration, or which frequency band it has switched to. This approach results in the complete loss of valuable interference data during device operation, making it impossible for device manufacturers and operators to quantitatively assess the electromagnetic environment quality of specific locations or to statistically analyze the interference pressure experienced by the device throughout its lifecycle. This hinders targeted hardware improvements, environmental optimization, or preventative maintenance. Second, the system lacks an active identification and early warning mechanism for "interference having caused substantial impact." Hardware frequency hopping aims to maintain uninterrupted touch functionality, but strong or unique interference can still cause frequency hopping to fail to completely suppress hopping points, resulting in the system continuously generating erroneous touch signals. Existing technology lacks the ability to intelligently identify these abnormal touch behaviors and correlate them with interference sources at the system software level. Therefore, even if the equipment remains in a state of latent failure for an extended period (such as intermittent jumps), it will not generate any logs or alarms until it triggers user complaints or transaction errors, missing the opportunity for early intervention. This makes the reliability and maintainability of the equipment highly dependent on proactive user feedback, resulting in high maintenance costs and poor risk control for large-scale deployments of unmanned equipment.

[0030] Existing technologies primarily rely on hardware methods (such as automatic frequency hopping and signal filtering) to passively resist interference at the underlying level, without identifying or reporting the interference phenomenon itself. The system cannot proactively determine whether touch point jumps are caused by electromagnetic interference, static electricity, or power adapter issues, nor does it generate records or alarms after an anomaly occurs. Consequently, the industry urgently needs a software solution capable of proactively sensing, quantitatively analyzing, intelligently warning, and supporting closed-loop management at the system level to compensate for the shortcomings of hardware solutions and improve the overall intelligent operation and maintenance level and long-term operational reliability of equipment. This application provides a touch interference jump self-checking and reporting method, system, and electronic device that not only monitors and judges touch events in non-operating areas at the software level but also introduces an electromagnetic interference detection mechanism to establish a correspondence between touch behavior and electromagnetic interference signal strength, enabling graded judgment of interference events and health trend analysis. This upgrades the system from simple "anomaly identification" to "interference level assessment and equipment health management."

[0031] Reference manual attached Figure 1 As shown, an embodiment of the touch interference jump point self-test reporting method of this application specifically includes the following steps: S1 monitors touch events in real time, obtains the coordinate information of the touch point, and determines whether the touch point is located within the coordinate range of the non-operation area.

[0032] This application relies on a touch chip to acquire the exact screen coordinates of each touch event in real time. Optionally, when a human finger approaches or touches the screen, it changes the electric field of the local sensor, causing a change in capacitance. The touch chip captures this change through its internal analog front-end and analog-to-digital converter, and runs a specific positioning algorithm via its built-in digital signal processor to accurately calculate the coordinate information of the touch point.

[0033] Subsequently, the touch chip quickly compares the current touch coordinates with the pre-loaded set of coordinates for the "non-operational area" in memory. If the coordinates fall within any range defined by the set, they are marked as abnormal touch events and counted and recorded.

[0034] In some optional implementations, the recording of touch events also includes categories such as: press (ACTION_DOWN), move (ACTION_MOVE), and release (ACTION_UP).

[0035] S2 collects electromagnetic interference detection data in real time by calling the underlying interface of the touch chip, and calculates the electromagnetic interference intensity index within a set time window.

[0036] In some implementations, for each touch event, it is determined whether its coordinates are located in a non-operational area. If so, the event is recorded in a temporary buffer, and the non-operational area touch counter is updated. Simultaneously, the event timestamp, coordinate information, and the current electromagnetic interference level (EMI_level) are recorded.

[0037] Specifically, through system calls or a dedicated hardware abstraction layer interface, the values ​​or status flags of registers related to electromagnetic noise sensing within the touch controller chip are periodically read. After preprocessing operations such as sampling, filtering, and normalization, this raw data is statistically analyzed within a preset time window to determine the electromagnetic interference intensity index EMI_level, which serves as the basis for classifying and judging the level of interference jump events. Optionally, the electromagnetic interference intensity index may include the root mean square value or peak hold value of the above raw data, etc., which is not limited in this application.

[0038] S3, within a set time window, if the frequency of abnormal touches in the non-operation area exceeds the first preset threshold and the electromagnetic interference intensity index exceeds the second preset threshold, then it is determined that an interference jump event has occurred in the non-operation area.

[0039] Specifically, the system counts the cumulative number of abnormal touches in non-operational areas within the same time window to calculate the touch anomaly frequency. The monitoring logic retrieves statistical data within a time-triggered judgment period: if the calculated touch anomaly frequency exceeds a preset frequency threshold (first preset threshold), and the average or peak value of the electromagnetic interference intensity index within the same period exceeds a preset intensity threshold (second preset threshold), then an interference jump event judgment is triggered.

[0040] For example, the time window is set to 1 hour, and the first preset threshold is 100 times / hour.

[0041] S4 classifies interference jump events into levels based on electromagnetic interference intensity indicators and abnormal touch frequency, generates interference reports, and uploads them to the cloud server.

[0042] Specifically, once an interference trigger event is identified, the system immediately determines its severity level based on the specific values ​​of the electromagnetic interference intensity index and the quantification level of the abnormal touch frequency in this event, referring to a pre-set classification rule mapping table. Finally, the system encapsulates a complete data packet, including the device identifier, event timestamp, determined interference level, touch coordinate samples, statistical frequency, and electromagnetic interference index value, into a structured report, and uploads it to the designated cloud server interface through the device's network connection module, completing the entire process of sensing, diagnosing, and reporting this interference event.

[0043] This application can proactively identify touch jump phenomena caused by environmental electromagnetic interference, static electricity, adapter interference, etc., and record, classify and report the interference, solving the problems of lack of interference quantification, classification statistics and proactive reporting in the prior art.

[0044] Based on the above embodiments, this application discloses another embodiment of a touch interference jump point self-test reporting method. Before step S1, please refer to the appendix to the specification. Figure 2 As shown, it also includes step S01, which predefines the coordinate range of the operating area and non-operating area of ​​the touch screen interface at the system layer.

[0045] The interactive area refers to the coordinate range of predefined buttons, sliders, or input boxes. The non-interactive area is all areas of the touchscreen interface other than the interactive area.

[0046] Specifically, during system initialization or application startup, the position and boundary information of all interactive UI components in the screen coordinate system are obtained by parsing the view layout file of the currently active interface or by directly calling the application programming interface of the user interface framework.

[0047] Based on this information, the system constructs one or more sets of logical regions in memory, which explicitly define the screen extent considered as the operation area. Subsequently, by excluding all defined operation areas from the physical or logical coordinate range of the entire screen, the system automatically derives the remaining screen area as the non-operation area. Optionally, the division of operation areas can adapt to dynamic changes in different application interface layouts without manual intervention.

[0048] This application provides another embodiment of a touch interference jump point self-test reporting method. Based on any embodiment of the above method, step S2 involves real-time acquisition of electromagnetic interference detection data by calling the underlying interface of the touch chip, and calculating the electromagnetic interference intensity index within a set time window. Specifically, it includes: S21 calls the registers of the touch chip driver layer through the low-level interface. It collects electromagnetic interference (EMI) detection data in real time. EMI detection data includes one or more of the following: capacitor signal noise power, capacitance change amplitude, interference count, and voltage noise threshold.

[0049] S22, within a set time window, statistical analysis is performed on the preprocessed electromagnetic interference detection data to obtain the electromagnetic interference intensity index.

[0050] Specifically, the system interface calls the registers or driver data at the bottom layer of the touch chip to collect capacitor signal noise power and electromagnetic interference intensity indicators, including but not limited to interference count, capacitor fluctuation amplitude, and voltage noise threshold. Within a set time window, the interference intensity index EMI_level is calculated as an auxiliary basis for judgment.

[0051] In some optional implementations, all multi-dimensional data undergoes comprehensive analysis in both the time and frequency domains within a set time window. For example, the data for each dimension may be normalized and then weighted and accumulated. Finally, using a preset linear or nonlinear fusion algorithm, these statistical characteristics are combined into a single, standardized, comprehensive quantitative value, namely the electromagnetic interference intensity index EMI_level.

[0052] Based on the above embodiments, this application provides another embodiment of the touch interference jump point self-test reporting method. Step S2 further includes: S23, treating touch events outside the operating area as abnormal touch events. Within a set time window, abnormal touch events are counted and timestamped. The ratio of the accumulated abnormal touch events to the duration of the set time window is calculated to obtain the touch abnormality frequency.

[0053] This application provides another embodiment of a touch interference jump point self-test reporting method. Based on any embodiment of the above method, step S3 is as follows: within a set time window, if the touch abnormality frequency in the non-operation area exceeds a first preset threshold and the electromagnetic interference intensity index exceeds a second preset threshold, then it is determined that an interference jump point event has occurred in the non-operation area.

[0054] Specifically, within a set time window, when the number of touch events in the non-operational area exceeds a first preset threshold, and simultaneously the detected electromagnetic interference intensity (EMI_level) exceeds a second preset threshold, it is comprehensively judged as an interference jump event. This dual judgment mechanism of "touch anomaly + electromagnetic interference signal" improves the accuracy of false alarm / missed alarm detection.

[0055] In other implementations, the determination logic can be further extended, for example, by incorporating the disordered nature of the touch point movement trajectory to improve accuracy. Optionally, step S3 may also include: S31, statistically analyze the coordinate sequence of touch points within a set time window to obtain movement trajectory characteristics, and judge the tension interference jump event based on movement trajectory characteristics, touch abnormal frequency and electromagnetic interference intensity index.

[0056] Specifically, if the movement trajectory characteristics meet the preset random scatter distribution or disordered jump conditions, and the abnormal touch frequency exceeds the first preset threshold, and the electromagnetic interference intensity index exceeds the second preset threshold, then it is determined that an interference jump event has occurred in the non-operation area.

[0057] The movement trajectory features include the scattered distribution characteristics of touch points and / or the statistical characteristics of jump distances. Specifically, the system determines whether the trajectory is abnormal by analyzing the dispersion of touch point coordinates and the jump distance between adjacent points: if the touch points are scattered and not clustered or the jump distance fluctuates drastically and greatly exceeds the normal sliding range, it is determined that the conditions of random scattered distribution or disordered jump are met.

[0058] The first preset threshold is a frequency threshold used to determine whether touch events in non-operating areas have reached an abnormally high level of activity. When the actual touch frequency exceeds this threshold, it indicates that there is abnormal behavior caused by suspected interference. The second preset threshold is an intensity threshold used to determine whether the current electromagnetic environment constitutes effective interference. When the collected electromagnetic interference index exceeds this threshold, it indicates that there is a physical interference source sufficient to affect touch stability. The above conditions together constitute the judgment mechanism. When the above conditions are met simultaneously, the system determines that an interference jump event has occurred, ensuring the accuracy and reliability of the judgment results.

[0059] In some implementations, step S3 further includes setting event classification rules and weights. Specifically, movement trajectory characteristics, abnormal touch frequency, and electromagnetic interference intensity indicators are assigned different weights, and a comprehensive score is obtained through weighted calculation or rule matching. Finally, the event level is determined based on the score range to ensure that the judgment result fully reflects the physical intensity and behavioral impact of the interference.

[0060] This application provides another embodiment of a touch interference jump point self-test reporting method, based on any of the above-described embodiments, with reference to the appendix to the specification. Figure 3 As shown, step S4 involves classifying interference jump events into different levels based on electromagnetic interference intensity indicators and abnormal touch frequencies, generating an interference report, and uploading it to the cloud server. Specifically, this includes: S41, based on the electromagnetic interference intensity index and the frequency of abnormal touch, classifies interference jump events into at least three levels: mild, moderate and severe.

[0061] The grading results are used for subsequent health trend analysis and operation and maintenance decisions.

[0062] After confirming the presence of interference, the system classifies it based on the interference intensity index and the abnormal touch frequency. In some implementations, the interference event is classified and processed according to a comprehensive index such as electromagnetic interference intensity (EMI_level) and abnormal touch frequency (F_touch). For example: Mild (Level 1 Interference): The abnormal touch frequency F_touch is an intermittent jump, and the EMI_level is below the first interference intensity threshold. At this time, the interference source may be environmental noise or transient interference, and it can recover automatically.

[0063] Moderate (Level 2 Interference): The abnormal touch frequency F_touch is moderate, and the EMI_level is between the first and second interference intensity thresholds, where the first interference intensity threshold is less than the second interference intensity threshold. In this case, the interference source may be the power supply, adapter, or nearby peripherals.

[0064] Severe (Level 3 Interference): The abnormal touch frequency F_touch is frequent, continuous, and wide-ranging, and the EMI_level is consistently higher than the second interference strength threshold. At this point, the interference source may be persistent electromagnetic pollution or a screen hardware malfunction.

[0065] After obtaining the above classification results, the classification results are written into the interference event structure for subsequent data reporting and health analysis.

[0066] S42, record and obtain relevant information about the interference jump event, including one or more of the following: device identifier, timestamp, interference duration, non-operational area touch point coordinate sequence, and electromagnetic interference intensity value.

[0067] Specifically, each interference event records information such as time, location, frequency, electromagnetic interference intensity, and classification results, forming a multi-dimensional interference data structure.

[0068] S43 compiles the classification results and related information into an interference report, and then uploads the interference report to the cloud server.

[0069] Specifically, the interference classification data is packaged into a report and proactively uploaded to the backend cloud service via the network. The backend operation and maintenance system automatically generates equipment health records based on the classification and trend analysis results, providing a basis for after-sales analysis and maintenance decisions.

[0070] In some optional implementations, when the system determines that there is an interference jump event, the generated interference report includes the following information: device ID, timestamp and interference duration, non-operational area touch point coordinate sequence, touch event frequency, electromagnetic interference intensity statistics (average, peak), and interference level (L1 / L2 / L3).

[0071] The report is uploaded to the backend cloud service via the network module, supporting HTTP / MQTT protocol transmission. Event logs are also saved locally for offline analysis and debugging.

[0072] This application provides another embodiment of a touch interference jump point self-test reporting method. Based on any embodiment of the above method, a cloud server is adapted to receive interference reports from multiple devices, calculate the average electromagnetic interference level and jump point trend of each device during its operating cycle using the distribution of interference jump point event levels of each device, and construct a device health model based on the average electromagnetic interference level and jump point trend. The device health model is adapted to generate dynamically adjusted interference judgment thresholds for each device. The interference judgment thresholds include a first preset threshold and a second preset threshold. The touch interference jump point self-test reporting method is described in the appendix to the specification. Figure 2 As shown, it also includes: step S5, receiving the interference judgment threshold generated by the cloud server, and updating the first preset threshold and the second preset threshold set on the device according to the interference judgment threshold.

[0073] Optionally, the backend cloud service performs trend analysis on the long-term reported data and builds equipment health models (such as interference frequency curves and electromagnetic interference mean change trends) to predict potential risks such as equipment aging and power interference.

[0074] In other alternative implementations, after receiving historical interference reports from multiple devices, the backend cloud service performs data aggregation analysis, including: statistically analyzing the frequency distribution of interference events at different levels; calculating the average EMI level and jump point trend of the devices over different operating cycles; and constructing a device health trend model to identify abnormal upward trends and predict potential hardware aging or power compatibility issues.

[0075] The cloud service can dynamically adjust the judgment threshold or optimization parameters sent to the terminal device based on the model output results, so as to realize closed-loop optimization and adaptive adjustment, and improve the overall robustness and adaptability of the system.

[0076] This application's embodiments, combined with electromagnetic interference detection, achieve dual determination of "interference source + touch behavior," improving the accuracy of jump point identification. Interference grading distinguishes anomalies of varying severity, facilitating strategic backend maintenance. A cloud-based health trend model upgrades interference management from passive detection to proactive prediction, significantly improving device stability and the level of intelligent maintenance.

[0077] Based on the same concept, this application also discloses a touch interference jump point self-test reporting system. The system is used to implement the steps described in any of the above method embodiments. (See attached specification.) Figure 4 As shown, specifically, one embodiment of the touch interference jump point self-test reporting system of this application includes: The touch monitoring module is used to monitor touch events in real time, obtain the coordinate information of the touch point, and determine whether the touch point is located within the coordinate range of the non-operation area.

[0078] The electromagnetic detection module is used to collect electromagnetic interference detection data in real time by calling the underlying interface of the touch chip, and to calculate the electromagnetic interference intensity index within a set time window.

[0079] The interference determination module is used to determine that an interference jump event has occurred in the non-operation area if the frequency of abnormal touches in the non-operation area exceeds a first preset threshold and the electromagnetic interference intensity index exceeds a second preset threshold within a set time window.

[0080] The hierarchical processing module is used to classify interference jump events into different levels based on electromagnetic interference intensity indicators and abnormal touch frequency.

[0081] The data reporting module is used to generate interference reports and report them to the cloud server.

[0082] Based on the above embodiments, please refer to the appendix to the specification. Figure 4 As shown, another embodiment of the touch interference jump point self-test reporting system disclosed in this application further includes: a region definition module, used to predefine the coordinate range of the operating area and non-operating area of ​​the touch screen interface at the system layer.

[0083] The operating area is the predefined coordinate range of buttons, sliders, or input boxes. The non-operating area is all areas of the touchscreen interface other than the operating area.

[0084] This application provides another embodiment of a touch interference jump point self-test reporting system. Based on any embodiment of the above system, the electromagnetic detection module is further used to call the registers of the touch chip driver layer through a low-level interface. Electromagnetic interference detection data is collected in real time. The electromagnetic interference detection data includes one or more of the following: capacitor signal noise power, capacitance change amplitude, interference count, and voltage noise threshold. Within a set time window, the preprocessed electromagnetic interference detection data is statistically analyzed to obtain an electromagnetic interference intensity index.

[0085] This application provides another embodiment of a touch interference jump point self-test reporting system. Based on any embodiment of the above system, the touch monitoring module is further used to treat touch events in non-operating areas as abnormal touch events.

[0086] The interference detection module is also used to count and timestamp abnormal touch events within a set time window. The ratio of the accumulated abnormal touch events to the duration of the set time window is calculated to obtain the touch abnormality frequency.

[0087] In other implementations, the interference determination module is also used to statistically analyze the coordinate sequence of touch points within a set time window to obtain movement trajectory characteristics, and to determine the tension interference jump event based on the movement trajectory characteristics, touch abnormality frequency and electromagnetic interference intensity index.

[0088] Specifically, if the movement trajectory characteristics meet the preset random scatter distribution or disordered jump conditions, and the abnormal touch frequency exceeds the first preset threshold, and the electromagnetic interference intensity index exceeds the second preset threshold, then it is determined that an interference jump event has occurred in the non-operation area.

[0089] Among them, the movement trajectory features include the scattered distribution features of touch points and / or the statistical features of jump distances.

[0090] This application provides another embodiment of a touch interference jump point self-test reporting system. Based on any embodiment of the above system, the hierarchical processing module is further used to classify the interference jump point event into at least three levels: mild, moderate and severe, based on the electromagnetic interference intensity index and the touch abnormal frequency.

[0091] Simultaneously, record and acquire relevant information about the interference jump event, including device identifier, timestamp, interference duration, non-operational area touch point coordinate sequence, and one or more of the electromagnetic interference intensity values.

[0092] The data reporting module is also used to compile the classification results and related information into an interference report, and then report the interference report to the cloud server.

[0093] Based on any of the above-described embodiments of the system, this application provides another embodiment of a touch interference jump point self-test reporting system, wherein the cloud server is also used to receive interference reports from multiple devices for data analysis and dynamically adjust the interference judgment threshold of each device.

[0094] Specifically, this includes: using cloud servers to statistically analyze the distribution of interference jump point event levels for each device, calculating the average electromagnetic interference level and jump point trend for each device during its operating cycle; constructing a device health trend model; and dynamically adjusting the interference judgment threshold for the devices based on the model analysis results.

[0095] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0096] Based on the same concept, this application also discloses an electronic terminal device, which includes the touch interference jump point self-test reporting system described in any of the above embodiments.

[0097] Optionally, the electronic terminal device is an intelligent terminal device that integrates at least a touch-screen human-computer interaction interface. Optionally, the touch-screen human-computer interaction interface relies on capacitive touch technology to achieve user interaction. Through the interference jump point self-testing and reporting method disclosed in this application, interference perception, hierarchical reporting, and health management at the system level of the electronic terminal device can be realized.

[0098] In other embodiments, such devices operate in commercial retail or service environments, including but not limited to: self-service checkout machines, handheld POS terminals, countertop smart POS machines, vending machines, self-service ordering machines, self-service ticket machines, self-service inquiry and guidance machines, and other self-service terminals used in supermarkets, convenience stores, and restaurants.

[0099] The touch interference jump point self-test reporting method, system and electronic device of this application have the same technical concept, and the technical details of the embodiments of the three are applicable to each other. In order to reduce repetition, they will not be described again here.

[0100] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of program modules is merely an example. In practical applications, the above functions can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program units or modules to complete all or part of the functions described above. The program modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software program unit. Furthermore, the specific names of the program modules are only for easy differentiation and are not intended to limit the scope of protection of this application.

[0101] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for reporting touch interference jump point self-checking, characterized in that, Includes the following steps: Real-time monitoring of touch events, acquisition of the coordinate information of the touch point, and determination of whether the touch point is located within the coordinate range of the non-operation area; Electromagnetic interference detection data is collected in real time by calling the underlying interface of the touch chip, and the electromagnetic interference intensity index within a set time window is calculated. If, within the set time window, the frequency of abnormal touches in the non-operation area exceeds a first preset threshold and the electromagnetic interference intensity index exceeds a second preset threshold, then it is determined that an interference jump event has occurred in the non-operation area. Based on the electromagnetic interference intensity index and the abnormal touch frequency, the interference jump point events are classified into levels, interference reports are generated and reported to the cloud server.

2. The method of claim 1, wherein the method further comprises: Also includes: The coordinate range of the operating area and the non-operating area of ​​the touch screen interface is predefined at the system layer; The operating area is the coordinate range of a predefined button, slider, or input box; the non-operating area is all areas of the touchscreen interface other than the operating area.

3. The touch interference jump point self-test reporting method as described in claim 1, characterized in that, The method of collecting electromagnetic interference detection data in real time by calling the underlying interface of the touch chip and calculating the electromagnetic interference intensity index within a set time window specifically includes: The touch chip driver layer registers are called through the underlying interface; the electromagnetic interference detection data is collected in real time; the electromagnetic interference detection data includes one or more of the following: capacitor signal noise power, capacitance change amplitude, interference count, and voltage noise threshold. Within the set time window, the preprocessed electromagnetic interference detection data is statistically analyzed to obtain the electromagnetic interference intensity index.

4. The touch interference jump point self-test reporting method as described in claim 1, characterized in that, Also includes: The touch event within the non-operational area is treated as an abnormal touch event; Within the set time window, count the abnormal touch events and timestamp them; The ratio of the accumulated abnormal touch events to the duration of the set time window is calculated to obtain the touch abnormality frequency.

5. A touch interference jump point self-test reporting method as described in claim 1 or 4, characterized in that, Also includes: The coordinate sequence of the touch points within the set time window is statistically analyzed to obtain the movement trajectory characteristics. Based on the movement trajectory characteristics, the touch anomaly frequency, and the electromagnetic interference intensity index, the interference jump event is determined.

6. The touch interference jump point self-test reporting method as described in claim 5, characterized in that, The determination of the interference jump event based on the movement trajectory characteristics, the abnormal touch frequency, and the electromagnetic interference intensity index specifically includes: If the movement trajectory features meet the preset random scatter distribution or disordered jump conditions, and the touch abnormality frequency exceeds the first preset threshold, and the electromagnetic interference intensity index exceeds the second preset threshold, then it is determined that an interference jump event has occurred in the non-operation area. The movement trajectory features include the scattered distribution features of the touch points and / or the statistical features of jump distances.

7. The touch interference jump point self-test reporting method as described in claim 1, characterized in that, The process of classifying interference jump events into levels based on the electromagnetic interference intensity index and the abnormal touch frequency, generating an interference report, and uploading it to the cloud server specifically includes: Based on the electromagnetic interference intensity index and the touch abnormality frequency, the interference jump point event is classified into at least three levels: mild, moderate and severe. Simultaneously, record and obtain relevant information about the interference jump event, including one or more of the following: device identifier, timestamp, interference duration, non-operation area touch point coordinate sequence, and electromagnetic interference intensity value; The grading results and related information are compiled to obtain the interference report, which is then uploaded to the cloud server.

8. The touch interference jump point self-test reporting method as described in claim 1, characterized in that, The cloud server is adapted to receive interference reports from multiple devices, calculate the average electromagnetic interference level and jump point trend of each device during its operating cycle by utilizing the distribution of interference jump point event levels of each device, construct a device health model based on the average electromagnetic interference level and the jump point trend, and the device health model is adapted to generate dynamically adjusted interference judgment thresholds for each device, the interference judgment thresholds including the first preset threshold and the second preset threshold. The method further includes: Receive the interference determination threshold generated by the cloud server; The first preset threshold and the second preset threshold set on the device are updated according to the interference determination threshold.

9. A touch interference jump point self-test reporting system, characterized in that, The system is used to implement the touch interference jump point self-test reporting method according to any one of claims 1-8, including: The touch monitoring module is used to monitor touch events in real time, obtain the coordinate information of the touch point, and determine whether the touch point is located within the coordinate range of the non-operation area. The electromagnetic detection module is used to collect electromagnetic interference detection data in real time by calling the underlying interface of the touch chip, and to calculate the electromagnetic interference intensity index within a set time window. An interference determination module is used to determine that an interference jump event has occurred in the non-operation area if, within the set time window, the frequency of abnormal touches in the non-operation area exceeds a first preset threshold and the electromagnetic interference intensity index exceeds a second preset threshold. The hierarchical processing module is used to classify the interference jump point event into levels based on the electromagnetic interference intensity index and the touch abnormality frequency. The data reporting module is used to generate interference reports and report them to the cloud server.

10. An electronic terminal device, characterized in that, The electronic terminal device includes the touch interference jump point self-test reporting system as described in claim 9.

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