Smart television remote diagnosis and repair processing method, device and terminal

Abstract

The invention discloses a smart television remote diagnosis and repair processing method and device and a terminal. The method comprises the following steps: acquiring operation data and fault information related to a smart television system; performing fault mode identification and reason inference on the collected operation data and fault information by using an artificial intelligence algorithm, and generating a preliminary diagnosis result of a fault problem; according to the generated preliminary diagnosis result of the fault problem, searching a preset fault problem repair knowledge base, and generating a fault repair scheme corresponding to the fault information problem; and displaying the generated fault repair scheme corresponding to the fault information problem in a graphical interface and / or voice form, and automatically guiding to complete corresponding repair operation. According to the method, the television restoration efficiency can be improved, inconvenience caused by equipment faults of a user is reduced, meanwhile, the requirement for on-site service is reduced, and convenience is provided for use of the user.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent terminals, and in particular to a method and device for remote diagnosis and repair of an intelligent television, an intelligent terminal and a storage medium. Background Art

[0002] With the development of science and technology and the continuous development of people's lives, the use of various smart terminals such as smart TVs is becoming more and more popular. Smart TVs have become an indispensable household appliance in people's lives.

[0003] In the prior art, if there is a problem with a smart TV, after-sales service is required to come to the customer's home to handle it, which is time-consuming and laborious. However, in practice, some of the problems may be caused by software problems, which can be solved by simple processing.

[0004] Therefore, the existing technology still needs to be improved and developed. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a method, device, smart terminal and storage medium for remote diagnosis and repair of smart TVs in response to the problems and defects of the above-mentioned prior art. The present invention can improve the efficiency of TV repair, reduce the inconvenience caused to users by equipment failure, and at the same time reduce the demand for on-site services, thereby providing convenience for users.

[0006] The technical solution adopted by the present invention to solve the problem is as follows:

[0007] A method for remote diagnosis and repair of a smart TV, comprising:

[0008] Collect and obtain operation data and fault information related to smart TV systems;

[0009] Use artificial intelligence algorithms to identify fault patterns and infer causes of collected operating data and fault information, and generate preliminary diagnostic results of fault problems;

[0010] According to the generated preliminary diagnosis result of the fault problem, a preset fault problem repair knowledge base is searched to generate a fault repair plan corresponding to the fault information problem;

[0011] The generated fault repair plan corresponding to the fault information problem is presented and displayed through a graphical interface and / or voice, and automatically guides the completion of the corresponding repair operations.

[0012] The method for remote diagnosis and repair of smart TVs, wherein the step of collecting and acquiring operation data and fault information related to the smart TV system comprises:

[0013] Various fault information problems of the smart TV and repair solutions corresponding to the fault information problems are stored in a preset fault problem repair knowledge base in advance.

[0014] The method for remote diagnosis and repair of smart TVs, wherein the step of collecting and acquiring operation data and fault information related to the smart TV system comprises:

[0015] When the smart TV is started, various operating data and fault information of the smart TV system are collected in real time through regular polling and event triggering. The operating data includes: system log, device status information, network connection status, and user operation records.

[0016] The method for remote diagnosis and repair of smart TVs, wherein the step of using an artificial intelligence algorithm to identify fault patterns and infer causes of the collected operating data and fault information to generate a preliminary diagnosis result of the fault problem comprises:

[0017] Establish a fault pattern recognition model by analyzing historical operation data and fault information in advance;

[0018] Perform data cleaning and preprocessing on the collected operation data and fault information to obtain preprocessed operation data and fault information;

[0019] By establishing a fault pattern recognition model and using machine learning and data mining techniques, fault pattern recognition and cause inference are performed on the pre-processed operating data and fault information, possible fault causes are inferred, and preliminary diagnostic results of the fault problem are generated.

[0020] The method for remote diagnosis and repair of smart TVs, wherein the step of searching a preset fault problem repair knowledge base based on the generated preliminary diagnosis result of the fault problem and generating a fault repair solution corresponding to the fault information problem comprises:

[0021] Obtain the preliminary diagnosis results of the generated fault problem;

[0022] According to the generated preliminary diagnosis result of the fault problem, a fault repair solution that matches the fault information problem is searched in a preset fault repair knowledge base;

[0023] Among them, the considerations of the fault repair solution corresponding to the fault information problem include: fault type and severity, user's technical ability, and existing hardware and software environment.

[0024] The method for remote diagnosis and repair of smart TVs, wherein the step of presenting the generated fault repair solution corresponding to the fault information problem in a graphical interface and / or voice form and automatically guiding the completion of the corresponding repair operation comprises:

[0025] The generated fault repair plan corresponding to the fault information problem is presented in a graphical interface and / or voice form, wherein the graphical interface displays detailed operation steps and solutions on the TV screen, and the voice form guides the user to troubleshoot the problem through voice interaction; and controls the push notification and operation guidance through the application on the corresponding mobile device to automatically guide the completion of the corresponding repair operation.

[0026] The method for remote diagnosis and repair of smart TVs, wherein the fault repair knowledge base stores various fault information problems of smart TVs related to fault diagnosis and repair, and repair solutions corresponding to the fault information problems, including:

[0027] Common faults and their characteristics, methods of repairing various faults, and diagnostic and repair procedures;

[0028] The knowledge base for controlling fault repair can be maintained and updated through manual input and automatic learning.

[0029] A smart TV remote diagnosis and repair processing device, wherein the device comprises:

[0030] A pre-setting module is used to store various fault information problems of the smart TV and repair solutions corresponding to the fault information problems in a preset fault problem repair knowledge base;

[0031] A data acquisition module is used to acquire operation data and fault information related to the smart TV system;

[0032] The data analysis module is used to use artificial intelligence algorithms to identify fault patterns and infer causes of the collected operating data and fault information, and generate preliminary diagnostic results of the fault problem;

[0033] A solution matching module is used to search a preset fault problem repair knowledge base according to the generated preliminary diagnosis result of the fault problem, and generate a fault repair solution corresponding to the fault information problem;

[0034] The solution display module is used to present the generated fault repair solution corresponding to the fault information problem through a graphical interface and / or voice, and automatically guide the completion of the corresponding repair operation.

[0035] An intelligent terminal includes a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, including the method for executing any one of the methods described above.

[0036] A computer-readable storage medium, wherein when instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute any one of the methods described above.

[0037] Beneficial effects of the invention: The invention provides a method, device, intelligent terminal and storage medium for remote diagnosis and repair of smart TVs. The invention relates to remote diagnosis and fault repair of TV systems implemented by software. The collected data is analyzed by AI technology, and a knowledge base of problem repair methods is combined to obtain recommended solutions and send them to users through the network. The invention can improve the efficiency of TV repair, reduce the inconvenience caused to users by equipment failure, reduce the demand for on-site services, and provide convenience for users. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 It is a flowchart of the smart TV remote diagnosis and repair processing method provided in Example 1 of the present invention.

[0040] Figure 2 It is a flowchart of the smart TV remote diagnosis and repair processing method provided by Embodiment 2 of the present invention.

[0041] Figure 3 A principle block diagram of an embodiment of a remote diagnosis and repair processing device for a smart television provided by the present invention.

[0042] Figure 4 It is a block diagram of the internal structure principle of the intelligent terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0045] For smart TVs in the prior art, if there is a problem, after-sales service is required to come to the customer's home to handle it, which is time-consuming and laborious. However, in reality, many problems may be minor problems. For example, some are caused by software problems and can be solved with simple processing.

[0046] Therefore, the present invention proposes a remote diagnosis and repair method for smart TVs. The present invention implements remote diagnosis and fault repair processing of TV systems through software, analyzes the collected data through AI technology, and combines the knowledge base of problem repair methods to obtain recommended solutions and send them to users through the network. This solution aims to improve TV maintenance efficiency, reduce the inconvenience caused to users by equipment failures, reduce the demand for on-site services, and provide convenience for users.

[0047] like Figure 1 As shown, a method for remote diagnosis and repair of a smart TV according to Embodiment 1 of the present invention comprises the following steps:

[0048] Step S100: Prestore various fault information problems of the smart TV and repair solutions corresponding to the fault information problems in a preset fault problem repair knowledge base.

[0049] In the embodiment of the present invention, various fault information problems of smart TVs and corresponding repair solutions will be collected in advance during the specific implementation. Examples of fault information problems and corresponding repair solutions are as follows:

[0050] Problem 1: No TV signal;

[0051] Information description: The TV screen displays "No Signal" or "Signal Input Error".

[0052] Repair plan: 1. Check whether the connection cable between the TV and the signal source (such as set-top box, DVD, game console, etc.) is correctly inserted; 2. Confirm that the signal source device is working properly and switch to the correct input source (such as HDMI1, HDMI2, etc.); 3. Restart the TV and signal source device. If using an antenna, check whether the antenna is well connected.

[0053] Problem 2: The TV image is blurry or distorted;

[0054] Information description: The TV image is not clear and the edges are distorted.

[0055] Repair solution: 1. Check the TV settings to make sure the screen resolution matches the input signal.

[0056] Adjust the TV's image settings, such as contrast, brightness, and sharpness. 2. If you connect an external device, make sure its output settings are also compatible with the TV.

[0057] Problem 3: The TV cannot be turned on;

[0058] Information description: There is no response after pressing the remote control or TV switch, and the indicator light is off.

[0059] Solution: 1. Check if the power cord is properly plugged in and make sure the power outlet is supplying power. 2. Press and hold the power button (usually on the side or back of the TV) to try restarting the device. 3. If the TV has a backup power supply, try starting it with the backup power supply.

[0060] Problem 4: Audio cannot be played or the volume is distorted;

[0061] Message description: There is no sound from the TV or the sound is distorted.

[0062] Solution: 1. Check the audio settings to make sure the volume is not muted and is set within a reasonable range; 2. Check the audio output settings to make sure the correct audio mode is selected (such as stereo, surround sound, etc.). 3. Make sure any external audio devices are well connected and working properly.

[0063] Problem 5: Streaming app crashes or fails to load;

[0064] Information description: Crashes or slow loading when using streaming applications (such as Netflix, YouTube, etc.).

[0065] Repair solution: 1. Check the Internet connection and make sure the Wi-Fi signal is stable and connected properly; 2. Restart the smart TV and network router; 3. Uninstall and reinstall the problematic application; 4. Update the TV's firmware and application to the latest version.

[0066] The above fault problems and corresponding repair solutions are examples. The present invention stores various fault information problems of smart TVs and the repair solutions corresponding to the fault information problems in a preset fault problem repair knowledge base.

[0067] The content stored in the preset fault problem repair knowledge base in the embodiment of the present invention includes: common faults and their characteristics, repair methods for various faults, diagnosis and maintenance steps.

[0068] When the present invention is implemented, a fault repair knowledge base is set up and can be maintained and updated by manual input and automatic learning, which can continuously improve the success rate of smart TV fault repair.

[0069] Step S200: collecting and acquiring operation data and fault information related to the smart TV system;

[0070] In the embodiment of the present invention, firstCollect and obtain the operation data and fault information related to the smart TV system. In the specific implementation, when the smart TV is started, various operation data and fault information of the smart TV system are collected remotely and in real time through regular polling and event triggering. The operation data includes: system logs, device status information, network connection status, and user operation records.

[0071] Specifically, during the operation of the smart TV, the present invention collects system operation data and fault information in two main ways: periodic polling and event triggering.

[0072] Periodic polling is a method of actively collecting data adopted by the present invention. In the embodiment of the present invention, a request is automatically sent to the smart TV at a set time interval (such as every minute, every hour, etc.) to obtain the current operating status and fault information. This method ensures that the system can continuously monitor the performance and health status of the TV. For example, the network connection status and system log of the device can be checked every five minutes to detect potential problems in a timely manner.

[0073] Event triggering is a passive data collection method adopted by the present invention. Under this collection method, relevant data will be automatically collected when a specific event occurs. For example, when a user performs an operation (such as opening an application, adjusting the volume, switching channels, etc.), the present invention will immediately record these operations and their results. For example, when a user tries to connect to Wi-Fi, if the connection fails, the present invention will automatically record the event and its related fault information (such as error code, signal strength, etc.).

[0074] Through the above two methods, the embodiment of the present invention can collect the following important operating data:

[0075] 1) System log: records historical information of system operation, including startup time, error information, crash records, etc.

[0076] 2) Device status information: including the TV’s power status, hardware status (such as CPU and memory usage), software version, etc.

[0077] 3) Network connection status: monitor the strength, delay, packet loss rate, etc. of the network connection to ensure smooth streaming media playback and online services.

[0078] 4) User operation records: record user operation habits and preferences to help analyze user behavior and optimize user experience.

[0079] For example, if a user encounters a video freeze problem when watching streaming media on a smart TV, through regular polling, the embodiment of the present invention can detect that the network connection is not good and record relevant network data (such as signal strength and delay). At the same time, when the user tries to reconnect to Wi-Fi, the event trigger mechanism will record the connection failure event and its error code.

[0080] It can be seen that, through regular polling and event triggering, the present invention can monitor the operation status of the smart TV in real time, discover and solve problems in time, thereby improving the reliability of the equipment and user satisfaction. The collected system logs and fault information can help the technical support team to quickly locate the problem, reduce the troubleshooting time, and improve service efficiency. The collected operation data provides manufacturers with valuable market feedback, which can be used for product improvement, function update and new product development.

[0081] Step S300: Using artificial intelligence algorithms to identify fault patterns and infer causes of the collected operating data and fault information, and generating preliminary diagnostic results of the fault problem;

[0082] In the embodiment of this step, an artificial intelligence algorithm can be used in the remote cloud to analyze the collected operating data and fault information to identify the fault mode and infer the cause of the fault.

[0083] Specifically, in this step embodiment, the collected diverse operation data and fault information are preprocessed to clean and organize the data, wherein the preprocessing includes removing noise, filling missing values ​​and standardizing the data format, so that the data is more suitable for subsequent analysis.

[0084] The present invention uses artificial intelligence algorithms (such as machine learning models) to extract important features from pre-processed operating data and fault information. These features are key to identifying fault modes, such as network latency, CPU usage, and user operation frequency.

[0085] Regarding fault mode identification, the present invention can use algorithms (such as cluster analysis, classification models, etc.) to analyze the extracted features to identify potential fault modes. For example, it can be known from historical data that when the CPU usage exceeds a certain threshold, users may experience video freezes.

[0086] The cause inference and preliminary diagnosis in the present invention are specifically that the present invention can provide preliminary fault diagnosis results, including recommended solutions or further inspection steps, based on the identified fault mode through an algorithm. This stage may involve the use of complex models such as decision trees and neural networks, so that the system can find correlations in rich data patterns.

[0087] For example, taking the problem of frequent restarts of a smart TV as an example, the present invention can obtain a large amount of operating data and user operation records through data collection, including system logs, device status and network connection information.

[0088] Then, in the data preprocessing stage, the embodiment of the present invention can first integrate various data, clean and standardize them, and then prepare for feature extraction.

[0089] Then, during feature extraction, the algorithm can be used to analyze features related to restart, such as CPU usage, memory usage, and network speed.

[0090] During fault mode identification, by training the model, the embodiment of the present invention can find that the probability of a device restarting significantly increases in certain specific situations (such as when an application processes multiple high-resolution streaming media).

[0091] When inferring the cause and making a preliminary diagnosis, the present invention can finally give a preliminary diagnostic result, such as "the device restarts under high load, which may be related to excessive CPU usage or internal temperature", and recommends that the user close some background applications or adjust the device ventilation.

[0092] It can be seen from the above examples that the present invention can not only quickly identify and diagnose problems, but also provide targeted suggestions to help users effectively deal with potential failures. This intelligent processing allows users to experience a smoother and less problematic experience when using smart TVs, thereby improving overall satisfaction.

[0093] In the embodiment of this step, the artificial intelligence algorithm can identify hidden fault modes through large-scale data analysis, thereby improving the accuracy and sensitivity of fault detection and reducing false positives and false negatives. And through automated algorithm analysis, it is possible to quickly generate preliminary diagnostic results of the fault, which greatly shortens the response time compared to the manual review process and improves the user experience. Moreover, the present invention can infer the cause based on real-time data, adjust the performance and settings of the TV in real time, or give optimized operation suggestions and downgrade user intervention. And the present invention also has the ability to learn and self-optimize, because the algorithm using machine learning can learn from each fault, and as the data accumulates, the accuracy of the model is improved, and the more it is used, the smarter it becomes.

[0094] In a further embodiment, the step S300 specifically includes:

[0095] S301, establishing a fault pattern recognition model by analyzing historical operation data and fault information in advance;

[0096] In this step, in this stage, the historical operation data and fault information are first analyzed in depth, with the goal of identifying the fault modes that occurred in the past and establishing a fault mode recognition model based on these modes. In the embodiment of the present invention, by learning from the historical data, this model will be able to understand which factors may cause faults under specific conditions, laying the foundation for subsequent fault diagnosis.

[0097] In this step, the fault pattern recognition model is constructed using historical data to improve the accuracy of diagnosis. By learning the fault pattern, the model can quickly identify similar fault conditions, reduce the time of manual judgment and reduce the possibility of error.

[0098] S302, performing data cleaning and preprocessing on the collected operation data and fault information to obtain preprocessed operation data and fault information;

[0099] In this step, the present invention cleans and preprocesses the collected operating data and fault information, including removing noise, filling missing values, standardizing data formats, etc. After these steps, the obtained preprocessed data will be more standardized and suitable for modeling and analysis.

[0100] Data cleaning and preprocessing can ensure data quality and make subsequent analysis more accurate. Effective data cleaning can reduce model failures caused by data errors or inconsistencies, thereby improving the success rate of fault detection.

[0101] S303. By establishing a fault pattern recognition model and using machine learning and data mining techniques, fault pattern recognition and cause inference are performed on the pre-processed operating data and fault information, possible fault causes are inferred, and a preliminary diagnosis result of the fault problem is generated.

[0102] In the embodiment of the present invention, the pre-processed operation data and fault information are analyzed by using the fault pattern recognition model established in S301, as well as machine learning and data mining techniques. By identifying patterns in existing data, fault pattern judgment and inference of potential fault causes are performed, which will generate a preliminary diagnosis result of the fault problem.

[0103] The present invention can efficiently process large-scale data through machine learning and data mining technology, automatically identify potential failure modes and causes, and greatly improve the speed and accuracy of fault diagnosis. In addition, the preliminary diagnosis results can provide a reference for subsequent manual intervention and reduce equipment downtime.

[0104] Step S400: searching a preset fault problem repair knowledge base according to the generated preliminary diagnosis result of the fault problem, and generating a fault repair solution corresponding to the fault information problem;

[0105] In the embodiment of this step, based on the preliminary diagnosis result of the fault problem generated in the previous step, the preset fault problem repair knowledge base of the present invention will be searched. This preset knowledge base pre-collects and stores various fault information problems, and repair solutions corresponding to the fault information problems, as well as maintenance experience, fault solutions and related technical documents, aiming to provide repair guidance for specific faults. By analyzing the preliminary diagnosis results, the embodiment of the present invention will locate the corresponding fault repair solution and generate specific repair suggestions.

[0106] In this way, the efficiency of fault repair can be improved. After a fault occurs, technicians no longer need to spend a lot of time analyzing the problem and looking for a repair solution. The present invention can quickly match the corresponding solution by searching the preset fault problem repair knowledge base based on the generated preliminary diagnosis results of the fault problem through remote diagnosis, thereby speeding up the fault repair process. And by establishing a fault repair knowledge base, the maintenance technology and experience within the organization can form a systematic knowledge accumulation, reduce errors caused by lack of experience, and improve the overall technical level of the maintenance team. And the use of standardized repair solutions can ensure that when different maintenance personnel perform maintenance, the same method is used to handle similar faults, thereby reducing the differences and risks caused by human factors.

[0107] In a further embodiment, the step S400 specifically includes:

[0108] S401, obtaining a generated preliminary diagnosis result of a fault problem;

[0109] At this stage, the remote diagnosis system of the smart TV of the embodiment of the present invention will first receive and process the fault information reported by the user, and analyze the preliminary diagnosis results of the fault problem through the built-in fault detection model. This may include identifying the nature of the fault, possible causes, and the context in which the fault occurred, such as the application being viewed by the user or the current network status.

[0110] S402. Based on the generated preliminary diagnosis result of the fault problem, search for a fault repair solution that matches the fault information problem in a preset fault problem repair knowledge base; wherein the considerations of the fault repair solution corresponding to the fault information problem include: fault type and severity, user's technical ability, and existing hardware and software environment.

[0111] In this step, according to the preliminary diagnosis result generated in S401, a preset fault problem repair knowledge base is accessed to automatically search for a fault repair solution that matches the fault information. In the matching process, the present invention will consider several important factors:

[0112] 1) Fault type and severity: The present invention will evaluate the specific type of fault (such as no image signal, freeze, audio problem, etc.) and severity (for example, whether it affects normal use or is just a minor problem) to prioritize major problems.

[0113] 2) User's technical ability: Considering the user's technical level, the complexity of the suggestions will be adjusted accordingly in the present invention. For example, for users with weaker technical ability, simple and easy-to-understand steps and interfaces should be provided for operation.

[0114] 3) Existing hardware and software environment: The present invention will identify the user's device configuration and software version to ensure that the provided solution is compatible with the user's environment and avoid inappropriate repair suggestions.

[0115] For example, taking the example of a user encountering a problem when using a smart TV, by detecting the operating data of the smart TV during use, it is identified that the smart TV is currently "unable to connect to the network".

[0116] Obtaining preliminary diagnosis results (S401): After receiving the fault report, the remote diagnosis system of the embodiment of the present invention uses a built-in algorithm to analyze the user's smart TV status and obtains a preliminary diagnosis of "network connection failure". During the analysis, the system finds that the signal strength is low or the DNS setting may be incorrect.

[0117] Finding a fault repair solution (S402): Next, the present invention searches for a repair solution matching the "network connection fault" in a preset fault repair knowledge base. Meanwhile, the following factors are taken into consideration:

[0118] Regarding the type and severity of the failure: This is a connection issue that affects the user's viewing experience, so it needs to be dealt with quickly.

[0119] Regarding the user's technical ability: If the system detects that the user may not be very familiar with network settings, it will prioritize simple suggestions to restart the router rather than complex network configuration steps.

[0120] Regarding the existing hardware and software environment: The system will check the user's TV model, confirm the firmware version it is running, and provide a solution that suits it, such as possibly updating network settings or reconnecting to Wi-Fi.

[0121] Finally, find the troubleshooting solution that matches the problem in the fault information, such as "Please try restarting your router and reconnecting to Wi-Fi. If you still can't connect, please check the DNS configuration in the settings."

[0122] It can be seen that the embodiment of the present invention can significantly improve the efficiency of problem solving and improve the user experience through such a remote diagnosis process.

[0123] Step S500: presenting and displaying the generated fault repair solution corresponding to the fault information problem in a graphical interface and / or voice form, and automatically guiding the completion of corresponding repair operations.

[0124] Specifically, in an embodiment of the present invention, the generated fault repair solution corresponding to the fault information problem can be presented through a graphical interface and / or voice form, wherein the graphical interface displays detailed operation steps and solutions on a TV screen, and the voice form guides the user to troubleshoot the problem through voice interaction; and controls the push of notifications and operation instructions through the application on the corresponding mobile device to automatically guide the completion of the corresponding repair operations.

[0125] In the embodiment of the present invention, at this stage, the generated fault repair solution is presented to the user through a user-friendly graphical interface and / or voice of the smart TV so that the user can understand and perform the corresponding repair operation. This presentation method is intended to allow the user to easily follow the guidance steps and quickly solve the fault problem.

[0126] For example, suppose a user's smart TV encounters a "video playback freeze" problem when watching a video, and the remote diagnosis system has generated a fault repair plan. The repair plan is presented as follows:

[0127] Regarding the graphical interface display: The present invention will pop up a user-friendly interface on the screen of the smart TV. In the interface, the specific steps of the fault repair solution will be displayed, including high-definition icons and concise text instructions. For example, "Step 1: Check network connection" may be accompanied by a graphic representation of the network signal strength, prompting the user how to check the strength of the Wi-Fi signal.

[0128] Regarding voice guidance: In addition, the present invention can also play voice guidance through the speaker of the TV to guide the user step by step, for example: "Please check the network signal icon in the upper left corner of the screen to ensure that the network connection is normal."

[0129] About automatic guidance to complete the corresponding repair operations:

[0130] If the user encounters any problems while executing the steps, the embodiment of the present invention will provide immediate feedback. For example, if the user confirms that the network connection is normal according to the first step but the problem still exists, an additional prompt may appear on the interface, such as "The network connection is normal, but the speed is slow, please try restarting the router."

[0131] If the user successfully completes a certain operation, the embodiment of the present invention will automatically update its status and guide the user to the next step, for example: "You have confirmed that the network connection is normal, please proceed to the next step: clean up the application cache." This can be reflected through a progress bar or step mark in the graphical interface, so that the user can understand which operations he has completed and what needs to be done.

[0132] Regarding feedback and confirmation of completion: In the embodiment of the present invention, after the user completes all steps, the user can be asked through a graphical interface: "Is the problem solved?" and provide two options of "Yes" and "No". If the user feedbacks "No", the system will automatically re-analyze the fault and provide a new repair plan.

[0133] If the problem has been solved, the user will see a prompt "Congratulations, the problem has been solved! Thank you for using our service.", which increases user satisfaction.

[0134] It can be seen that the present invention presents the fault repair solution in the form of a graphical interface and voice, which not only improves the user's operating experience, but also reduces the obstacles caused by differences in technical capabilities, allowing more users to independently and effectively handle common faults of smart TVs. In addition, through the real-time feedback mechanism, the system can achieve adaptive guidance to ensure that users feel smooth and effective when solving problems.

[0135] The following is a further detailed description of the smart TV remote diagnosis and repair processing method of the present invention through a specific application embodiment:

[0136] When implementing the specific application embodiment of the present invention, the software architecture must be carried out first, including: 1). Back-end server: deployed in the cloud, responsible for data analysis, knowledge base management and solution generation. The technology stack used includes Python, TensorFlow, MySQL, etc. 2). Front-end application: deployed on TVs and mobile devices, responsible for data collection and user interaction. The technology stack used includes React Native, Android / iOS development framework, etc. 3). Data transmission protocol: HTTP / HTTPS protocol is used to achieve secure data transmission.

[0137] like Figure 2 As shown, this specific application embodiment 2 provides a smart TV remote diagnosis and repair processing method, including the following steps:

[0138] Step S10, power on, and proceed to step S11;

[0139] Step S11, data collection, collecting operation data and fault information, and proceeding to step S12;

[0140] After the TV system is started, the data collection module starts working to collect operating data and fault information; and sends the collected data to the cloud server via the Internet.

[0141] Step S12: Analyze the diagnostic model data, identify the fault mode and infer the cause, and then proceed to step S13;

[0142] Step S13, generate a preliminary diagnosis result, and proceed to step S14;

[0143] The data analysis module in the cloud performs fault pattern identification and cause inference to generate preliminary diagnostic results.

[0144] Step S14, connect to the preset fault problem repair knowledge base for matching, and proceed to step S15;

[0145] In the embodiment of this step, according to the diagnosis result, a preset fault problem repair knowledge base is connected, and a matching repair solution is retrieved from the knowledge base.

[0146] Step S15, output the repair plan and proceed to step S16;

[0147] Generate a repair plan suitable for the user, including specific operation steps.

[0148] Step S16, display the repair plan and notify the user, and then proceed to step S17;

[0149] In this embodiment, the smart TV will present the corresponding repair plan to the user and guide him to complete the corresponding operations.

[0150] Step S17, according to the displayed repair solution, perform a repair operation to repair the problem, and proceed to step S18;

[0151] Step S18: The user provides feedback on the repair status, and the process ends when the problem is repaired.

[0152] In the embodiment of the present invention, after the repair operation is completed according to the displayed repair solution, user feedback and operation results are collected to improve the diagnosis model and knowledge base.

[0153] The present invention provides an example of a smart TV fault diagnosis process embodiment as follows:

[0154] S21. Initialization: When the user finds that there is a problem with the TV, he / she selects the "remote diagnosis" function through the TV system interface.

[0155] S22, data collection: The TV system starts collecting data, including system logs, device status, network status, etc.

[0156] S23, upload data: automatically upload the collected data to the cloud server.

[0157] S24, analysis and diagnosis: The data analysis module on the server side processes and analyzes the uploaded data, identifies the cause of the fault and generates preliminary diagnosis results.

[0158] S25, searching for solutions: according to the diagnosis results, the preset fault problem repair knowledge base is retrieved for relevant repair solutions.

[0159] S26, generating guidance: generating specific operation steps and guidance suitable for the user, and presenting them to the user through the user interaction module.

[0160] S27, operation execution: The user performs the operation according to the instructions, and the system monitors the operation progress in real time and provides feedback.

[0161] S28. Result feedback: After the operation is completed, the system collects the results and feeds them back to the cloud to optimize the diagnostic model and knowledge base.

[0162] Of course, in a further embodiment of the present invention, the preset fault problem repair knowledge base can be updated, specifically in the following two ways:

[0163] One is through manual updating, where professional maintenance personnel regularly input new fault information and repair solutions to update the knowledge base. Another way is automatic learning of the preset fault problem repair knowledge base: in the present invention, the fault identification model and solution are automatically learned and optimized based on user feedback and operation results.

[0164] Of course, in a further embodiment of the present invention, the specific operation steps and instructions suitable for the user are generated and presented to the user through the user interaction module, wherein the interactive interface can adopt a graphical interface, that is, the detailed diagnosis results and operation steps are displayed on the main screen of the TV, including text and image descriptions. The voice assistant method can broadcast the operation steps by voice and answer the user's questions in real time. In addition, mobile notifications can also be used, such as pushing operation instructions and reminder information on the mobile device bound to the user.

[0165] It can be seen that the embodiment of the present invention realizes remote diagnosis and troubleshooting of the TV system by introducing AI technology and knowledge base, improves the efficiency and accuracy of fault handling, and reduces the cost and inconvenience of users. The system has broad application prospects and will play an important role in the fields of smart home and Internet of Things.

[0166] Exemplary Devices

[0167] like Figure 3 As shown, an embodiment of the present invention provides a smart TV remote diagnosis and repair processing device, the device comprising:

[0168] The presetting module 310 is used to store various fault information problems of the smart TV and the repair solutions corresponding to the fault information problems in a preset fault problem repair knowledge base;

[0169] The data acquisition module 320 is used to acquire operation data and fault information related to the smart TV system;

[0170] The data analysis module 330 is used to use artificial intelligence algorithms to identify fault patterns and infer causes of the collected operating data and fault information, and generate preliminary diagnosis results of the fault problem;

[0171] A solution matching module 340 is used to search a preset fault problem repair knowledge base according to the generated preliminary diagnosis result of the fault problem, and generate a fault repair solution corresponding to the fault information problem;

[0172] The solution display module 350 is used to present the generated fault repair solution corresponding to the fault information problem in a graphical interface and / or voice form, and automatically guide the completion of the corresponding repair operation, as described above.

[0173] Based on the above embodiments, the present invention further provides an intelligent terminal, whose principle block diagram can be shown as follows: Figure 4 As shown. The smart terminal includes a processor, a memory, a network interface, a display screen, and a database connected through a system bus. Among them, the processor of the smart terminal is used to provide computing and control capabilities. The memory of the smart terminal includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the smart terminal is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for remote diagnosis and repair processing of a smart TV is implemented. The database of the smart terminal is used to store a remote diagnosis and repair processing program for a smart TV.

[0174] Those skilled in the art will understand that Figure 4 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the smart terminal to which the scheme of the present invention is applied. The specific smart terminal may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0175] In one embodiment, a smart terminal is provided, comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, and the one or more programs include instructions for performing the following operations:

[0176] Collect and obtain operation data and fault information related to smart TV systems;

[0177] Use artificial intelligence algorithms to identify fault patterns and infer causes of collected operating data and fault information, and generate preliminary diagnostic results of fault problems;

[0178] According to the generated preliminary diagnosis result of the fault problem, a preset fault problem repair knowledge base is searched to generate a fault repair plan corresponding to the fault information problem;

[0179] The generated fault repair solution corresponding to the fault information problem is presented and displayed in the form of a graphical interface and / or voice, and automatically guides the completion of the corresponding repair operation, as described above.

[0180] The step of collecting and acquiring operation data and fault information related to the smart TV system includes:

[0181] Various fault information problems of the smart TV and repair solutions corresponding to the fault information problems are stored in a preset fault problem repair knowledge base in advance.

[0182] The step of collecting and acquiring operation data and fault information related to the smart TV system includes:

[0183] When the smart TV is started, various operating data and fault information of the smart TV system are collected in real time through regular polling and event triggering. The operating data includes: system log, device status information, network connection status, and user operation records.

[0184] The step of using an artificial intelligence algorithm to identify fault patterns and infer causes of the collected operating data and fault information to generate a preliminary diagnosis result of the fault problem includes:

[0185] Establish a fault pattern recognition model by analyzing historical operation data and fault information in advance;

[0186] Perform data cleaning and preprocessing on the collected operation data and fault information to obtain preprocessed operation data and fault information;

[0187] By establishing a fault pattern recognition model and using machine learning and data mining techniques, fault pattern recognition and cause inference are performed on the pre-processed operating data and fault information, possible fault causes are inferred, and preliminary diagnostic results of the fault problem are generated.

[0188] The step of searching a preset fault problem repair knowledge base according to the generated preliminary diagnosis result of the fault problem and generating a fault repair solution corresponding to the fault information problem includes:

[0189] Obtain the preliminary diagnosis results of the generated fault problem;

[0190] According to the generated preliminary diagnosis result of the fault problem, a fault repair solution that matches the fault information problem is searched in a preset fault repair knowledge base;

[0191] Among them, the considerations of the fault repair solution corresponding to the fault information problem include: fault type and severity, user's technical ability, and existing hardware and software environment.

[0192] The step of presenting the generated fault repair solution corresponding to the fault information problem in a graphical interface and / or voice form and automatically guiding the completion of the corresponding repair operation includes:

[0193] The generated fault repair plan corresponding to the fault information problem is presented in a graphical interface and / or voice form, wherein the graphical interface displays detailed operation steps and solutions on the TV screen, and the voice form guides the user to troubleshoot the problem through voice interaction; and controls the push notification and operation guidance through the application on the corresponding mobile device to automatically guide the completion of the corresponding repair operation.

[0194] The fault problem repair knowledge base stores various fault information problems of smart TVs related to fault diagnosis and repair, and repair solutions corresponding to the fault information problems, including:

[0195] Common faults and their characteristics, methods of repairing various faults, and diagnostic and repair procedures;

[0196] The knowledge base for controlling fault repair can be maintained and updated through manual input and automatic learning, as described above.

[0197] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0198] In summary, the present invention provides a method, device, intelligent terminal and storage medium for remote diagnosis and repair of smart TVs. The present invention relates to remote diagnosis and fault repair of a TV system implemented by software, which analyzes the collected data through AI technology, and combines the knowledge base of the problem repair method to obtain a recommended solution and send it to the user through the network. The present invention can improve the efficiency of TV repair, reduce the inconvenience caused to users by equipment failure, and reduce the demand for on-site services, providing convenience for users.

Claims

1. A method for remote diagnosis and repair of a smart TV, characterized in that: include: Collect and obtain operation data and fault information related to smart TV systems; Use artificial intelligence algorithms to identify fault patterns and infer causes of collected operating data and fault information, and generate preliminary diagnostic results of fault problems; According to the generated preliminary diagnosis result of the fault problem, a preset fault problem repair knowledge base is searched to generate a fault repair plan corresponding to the fault information problem; The generated fault repair plan corresponding to the fault information problem is presented and displayed through a graphical interface and / or voice, and automatically guides the completion of the corresponding repair operations.

2. The method for remote diagnosis and repair of a smart TV according to claim 1, characterized in that: The step of collecting and obtaining operation data and fault information related to the smart TV system includes: Various fault information problems of the smart TV and repair solutions corresponding to the fault information problems are stored in a preset fault problem repair knowledge base in advance.

3. The method for remote diagnosis and repair of a smart TV according to claim 1, characterized in that: The step of collecting and acquiring operation data and fault information related to the smart TV system includes: When the smart TV is started, various operating data and fault information of the smart TV system are collected in real time through regular polling and event triggering. The operating data includes: system log, device status information, network connection status, and user operation records.

4. The method for remote diagnosis and repair of a smart TV according to claim 1, characterized in that: The step of using an artificial intelligence algorithm to identify fault patterns and infer causes of the collected operating data and fault information to generate a preliminary diagnosis result of the fault problem includes: Establish a fault pattern recognition model by analyzing historical operation data and fault information in advance; Perform data cleaning and preprocessing on the collected operation data and fault information to obtain preprocessed operation data and fault information; By establishing a fault pattern recognition model and using machine learning and data mining techniques, fault pattern recognition and cause inference are performed on the pre-processed operating data and fault information, possible fault causes are inferred, and preliminary diagnostic results of the fault problem are generated.

5. The method for remote diagnosis and repair of a smart TV according to claim 1, characterized in that: The step of searching a preset fault problem repair knowledge base according to the generated preliminary diagnosis result of the fault problem and generating a fault repair solution corresponding to the fault information problem comprises: Obtain the preliminary diagnosis results of the generated fault problem; According to the generated preliminary diagnosis result of the fault problem, a fault repair solution that matches the fault information problem is searched in a preset fault repair knowledge base; Among them, the considerations of the fault repair solution corresponding to the fault information problem include: fault type and severity, user's technical ability, and existing hardware and software environment.

6. The method for remote diagnosis and repair of a smart TV according to claim 1, characterized in that: The step of presenting the generated fault repair solution corresponding to the fault information problem in a graphical interface and / or voice form and automatically guiding the completion of the corresponding repair operation includes: The generated fault repair plan corresponding to the fault information problem is presented in a graphical interface and / or voice form, wherein the graphical interface displays detailed operation steps and solutions on the TV screen, and the voice form guides the user to troubleshoot the problem through voice interaction; and controls the push notification and operation guidance through the application on the corresponding mobile device to automatically guide the completion of the corresponding repair operation.

7. The method for remote diagnosis and repair of a smart TV according to claim 2, characterized in that: The fault problem repair knowledge base stores various fault information problems of smart TVs related to fault diagnosis and repair, and repair solutions corresponding to the fault information problems, including: Common faults and their characteristics, repair methods for various faults, and diagnosis and repair procedures; The knowledge base for controlling fault repair can be maintained and updated through manual input and automatic learning.

8. A remote diagnosis and repair processing device for a smart TV, characterized in that: The device comprises: A pre-setting module is used to store various fault information problems of the smart TV and repair solutions corresponding to the fault information problems in a preset fault problem repair knowledge base; A data acquisition module is used to acquire operation data and fault information related to the smart TV system; The data analysis module is used to use artificial intelligence algorithms to identify fault patterns and infer causes of the collected operating data and fault information, and generate preliminary diagnostic results of the fault problem; A solution matching module is used to search a preset fault problem repair knowledge base according to the generated preliminary diagnosis result of the fault problem, and generate a fault repair solution corresponding to the fault information problem; The solution display module is used to present the generated fault repair solution corresponding to the fault information problem through a graphical interface and / or voice, and automatically guide the completion of the corresponding repair operation.

9. An intelligent terminal, characterized in that: The device comprises a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, and the one or more programs include being used to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method as described in any one of claims 1 to 7.

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