Electronic apparatus and the method thereof

Abstract

An electronic device according to one embodiment of the present invention comprises a processor that acquires state data regarding the operation of a plurality of components of the electronic device, identifies a state error of a first component among the plurality of components based on the acquired state data, acquires error data indicating a mutual correlation between the identified state error of the first component and a second component that causes the state error, identifies the possibility of occurrence of the state error of the first component based on the acquired state data and error data, and performs an error-related operation for the second component associated with the state error of the first component for which the possibility of occurrence has been identified.

Description

Technology Field

[0001] The present disclosure relates to an electronic device and a control method thereof for resolving the occurrence of an error in an electronic device. Background Technology

[0002] As the types and functions of electronic devices become more diverse, interest in detecting errors occurring in electronic devices and solutions for them is increasing.

[0003] If an electronic device cannot detect the occurrence of an error on its own, or cannot identify or improve conditions where an error is likely to occur in advance, it can only resolve the issue when the error actually occurs.

[0004] Alternatively, even if an error occurs in an electronic device, if the system only retains information regarding errors that frequently occur in the device or predefined errors, it may notify the user of the error or provide a guide to resolve it only if information corresponding to the error exists. In this case, the conditions under which the user takes action and the conditions under which a service engineer takes action are not significantly different in the predetermined guide. Therefore, when an engineer takes action, the reality is that differentiated services are provided based on the engineer's experience and capabilities, in addition to the given service guide.

[0005] Furthermore, predefined diagnoses or solutions can lead to secondary problems caused by incorrect diagnoses and services, or result in reduced service reliability due to re-services. This leads to unnecessary services, causing intangible losses by damaging the product and company image, while frequently incurring tangible quality costs due to re-services and multiple parts services resulting from incorrect diagnoses. The problem to be solved

[0006] The purpose of the present disclosure is to provide an electronic device and a control method therefor that can more efficiently predict and prevent errors. means of solving the problem

[0007] An electronic device according to one embodiment of the present invention comprises a processor that acquires state data regarding the operation of a plurality of components of the electronic device, identifies a state error of a first component among the plurality of components based on the acquired state data, acquires error data indicating a mutual correlation between the identified state error of the first component and a second component that causes the state error, identifies the possibility of occurrence of the state error of the first component based on the acquired state data and error data, and performs an error-related operation for the second component associated with the state error of the first component for which the possibility of occurrence has been identified.

[0008] The above error data may include a model trained to perform operations regarding the mutual correlation between the state error of the identified first configuration and the second configuration that causes the state error.

[0009] The processor may display a graphic user interface (GUI) on a display that indicates a state error of the first configuration and parameters of the second configuration corresponding to the state error.

[0010] The above processor can perform error-related operations for the second configuration based on user input received using the GUI.

[0011] The above processor can perform error-related operations by changing the settings of the parameters regarding the second configuration so that the probability of the state error occurring is reduced.

[0012] If the probability of the state error occurring is not reduced through the setting of the changed parameters, the processor may display a GUI on a display showing the state error of the first configuration and the parameters of the second configuration corresponding to the state error, and perform an error-related operation for the second configuration based on user input received using the GUI.

[0013] The above processor can periodically identify whether there is a possibility of a state error of the first configuration occurring.

[0014] A method for controlling an electronic device according to an embodiment of the present invention may include: a step of acquiring state data regarding the operation of a plurality of components of the electronic device; a step of identifying a state error of a first component among the plurality of components based on the acquired state data; a step of acquiring error data indicating a mutual correlation between the identified state error of the first component and a second component that is the cause of the state error; a step of identifying the possibility of occurrence of the state error of the first component based on the acquired state data and error data; and a step of performing an error-related operation for the second component associated with the state error of the first component for which the possibility of occurrence has been identified.

[0015] The above error data may include a model trained to perform operations regarding the mutual correlation between the state error of the identified first configuration and the second configuration that causes the state error.

[0016] The method may further include the step of displaying a graphic user interface (GUI) on a display that indicates a state error of the first configuration and parameters of the second configuration corresponding to the state error.

[0017] It may include a step of performing an error-related operation for the second configuration based on user input received using the GUI.

[0018] The step of performing an error-related operation may include the step of performing an error-related operation by changing the setting of the parameter regarding the second configuration so that the probability of the state error occurring is lowered.

[0019] The step of performing an error-related operation may include: displaying a GUI on a display that indicates the state error of the first configuration and the parameter of the second configuration corresponding to the state error when the probability of the state error occurring is not reduced through the setting of the changed parameter; and performing an error-related operation for the second configuration based on user input received using the GUI.

[0020] The step of identifying the possibility of a state error of the first configuration may include the step of periodically identifying whether there is a possibility of a state error of the first configuration occurring.

[0021] In a recording medium storing a computer program that includes code for performing a control method of an electronic device as computer-readable code, the control method of the electronic device may include: a step of acquiring state data regarding the operation of a plurality of components of the electronic device; a step of identifying a state error of a first component among the plurality of components based on the acquired state data; a step of acquiring error data indicating a mutual correlation between the identified state error of the first component and a second component that is the cause of the state error; a step of identifying the possibility of occurrence of the state error of the first component based on the acquired state data and error data; and a step of performing an error-related operation for the second component associated with the state error of the first component for which the possibility of occurrence has been identified. Effects of the invention

[0022] According to one embodiment of the present invention, the quality of the service can be standardized upward rather than varying according to individual capabilities.

[0023] According to one embodiment of the present invention, by applying artificial intelligence (AI) to monitor the possibility of error occurrence in real time and allowing the electronic device to maintain an optimal operating state on its own, errors can be prevented. Brief explanation of the drawing

[0024] FIG. 1 is a drawing illustrating the operation of an electronic device according to one embodiment of the present invention. FIG. 2 is a block diagram illustrating the configuration of an electronic device according to one embodiment of the present invention. FIG. 3 is a diagram illustrating the operation flowchart of an electronic device according to one embodiment of the present invention. FIG. 4 is a drawing illustrating the operation of an electronic device according to one embodiment of the present invention. FIG. 5 is a diagram illustrating the operation flowchart of an electronic device according to one embodiment of the present invention. FIG. 6 is a diagram illustrating the use of error data according to an embodiment of the present invention. FIG. 7 is a drawing illustrating the operation of an electronic device according to one embodiment of the present invention. Specific details for implementing the invention

[0025] Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the drawings, identical reference numbers or symbols refer to components that perform substantially the same function, and the size of each component in the drawings may be exaggerated for clarity and convenience of explanation. However, the technical concept of the present invention and its core components and operations are not limited only to the components or operations described in the following embodiments. In describing the present invention, if it is determined that a detailed description of known technologies or components related to the present invention may unnecessarily obscure the essence of the invention, such detailed description will be omitted.

[0026] In embodiments of the present invention, terms including ordinal numbers, such as first, second, etc., are used solely for the purpose of distinguishing one component from another, and singular expressions include plural expressions unless the context clearly indicates otherwise. Furthermore, in embodiments of the present invention, terms such as 'composed of,' 'include,' 'have,' etc., should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof. Additionally, in embodiments of the present invention, 'module' or 'part' performs at least one function or action and may be implemented in hardware or software, or as a combination of hardware and software, or may be implemented as an integrated unit of at least one module. Furthermore, in embodiments of the present invention, 'at least one' among a plurality of elements refers not only to all of the plurality of elements but also to each individual element excluding the remainder or all combinations thereof.

[0027] FIG. 1 is a drawing illustrating the operation of an electronic device according to one embodiment of the present invention.

[0028] In this drawing, an electronic device (100) including a first component (10), a second component (20), and a processor (180) is illustrated.

[0029] An electronic device (100) according to one embodiment of the present invention may be implemented as a TV, but is not limited thereto, and may be implemented as a smartphone, tablet PC, laptop PC, HMD (Head mounted Display), NED (Near Eye Display), LFD (large format display), Digital Signage, DID (Digital Information Display), video wall, projector display, QD (quantum dot) display panel, QLED (quantum dot light-emitting diodes), μLED (Micro light-emitting diodes), Mini LED, etc., and various types of displays, as well as a camera, camcorder, printer, server, etc.

[0030] Alternatively, the electronic device (100) may be implemented as a touch screen combined with a touch sensor, a flexible display, a rollable display, a 3D display, or a display in which multiple display modules are physically connected. Alternatively, the electronic device (100) may be in a state where there is no display unit, such as a Set-Top Box (STB), or a simple display unit for notifications, and may output images to an external device equipped with a separate display through a wired / wireless interface. In addition, it may be the system itself in which a cloud computing environment is established, and any device that processes data using an artificial intelligence model is not limited to this and can be applied.

[0031] The electronic device (100) includes a plurality of configurations including a first configuration (10) and a second configuration (20), and the configurations are not limited to hardware or software. For example, the configurations may refer to hardware configurations such as an HDMI port of the interface unit, a display of the display unit, a user input unit, etc., described later in FIG. 2, and may refer to software configurations such as a boot sequence.

[0032] Multiple components of the electronic device (100) may have errors during operation, which are referred to as state errors. State errors can be identified based on state data obtained regarding the operation of multiple components of the electronic device (100). State data refers to all data that can be collected in relation to the operation of multiple components.

[0033] According to one embodiment of the present invention, the first configuration (10) refers to a configuration in which a state error occurs or is expected to occur during the operation of an electronic device (100), and the second configuration (20) refers to a configuration that causes the state error. More specifically, the second configuration (20) is at least one configuration that can have a complex effect on the state error of the first configuration (10).

[0034] In the present invention, the electronic device (100), more specifically the processor (180), independently diagnoses the operation of a plurality of configurations and resets the first configuration (10) in which a state error is detected or the second configuration (20) that is the cause of the state error to an optimal state, or provides the correct guidance to the user so that the electronic device operates continuously in a stable state.

[0035] At this time, the electronic device (100) can perform calculations regarding the mutual correlation between the state error of the identified first configuration (10) and the second configuration (20) that causes the state error using artificial intelligence (AI) technology.

[0036] A processor (180) for executing AI technology can be implemented through a combination of software and a graphics-dedicated processor such as a GPU, VPU (Vision Processing Unit), or an AI-dedicated processor such as an NPU (Neural Processing Unit), in addition to a general-purpose processor such as a CPU, AP, DSP (Digital Signal Processor).

[0037] AI technology can consist of machine learning (deep learning) and technologies utilizing machine learning. Further details will be discussed later.

[0038] According to one embodiment of the present invention, since the possibility of a state error occurring is identified by utilizing an AI model learned based on state data regarding the operation of a plurality of configurations, more reliable results can be obtained.

[0039] FIG. 2 is a block diagram illustrating the configuration of an electronic device according to one embodiment of the present invention.

[0040] As illustrated in FIG. 2, the electronic device (100) may include an interface part (110).

[0041] The interface section (110) may include a wired interface section (111). The wired interface section (111) includes a connector or port to which an antenna capable of receiving a broadcast signal according to a broadcasting standard, such as terrestrial / satellite broadcasting, or a cable capable of receiving a broadcast signal according to a cable broadcasting standard, can be connected. As another example, the electronic device (100) may have an antenna capable of receiving a broadcast signal built in. The wired interface section (111) may include a connector or port according to a video and / or audio transmission standard, such as an HDMI port, DisplayPort, DVI port, Thunderbolt, composite video, component video, super video, SCART, etc. The wired interface section (111) may include a connector or port according to a universal data transmission standard, such as a USB port. The wired interface section (111) may include a connector or port to which an optical cable can be connected according to an optical transmission standard. The wired interface section (111) may include a connector or port, etc., to which an external microphone or an external audio device equipped with a microphone is connected, and to which an audio signal can be received or input from the audio device. The wired interface section (111) may include a connector or port, etc., to which an audio device such as a headset, earphones, or external speaker is connected, and to which an audio signal can be transmitted or output to the audio device. The wired interface section (111) may include a connector or port according to a network transmission standard such as Ethernet. For example, the wired interface section (111) may be implemented as a LAN card, etc., that is wiredly connected to a router or gateway.

[0042] The wired interface unit (111) is wired to an external device, such as a set-top box or an optical media player, or to an external display device, speaker, server, etc., in a 1:1 or 1:N (N is a natural number) manner through the connector or port, thereby receiving video / audio signals from the external device or transmitting video / audio signals to the external device. The wired interface unit (111) may include a connector or port that transmits video / audio signals separately.

[0043] In addition, according to the present embodiment, the wired interface part (111) is embedded in the electronic device (100), but may be implemented in the form of a dongle or module and may be attached to or detached from the connector of the electronic device (100).

[0044] The interface unit (110) may include a wireless interface unit (112). The wireless interface unit (112) may be implemented in various ways corresponding to the implementation form of the electronic device (100). For example, the wireless interface unit (112) may use wireless communication such as RF (radio frequency), Zigbee, Bluetooth, Wi-Fi, UWB (Ultra WideBand), and NFC (Near Field Communication) as a communication method. The wireless interface unit (112) may be implemented as a wireless communication module that performs wireless communication with an AP according to the Wi-Fi method, or as a wireless communication module that performs one-to-one direct wireless communication such as Bluetooth. The wireless interface unit (112) can transmit and receive data packets between itself and a server by wirelessly communicating with a server on a network. The wireless interface unit (112) may include an IR transmitter and / or an IR receiver capable of transmitting and / or receiving an IR (Infrared) signal according to an infrared communication standard. The wireless interface unit (112) may receive or input a remote control signal from a remote control or other external device, or transmit or output a remote control signal to another external device through the IR transmitter and / or the IR receiver. As another example, the electronic device (100) may transmit and receive a remote control signal to or from a remote control or other external device through a wireless interface unit (112) of a different type, such as Wi-Fi or Bluetooth.

[0045] The electronic device (100) may further include a tuner that tunes the received broadcast signal by channel when the video / audio signal received through the interface unit (110) is a broadcast signal.

[0046] When an electronic device (100) is implemented as a display device, it may include a display unit (120). The display unit (120) includes a display (121) capable of displaying an image on a screen. The display (121) is provided with a light-receiving structure such as a liquid crystal method or a self-emissive structure such as an OLED method. Depending on the structure of the display (121), the display unit (120) may additionally include additional configurations. For example, if the display (121) is a liquid crystal method, the display unit (120) includes a liquid crystal display panel, a backlight unit that supplies light, and a panel driving board that drives the liquid crystal of the liquid crystal display panel.

[0047] The electronic device (100) may include a user input unit (130). The user input unit (130) includes various types of input interface-related circuits provided to perform user input. The user input unit (130) can be configured in various forms depending on the type of electronic device (100), for example, a mechanical or electronic button unit of the electronic device (100), a remote controller separated from the electronic device (100), an input unit from an external device connected to the electronic device (100), a touchpad, a touchscreen installed on a display unit (120), etc.

[0048] The electronic device (100) may include a storage unit (140). The storage unit (140) stores digitized data. The storage unit (140) includes storage with non-volatile properties that can preserve data regardless of whether power is provided, and memory with volatile properties in which data to be processed by the processor (180) is loaded and data cannot be preserved if power is not provided. Storage includes flash memory, hard-disc drive (HDD), solid-state drive (SSD), and ROM (Read Only Memory), and memory includes buffer and RAM (Random Access Memory).

[0049] The storage unit (140) may store information regarding an artificial intelligence model including multiple layers. Here, storing information regarding an artificial intelligence model may mean storing various information related to the operation of the artificial intelligence model, such as information regarding multiple layers included in the artificial intelligence model, and information regarding parameters used in each of the multiple layers (e.g., filter coefficients, bias, etc.). For example, according to one embodiment, the storage unit (140) may store information regarding an artificial intelligence model trained to acquire upscaling information of an input image (or information related to speech recognition, object information within an image, etc.). However, if the processor is implemented as hardware dedicated to the artificial intelligence model, the information regarding the artificial intelligence model may be stored in the processor's internal memory.

[0050] The electronic device (100) may include a microphone (150). The microphone (150) collects sounds from the external environment, including user voice. The microphone (150) transmits the collected sound signal to a processor (180). The electronic device (100) may be equipped with a microphone (150) that collects user voice, or may receive voice signals from an external device, such as a remote controller or smartphone, that has a microphone, through an interface unit (110). A remote controller application may be installed on the external device to control the electronic device (100) or perform functions such as voice recognition. In the case of an external device with such an application installed, user voice can be received, and since the external device can transmit and receive data and control the electronic device (100) using Wi-Fi / BT or infrared, a plurality of interface units (110) capable of implementing the above communication method may exist within the electronic device (100).

[0051] The electronic device (100) may include a speaker (160). The speaker (160) outputs audio data processed by the processor (180) as sound. The speaker (160) may include a unit speaker provided to correspond to audio data of one audio channel, and may include multiple unit speakers to correspond to audio data of multiple audio channels. In another embodiment, the speaker (160) may be provided separately from the electronic device (100), in which case the electronic device (100) may transmit audio data to the speaker (160) through the interface unit (110).

[0052] The electronic device (100) may include a sensor (170). The sensor (170) may detect the state of the electronic device (100) or the state of the electronic device (100) and transmit the detected information to a processor (180). The sensor (170) may include at least one of a magnetic sensor, an acceleration sensor, a temperature / humidity sensor, an infrared sensor, a gyroscope sensor, a position sensor (e.g., GPS), a barometric pressure sensor, a proximity sensor, and an RGB sensor (illuminance sensor), but is not limited thereto. Since the function of each sensor can be intuitively inferred by a person skilled in the art from its name, a detailed description is omitted. The processor (180) may store the sensing value defined by the tap between the electronic device (100) and the external device (200) in a storage unit (140). Subsequently, when a user event is detected, the processor (180) can identify whether the user event has occurred based on whether the detected sensing value corresponds to a stored sensing value.

[0053] The electronic device (100) may include a processor (180). The processor (180) includes one or more hardware processors, such as a CPU, chipset, buffer, and circuit, which are mounted on a printed circuit board, and may be implemented as a system on chip (SOC) depending on the design method. When the electronic device (100) is implemented as a display device, the processor (180) includes modules corresponding to various processes, such as a demultiplexer, decoder, scaler, audio DSP (Digital Signal Processor), and amplifier. Here, some or all of these modules may be implemented as an SOC. For example, modules related to image processing, such as a demultiplexer, decoder, and scaler, may be implemented as an image processing SOC, and the audio DSP may be implemented as a chipset separate from the SOC.

[0054] The processor (180) can be controlled to process input data according to a predefined operation rule or artificial intelligence model stored in the storage unit (140). Alternatively, if the processor (180) is a dedicated processor (or an artificial intelligence dedicated processor), it can be designed with a hardware structure specialized for processing a specific artificial intelligence model. For example, hardware specialized for processing a specific artificial intelligence model can be designed as a hardware chip such as an ASIC or FPGA.

[0055] Output data can take various forms depending on the type of artificial intelligence model. For example, output data may include, but is not limited to, images with enhanced resolution, information regarding objects contained within images, and text corresponding to speech.

[0056] When the processor (180) acquires a voice signal for a user's voice by means of a microphone (150) or the like, it can convert the voice signal into voice data. At this time, the voice data may be text data obtained through a Speech-to-Text (STT) processing process that converts the voice signal into text data. The processor (180) identifies a command indicated by the voice data and performs an operation according to the identified command. The voice data processing process and the command identification and execution process may all be executed in the electronic device (100). However, in this case, the system load and required storage capacity of the electronic device (100) become relatively large, so at least some of the processes may be performed by at least one server connected to the electronic device (100) via a network to enable communication.

[0057] A processor (180) according to the present invention can call at least one instruction among the instructions of software stored in a storage medium readable by a machine such as an electronic device (100) and execute it. This enables the machine such as the electronic device (100) to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by a machine may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and this term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily in the storage medium.

[0058] Meanwhile, the processor (180) may acquire state data regarding the operation of a plurality of components of an electronic device, identify a state error of a first component among the plurality of components based on the acquired state data, acquire error data indicating the mutual correlation between the identified state error of the first component and a second component that causes the state error, identify the possibility of occurrence of a state error of the first component based on the acquired state data and error data, and perform at least some of the data analysis, processing, and result information generation for performing error-related operations for a second component associated with the state error of the first component identified as having a possibility of occurrence, using at least one of a machine learning, neural network, or deep learning algorithm as a rule-based or artificial intelligence (AI) algorithm.

[0059] An artificial intelligence system is a computer system that implements human-level intelligence, in which machines learn and make judgments on their own, and whose recognition rate improves with use.

[0060] Artificial intelligence technology consists of machine learning (deep learning) technology, which utilizes algorithms to self-classify and learn the characteristics of input data, and component technologies that mimic the functions of the human brain, such as cognition and judgment, by utilizing machine learning algorithms.

[0061] The elemental technologies may include, for example, linguistic understanding technology that recognizes human language / characters, visual understanding technology that recognizes objects like human vision, reasoning / prediction technology that judges information to logically reason and predict, knowledge representation technology that processes human experience information into knowledge data, and motion control technology that controls autonomous driving of vehicles and the movement of robots.

[0062] Linguistic understanding refers to the technology of recognizing, applying, and processing human language and text, and includes natural language processing, machine translation, dialogue systems, question answering, and speech recognition / synthesis. Visual understanding refers to the technology of perceiving and processing objects in the manner of human vision, and includes object recognition, object tracking, image search, person recognition, scene understanding, spatial understanding, and image enhancement. Inference and prediction refer to the technology of logically reasoning and predicting by judging information, and include knowledge / probability-based inference, optimization prediction, preference-based planning, and recommendation. Knowledge representation refers to the technology of automatically processing human experiential information into knowledge data, and includes knowledge construction (data generation / classification) and knowledge management (data utilization).

[0063] For example, the processor (180) can perform the functions of both a learning unit and a recognition unit. The learning unit performs the function of generating a learned neural network, and the recognition unit performs the function of recognizing (or inferring, predicting, estimating, or judging) data using the learned neural network.

[0064] The learning unit can create or update a neural network. The learning unit can acquire training data to create a neural network. For example, the learning unit can acquire training data from a storage unit (140) or from an external source. The training data may be data used for training the neural network, and the neural network can be trained using the data that has undergone the above-mentioned operation as training data.

[0065] The learning unit may perform preprocessing on the acquired training data or select data to be used for training from among multiple training data before training a neural network using the training data. For example, the learning unit may process the training data into a pre-set format, filter it, or add / remove noise to process it into a form suitable for training. The learning unit may generate a neural network configured to perform the above operations using the preprocessed training data.

[0066] A trained neural network may be composed of multiple neural networks (or layers). The nodes of the multiple neural networks have weight values ​​and perform neural network operations through operations between the results of previous layers and the multiple weights. Multiple neural networks may be connected to each other so that the output value of one neural network is used as the input value of another neural network. Examples of neural networks may include models such as CNN (Convolutional Neural Network), DNN (Deep Neural Network), RNN (Recurrent Neural Network), RBM (Restricted Boltzmann Machine), DBN (Deep Belief Network), BRDNN (Bidirectional Recurrent Deep Neural Network), and Deep Q-Networks.

[0067] Meanwhile, the recognition unit may acquire target data to perform the above-mentioned operation. The target data may be acquired from the storage unit (140) or from an external source. The target data may be data to be recognized by the neural network. Before applying the target data to the trained neural network, the recognition unit may perform preprocessing on the acquired target data or select data to be used for recognition from among multiple target data. For example, the recognition unit may process the target data into a preset format, filter it, or add / remove noise to process it into a form of data suitable for recognition. By applying the preprocessed target data to the neural network, the recognition unit may acquire an output value output from the neural network. Along with the output value, the recognition unit may acquire a probability value or a confidence value.

[0068] The learning of artificial intelligence models and the generation of training data can be performed through external servers. However, it goes without saying that in some cases, the learning of artificial intelligence models may take place on electronic devices, and the training data may also be generated on electronic devices.

[0069] For example, a control method for an electronic device (100) according to the present invention may be provided by being included in a computer program product. The computer program product may include instructions of software executed by the processor (180) described above. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., CD-ROM), or distributed online (e.g., download or upload) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created in a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0070] FIG. 3 is a diagram illustrating the operation flowchart of an electronic device according to one embodiment of the present invention.

[0071] According to one embodiment of the present invention, the processor (180) obtains state data regarding the operation of a plurality of configurations of the electronic device (100) (S310).

[0072] As previously explained, state data refers to all data that can be collected in relation to the operation of multiple configurations.

[0073] Accordingly, the state data includes not only operation data of multiple configurations of the electronic device (100), but also time-series trends of each operation data, the surrounding environment of the electronic device (100), and data related to surrounding external devices.

[0074] Status data includes, for example, the hot plug duration time of the HDMI port, processor usage, minimum and maximum values ​​of various Phase Locked Loops (PLLs) including the processor, the stable operation timing margin value of DDR (Double Data Rate) memory, the equalizer (EQ) margin value of the connected cable, the type and number of connected external devices, the display operating mode or resolution, the temperature of multiple components including the main circuit, and the ambient temperature of electronic devices.

[0075] The processor (180) can collect state data during operation in real time and acquire state data periodically or for defined configuration units. The processor (180) can store the acquired state data in the storage unit (140).

[0076] According to one embodiment of the present invention, the processor (180) identifies a state error of a first configuration among a plurality of configurations based on acquired state data (S320).

[0077] A state error is an error identified based on state data obtained regarding the operation of a plurality of components of an electronic device (100).

[0078] For example, the processor (180) can identify an output error of the display (121) based on the fact that the feedback voltage detected by the Hot Plug Detect (HPD) line is lower than a predefined voltage as a state error, or an error in which the power circuit operates abnormally based on the fact that the temperature of the power circuit is maintained at 30 to 40°C and then suddenly increases to 60°C or higher, or that the voltage and current values ​​collected from the power circuit are detected outside the control range.

[0079] As described in the example, a state error can be identified based on the state data of the first configuration itself where the error occurred, but it is not identified based solely on the state data of the first configuration, and can also be identified through the state data of other configurations that affect the state error of the first configuration.

[0080] According to one embodiment of the present invention, the processor (180) obtains error data indicating the mutual correlation between the state error of the identified first configuration and the second configuration that causes the state error (S330).

[0081] According to one embodiment of the present invention, error data may be provided based on the relationship between a state error of a first configuration and a second configuration identified from state data of a plurality of configurations of an electronic device (100). The operation of the second configuration may affect the state error of the first configuration, and the processor (180) may identify the mutual correlation of how a change in the operation of the second configuration affects the state error of the first configuration based on state data obtained in many situations.

[0082] The error data includes a model trained to perform operations on the mutual correlation between the state error of the identified first configuration (10) and the second configuration (20) that causes the state error.

[0083] The processor (180) can periodically acquire state data at a specific point in time or under a specific situation and create a model by learning the time-series trends of the state data or changes in state data before and after a state error occurs. Regarding this, the operation of the processor in FIG. 2 above is referenced, and more specifically, it will be described later with reference to FIG. 4, etc.

[0084] According to one embodiment of the present invention, the processor (180) identifies the possibility of a state error of the first configuration based on acquired state data and error data (S340).

[0085] The state data obtained in this step refers to state data obtained during the current operation of the electronic device (100). Accordingly, the processor (180) can identify the possibility of a state error occurring in at least one configuration, i.e., the first configuration, based on the obtained state data and error data including a previously learned model. More specific details will be described later with reference to FIG. 5.

[0086] According to one embodiment of the present invention, the processor (180) performs an error-related operation for a second configuration associated with a state error of a first configuration identified as likely to occur (S350).

[0087] The processor (180) can identify the possibility of a state error in the first configuration based on the operation of the second configuration currently being measured and the state data resulting therefrom, using error data. Accordingly, the processor (180) can perform an error-related operation, for example, by changing the settings of parameters regarding the second configuration so that the possibility of a state error occurring is reduced. More specific details will be described later with reference to FIGS. 5 and 6.

[0088] According to one embodiment of the present invention, the electronic device (100) can maintain the state of the electronic device (100) optimally on its own by using periodically identified state data to monitor potential state errors in real time and performing necessary error-related operations.

[0089] FIG. 4 is a drawing illustrating the operation of an electronic device according to an embodiment of the present invention. FIG. 4 illustrates an electronic device (100) connected to a set-top box (420) through an HDMI port (410). In this drawing, the HDMI port (410) is built into the electronic device (100) and is drawn in an exaggerated manner for convenience of explanation, and its shape and location are not limited to any one.

[0090] As described in S340 of FIG. 3, the processor (180) obtains state data regarding the operation of a plurality of configurations and identifies a state error of the first configuration.

[0091] For example, the first configuration (10) is assumed to be the display (121) shown in FIG. 4. The processor (180) can identify that the output signal of the display (121), which is the first configuration (10) among the multiple configurations, is not detected based on the state data regarding the multiple configurations described above.

[0092] The processor (180) can identify, using the error data described in S330 of FIG. 3, that a state error of the first configuration (10) may occur, for example, in relation to the second configuration (20) among the multiple configurations, such as the HDMI port (410). More specifically, the processor (180) can identify that the occurrence of a state error of the first configuration (10) is determined as the state data changes according to the operation of the second configuration (20), based on the error data including a known algorithm or a model generated through machine learning. Accordingly, the processor (180) can identify that an error occurs in which an output signal is not detected at the display (121) as the state data changes according to the operation of the HDMI port (410) based on the error data.

[0093] In relation to the present drawing, the processor (180) can obtain data of a voltage value that detects the hot plug detect pin voltage of the HDMI port (410) as state data according to the operation of the HDMI port (410).

[0094] Hot plug detect refers to a circuit or system that detects signal input / output when the power is turned on for the connected electronic device (100) and the connected set-top box (420). That is, when voltage is first output from the set-top box (420) and transmitted to the HDMI port (410) of the electronic device (100) through the cable (430), the voltage output from the HDMI port (410) is fed back to the set-top box (420) through the hot plug detect line. If the feedback voltage is normal, the set-top box (420) determines that the connection is normal and outputs a video signal to the electronic device (100).

[0095] The error data of the present embodiment includes data of the hot plug detect pin voltage of the HDMI port (410) collected under various operating conditions of the electronic device (100). Additionally, the error data includes data indicating when a state error has occurred in the output signal of the display (121) at what value the hot plug detect pin voltage of the HDMI port (410) is. The electronic device (100) may generate error data by using a known algorithm to obtain a result indicating the correlation between the hot plug detect pin voltage of the HDMI port (410) and the state error occurring in the output signal of the display (121), or by using a model trained to identify the mutual correlation between the two through machine learning, etc.

[0096] The processor (180) can identify whether there is a possibility of a state error occurring in the output signal of the display (121) through the hot plug detect pin voltage of the current HDMI port (410) based on the generated error data. For example, if the processor (180) identifies, based on the error data, that a state error occurs in the output signal of the display (121) at a level where the hot plug detect pin voltage of the HDMI port (410) has a value of 100, it can determine that there is a possibility of a state error occurring in the output signal of the display (121) when the hot plug detect pin voltage of the current HDMI port (410) has a value of approximately 90. Of course, these values ​​are merely examples, and the threshold value of the hot plug detect pin voltage of the HDMI port (410) for the possibility of a state error occurring in the output signal of the display (121) can be set in various ways.

[0097] If it is identified that there is a possibility of a state error occurring in the output signal of the display (121) based on the hot-plug detect pin voltage of the HDMI port (410), the processor (180) may perform an error-related operation for the HDMI port (410) associated with the state error of the display (121). The processor (180) may display a graphic user interface (GUI) indicating the state error of the display (121) on the display (121). For example, as shown in FIG. 4, "No Signal" may be displayed to indicate that no output signal is input to the display (121).

[0098] If it is identified that there is no problem with the HDMI port (410), the processor (180) can identify the cause through state data regarding the operation of another second configuration that may affect the state error of the first configuration and perform an error-related operation.

[0099] In addition to cases where a state error of the display (121) has already occurred, the processor (180) periodically collects state data regarding the hot plug detection of the HDMI port (410) or other second configuration operations related to the output of the display (121) to identify the possibility of a state error occurring before a state error occurs in the display (121).

[0100] According to one embodiment of the present invention, when a state error occurs, the electronic device (100) identifies the cause of the state error based on error data, performs an operation to resolve it, and furthermore, can identify the possibility of a state error occurring in advance to prevent the state error in advance.

[0101] FIG. 5 is a diagram illustrating the operation flowchart of an electronic device according to one embodiment of the present invention.

[0102] FIG. 5 is a flowchart illustrating the operation process of the electronic device (100) described in FIG. 3 in more detail, with particular emphasis on S340 of FIG. 3.

[0103] The processor (180) acquires state data to identify the possibility of an error occurring and identifies a state error based on the acquired state data (S510). The processor (180) analyzes the acquired state data based on the error data (S520).

[0104] The processor (180) identifies whether there is a possibility of a state error occurring based on the analysis results (S530). If it is identified that there is no possibility of a state error occurring (Yes in S530), the processor (180) terminates the operation but diagnoses it periodically.

[0105] On the other hand, if it is identified that there is a possibility of a state error occurring (Yes in S530), the processor (180) identifies and resets the configuration parameters that cause the state error (S540).

[0106] A parameter according to one embodiment of the present invention is a characteristic capable of controlling the state of each configuration, for example, when the temperature of the power circuit (first configuration) is maintained at 30 to 40°C and then suddenly increases to 60°C or higher (state error), the timing margin of the DDR memory (second configuration) which is related to the temperature of the power circuit, or the PLL voltage of the processor (second configuration) may correspond to the parameter.

[0107] The processor (180) can perform error-related operations by changing the settings of parameters regarding the identified second configuration so that the probability of a state error occurring is reduced. In this embodiment, the processor (180) diagnoses the timing margin to block timing risk, and if the valid margin is insufficient or skewed to one side due to temperature characteristics, it can secure the margin by adjusting the intermediate value. The processor (180) can also verify internally whether the margin has actually been secured by adjusting the parameter values.

[0108] Additionally, the processor (180) can optimize the electronic device (100) in a way that reduces the temperature by lowering the processor's PLL voltage.

[0109] Another example related to parameters is described in Fig. 6.

[0110] The processor (180) identifies whether the problem has been resolved (S550), and if the problem has been resolved (Yes in S550), terminates the operation. If the problem has not been resolved despite performing the error-related operation described above (No in S550), the processor (180) guides the user (S560). More details are described in FIG. 7.

[0111] According to one embodiment of the present invention, an electronic device (100) can prevent operational failure by identifying the possibility of a state error based on error data and performing an operation to set and tune parameters of a configuration that causes the state error, thereby maintaining an optimal state regarding quality levels and changes over time.

[0112] FIG. 6 is a diagram illustrating the use of error data according to an embodiment of the present invention.

[0113] The embodiment of FIG. 6 describes another example of performing an error-related operation described with reference to S540 of FIG. 5 in the case of the mutual association between the display (121) and the HDMI port (410) described with reference to FIG. 4.

[0114] Using the table (600) of FIG. 6, it is possible to predict the state error and the possibility of the state error based on the state data of the display (121) and the HDMI port (410).

[0115] As previously explained in FIG. 4, the display (121) may have a state error caused by the operation of the HDMI port (410).

[0116] The processor (180) can identify and reset parameters of the HDMI port (410) that cause a state error of the display (121). As illustrated in FIG. 6, according to one embodiment of the present invention, the processor (180) identifies the Hot Plug Voltage, Equalizer (EQ), and Hot Plug duration time as parameters of the HDMI port (410).

[0117] The processor (180) acquires status data for each parameter of the HDMI port (410) in different situations and identifies whether there is a status error of the display (121) or the possibility of a status error occurring based on changes in the parameter values ​​of the HDMI port (410). However, at this time, the processor (180) acquires not only status data related to the display (121) and the HDMI port (410), but also status data of the entire plurality of configurations.

[0118] Looking at the table (600) shown in Fig. 6, in situation 1, the hot plug voltage of the HDMI port (410) is 1V, the equalizer is 7, and the hot plug duration is 900ms.

[0119] Based on the error data, the processor (180) determines that it cannot receive a signal from the set-top box (420) due to a low hot-plug voltage, and identifies the setting of a parameter that can compensate for the signal strength of the set-top box (420) and adjusts it to an optimal value or lowers the resolution so that the signal is output.

[0120] In situation 2 of table (600), the hot plug voltage of the HDMI port (410) is 5V, the equalizer is 8, and the hot plug duration is 400ms. At this time, it is assumed that the normal hot plug duration of the electronic device (100) according to one embodiment of the present invention is 800ms to 1000ms.

[0121] Based on the error data, the processor (180) determines that the reason no output signal is detected on the display (121) even though the hot plug voltage is normal at 5V is due to the hot plug duration, and adjusts the hot plug duration to within the range of 800ms to 1000ms.

[0122] In situation 3 of the table (600), the hot plug voltage of the HDMI port (410) is 5V, the equalizer is -12, and the hot plug duration is 1000ms. At this time, it is assumed that the normal equalizer value of the electronic device (100) according to one embodiment of the present invention is 6 to 10.

[0123] The processor (180) acquires state data for a plurality of configurations and analyzes the acquired state data to identify that the equalizer of the HDMI port (410) is -12. The processor (180) can identify that the equalizer value is outside the normal range based on error data. The processor (180) can identify the possibility of a state error occurring in the display (121) if the equalizer value persists. In this case, the processor (180) adjusts the equalizer value to a range of 6 to 10.

[0124] Alternatively, based on error data, if the possibility of a state error of the display (121) occurring is identified even if the processor (180) adjusts the equalizer value to a normal range (since the display (121) could operate due to the abnormal value of the equalizer), the processor (180) determines, based on the error data, that the problem is caused by the cable (430) and performs an error-related operation.

[0125] According to one embodiment of the present invention, the processor identifies inter-components based on error data including a model learned based on artificial intelligence technology, and resolves state errors by making independent judgments, thereby increasing user convenience. Furthermore, since the error data is learned using the collection of vast state data and an inter-component algorithm, service costs can be reduced and inefficiencies improved through accurate measures.

[0126] FIG. 7 is a drawing illustrating the operation of an electronic device according to one embodiment of the present invention.

[0127] FIG. 7 illustrates an example in which, in relation to S560 of FIG. 5, the processor (180) in FIG. 6 performs an error-related operation to resolve the state error itself, but the state error is not resolved.

[0128] If the processor (180) does not reduce the likelihood of a state error occurring through the setting of the changed parameters, it displays a GUI on the display (121) that shows the state error of the first configuration and the parameters of the second configuration corresponding to the state error.

[0129] It is assumed that, as shown in FIG. 6, even though the processor (180) has performed signal compensation processing, an equalizer, and adjustment of the hot plug duration, it has not been able to resolve the state error of the display (121) or reduce the possibility of the state error occurring.

[0130] In this case, the problem can be solved by turning the power of the set-top box (420) on and off or reconnecting the cable. However, since this cannot be done by the electronic device (100) itself, the processor (180) can display a GUI on the display (121) to guide the user to do this. Accordingly, in FIG. 7, the processor (180) displays a GUI (710) on the display (121) that guides, "There is a problem with the cable connection with the external device STB. Please reconnect the cable or reboot the STB."

[0131] In addition, the processor can perform error-related operations for the second configuration based on user input received using the GUI.

[0132] For example, the processor (180) can receive user input that adjusts parameters such as hot plug duration using a user input unit (130), such as a remote control or a touchscreen, and can perform error-related operations based on the received user input.

[0133] In addition, if the issue is not resolved based on user input, for example, if replacement of consumable parts is required, the processor (180) can display a GUI on the display (121) that provides guidance on matters required for service.

[0134] If the problem cannot be resolved even by this method, the processor (180) transmits the relevant information to the service center through the interface unit (110) and guides the user to receive appropriate service measures.

[0135] According to one embodiment of the present invention, user convenience can be increased and service satisfaction improved by guiding the user to easily solve hardware-related problems. Explanation of the symbols

[0136] 100: Electronic device 110: Interface section 120: Display section 130: User Input Section 140: Storage section 150: Microphone 160: Speaker 170: Sensor 180: Processor

Claims

Claim 1 An electronic device comprising a processor that acquires state data regarding the operation of a plurality of configurations of the electronic device, identifies a second configuration corresponding to a first configuration having a possibility of a state error based on error data indicating a mutual correlation between the plurality of configurations regarding the acquired state data, and performs an error-related operation for the second configuration by changing the setting of a parameter regarding the second configuration to reduce the possibility of a state error of the first configuration, wherein the parameter regarding the second configuration includes at least one of a timing margin of the memory of the electronic device, a PLL voltage of the processor, a hot plug voltage of a communication connection port of the electronic device, an equalizer, a hot plug duration, or a connection state of a cable. Claim 2 An electronic device according to claim 1, wherein the error data comprises a model learned to perform operations regarding the state error of the first configuration and the mutual correlation between the second configuration that causes the state error. Claim 3 In claim 1, the processor is an electronic device that displays a graphic user interface (GUI) on a display representing a state error of the first configuration and parameters of the second configuration corresponding to the state error. Claim 4 In paragraph 3, the processor is an electronic device that performs an error-related operation for the second configuration based on user input received using the GUI. Claim 5 delete Claim 6 An electronic device according to claim 1, wherein the processor displays a GUI on a display showing a state error of the first configuration and a parameter of the second configuration corresponding to the state error when the probability of the state error occurring is not lowered through the setting of the changed parameter, and performs an error-related operation for the second configuration based on user input received using the GUI. Claim 7 In claim 1, the processor is an electronic device that periodically identifies whether there is a possibility of a state error of the first configuration occurring. Claim 8 A method for controlling an electronic device comprises: a step of acquiring state data regarding the operation of a plurality of components of the electronic device; a step of identifying a second component corresponding to a first component having a possibility of a state error occurring based on error data indicating the mutual correlation between the plurality of components regarding the acquired state data; and a step of performing an error-related operation for the second component by changing the setting of a parameter regarding the second component to reduce the possibility of a state error occurring in the first component, wherein the parameter regarding the second component includes at least one of a timing margin of the memory of the electronic device, a PLL voltage of the processor of the electronic device, a hot plug voltage of the communication connection port of the electronic device, an equalizer, a hot plug duration, or a cable connection state. Claim 9 A control method for an electronic device according to claim 8, wherein the error data comprises a model learned to perform operations regarding the state error of the first configuration and the mutual correlation between the second configuration that causes the state error. Claim 10 A method for controlling an electronic device according to claim 8, further comprising the step of displaying on a display a graphic user interface (GUI) representing a state error of the first configuration and parameters of the second configuration corresponding to the state error. Claim 11 A method for controlling an electronic device according to claim 10, comprising the step of performing an error-related operation for the second configuration based on user input received using the GUI. Claim 12 delete Claim 13 In claim 8, the step of performing the error-related operation comprises: displaying a GUI on a display that indicates the state error of the first configuration and the parameter of the second configuration corresponding to the state error when the probability of the state error occurring is not lowered through the setting of the changed parameter; and performing an error-related operation for the second configuration based on user input received using the GUI. Claim 14 A control method for an electronic device according to claim 8, comprising the step of periodically identifying whether there is a possibility of a state error occurring in the first configuration. Claim 15 A recording medium storing a computer program that includes code for performing a control method of an electronic device, wherein the control method of the electronic device comprises: a step of acquiring state data regarding the operation of a plurality of components of the electronic device; a step of identifying a second component corresponding to a first component having a possibility of a state error based on error data indicating the mutual correlation between the plurality of components regarding the acquired state data; and a step of performing an error-related operation for the second component by changing the setting of a parameter regarding the second component to reduce the possibility of a state error of the first component, wherein the parameter regarding the second component includes at least one of a timing margin of the memory of the electronic device, a PLL voltage of the processor of the electronic device, a hot plug voltage of the communication connection port of the electronic device, an equalizer, a hot plug duration, or a connection state of a cable.

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