A method, device, equipment and medium for cooperative response of a power self-service terminal

Abstract

The application discloses a power self-service terminal cooperative response method and device, equipment and medium, and relates to the technical field of power. The method comprises the following steps: acquiring the equipment health degree level and the user operation difficulty level of the power self-service terminal; matching the corresponding scheduling strategy from a preset joint evaluation matrix according to the equipment health degree level and the user operation difficulty level, wherein the joint evaluation matrix comprises the mapping relationship among the equipment health degree level, the user operation difficulty level and the scheduling strategy; and performing a cooperative response operation according to the scheduling strategy. The method can accurately realize the cooperative linkage of equipment state perception and user behavior perception.

Description

Technical Field

[0001] This application relates to the field of power technology, and in particular to a collaborative response method, apparatus, equipment and medium for a power self-service terminal. Background Technology

[0002] With the deepening of digital transformation in the power industry, self-service terminals (wall-mounted e-cabinets) have been deployed on a large scale in multiple service outlets, providing users with comprehensive services such as electricity bill payment and bill inquiry around the clock. This effectively makes up for the limited service hours of traditional business halls and has become the carrier of the last mile of power services.

[0003] In terms of terminal operation and maintenance management, existing technologies mainly focus on equipment status monitoring and fault alarms. Existing patents have proposed solutions such as fault prediction methods based on machine learning and paper consumption prediction methods based on multi-sensor fusion. Regarding user interaction experience, existing patents involve technologies such as self-service terminal interaction methods based on voice recognition and interactive user terminal management methods based on spatiotemporal graph structures. However, these two types of technical solutions have evolved independently, resulting in data not being shared between the equipment operation and maintenance system and the user interaction system, and the systems remaining isolated from each other.

[0004] However, existing technical solutions cannot accurately achieve coordinated linkage between device status perception and user behavior perception. Summary of the Invention

[0005] This application provides a collaborative response method, device, equipment, and medium for a power self-service terminal, which can accurately realize the collaborative linkage between equipment status perception and user behavior perception.

[0006] To achieve the above objectives, this application adopts the following technical solution: Firstly, this application provides a collaborative response method for a power self-service terminal, comprising: Obtain the device health level and user operation difficulty level of the power self-service terminal; Based on the device health level and the user operation difficulty level, a corresponding scheduling strategy is matched from a preset joint evaluation matrix. The joint evaluation matrix contains the mapping relationship between the device health level, the user operation difficulty level and the scheduling strategy. According to the scheduling strategy, perform coordinated response operations.

[0007] Optionally, obtaining the device health level of the power self-service terminal includes: Collect various device status parameters of the power self-service terminal; Based on the various device status parameters, calculate the current health score for each dimension; Based on the current health score of each dimension and the corresponding dynamic weight coefficient, calculate the overall health score of the device; The health level of the device is determined based on the score range of the overall health score.

[0008] Optionally, the user operation difficulty level is obtained in the following way: Collect user behavior characteristics on the power self-service terminal; Based on the operational behavior characteristics, identify the type of operational difficulty the user faces; The user's operational difficulty level is determined based on the operational difficulty type, wherein the operational difficulty level includes normal, mild, and difficult.

[0009] Optionally, the step of matching a corresponding scheduling strategy from a preset joint evaluation matrix based on the device health level and the user operation difficulty level includes: If the device health level is excellent or good and the user operation difficulty level is normal, then the collaborative mode is matched. If the device health level is excellent or good and the user operation difficulty level is mild or severe, then the operation and maintenance response mode is matched. If the device health level is warning or severe and the user operation difficulty level is normal, then a friendly downgrade mode is matched. If the device health level is warning or severe and the user operation difficulty level is mild or difficult, then the human-machine linkage emergency mode is matched.

[0010] Optionally, performing the coordinated response operation according to the scheduling strategy includes: When the scheduling strategy is in operation and maintenance response mode, operation guidance will pop up through the interactive interface of the power self-service terminal, and when the user's operation difficulty level is "difficult" and the difficult state continues to exceed the time threshold, a collaborative work order will be pushed to the cloud operation and maintenance platform. When the scheduling strategy is in friendly degradation mode, the device status is abnormal at the service entry point in the service selection interface of the power self-service terminal, and the user is guided to a nearby normal power self-service terminal. When the scheduling strategy is in the human-machine collaborative emergency mode, a collaborative work order is pushed to the cloud operation and maintenance platform and the power self-service terminal is switched to the downgraded acceptance mode.

[0011] Optionally, the method further includes: When the device health level is warning or severe, a self-healing strategy is executed according to the fault type: If the fault type is a communication interruption or module stagnation, the faulty module will be automatically restarted when the power self-service terminal is in an idle state. If the fault type is excessive network packet loss, the data to be uploaded will be temporarily stored through asynchronous local caching. After the network is restored, the temporarily stored data will be uploaded to the cloud in batches. If the fault type is that the main control module is offline, the main control system of the power self-service terminal will be automatically restarted after the current user session ends safely.

[0012] Optionally, the adjustment method for the dynamic weighting coefficient includes: Obtain fault frequency data for each dimension within a historical time period; Based on the failure frequency data of each dimension, determine the impact coefficient of each dimension on user experience; The dynamic weight coefficients are periodically updated based on the influence coefficients of each dimension.

[0013] Secondly, this application provides a collaborative response device for a power self-service terminal, comprising: The acquisition module is used to acquire the device health level and user operation difficulty level of the power self-service terminal. The processing module is used to match a corresponding scheduling strategy from a preset joint evaluation matrix based on the device health level and the user operation difficulty level. The joint evaluation matrix contains the mapping relationship between the device health level, the user operation difficulty level and the scheduling strategy. The execution module is used to perform coordinated response operations according to the scheduling strategy.

[0014] Thirdly, this application provides a computing device, including a memory and a processor; The memory stores one or more computer programs, the one or more computer programs including instructions; when the instructions are executed by the processor, the computing device performs the method as described in any one of the first aspects.

[0015] Fourthly, this application provides a computer-readable storage medium for storing a computer program for performing the method as described in any one of the first aspects.

[0016] As can be seen from the above technical solution, this application has at least the following beneficial effects: This application achieves cross-domain fusion of device status perception and user behavior perception by simultaneously acquiring device health level and user operation difficulty level, and matching corresponding scheduling strategies based on a joint evaluation matrix. This breaks the isolation between the device operation and maintenance system and the user interaction system in existing technologies. When the device health level is excellent or good and the user is in a mild or difficult situation, the system displays operation guidance on the interactive interface and decides whether to push a collaborative work order to the cloud operation and maintenance platform based on the duration of the difficulty. This allows operation and maintenance personnel to know about potential equipment problems before the user reports a problem, shortening the fault discovery time. When the device health level is warning or severe and the user's operation is normal, the system prompts an abnormal status at the business entry point and guides the user to a nearby normal terminal, avoiding the time wasted and experience degradation caused by repeated attempts to operate on abnormal devices. When the device health level is warning or severe and the user is in a mild or difficult situation, the system simultaneously pushes a collaborative work order to the cloud operation and maintenance platform and switches the terminal to a downgraded acceptance mode, so that fault handling and user business acceptance are carried out simultaneously. In addition, when the device health level is warning or severe, the system automatically performs self-healing operations such as communication interruption restart, network packet loss cache upload, or main control offline safe restart according to the fault type. During the self-healing process, the system ensures the safe submission of current user session data, avoiding the problem of user transaction interruption caused by completely closing the interaction entry during self-healing in traditional solutions.

[0017] It should be understood that the descriptions of technical features, technical solutions, beneficial effects, or similar language in this application do not imply that all features and advantages can be achieved in any single embodiment. Rather, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution, or beneficial effect is included in at least one embodiment. Therefore, the descriptions of technical features, technical solutions, or beneficial effects in this specification do not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions, and beneficial effects described in this embodiment can be combined in any suitable manner. Those skilled in the art will understand that embodiments can be implemented without one or more specific technical features, technical solutions, or beneficial effects of a particular embodiment. In other embodiments, additional technical features and beneficial effects may be identified in specific embodiments that do not embody all embodiments. Attached Figure Description

[0018] Figure 1 A flowchart illustrating a collaborative response method for a power self-service terminal provided in this application embodiment; Figure 2 A schematic diagram of a collaborative response device for a power self-service terminal provided in an embodiment of this application; Figure 3 This is a schematic diagram of a computing device provided in an embodiment of this application. Detailed Implementation

[0019] The terms "first," "second," and "third," etc., used in this application specification and accompanying drawings are used to distinguish different objects, not to limit a specific order.

[0020] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0021] To ensure clarity and conciseness in the description of the following embodiments, a brief introduction to the related technologies is given first: In existing power self-service terminals, the equipment operation and maintenance management system and the user interaction system are independent and do not share data, resulting in a lack of coordinated action between equipment status perception and user behavior perception. When equipment malfunctions, the interface neither detects the malfunction nor dynamically adjusts the service navigation path, often leaving users frustrated by repeated operational failures. Similarly, when users encounter difficulties, the operation and maintenance system cannot detect operational anomalies in real time, leading to delayed fault detection and response. The root cause of this problem lies in the fact that existing technical solutions evolve equipment-side operation and maintenance management and user-side interactive experience as two independent technical paths, lacking the technical means to cross-domain integrate and analyze equipment health status and user operational behavior. Consequently, equipment malfunction information cannot be transformed into user-side behavioral perception, and user operational difficulties cannot trigger collaborative handling on the operation and maintenance side. There is no two-way information channel for linkage between the two.

[0022] Therefore, the technical problem to be solved by this application is how to integrate the multi-dimensional status perception of the power self-service terminal with the perception of user operation behavior across domains, and establish a two-way information linkage between the device side and the user side, so as to achieve a coordinated response based on the health status of the device and the difficulty of user operation.

[0023] In view of this, embodiments of this application provide a collaborative response method for a power self-service terminal, which can be executed by a processing device. The processing device can be a terminal or a server. Terminals include, but are not limited to, smartphones, tablets, laptops, personal digital assistants, or smart wearable devices. Servers can be cloud servers, such as central servers in a central cloud computing cluster or edge servers in an edge cloud computing cluster. Alternatively, servers can be located in a local data center. A local data center refers to a data center directly controlled by the user.

[0024] This application addresses the current technical situation where the equipment operation and maintenance system and the user interaction system in existing power self-service terminals are independent and unable to coordinate and link. It proposes a collaborative response method that integrates equipment health perception and user operation difficulty perception across domains. This application constructs a joint evaluation matrix that includes equipment health level and user operation difficulty level, mapping equipment-side status information and user-side behavioral information to the same decision space. Differentiated scheduling strategies are matched based on different combinations of these two factors. This allows the system to proactively adjust the user interface to guide users when equipment malfunctions and to trigger operation and maintenance early warnings when users experience operational difficulties, thereby achieving integrated collaboration between equipment operation and maintenance and user services.

[0025] To make the technical solution of this application clearer and easier to understand, the following describes a collaborative response method for a power self-service terminal provided by an embodiment of this application, in conjunction with the accompanying drawings. Figure 1 As shown, this figure is a flowchart of a collaborative response method for a power self-service terminal provided in an embodiment of this application. In this embodiment, the method includes: S201, Processing equipment obtains the equipment health level and user operation difficulty level of the self-service power terminal.

[0026] The equipment health level is a classification based on a comprehensive evaluation of the overall operational status of the power self-service terminal, including four levels: Excellent, Good, Warning, and Critical. The user operation difficulty level is a classification based on an evaluation of the degree of obstruction users encounter when operating the power self-service terminal, including three levels: Normal, Slightly Difficult, and Difficult.

[0027] In some embodiments, the device health level of the power self-service terminal is obtained in the following ways: The system collects various device status parameters from the power self-service terminal; calculates the current health score for each dimension based on these parameters; calculates the comprehensive health score based on the current health score and its corresponding dynamic weighting coefficient; and determines the device health level based on the range of the comprehensive health score.

[0028] Multiple equipment status parameters are raw data reflecting the operational status of various components of the self-service power terminal. These include five categories: consumables remaining quantity parameters (remaining ticket paper and receipt paper), cash module parameters (remaining cash box quantity and status), electrical operation parameters (main control voltage, printer status, and connectivity of each module), network communication parameters (network packet loss rate, latency, and bandwidth), and core component parameters (hard drive lifespan, memory usage, and CPU temperature). The current health score is a score between 0 and 100 points obtained by quantifying the status parameters of each dimension, reflecting the current health level of that dimension. The dynamic weighting coefficient is a weight value assigned to each dimension, with the sum of the weighting coefficients for the five dimensions being 1. This dynamic weighting coefficient is dynamically adjusted based on the historical failure frequency and impact on user experience of each dimension. The score range divides the 0-100 score into four intervals, corresponding to four health levels: When the overall health score of the equipment is greater than or equal to 85, the equipment health level is determined to be excellent; when the overall health score of the equipment is greater than or equal to 70 and less than 85, the equipment health level is determined to be good; when the overall health score of the equipment is greater than or equal to 50 and less than 70, the equipment health level is determined to be warning; when the overall health score of the equipment is less than 50, the equipment health level is determined to be serious.

[0029] The processing equipment (i.e., the cloud management platform) first collects raw data of the above five types of equipment status parameters through multiple types of sensors deployed in the power self-service terminal; then, after filtering and denoising the raw data of each dimension and removing outliers, it calculates the current health score for that dimension; next, it multiplies the current health scores of the five dimensions by their respective dynamic weight coefficients and sums them to calculate the comprehensive health score of the equipment; finally, based on the score range in which the comprehensive score falls, it determines the equipment health level of the terminal.

[0030] The expression for the equipment health level is:

[0031] in, Indicates the health level of the equipment. This represents the dynamic weighting coefficient corresponding to the consumables balance dimension. This indicates the current health score in terms of consumables remaining quantity. This represents the dynamic weight coefficient corresponding to the cash module dimension. This indicates the current health score in the cash module dimension. This represents the dynamic weighting coefficient corresponding to the electrical operation dimension. This indicates the current health score in the electrical operation dimension. This represents the dynamic weight coefficient corresponding to the network communication dimension. This represents the current health score in the network communication dimension. This represents the dynamic weight coefficient corresponding to the core component dimension. This indicates the current health score for the core component dimension.

[0032] The expressions for the current health score in each dimension are:

[0033]

[0034]

[0035]

[0036]

[0037] in, This represents the weighting coefficient of the remaining paper quantity within the consumables quantity dimension. This represents the valid data obtained after processing the remaining amount of the receipt paper. This represents the function for mapping the remaining amount of paper in the bill. This represents the weighting coefficient of the remaining receipt amount within the consumables amount dimension. Represents the function for mapping the remaining amount of receipts. This indicates the valid data obtained after processing the remaining amount on the receipt. This represents the weighting coefficient of the cash box balance within the cash module dimension. This represents the function for mapping the remaining amount in the cash box. This represents the valid data obtained after processing the remaining amount in the cash box. This represents the weighting coefficient of the cash box status within the cash module dimension. This represents the function that maps the cash box state. This represents the valid data obtained after processing the cash box status. This represents the weighting coefficient of the main control voltage within the electrical operation dimension. This represents the master control voltage mapping function. This represents the valid data obtained after processing the main control voltage. This represents the weighting coefficient of the printer status within the electrical operation dimension. This represents the printer state mapping function. This indicates the valid data obtained after printer status processing. This represents the weighting coefficient of each module's connectivity within the electrical operation dimension. This represents the connectivity mapping function for each module. This represents the valid data obtained after connectivity processing of each module; This represents the weighting coefficient of network packet loss rate within the network communication dimension. This represents the network packet loss rate mapping function. This represents the valid data obtained after processing the network packet loss rate. This represents the weighting coefficient of network latency within the network communication dimension. Represents the network delay mapping function. This represents the valid data obtained after processing for network latency. This represents the weighting coefficient of network bandwidth within the network communication dimension. This represents a network bandwidth mapping function. This represents the valid data obtained after network bandwidth processing. This represents the weighting coefficient of hard drive lifespan within the core component dimension. This represents a hard disk lifespan mapping function. This represents the valid data obtained after hard drive lifespan processing. This represents the weighting coefficient of memory usage within the core component dimension. This represents a function that maps memory usage. This represents the valid data obtained after processing the memory usage rate. This represents the weighting coefficient of CPU temperature within the core component dimension. Represents the CPU temperature mapping function. This represents the valid data obtained after CPU temperature processing.

[0038] The adjustment methods for dynamic weighting coefficients include: The processing device acquires fault frequency data for each dimension over a historical time period; based on the fault frequency data for each dimension, it determines the impact coefficient of each dimension on user experience; and based on the impact coefficient of each dimension, it periodically updates the dynamic weight coefficient.

[0039] Fault frequency data is the ratio of the number of faults occurring in each dimension to the total operating time of the terminal within a historical period, reflecting the frequency of faults in that dimension. The impact coefficient is a value calculated based on the fault frequency data for each dimension. The higher the fault frequency, the greater the interference of that dimension on the user experience, and the larger the impact coefficient.

[0040] The processing device first collects fault frequency data for each dimension within a preset historical time period; then, it calculates the impact coefficient of each dimension on user experience based on the fault frequency data for each dimension. The higher the fault frequency, the greater the impact coefficient; finally, based on the current impact coefficient of each dimension, it updates the dynamic weight coefficient of each dimension according to a preset period, so that the dimension with the greater impact coefficient receives a higher weight in the overall health score of the device.

[0041] Through the above method, the processing device obtains the updated dynamic weight coefficients for each dimension. These weight coefficients represent the importance proportion of each dimension in the next cycle of device health assessment. The higher the historical failure frequency of a dimension, the more likely that dimension is to affect the normal operation of the terminal and the greater the interference with the user experience. Therefore, it should be given higher attention in the assessment.

[0042] The expression for periodically updating the dynamic weight coefficients is:

[0043] in, Indicates the first Each dimension in historical time period Internal failure frequency, Indicates the first Each dimension in historical time period The number of failures within the system Indicates the terminal during the historical time period Total runtime within, Indicates the first Each dimension in historical time period The degree of influence of internal factors on user experience. Indicates the first Each dimension in historical time period Internal failure frequency, Indicates the normalization scaling factor. Indicates the first The dynamic weight coefficients of each dimension in the next period. Indicates the first The dynamic weight coefficients of each dimension in the current period. Represents the smoothing factor, with a range of values. This is used to control the degree to which historical weights influence the update results. Indicates the first Each dimension in historical time period The degree of influence of internal factors on user experience. Indicates the first The dynamic weight coefficients of each dimension in the current period.

[0044] In some embodiments, the user operation difficulty level is obtained in the following way: The processing equipment collects user operation behavior characteristics on the power self-service terminal; based on the operation behavior characteristics, it identifies the user's operation difficulty type; based on the operation difficulty type, it determines the user's operation difficulty level, which includes normal, mild difficulty, and difficult difficulty.

[0045] User behavior characteristics are quantifiable metrics extracted from user operation logs to reflect the user's operational status. These include page dwell time, number of clicks, repeat click rate, cancellation / return ratio, operation path continuity, and frequency of help function calls. Operation difficulty type is determined based on the user behavior characteristics to categorize the reasons for the user's operational obstruction, including stagnation, obstacle, and help-seeking. Stagnation difficulty refers to situations where the user is unsure how to continue based on page dwell time and time spent without touchscreen interaction; obstacle difficulty refers to situations where the user is unable to complete a certain step based on the number of consecutive failures; and help-seeking difficulty refers to situations where the user needs additional guidance based on the number of help function calls. User operation difficulty level is a classification based on the type and severity of the operation difficulty, including normal, mild, and difficult. Normal indicates no operation difficulty type identified; mild indicates an operation difficulty type identified but with low severity; and difficult indicates an operation difficulty type identified and with high severity.

[0046] The processing device first extracts operational behavior features (such as page dwell time, number of clicks, and repeat click rate) from the operation logs collected from the terminal. Then, it compares each operational behavior feature with preset judgment thresholds to identify the type of operational difficulty the user currently faces: if the page dwell time exceeds 60 seconds without touch screen operation, it is judged as stagnation type; if the same operation fails more than 3 times consecutively, it is judged as obstacle type; if the operation is repeatedly called for help but still cannot be completed, it is judged as help-seeking type. Finally, based on the identified operational difficulty type and its severity, the user's operational difficulty level is determined: if no operational difficulty type is identified, the level is normal; if an operational difficulty type is identified and the degree is mild (such as the dwell time just exceeding the threshold or the number of failures is 2), the level is mild difficulty; if an operational difficulty type is identified and the degree is severe (such as three or more consecutive failures or the difficult state lasting longer than the preset time threshold), the level is difficult.

[0047] Through the above method, the processing device obtains the user's operational difficulty level (one of normal / mild / difficult) for the current user of the terminal. This level characterizes the degree to which the current user's operation on the terminal is hindered.

[0048] S202. The processing device matches the corresponding scheduling strategy from the preset joint evaluation matrix based on the device health level and the user operation difficulty level. The joint evaluation matrix contains the mapping relationship between the device health level, the user operation difficulty level and the scheduling strategy.

[0049] The joint evaluation matrix is ​​a two-dimensional table that uses equipment health levels (excellent / good / warning / critical) as rows and user operation difficulty levels (normal / mild / difficult) as columns, with corresponding scheduling strategies pre-set at the intersections of rows and columns. The processing equipment locates its unique intersection in the matrix based on its current two levels, thus determining the appropriate scheduling strategy.

[0050] The scheduling strategy is a specific response method obtained by matching the processing equipment from a joint evaluation matrix based on a combination of equipment health level and user operation difficulty level. There are four scheduling strategies: collaborative mode, operation and maintenance response mode, friendly degradation mode, and human-machine collaborative emergency mode.

[0051] In some embodiments, if the device health level is excellent or good and the user operation difficulty level is normal, then a collaborative mode is matched; if the device health level is excellent or good and the user operation difficulty level is mild or severe, then an operation and maintenance response mode is matched; if the device health level is warning or severe and the user operation difficulty level is normal, then a friendly degradation mode is matched; if the device health level is warning or severe and the user operation difficulty level is mild or severe, then a human-machine linkage emergency mode is matched.

[0052] The collaborative mode is a scheduling strategy applied when the device health level is excellent or good and user operation is normal. In this mode, the terminal maintains standard interaction methods, all service entry points are open, and no additional intervention is performed.

[0053] The maintenance response mode is a scheduling strategy used when the device's health level is excellent or good, but the user is experiencing operational difficulties. This mode indicates that the device is in normal condition, and the user's difficulties are caused by factors such as operational complexity. The terminal proactively displays operation guidance through the interactive interface to help the user.

[0054] The friendly degradation mode is a scheduling strategy applied when the device health level is in the warning or critical stage but the user operation is normal. This mode indicates that abnormal device status may affect service processing. The terminal proactively displays the device status at the service entry point and guides the user to a nearby normal terminal to process the service.

[0055] The human-machine collaborative emergency mode is a scheduling strategy that is applied when the equipment health level is at the warning or critical level and the user is experiencing operational difficulties. This mode indicates that the equipment malfunction and the user's difficulties may be related, and the terminal simultaneously pushes a collaborative work order to the cloud-based operation and maintenance platform and switches the current terminal to a downgraded acceptance mode.

[0056] After obtaining the equipment health level and the user operation difficulty level, the processing device uses these two levels as indexes to search for the corresponding scheduling strategy in a preset joint evaluation matrix. Specifically, the processing device first determines whether the equipment health level is "Excellent / Good" or "Warning / Severe," and simultaneously determines whether the user operation difficulty level is "Normal" or "Mild / Difficult." Then, based on the combination of the two determinations, it matches a uniquely corresponding strategy from four scheduling strategies: when the equipment health level is Excellent or Good and the user operation difficulty level is Normal, it matches the collaborative mode; when the equipment health level is Excellent or Good and the user operation difficulty level is Mild or Difficult, it matches the maintenance response mode; when the equipment health level is Warning or Severe and the user operation difficulty level is Normal, it matches the friendly degradation mode; and when the equipment health level is Warning or Severe and the user operation difficulty level is Mild or Difficult, it matches the human-machine linkage emergency mode.

[0057] Through the above method, the processing device obtains a scheduling strategy (one of the following: collaborative mode, operation and maintenance response mode, friendly degradation mode, or human-machine linkage emergency mode) that matches the current device operating status and user operation status. This scheduling strategy characterizes the response method to be adopted under the current combination of device health status and user operation status.

[0058] S203. The processing equipment executes a coordinated response operation according to the scheduling strategy.

[0059] Collaborative response operations are a set of specific execution instructions issued by the processing equipment to the power self-service terminal and the cloud-based operation and maintenance platform based on the matched scheduling strategy.

[0060] In some embodiments, when the scheduling strategy is in operation and maintenance response mode, operation guidance is displayed on the interactive interface of the power self-service terminal, and a collaborative work order is pushed to the cloud operation and maintenance platform when the user's operation difficulty level is "difficult" and the difficult state continues for more than a time threshold; when the scheduling strategy is in friendly degradation mode, the abnormal equipment status is displayed at the service entry point in the service selection interface of the power self-service terminal, and the user is guided to a nearby normal power self-service terminal; when the scheduling strategy is in human-machine linkage emergency mode, a collaborative work order is pushed to the cloud operation and maintenance platform and the power self-service terminal is switched to degradation acceptance mode.

[0061] Operation guidance is information displayed to users on the interactive interface of the power self-service terminal in the form of pop-ups, animations, or text prompts to help users complete the current business.

[0062] Collaborative work orders are structured task orders generated by processing equipment. They include a unique identifier for the faulty equipment, a user difficulty type code (stagnation / obstacle / help request), a detailed assessment of the current equipment health, the most likely fault source associated with the difficulty, and statistics on the failure rate of the last N users' operations on this equipment. These information are used to push the work orders to the handheld terminals of maintenance personnel.

[0063] The time threshold is a preset time limit value used to determine whether a user's predicament has lasted for too long. When the duration of the predicament exceeds this limit value, the action of pushing a collaborative work order to the cloud operation and maintenance platform is triggered.

[0064] The downgraded service mode is the operating mode that the power self-service terminal switches to when the equipment health is severely insufficient. In this mode, the terminal interface only retains lightweight business entry points such as emergency payment, and guides users to download the power APP by scanning the code to complete other business transactions.

[0065] The processing device issues corresponding execution instructions to the terminal and the operation and maintenance platform according to the matched scheduling policy. When the scheduling policy is in operation and maintenance response mode, the processing device issues instructions to the power self-service terminal, and the terminal displays operation guidance through the interactive interface to help the user complete the business. At the same time, the processing device continuously monitors the user's operation difficulty level. When the user's operation difficulty level is "difficult" and the duration of the difficult state exceeds a preset time threshold, the processing device generates a collaborative work order and pushes it to the cloud operation and maintenance platform. When the scheduling policy is in friendly degradation mode, the processing device issues instructions to the power self-service terminal, and the terminal indicates the abnormal device status by graying out or text labeling at the business entry point on the business selection interface, and displays the location information and navigation path of nearby normal terminals to the user. When the scheduling policy is in human-machine linkage emergency mode, the processing device generates a collaborative work order and pushes it to the cloud operation and maintenance platform, and issues instructions to the power self-service terminal, and the terminal switches the interactive interface to degradation acceptance mode.

[0066] Through the above methods, the processing device executes a coordinated response operation corresponding to the current scheduling strategy. The operation in the maintenance response mode represents the system's ability to guide and assist users in completing their tasks when the device is in normal condition but the user is experiencing operational difficulties, and to notify maintenance personnel if the difficulties persist. The operation in the friendly degradation mode represents the system's ability to proactively inform the user of the device status and provide an alternative terminal when the device is in an abnormal condition but the user is operating normally. The operation in the human-machine collaborative emergency mode represents the system's ability to simultaneously initiate maintenance procedures and accept terminal degradation when both device abnormalities and user difficulties exist.

[0067] The method also includes: When the device health level is warning or severe, a self-healing strategy is executed according to the fault type: if the fault type is communication interruption or module stagnation, the faulty module will be automatically restarted when the power self-service terminal is in an idle state; if the fault type is excessive network packet loss, the data to be uploaded will be temporarily stored through asynchronous local caching, and the temporarily stored data will be uploaded to the cloud in batches after the network is restored; if the fault type is main control module offline, the main control system of the power self-service terminal will be automatically restarted after the current user session ends securely.

[0068] The self-healing strategy is a recovery operation that is automatically performed on the equipment when the equipment health level is in the warning or critical stage, based on the specific fault type. It aims to restore the faulty module to normal operation without the need for on-site human intervention.

[0069] The fault type is a specific abnormal category of the device determined based on multiple device status parameters, including communication intermittent interruption (network connection is briefly interrupted and then recovers on its own), module stagnation (components such as the OCR recognition module temporarily respond slowly or get stuck), excessive network packet loss (network communication quality deteriorates and the data packet loss rate exceeds the normal range), and main control module offline (the terminal main control system stops responding or crashes).

[0070] Asynchronous local cache requests are a processing method where, when network anomalies prevent data from being uploaded to the cloud in real time, the terminal temporarily stores the data to be uploaded locally and uploads it in batches once the network is restored.

[0071] A user session is the complete interactive process from when a user starts operating on a power self-service terminal until the user completes the transaction and logs out.

[0072] A secure session termination occurs when all transaction data for the current user session has been completely saved, the user has retrieved their personal credentials (such as bank cards, ID cards, etc.), and the session has been closed normally.

[0073] When the processing device determines that the device's health level is in the warning or critical stage, it identifies the specific fault type based on multiple device status parameters and then issues corresponding self-healing execution instructions according to the fault type. If the fault type is a communication interruption or module stagnation, the processing device monitors whether the terminal is in an idle state. After confirming that no user is using the terminal, it issues an instruction to automatically restart the faulty module. During the restart process, the terminal's main interface remains running, and user interaction is uninterrupted. If the fault type is excessive network packet loss, the processing device issues an instruction to the terminal to temporarily store the data to be uploaded in the local cache. After the network quality is restored, the temporarily stored data is uploaded to the cloud in batches. If the fault type is that the main control module is offline, the processing device first confirms that all transaction data of the current user session has been securely saved and the user has retrieved their personal credentials. After the session is securely terminated, it issues an instruction to automatically restart the terminal's main control system.

[0074] Through the above methods, the processing equipment executes a self-healing strategy corresponding to the fault type. The automatic restart operation when communication is interrupted or the module is stuck demonstrates that the system can recover without manual intervention in the event of a minor anomaly, without affecting normal user use; the local caching operation when network packet loss exceeds the limit demonstrates that the system can ensure that data is not lost when the network fluctuates, and automatically retransmit it after the network is restored; the safe restart operation when the main control module is offline demonstrates that the system can ensure the integrity of user transaction data and the security of session state in the event of a serious fault.

[0075] Based on the above description, this application has the following beneficial effects: This application utilizes a joint assessment of user operational difficulty levels and device health levels to transform abnormal user-side operational events into crucial supplementary diagnostic information for device health. This allows potential device problems to be detected in advance through user behavior characteristics, triggering preventative responses before a fault actually occurs. When a user's operational difficulty level is mild or severe and the device health level enters warning or critical territory, the system directly matches the human-machine collaborative emergency mode, simultaneously initiating maintenance work order push and terminal downgrade acceptance. This avoids the excessively long processing chain caused by repeated unsuccessful user requests followed by manual repairs in traditional solutions. Furthermore, in maintenance response mode, the system only pushes work orders to the cloud when the user's difficult state persists for more than a time threshold, effectively filtering invalid alarms caused by occasional operational difficulties and reducing redundant workload for maintenance personnel. In addition, the system performs differentiated self-healing actions based on fault type, such as communication intermittent restart, network packet loss cache uploading, or main control offline safety restart. This allows minor anomalies to be recovered without manual intervention, with maintenance personnel only needing to handle severe anomalies on-site, reducing maintenance attendance frequency.

[0076] The above text combined Figure 1 The collaborative response method of the power self-service terminal provided in the embodiments of this application has been described in detail. The apparatus and equipment provided in the embodiments of this application will be described below with reference to the accompanying drawings.

[0077] like Figure 2 As shown in the figure, this is a schematic diagram of a collaborative response device for a power self-service terminal provided in an embodiment of this application. The device includes: The acquisition module 301 is used to acquire the device health level and user operation difficulty level of the power self-service terminal; The processing module 302 is used to match a corresponding scheduling strategy from a preset joint evaluation matrix based on the device health level and the user operation difficulty level. The joint evaluation matrix contains the mapping relationship between the device health level, the user operation difficulty level and the scheduling strategy. The execution module 303 is used to perform a coordinated response operation according to the scheduling strategy.

[0078] Optionally, the processing module 302 is specifically used to collect various device status parameters of the power self-service terminal; Based on the various device status parameters, calculate the current health score for each dimension; Based on the current health score of each dimension and the corresponding dynamic weight coefficient, calculate the overall health score of the device; The health level of the device is determined based on the score range of the overall health score.

[0079] Optionally, the processing module 302 is specifically used to collect the user's operational behavior characteristics on the power self-service terminal; Based on the operational behavior characteristics, identify the type of operational difficulty the user faces; The user's operational difficulty level is determined based on the operational difficulty type, wherein the operational difficulty level includes normal, mild, and difficult.

[0080] Optionally, the processing module 302 is specifically used to match the collaborative mode if the device health level is excellent or good and the user operation difficulty level is normal. If the device health level is excellent or good and the user operation difficulty level is mild or severe, then the operation and maintenance response mode is matched. If the device health level is warning or severe and the user operation difficulty level is normal, then a friendly downgrade mode is matched. If the device health level is warning or severe and the user operation difficulty level is mild or difficult, then the human-machine linkage emergency mode is matched.

[0081] Optionally, the execution module 303 is specifically used to pop up operation guidance through the interactive interface of the power self-service terminal when the scheduling strategy is the operation and maintenance response mode, and to push a collaborative work order to the cloud operation and maintenance platform when the user's operation difficulty level is a predicament and the predicament state continues to exceed the time threshold. When the scheduling strategy is in friendly degradation mode, the device status is abnormal at the service entry point in the service selection interface of the power self-service terminal, and the user is guided to a nearby normal power self-service terminal. When the scheduling strategy is in the human-machine collaborative emergency mode, a collaborative work order is pushed to the cloud operation and maintenance platform and the power self-service terminal is switched to the downgraded acceptance mode.

[0082] Optionally, the execution module 303 is further configured to execute a self-healing strategy based on the fault type when the device health level is in the warning or critical state: If the fault type is a communication interruption or module stagnation, the faulty module will be automatically restarted when the power self-service terminal is in an idle state. If the fault type is excessive network packet loss, the data to be uploaded will be temporarily stored through asynchronous local caching. After the network is restored, the temporarily stored data will be uploaded to the cloud in batches. If the fault type is that the main control module is offline, the main control system of the power self-service terminal will be automatically restarted after the current user session ends safely.

[0083] Optionally, the processing module 302 is also used to obtain fault frequency data for each dimension within a historical time period; Based on the failure frequency data of each dimension, determine the impact coefficient of each dimension on user experience; The dynamic weight coefficients are periodically updated based on the influence coefficients of each dimension.

[0084] The collaborative response device of the power self-service terminal according to the embodiments of this application can correspond to executing the method described in the embodiments of this application, and the other operations and / or functions of each module / unit of the collaborative response device of the power self-service terminal are respectively for implementing Figure 1 For the sake of brevity, the corresponding processes of each method in the illustrated embodiments will not be described in detail here.

[0085] This application also provides a computing device. For example... Figure 3 As shown in the figure, this is a schematic diagram of a computing device provided in an embodiment of this application. The computing device 400 includes a bus 401, a processor 402, a communication interface 403, and a memory 404. The processor 402, the memory 404, and the communication interface 403 communicate with each other via the bus 401.

[0086] Bus 401 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0087] Processor 402 can be any one or more of the following processors: central processing unit (CPU), graphics processing unit (GPU), microprocessor (MP), or digital signal processor (DSP).

[0088] Communication interface 403 is used for communication with external devices.

[0089] Memory 404 may include volatile memory, such as random access memory (RAM). Memory 404 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0090] The memory 404 stores executable code, and the processor 402 executes the executable code to perform the aforementioned collaborative response method of the power self-service terminal.

[0091] Specifically, in achieving Figure 2 In the case of the illustrated embodiment, and Figure 2 When the modules or units of the collaborative response device of the power self-service terminal described in the embodiment are implemented through software, the following steps are executed: Figure 2 The software or program code required for the functions of each module / unit can be partially or wholly stored in memory 404. Processor 402 executes the program code corresponding to each unit stored in memory 404, and executes the aforementioned collaborative response method of the power self-service terminal.

[0092] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that a computing device can store, or a data storage device such as a data center containing one or more 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 (e.g., solid-state drive). The computer-readable storage medium includes instructions that instruct the computing device to execute the aforementioned collaborative response method of the power self-service terminal.

[0093] This application also provides a computer program product comprising one or more computer instructions. When the computer instructions are loaded and executed on a computing device, all or part of the processes or functions described in this application are generated.

[0094] The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, or data center to another website, computer, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0095] When the computer program product is executed by a computer, the computer executes any of the aforementioned collaborative response methods of the power self-service terminal. The computer program product can be a software installation package; when any of the aforementioned collaborative response methods of the power self-service terminal needs to be used, the computer program product can be downloaded and executed on the computer.

[0096] The descriptions of the processes or structures corresponding to the above figures each have their own emphasis. For parts of a process or structure that are not described in detail, please refer to the relevant descriptions of other processes or structures.

[0097] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be covered within the scope of protection of this application.

Claims

1. A collaborative response method for a self-service electricity terminal, characterized in that, The method includes: Obtain the device health level and user operation difficulty level of the power self-service terminal; Based on the device health level and the user operation difficulty level, a corresponding scheduling strategy is matched from a preset joint evaluation matrix. The joint evaluation matrix contains the mapping relationship between the device health level, the user operation difficulty level and the scheduling strategy. According to the scheduling strategy, perform coordinated response operations.

2. The method according to claim 1, characterized in that, The process of obtaining the device health level of the self-service electricity terminal includes: Collect various device status parameters of the power self-service terminal; Based on the various device status parameters, calculate the current health score for each dimension; Based on the current health score of each dimension and the corresponding dynamic weight coefficient, calculate the overall health score of the device; The health level of the device is determined based on the score range of the overall health score.

3. The method according to claim 1, characterized in that, The user operation difficulty level is obtained in the following way: Collect user behavior characteristics on the power self-service terminal; Based on the operational behavior characteristics, identify the type of operational difficulty the user faces; The user's operational difficulty level is determined based on the operational difficulty type, wherein the operational difficulty level includes normal, mild, and difficult.

4. The method according to claim 1, characterized in that, The step of matching a corresponding scheduling strategy from a preset joint evaluation matrix based on the device health level and the user operation difficulty level includes: If the device health level is excellent or good and the user operation difficulty level is normal, then the collaborative mode is matched. If the device health level is excellent or good and the user operation difficulty level is mild or severe, then the operation and maintenance response mode is matched. If the device health level is warning or severe and the user operation difficulty level is normal, then a friendly downgrade mode is matched. If the device health level is warning or severe and the user operation difficulty level is mild or difficult, then the human-machine linkage emergency mode is matched.

5. The method according to claim 1, characterized in that, The step of performing a coordinated response operation according to the scheduling strategy includes: When the scheduling strategy is in operation and maintenance response mode, operation guidance will pop up through the interactive interface of the power self-service terminal, and when the user's operation difficulty level is "difficult" and the difficult state continues to exceed the time threshold, a collaborative work order will be pushed to the cloud operation and maintenance platform. When the scheduling strategy is in friendly degradation mode, the device status is abnormal at the service entry point in the service selection interface of the power self-service terminal, and the user is guided to a nearby normal power self-service terminal. When the scheduling strategy is in the human-machine collaborative emergency mode, a collaborative work order is pushed to the cloud operation and maintenance platform and the power self-service terminal is switched to the downgraded acceptance mode.

6. The method according to claim 1, characterized in that, The method further includes: When the device health level is warning or severe, a self-healing strategy is executed according to the fault type: If the fault type is a communication interruption or module stagnation, the faulty module will be automatically restarted when the power self-service terminal is in an idle state. If the fault type is excessive network packet loss, the data to be uploaded will be temporarily stored through asynchronous local caching. After the network is restored, the temporarily stored data will be uploaded to the cloud in batches. If the fault type is that the main control module is offline, the main control system of the power self-service terminal will be automatically restarted after the current user session ends safely.

7. The method according to claim 2, characterized in that, The adjustment methods for the dynamic weighting coefficients include: Obtain fault frequency data for each dimension within a historical time period; Based on the failure frequency data of each dimension, determine the impact coefficient of each dimension on user experience; The dynamic weight coefficients are periodically updated based on the influence coefficients of each dimension.

8. A collaborative response device for a self-service electricity terminal, characterized in that, The device includes: The acquisition module is used to acquire the device health level and user operation difficulty level of the power self-service terminal. The processing module is used to match a corresponding scheduling strategy from a preset joint evaluation matrix based on the device health level and the user operation difficulty level. The joint evaluation matrix contains the mapping relationship between the device health level, the user operation difficulty level and the scheduling strategy. The execution module is used to perform coordinated response operations according to the scheduling strategy.

9. A computing device, characterized in that, Including memory and processor; The memory stores one or more computer programs, the one or more computer programs including instructions; when the instructions are executed by the processor, the computing device performs the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program for performing the method as described in any one of claims 1 to 7.

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