A data analysis method, a printing management system, and an image forming apparatus

Abstract

This application relates to the field of image forming technology, and in particular provides a data analysis method, a printing control system, and an image forming device. The method involves acquiring the data type of the data to be analyzed for the image forming device, determining prompt words that match the data type to characterize the analysis problem, generating a data analysis request based on the prompt words and the data to be analyzed, and sending it to an artificial intelligence model. The AI ​​model then analyzes the data, outputs the analysis results, and displays them to the user. In this process, setting different prompt words for different data types can increase the analytical dimensions, make the analysis more flexible, meet complex analytical needs, and improve the accuracy of data analysis. Using artificial intelligence for data analysis eliminates the need for human assistance, deeply uncovering the correlations and future trends between data, and improving analytical efficiency.

Description

Technical Field

[0001] This application relates to the field of image forming technology, and in particular to a data analysis method, a printing control system, and an image forming device. Background Technology

[0002] Currently, multiple image forming devices (such as printers) are typically deployed in business settings such as corporate offices, schools, and hospitals. Status acquisition devices can be used to monitor the status of these devices. The status acquisition device can report the monitored status data to the print management system, which then analyzes and processes the status data of the image forming devices.

[0003] Some existing print management systems can only collect historical status data, lacking the ability to deeply mine and analyze trends from historical status data. Data analysis relies on manual interpretation, which is inefficient and prone to missing key information. Other print management systems can perform data analysis, but the analysis logic for analyzing status data is pre-coded by developers, resulting in a single analysis dimension, poor flexibility, and inability to meet complex analysis needs. Summary of the Invention

[0004] This application is made in view of the above-mentioned problems. This application provides a data analysis method, a print control system, and an image forming apparatus.

[0005] According to one aspect of this application, a data analysis method is provided, the data analysis method being applied to a data analysis module, the data analysis method comprising:

[0006] Acquire the data type of the data to be analyzed for the image forming device;

[0007] Identify cue words that match the data type, the cue words being used to characterize the analytical problem that needs to be analyzed;

[0008] Based on the prompt words and the data to be analyzed, a data analysis request is generated;

[0009] The data analysis request is sent to the artificial intelligence model so that the artificial intelligence model can analyze the data to be analyzed according to the prompt words and output the analysis results.

[0010] The analysis results returned by the artificial intelligence model are displayed.

[0011] Optionally, determining prompt words that match the data type includes:

[0012] Find the set of prompt words corresponding to the data type, and display the prompt word interface containing the set of prompt words;

[0013] The system receives the prompt word selected by the user in the prompt word interface and uses it as the prompt word that matches the data type.

[0014] Optionally, determining prompt words that match the data type includes:

[0015] Find the set of prompt words corresponding to the data type, and display the prompt word interface containing the set of prompt words;

[0016] The system receives prompts edited by the user in the prompt interface as prompts that match the data type, wherein the editing includes at least: adding, deleting, and modifying.

[0017] Optionally, based on the prompt words and the data to be analyzed, a data analysis request is generated, including:

[0018] Generate and display a problem description for the data to be analyzed based on the prompt words;

[0019] Based on the user's request to change the prompt words in the problem description, a prompt word interface is displayed, which allows for prompt word selection and / or editing;

[0020] The prompt word that the user redetermines in the prompt word interface is taken as the changed prompt word;

[0021] A data analysis request is generated based on the changed prompt words and the data to be analyzed.

[0022] Optionally, the data types include at least: print volume type, fault information type, and consumable replacement record type;

[0023] When the data type is print volume, the prompt words should at least include: peak and off-peak months, trend, abnormal months and reasons, and year-on-year growth rate;

[0024] When the data type is fault information, the prompt words should include at least: common fault types, fault patterns, and predicted future fault risks of the image forming equipment;

[0025] When the data type is consumable replacement record, the prompt words should include at least: the total number of replacements for each type of consumable, the average replacement cycle for each type of consumable, and the model of the most frequently replaced consumable.

[0026] According to another aspect of this application, a print control system is provided, the print control system comprising: a data analysis module, wherein the data analysis module, when executed, implements the data analysis method of any of the above embodiments.

[0027] According to another aspect of this application, an image forming apparatus is provided, the image forming apparatus comprising: a data analysis module, which, when executed, implements the data analysis method of any of the above embodiments.

[0028] According to another aspect of this application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the data analysis method of any of the above embodiments.

[0029] According to another aspect of this application, a computer-readable storage medium is provided that stores a computer program / instructions thereon, which, when executed by a processor, implements the data analysis method of any of the above embodiments.

[0030] According to another aspect of this application, a computer program product is provided, including a computer program / instructions that, when executed by a processor, implement the data analysis method of any of the above embodiments.

[0031] As will be described in detail below, a data analysis method, printing control system, and image forming apparatus according to embodiments of this application acquire the data type of the data to be analyzed for the image forming apparatus, determine prompt words matching the data type to characterize the analysis problem, generate a data analysis request based on the prompt words and the data to be analyzed, and send it to an artificial intelligence model so that the artificial intelligence model can analyze the data to be analyzed, output the analysis results, and display them to the user. In this process, setting different prompt words for different data types of data to be analyzed can increase the analysis dimensions, make the analysis problem more flexible, meet complex analysis needs, and improve the accuracy of data analysis. Using artificial intelligence for data analysis eliminates the need for manual assistance, can deeply explore the correlations and future trends between data, and improve analysis efficiency.

[0032] It should be understood that both the foregoing general description and the following detailed description are exemplary and intended to provide further illustration of the claimed technology. Attached Figure Description

[0033] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The accompanying drawings are used to provide a further understanding of the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0034] Figure 1 This is a schematic diagram of the panel of an image forming apparatus provided in an embodiment of this application.

[0035] Figure 2A This is a structural framework diagram showing a separate data analysis module for the image forming apparatus body provided in this application embodiment.

[0036] Figure 2B This application provides a structural framework diagram for setting up a data analysis module within the built-in network service module of the image forming apparatus.

[0037] Figure 2C This is a structural framework diagram of a print control system including a data analysis module deployed in an image forming apparatus provided in an embodiment of this application.

[0038] Figure 2D This is a structural framework diagram of the built-in network service module of the image forming apparatus provided in this application embodiment, which is used to deploy a printing control system.

[0039] Figure 3 This is a schematic diagram of a data analysis process provided in an embodiment of this application.

[0040] Figure 4 This is a schematic diagram of the data acquisition interface provided in an embodiment of this application.

[0041] Figure 5 This is a schematic diagram of the prompt word interface provided in an embodiment of this application.

[0042] Figure 6 A schematic diagram of the problem interface provided in the embodiments of this application.

[0043] Figure 7 This is a schematic diagram of the result display interface provided in the embodiments of this application.

[0044] Figure 8 This is a schematic diagram of the model configuration interface provided in an embodiment of this application.

[0045] Figure 9 This is a hardware block diagram of an electronic device provided in an embodiment of this application.

[0046] Figure 10 This is a schematic diagram of a computer-readable storage medium provided in an embodiment of this application. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application more apparent, exemplary embodiments according to this application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0048] As described in the background section, existing print management systems suffer from a lack of in-depth data mining and trend analysis capabilities, low analysis efficiency, limited analytical dimensions, poor flexibility, and inability to meet complex analytical needs. This application provides a data analysis method applied to a data analysis module, which can be integrated independently into the print management system or an image forming device. The image forming device can also deploy a print management system integrated with the data analysis module. This data analysis module can communicate with an artificial intelligence model to analyze historical state data according to analytical requirements and return the analysis results to the data analysis module for display. When constructing analytical requirements, different types of state data are assigned different analytical requirements. These requirements can be represented by one or more prompts, each prompt representing an analytical question. Different types of state data correspond to different analytical requirements, and the same type of state data can also have different analytical questions, thus satisfying complex analytical scenarios and the diverse analytical needs of different users. Furthermore, data analysis using AI models improves the in-depth mining and trend analysis capabilities of historical data and also increases data analysis efficiency.

[0049] The status data includes at least: print volume data, fault information, consumable replacement records, consumable balance, and operating status (such as online, offline, or hibernation).

[0050] This application also provides a printing control system, which is a system capable of managing image forming equipment. The management content of the image forming equipment includes, but is not limited to: data statistics (such as print volume statistics, fault information statistics, etc.), data analysis, status warning of the image forming equipment, monitoring of the remaining amount of consumables (such as toner) of the image forming equipment, life monitoring of vulnerable parts (such as paper feed rollers, fixing components, scanning components, etc.) of the image forming equipment, group management of the image forming equipment, and management of the data acquisition device for collecting status data of the image forming equipment.

[0051] The printing control system includes at least the following modules: data analysis module, early warning module, image forming equipment grouping module, custom report export module, and print volume cost calculation module.

[0052] Print management systems can be deployed on servers, computers, image forming equipment, mobile terminals, and other devices. When deployed on an image forming equipment, the image forming equipment can manage itself based on the print management system, or it can manage a cluster of multiple image forming equipment connected together. When an image forming equipment manages a cluster of image forming equipment, the image forming equipment with the print management system deployed acts as the master image forming equipment, and the other image forming equipment acts as slave image forming equipment. The slave image forming equipment needs to periodically report its status data to the master image forming equipment.

[0053] Image forming equipment can refer to equipment with at least one function such as printing, scanning, copying, or faxing, including but not limited to laser printers, inkjet printers, multifunction printers, label printers, thermal printers, light-emitting diode (LED) printers, multifunction printers, and multi-functional peripherals (MFPs) that perform the above functions in a single device.

[0054] Mobile terminals can include mobile communication devices such as laptops, mobile phones, tablets, and in-vehicle computers.

[0055] For the print control system:

[0056] The data analysis module is used to: acquire the data to be analyzed and its data type; determine prompt words matching the data type; combine the prompt words with the data to be analyzed to generate a data analysis request; and send the data analysis request to the artificial intelligence model. After the artificial intelligence model outputs its analysis results, the module receives and displays those results. The artificial intelligence model can refer to a large-scale language model, such as Deepseek, GPT, Wenxin Yiyan, Xunfei Xinghuo, ChatGLM, or Baichuan. The artificial intelligence model can be deployed on servers (such as cloud servers), image forming equipment, mobile terminals, computers, etc.

[0057] The data analysis module also includes: a display submodule, which provides a user-friendly interface. This includes: a data acquisition interface, allowing users to identify the data to be analyzed and its data type; a prompt word interface, allowing users to select a prompt word from multiple prompt words corresponding to the data type; and a results display interface, showcasing the data analysis results.

[0058] Determining prompt words can include selecting prompt words, editing prompt words, and changing prompt words.

[0059] The early warning module is used to issue warnings when fault information of the image forming equipment or when vulnerable parts exceed their service life is detected.

[0060] For fault information from image forming equipment, users can configure alert notification methods in the early warning module, such as email alerts or in-app notifications. Email alerts can be configured to be sent in real-time or periodically. Upon detecting a fault in the image forming equipment, an alert will be issued according to the pre-defined notification method.

[0061] For vulnerable components of the image forming equipment, different print volume thresholds can be set for different components to represent their corresponding lifespan thresholds. For a specific vulnerable component, when the detected current print volume exceeds the print volume threshold (lifespan threshold), a warning message is displayed. The print volume for that vulnerable component continues to accumulate until the user clicks the "Confirm Replacement" button; when the user clicks the "Confirm Replacement" button, the print volume accumulation stops, and a new round of print volume statistics begins for that component. After clicking the "Confirm Replacement" button, the user can also click the "Replacement Time" button to modify the replacement time for that vulnerable component.

[0062] The image forming equipment grouping module is used to group all monitored image forming equipment according to departments or sections.

[0063] The image forming equipment of each department or section can be managed separately. For example, the print volume report of the image forming equipment can be exported by department or section through the custom report export module, and the print volume cost calculation module can be used to calculate the print volume cost of the image forming equipment by department or section.

[0064] The custom report export module allows users to select different export items as headers before exporting reports, generating different export templates. During report export, a target template is selected from multiple templates, and the relevant data is exported according to the headers of that target template to generate an Excel report. The headers include: department, section, image forming equipment model, print volume, and print cost.

[0065] The print volume cost calculation module is used to: set different paper categories according to paper type; and set different unit costs for different paper categories. When users need to calculate costs by department or section, they can calculate the total print volume of each paper category for a specific department or section, and then calculate the total print volume cost for each department or section based on the unit cost of each paper category. Paper categories include: A4 black and white, A4 color, A3 black and white, A3 color, etc.

[0066] The printing control system provided in this application embodiment can be applied to business scenarios such as schools, enterprises, and hospitals. For different business scenarios, the image forming device grouping module in the printing control system can group and statistically analyze image forming devices according to class, department, or section.

[0067] This application also provides an image forming apparatus, which includes at least: a data analysis module, a printing module, a scanning module, a copying module, a faxing module, and a built-in network service module. The data analysis module can be separately located within the image forming apparatus body or integrated into the built-in network service module. Furthermore, the image forming apparatus body can deploy a print management system including the data analysis module, or the built-in network service module of the image forming apparatus can deploy a print management system including the data analysis module.

[0068] Users can access the network service interface provided by the built-in network service module through a browser using the network address corresponding to the built-in network service module. In the network service interface, users can configure network and security settings for the image forming device, and also view product information such as product name, serial number, and operating status.

[0069] The network settings include protocol settings and wireless settings. Protocol settings may include wired IP configuration, RAW / LPD, SNMP, WSD, SNTP, SMTP, AirPrint, and SSL / TLS functionality configurations. Wireless settings may include wireless port settings, wireless network settings, wireless IP settings, WPS, and Wi-Fi Direct configuration. Security settings may include management protocol on / off settings, settings for accessing the image forming device's network ports, and scanning permission on / off settings.

[0070] When the built-in network service module deploys a data analysis module (whether deployed separately or within a print management system that includes the data analysis module), the user can determine the data to be analyzed and its data type in the network service interface provided by the built-in network service module (the interface provided by the display submodule of the data analysis module is integrated into the network service interface). Then, the user selects a prompt word from multiple prompt words corresponding to the data type as the matching prompt word. Next, the data analysis module generates a data analysis request based on the selected prompt word and the data to be analyzed. Finally, the data analysis module sends the data analysis request to the artificial intelligence model to display the analysis results output by the artificial intelligence model on the network service page.

[0071] When the data analysis module is deployed independently on the image forming device itself, rather than within the built-in network service module, data analysis controls can be displayed on the device's control panel. Users can trigger these controls from the control panel to perform data analysis; that is, the interface provided by the data analysis module's display submodule is integrated into the control panel. Specifically, when the control panel detects that a user has triggered the data analysis controls, it displays a data acquisition interface, a prompt interface, and a results display interface on the control panel.

[0072] Figure 1 This is a schematic diagram of the panel of an image forming apparatus provided in an embodiment of this application. The panel of the image forming apparatus displays printing controls, scanning controls, copying controls, faxing controls, and data analysis controls. The user clicks the data analysis control to activate the data analysis function.

[0073] When a print management system including a data analysis module is deployed separately on the image forming device, print management controls can be displayed on the device's panel. Users can activate the print management system by triggering these controls, and the panel will display controls for each module of the system. Examples include: data analysis controls for the data analysis module, report export controls for the custom report export module, cost calculation controls for the print volume cost calculation module, and warning setting controls for the warning module.

[0074] For example, when a user triggers the data analysis control on the panel, a data acquisition interface is displayed, allowing the user to specify the data to be analyzed and its data type. When a user triggers the alert settings control on the panel, an alert settings interface is displayed, where the user can configure the alert notification method.

[0075] It should be noted that when the image forming device includes a data analysis module, it can acquire its own status data for analysis, or it can acquire status data from multiple image forming devices for analysis. When acquiring status data from multiple image forming devices, these devices can be networked to form a device cluster. The image forming device with the data analysis module in the cluster acts as the master image forming device, and the other image forming devices act as slave image forming devices. The slave image forming devices periodically report their own status data to the master image forming device.

[0076] Figure 2A A structural framework diagram showing a separate data analysis module for the image forming device itself. Figure 2AThe image forming apparatus 100 includes a data storage module 110, a data analysis module 120, a panel display module 130, and a built-in network service module 140. The data storage module 110 stores status data. The data analysis module 120 acquires the data to be analyzed, the data type of the data, the corresponding prompts, and displays the analysis results. The panel display module 130 displays the printing, scanning, and copying controls of the image forming apparatus, and can also display the interface corresponding to the data analysis module. The built-in network service module 140 manages the network services of the image forming apparatus. The user's browser accesses the network services through the network address of the built-in network service module.

[0077] Figure 2B A structural framework diagram for setting up the data analysis module of the built-in network service module of the image forming device. Figure 2B Except for the data analysis module, which is deployed within the built-in network service module and cannot be displayed through the panel display module, the purpose of each module in the image forming device is the same as... Figure 2A The functions of each module are the same, so I will not go into detail again.

[0078] Figure 2C A structural framework diagram for deploying a print control system including a data analysis module for image forming equipment. Figure 2D This diagram illustrates the structural framework for deploying a print management and control system on the built-in network service module of an image forming device. The print management system 150 is used to manage and control the image forming device. Figure 2C and Figure 2D The purpose of each module and Figure 2A The functions of each module are the same, so I will not go into detail again.

[0079] Based on the functions of the aforementioned data analysis module, this application provides a data analysis method applied to the data analysis module. For example... Figure 3 As shown, the data analysis method includes:

[0080] S300: Acquire the data type of the data to be analyzed for the image forming device.

[0081] In this embodiment, the data analysis module includes a display submodule, which provides a human-computer interaction interface. The human-computer interaction interface includes at least: a data acquisition interface, a prompt interface, and a result display interface.

[0082] When a user wants to perform data analysis, they can activate the data analysis module to display the data acquisition interface. The data acquisition interface includes at least one type control, where each type control represents a data type. The data types include at least: print volume type, fault information type, and consumable replacement record type. Print volume type data is print volume data, fault information type data is fault information, and consumable replacement record type data is consumable replacement records.

[0083] Users can select the data type they want to analyze using a type control in the data acquisition interface. The data analysis module then retrieves the selected data type. After the data type is determined, the data analysis module can obtain the data to be analyzed that matches that data type.

[0084] In one embodiment, after the user sets the data type, all data of that data type can be directly used as the data to be analyzed.

[0085] In another embodiment, after the user sets the data type, the data of that data type can be filtered, and a portion of the data of that data type can be used as the data to be analyzed.

[0086] In addition, the data acquisition interface may include at least one data filtering control, with each data filtering control representing a filtering item. Filtering items may include at least: time period, customer, department, section, paper type, brand of image forming equipment, and model of image forming equipment.

[0087] Specifically, the user selects the data type to be analyzed in the data acquisition interface, and then sets filter parameters for each filter item under that data type to form the filter conditions for the data to be analyzed. The data analysis module monitors the user's selection of the data type control in the data acquisition interface, obtains the selected data type, and displays the filter items related to the selected data type in the data acquisition interface. The data analysis module obtains the filter parameters set by the user for each filter item in the data acquisition interface and generates the filter conditions for the data to be analyzed. After obtaining the data type and filter conditions, the data analysis module can retrieve data from the database that matches the data type and satisfies the filter conditions as the data to be analyzed.

[0088] Figure 4The data acquisition interface provided in this application embodiment includes: a print volume analysis control, a fault analysis control, a consumables analysis control, a view prompt word control, and an AI analysis control (i.e., an analysis start control). When the user selects the print volume analysis control, the data analysis module obtains the print volume type and displays three filter options: time period, department, and paper category. After the user sets the filter parameter for the past month for the time period, selects the finance department for the department, and sets the filter parameter for A4 black and white paper category, the data analysis module obtains the daily print volume of A4 black and white paper of the finance department over the past month as the data to be analyzed.

[0089] S302: Determine a prompt word that matches the data type, the prompt word being used to characterize the analytical problem that needs to be analyzed.

[0090] In this embodiment, after the user selects a data type, the data analysis module can determine prompt words that match the selected data type. These prompt words characterize the analytical problem to be analyzed. Different data types correspond to different prompt words, and the same data type can correspond to one prompt word or multiple different prompt words.

[0091] When the data type is print volume, the prompt words should include at least: peak and off-peak months, trend, abnormal months and reasons, and year-on-year growth rate.

[0092] When the data type is fault information, the prompt words should include at least: common fault types, fault patterns, predicted future fault risks of image forming equipment, and image forming equipment with high-frequency faults.

[0093] When the data type is consumable replacement record, the prompt words should include at least: the total number of replacements for each type of consumable, the average replacement cycle for each type of consumable, and the model of the most frequently replaced consumable.

[0094] In one embodiment, after the user sets the data type or filtering parameters in the data acquisition interface, the data analysis module can default to using multiple prompt words corresponding to the user-selected data type as prompt words matching that data type. The user can trigger the analysis start control in the data acquisition interface to allow the data analysis module to send a data analysis request to the artificial intelligence model. The data analysis module displays the analysis results fed back by the artificial intelligence model. The data acquisition interface also includes an analysis start control.

[0095] exist Figure 4 In the middle, when users do not want to manually set prompt words, they can click the AI ​​analysis control to start artificial intelligence analysis.

[0096] In this embodiment, users do not need to manually select or edit prompts; they can simply trigger the analysis start control to directly display the analysis results. This process simplifies user operations and improves the convenience of data analysis.

[0097] To meet the diverse analytical needs of different users, the data analysis module can provide users with multiple prompts corresponding to the data type they select, allowing them to choose or edit, thereby improving the user experience. For this purpose, a prompt control can be displayed on the data acquisition interface.

[0098] In another embodiment, the user can trigger a prompt word control on the data acquisition interface. The data analysis module searches for a set of prompt words corresponding to the data type selected by the user and displays the prompt word interface. The prompt word interface displays multiple prompt words from the set. Then, the user can select or edit the displayed prompt words according to their analysis needs. After determining at least one prompt word for the data to be analyzed, the user can trigger an analysis start control on the data acquisition interface to allow the data analysis module to send a data analysis request to the artificial intelligence model.

[0099] Specifically, users can directly select the desired prompts in the prompt message interface. In other words, the data analysis module receives the prompts selected by the user in the prompt message interface and uses them as prompts that match the data type.

[0100] In addition to selecting matching prompts from a set of prompts, users can also edit prompts based on the existing prompts. Editing includes at least adding, deleting, and modifying prompts.

[0101] Specifically, it receives prompts edited by the user in the prompts interface and uses them as prompts that match the data type.

[0102] For example: The prompt word interface displays the following prompt word set: peak and off-peak months, trend, and abnormal months. After deleting multiple prompt words from the prompt word set, the resulting prompt word set is: peak and off-peak months, and trend. After adding multiple prompt words to the prompt word set, the resulting prompt word set is: peak and off-peak months, trend, abnormal months, and year-on-year growth rate. After modifying multiple prompt words, the resulting prompt word set is: peak and off-peak months, trend, abnormal months, and reason.

[0103] For example, after seeing the default consumables analysis prompt, if a user is particularly concerned about the replacement status of the "cyan (C) toner cartridge," they can add to the end of the prompt: "Please pay special attention to whether the replacement cycle of the cyan toner cartridge is abnormal." This way, the analysis results output by the AI ​​model will include targeted analysis. This greatly improves the practicality and flexibility of the data analysis module.

[0104] exist Figure 4 In the middle, when a user wants to manually set the prompt words, they can click to view the prompt word control, which will display the prompt word interface. Figure 5 The prompt word interface provided in this embodiment displays multiple prompt words. Users can modify or select any prompt word, and can also add or delete prompt words from existing prompt words using the add / delete controls. After selecting a prompt word, users can click the confirm control. After adding, deleting, or editing a prompt word, users can click the save control to save the changes. If users regret adding, deleting, or editing a prompt word, they can click the reset control to restore the edited prompt word.

[0105] Furthermore, to simplify the editing process for users, the data analysis module displays default prompts while providing multiple alternative templates (such as "Simplified Version," "Detailed Version," and "Anomaly Detection Focus Version") for users to switch between with a single click. After selecting a template, users can fine-tune multiple prompts based on that template. This demonstrates the diversity in how prompts are provided.

[0106] S304: Generate a data analysis request based on the prompt words and the data to be analyzed.

[0107] In this embodiment, after determining a prompt word that matches the data type, the data analysis module can generate a data analysis request to be sent to the artificial intelligence model based on the prompt word and the obtained data to be analyzed. The data analysis request carries a problem description corresponding to the prompt word and the data to be analyzed.

[0108] In one embodiment, the data analysis module can generate a problem description for the data to be analyzed based on prompts. The problem description describes the various analytical questions to be addressed in analyzing the data. Then, based on the problem description and the data to be analyzed, a data analysis request is generated.

[0109] After generating the problem description, the description can be displayed to the user, allowing them to reconfirm whether their analysis requirements for the data to be analyzed are accurate, thereby improving the accuracy of data analysis.

[0110] In one embodiment, after generating the problem description, the data analysis module displays a problem interface. This problem interface displays a problem description for the data to be analyzed. Users can trigger a prompt word change control in the problem interface, and users can also trigger a confirmation control in the prompt word interface. When the data analysis module detects that a user has triggered the prompt word change control, it generates a data analysis request based on the problem description for the data to be analyzed and the data to be analyzed.

[0111] When the data analysis module detects that a user has triggered the prompt word change control, it obtains the prompt word change request and displays the prompt word interface. Users can reselect or edit prompt words in the prompt word interface. The data analysis module uses the reselected or edited prompt words as the changed prompt words, and based on these changed prompt words, regenerates the question description and re-displays it in the question interface. When the user triggers the confirmation control in the question interface, a data analysis request is generated based on the question description corresponding to the changed prompt words and the data to be analyzed.

[0112] For example, regarding fault information, the problem description could be: Regarding fault information, please analyze the following: 1. Count the total number of faults for each device and find the device with the highest failure rate; 2. Classify common fault types (such as paper jams, print quality, scanning faults, system errors); 3. Calculate the average fault interval time; 4. Analyze whether there is a time pattern to the occurrence of faults (such as specific seasons, weekdays, etc.).

[0113] Regarding consumable replacement records, the problem description could be: Analyze the following: 1. Calculate the total number of replacements and average replacement cycle for each type of consumable (e.g., black toner cartridge, color toner cartridge); 2. Identify the most frequently replaced consumable model; 3. Determine if any component of the device is replaced abnormally frequently, which may indicate a potential malfunction.

[0114] Figure 6 The problem interface provided in this application embodiment displays a problem description generated by prompt words, such as: For print volume data, please analyze the following: 1. The months with the highest and lowest print volume, and calculate their month-on-month / year-on-year growth rates; 2. Identify the trend of print volume (e.g., stable growth, seasonal fluctuations, decline); 3. Indicate the months that may have anomalies (such as a surge or sharp decrease in print volume), and analyze the possible reasons.

[0115] S306: Send the data analysis request to the artificial intelligence model so that the artificial intelligence model can analyze the data to be analyzed according to the prompt words and output the analysis results.

[0116] S308: Display the analysis results returned by the artificial intelligence model.

[0117] In this embodiment, the data analysis module can access the artificial intelligence model by calling its application programming interface (API). Specifically, by calling the API, the data analysis request is sent to the AI ​​model, allowing it to analyze the data according to the question description corresponding to the prompt and output the analysis results. The AI ​​model then returns the analysis results to the data analysis module, which displays them in the results display interface.

[0118] Figure 7 The results display interface provided in this application embodiment shows the analysis results. For example, during the analysis period, the peak print volume occurred in October, totaling 10,378 pages, a month-on-month increase of 15%. The trend shows a stable upward trend, and no obvious abnormal fluctuations were detected.

[0119] Before the data analysis module can access the AI ​​model, it needs to obtain access permissions for the AI ​​model. The display submodule of the data analysis module also provides a model configuration interface. This interface includes at least: a model provider input box, a key input box, a model name input box, test controls, and a model acquisition control.

[0120] Specifically, users can enter the model provider's API key and the AI ​​model's API key in the model configuration interface. Then, the user can trigger a test control. When the data analysis module detects this, it retrieves the entered API key and sends it to the model provider's cloud server. The model provider's cloud server verifies the API key. If verification is successful, the data analysis module gains access to the model provider's cloud server, meaning it has access to the AI ​​model provided by the model provider. If verification fails, the data analysis module cannot access the AI ​​model provided by the model provider.

[0121] If the data analysis module has access to the AI ​​models provided by the model provider, the user can trigger the "Get Model" control in the model configuration interface to obtain various AI models provided by the model provider. The user can then select one AI model from the obtained models to use for data analysis.

[0122] Figure 8 The model configuration interface provided in this application embodiment displays a model provider input box, an API key input box, a model name input box, a test control, and a model acquisition control.

[0123] Figure 9 This is a hardware block diagram of an electronic device provided in an embodiment of this application. The electronic device 900 according to an embodiment of this application includes at least a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the task execution method described in any of the above embodiments.

[0124] Figure 9The illustrated electronic device 900 specifically includes a central processing unit (CPU) 901, a graphics processing unit (GPU) 902, and a memory 903. These units are interconnected via a bus 904. The CPU 901 and / or GPU 902 can function as the aforementioned processor, and the memory 903 can function as the aforementioned memory storing computer-readable instructions. Furthermore, the electronic device 900 may also include a communication unit 905, a storage unit 906, an output unit 907, an input unit 908, and an external device 909, all of which are also connected to the bus 904.

[0125] Figure 10 This is a schematic diagram of a computer-readable storage medium provided in an embodiment of this application. The computer-readable storage medium according to an embodiment of this application stores computer programs / instructions (including but not limited to computer-readable instructions). Specifically, as shown... Figure 10 As shown, a computer-readable storage medium 1000 stores computer-readable instructions 1001. When executed by a processor, this computer program / instruction implements the task execution method described in any of the preceding embodiments of this application. The computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0126] This application further provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the task execution method described in any of the preceding embodiments of this application.

[0127] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the application to the necessity of employing the aforementioned specific details for implementation.

[0128] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0129] Additionally, as used herein, the "or" used in a list of items beginning with "at least one" indicates a separate list, such that a list of, for example, "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not imply that the described example is preferred or better than other examples.

[0130] It should also be noted that in the system and method of this application, the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions of this application.

[0131] Various changes, substitutions, and modifications can be made to the technology described herein without departing from the teachings defined by the appended claims. Furthermore, the scope of the claims is not limited to the specific aspects of the processes, machines, manufactures, events, means, methods, and actions described above. Currently existing or later-developed processes, machines, manufactures, events, means, methods, or actions that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein can be utilized. Therefore, the appended claims include such processes, machines, manufactures, events, means, methods, or actions within their scope.

[0132] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0133] The above description has been given for illustrative and descriptive purposes. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A data analysis method, characterized in that, The data analysis method is applied to the data analysis module, and the data analysis method includes: Acquire the data type of the data to be analyzed for the image forming device; Identify cue words that match the data type, the cue words being used to characterize the analytical problem that needs to be analyzed; Based on the prompt words and the data to be analyzed, a data analysis request is generated; The data analysis request is sent to the artificial intelligence model so that the artificial intelligence model can analyze the data to be analyzed according to the prompt words and output the analysis results. The analysis results returned by the artificial intelligence model are displayed.

2. The data analysis method according to claim 1, characterized in that, Determining prompt words that match the data type includes: Find the set of prompt words corresponding to the data type, and display the prompt word interface containing the set of prompt words; The system receives the prompt word selected by the user in the prompt word interface and uses it as the prompt word that matches the data type.

3. The data analysis method according to claim 1, characterized in that, Determining prompt words that match the data type includes: Find the set of prompt words corresponding to the data type, and display the prompt word interface containing the set of prompt words; The system receives prompts edited by the user in the prompt interface as prompts that match the data type, wherein the editing includes at least: adding, deleting, and modifying.

4. The data analysis method according to claim 1, characterized in that, Based on the prompt words and the data to be analyzed, a data analysis request is generated, including: Generate and display a problem description for the data to be analyzed based on the prompt words; Based on the user's request to change the prompt words in the problem description, a prompt word interface is displayed, which allows for prompt word selection and / or editing; The prompt word that the user redetermines in the prompt word interface is taken as the changed prompt word; A data analysis request is generated based on the changed prompt words and the data to be analyzed.

5. The data analysis method according to claim 1, characterized in that, Data types should include at least: print volume type, fault information type, and consumable replacement record type; When the data type is print volume, the prompt words should at least include: peak and off-peak months, trend, abnormal months and reasons, and year-on-year growth rate; When the data type is fault information, the prompt words should include at least: common fault types, fault patterns, and predicted future fault risks of the image forming equipment; When the data type is consumable replacement record, the prompt words should include at least: the total number of replacements for each type of consumable, the average replacement cycle for each type of consumable, and the model of the most frequently replaced consumable.

6. A printing control system, characterized in that, The printing control system includes: a data analysis module, which, when executed, implements the data analysis method of any one of claims 1-4; The printing control system is deployed in at least one of a server, computer, mobile terminal, and image forming equipment.

7. An image forming apparatus, characterized in that, The image forming apparatus includes a data analysis module, which, when executed, implements the data analysis method of any one of claims 1-4.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the data analysis method of any one of claims 1-4.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instruction is executed by the processor, it implements the data analysis method of any one of claims 1-4.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the data analysis method of any one of claims 1-4.

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