Electronic device management method, apparatus, and storage medium

Abstract

The application embodiment discloses an electronic device management method, device and storage medium. The electronic device management method comprises the following steps: acquiring basic information of an electronic device; the basic information comprises one or more of the following: a running state of a current bottom layer hardware of the electronic device, current foreground process information, current background process information, current environment information of the electronic device and a current screen snapshot; determining a current use scenario of the electronic device according to the basic information and a preset first prompt; determining recommended setting information of the electronic device at present according to the current use scenario; and adjusting a current system setting and / or resource configuration of the electronic device according to the recommended setting information.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and more specifically, to an electronic device management method, apparatus, and storage medium. Background Technology

[0002] Users engage with electronic devices in various scenarios, such as text editing, graphic design, gaming, and reading. Different users may have different preferences for system settings in different scenarios. Currently, most electronic device control centers or user assistants rely on traditional solutions involving manual operation or triggering of specific scenarios. Summary of the Invention

[0003] This application provides an electronic device management method, apparatus, and storage medium, which not only improves the user's experience but also increases the efficiency of using electronic devices.

[0004] This application provides an electronic device management method, including:

[0005] Obtain basic information about the electronic device; the basic information includes one or more of the following: the current operating status of the underlying hardware of the electronic device, the current foreground process information, the current background process information, the current environment information of the electronic device, and the current screen snapshot;

[0006] The current usage scenario of the electronic device is determined based on the basic information and the preset first prompt; the preset first prompt includes a statement indicating the determination of the current usage scenario of the electronic device.

[0007] Determine the recommended settings for the electronic device based on the current usage scenario;

[0008] Adjust the current system settings and / or resource configuration of the electronic device according to the recommended settings information.

[0009] In one exemplary embodiment, the statement instructing the determination of the current usage scenario of the electronic device includes a statement instructing the determination of the current usage scenario of the electronic device based on basic information;

[0010] Determining the current usage scenario of the electronic device based on the basic information and the preset first prompt includes:

[0011] The basic information and the preset first prompt are input into the large language model, and the current usage scenario of the electronic device is obtained through the reasoning of the large language model.

[0012] In one exemplary embodiment, the statement instructing the determination of the current usage scenario of the electronic device includes a statement instructing the determination of the current usage scenario of the electronic device based on basic information, user behavior logs, and / or a process whitelist.

[0013] Determining the current usage scenario of the electronic device based on the basic information and the preset first prompt includes:

[0014] The enhanced generation algorithm performs a search in a preset knowledge base based on the basic information and the preset first prompt; wherein, the preset knowledge base stores user behavior logs and / or process whitelists;

[0015] The current usage scenario of the electronic device is obtained by reasoning based on the retrieved information, the basic information, and the preset first prompt using a large language model.

[0016] In one exemplary embodiment, determining the current recommended settings information of the electronic device based on the current usage scenario includes:

[0017] The recommended settings information for the electronic device are determined based on the correspondence between the current usage scenario, the preset usage scenario, and the recommended settings information.

[0018] In one exemplary embodiment, determining the current recommended settings information of the electronic device based on the current usage scenario includes:

[0019] The recommended settings information of the electronic device are determined based on the current usage scenario, the preset second prompt, and multiple preset recommended settings information; the preset second prompt includes a statement that instructs the determination of the recommended settings information of the electronic device.

[0020] In one exemplary embodiment, the statement instructing the determination of recommended settings information for the electronic device includes a statement instructing the determination of recommended settings information for the electronic device based on the usage scenario;

[0021] The step of determining the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and multiple preset recommended settings includes:

[0022] The current usage scenario and the preset second prompt are input into the large language model, and the recommended settings information of the electronic device are determined by the large language model through reasoning.

[0023] The recommended setting information that best matches the recommended setting information of the electronic device determined by the large language model among multiple preset recommended setting information is determined as the current recommended setting information of the electronic device.

[0024] In one exemplary embodiment, the statement instructing the determination of recommended settings information for an electronic device includes a statement instructing the determination of recommended settings information for an electronic device from a plurality of preset recommended settings information based on a usage scenario;

[0025] The step of determining the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and multiple preset recommended settings includes:

[0026] The current usage scenario, the preset second prompt, and the preset recommended settings information are input into the large language model. After reasoning by the large language model, the recommended settings information that best matches the current usage scenario of the electronic device among the preset recommended settings information is determined as the current recommended settings information of the electronic device. The second prompt is a statement that instructs the determination of the recommended settings information of the electronic device based on the usage scenario and the preset recommended settings information.

[0027] In one exemplary embodiment, the statement instructing the determination of recommended settings information for an electronic device includes a statement instructing the determination of recommended settings information for an electronic device from a plurality of preset recommended settings information based on user behavior preferences in the usage scenario;

[0028] The step of determining the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and multiple preset recommended settings includes:

[0029] The enhanced generation algorithm retrieves information from a preset knowledge base based on the basic information and the preset second prompt; wherein, the preset knowledge base stores user behavior logs.

[0030] Based on the retrieved information, the current usage scenario, the preset second prompt, and the preset recommended settings information, the large language model infers and determines the recommended settings information that best matches the current usage scenario of the electronic device from among multiple preset recommended settings information as the current recommended settings information of the electronic device.

[0031] In one exemplary embodiment, prior to adjusting the current system settings and / or resource configuration of the electronic device based on recommended setting information, the method further includes:

[0032] The recommended settings information is processed to match the information format of the tool that performs the recommended settings.

[0033] In one exemplary embodiment, adjusting the current system settings and / or resource configuration of the electronic device according to the recommended setting information includes:

[0034] The recommended settings are executed using robotic process automation tools to adjust the current system settings and / or resource configuration of the electronic device.

[0035] In one exemplary embodiment, the electronic device is a computer.

[0036] This application also provides an electronic device management apparatus, including a memory and a processor.

[0037] The memory is used to store programs for electronic device management methods;

[0038] The processor is configured to read the program that executes the electronic device management method and execute the method described in any of the above embodiments.

[0039] This application also provides an electronic device readable storage medium storing electronic device executable instructions, wherein the electronic device executable instructions are used to cause the electronic device to perform the method described in any of the above embodiments.

[0040] This application also provides an electronic device management apparatus, including:

[0041] The data acquisition module is configured to collect basic information of the current electronic device. The basic information includes one or more of the following: the operating status of the underlying hardware of the current electronic device, the current foreground process information, the background process information, the environment information of the current electronic device, and the current screen snapshot.

[0042] The main control module is configured to call the large language model and the robotic process automation tool module.

[0043] The large language model is configured to determine the current usage scenario of the electronic device based on the basic information and a preset first prompt; and to determine the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and preset recommended settings information; the preset first prompt includes a statement indicating the determination of the current usage scenario of the electronic device; the preset second prompt includes a statement indicating the determination of the recommended settings information of the electronic device.

[0044] The robotic process automation tool module includes a robotic process automation tool configured to adjust the current system settings and / or resource configuration of the electronic device based on the recommended settings information.

[0045] In one exemplary embodiment, a retrieval enhancement generation algorithm module is also included;

[0046] The main control module is also configured to call the retrieval enhancement generation algorithm module;

[0047] The retrieval enhancement generation algorithm module is configured to perform retrieval in a preset knowledge base based on the basic information and the preset first prompt; and to perform retrieval in the preset knowledge base based on the basic information and the preset second prompt.

[0048] The large language model is further configured to infer the current usage scenario of the electronic device based on the retrieved information, the basic information, and the preset first prompt; and to determine the current recommended settings information of the electronic device based on the retrieved information, the current usage scenario, the preset second prompt, and multiple preset recommended settings information.

[0049] This application embodiment determines the current usage scenario of the electronic device based on the basic information and the preset first prompt; determines the current recommended settings information of the electronic device based on the current usage scenario; and adjusts the current system settings and / or resource configuration of the electronic device based on the recommended settings information, so that the system settings and resource configuration automatically adapt to the usage scenario. This not only improves the user's device experience, but also improves the efficiency of the user's use of the electronic device without requiring user operation or manual scenario triggering.

[0050] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description and the accompanying drawings. Attached Figure Description

[0051] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0052] Figure 1 This is a schematic diagram of an electronic device management method according to an embodiment of this application;

[0053] Figure 2 This is a process diagram illustrating an example of an electronic device management method according to an embodiment of this application;

[0054] Figure 3 This is a schematic diagram of an electronic device management device according to an embodiment of this application. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be arbitrarily combined with each other.

[0056] The inventors of this application discovered that when users run demanding games or use large graphics software, the resources (CPU / memory / graphics card) of electronic devices are greatly consumed. If other processes consume excessive resources at this time, it can cause the currently running process to lag, crash, or exhibit other abnormal phenomena. In traditional solutions, users typically manually check and close unnecessary processes to free up resources, which is time-consuming, especially for some low-spec electronic devices, requiring frequent such operations, which is also a significant inconvenience for users. The inventors of this application also discovered that for non-desktop electronic devices (such as laptops or tablets), battery life is a critical indicator when not connected to an external power source (DC mode). When used under DC power, many processes that are open but not used for extended periods, or some third-party scanning programs, waste a lot of unnecessary power resources (some unnecessary third-party processes are not clearly described, and most users lack the ability to identify them, causing them to hesitate to close these processes). This weakens the PC's battery life, thus affecting normal user operation. For different user scenarios, such as reading where the screen color temperature needs to be warm and the brightness moderate, and gaming where the brightness needs to be increased and the color temperature warm, users will adjust the screen or other hardware parameters to meet their own user comfort in various scenarios. Traditional manual adjustment methods will also waste some time.

[0057] To address the aforementioned problems, this application proposes a method for managing electronic devices.

[0058] Figure 1 This is a schematic diagram of an electronic device management method according to an embodiment of this application. The electronic device management method is as follows: Figure 1 As shown, it includes the following steps 11 to 14:

[0059] Step 11: Obtain the current basic information of the electronic device;

[0060] Step 12: Determine the current usage scenario of the electronic device based on the basic information and the preset first prompt;

[0061] Step 13: Determine the recommended settings for the current electronic device based on the current usage scenario;

[0062] Step 14: Adjust the current system settings and / or resource configuration of the electronic device according to the recommended settings information.

[0063] The basic information includes one or more of the following: the current operating status of the underlying hardware of the electronic device, the current foreground process information, the current background process information, the current environment information of the electronic device, and the current screen snapshot; the preset first prompt includes a statement indicating the current usage scenario of the electronic device.

[0064] This application embodiment determines the current usage scenario of the electronic device based on the basic information and the preset first prompt; determines the current recommended settings information of the electronic device based on the current usage scenario; and adjusts the current system settings and / or resource configuration of the electronic device based on the recommended settings information, so that the system settings and resource configuration automatically adapt to the usage scenario. This not only improves the user's device experience, but also improves the efficiency of the user's use of the electronic device without requiring user operation or manual scenario triggering.

[0065] Recommended settings information can be system settings and / or resource configurations recommended to users in the current usage scenario.

[0066] In step 11, for example, the operating status and real-time parameters of the underlying hardware can be obtained through a hardware interface or firmware interface. For instance, current screen setting parameters (such as resolution, interface mode, timing parameters, synchronization signals, etc.) can be obtained through the timing controller (Tcon) interface; fan information, battery information, keyboard information, etc., can be obtained through the interface communicating with the embedded controller (EC).

[0067] For example, foreground process information and background process information can be obtained through the system application programming interface (API).

[0068] For example, a screenshot of the current screen can be obtained by using the system screenshot API.

[0069] For example, the current real-time video stream can be obtained through the camera interface of the current electronic device; the ambient light level of the environment in which the current electronic device is located can be known through the obtained video stream.

[0070] In step 12, in one exemplary embodiment, the statement indicating the determination of the current usage scenario of the electronic device includes a statement indicating the determination of the current usage scenario of the electronic device based on basic information;

[0071] Determining the current usage scenario of the electronic device based on the basic information and the preset first prompt may include:

[0072] The basic information and the preset first prompt are input into the large language model, and the current usage scenario of the electronic device is obtained through the reasoning of the large language model.

[0073] Large Language Model (LLM) is a deep learning-based technique in the fields of artificial intelligence and natural language processing. It is a complex artificial intelligence model with billions or even trillions of parameters.

[0074] LLM can be deployed on a local large model within the operating system, possessing multimodal capabilities. It is generated by fine-tuning and quantizing pre-trained models using professional data from the electronic device domain, followed by reinforcement learning. It has powerful text and graph reasoning capabilities, enabling it to reason and analyze data from electronic devices in various scenarios and generate accurate judgment responses.

[0075] For example, if the basic information includes high proportions of graphics card and CPU usage, and currently running processes include game processes, then it can be determined that the current usage scenario of the electronic device is a game scenario.

[0076] For example, the preset first prompt could be "Determine the current usage scenario of the electronic device".

[0077] For example, the preset first prompt could be "Please determine the current usage scenario of the electronic device".

[0078] For example, the preset first prompt could be "What is the current usage scenario of the electronic device?"

[0079] For example, the preset first prompt could be "Determine the current usage scenario of the electronic device based on basic information".

[0080] For example, the preset first prompt could be "Determine the current usage scenario of the electronic device based on basic information".

[0081] In one exemplary embodiment, the statement instructing the determination of the current usage scenario of the electronic device includes a statement instructing the determination of the current usage scenario of the electronic device based on basic information, user behavior logs, and / or a process whitelist.

[0082] Determining the current usage scenario of the electronic device based on the basic information and the preset first prompt includes:

[0083] The enhanced generation algorithm performs a search in a preset knowledge base based on the basic information and the preset first prompt; wherein, the preset knowledge base stores user behavior logs and / or process whitelists;

[0084] The current usage scenario of the electronic device is obtained by reasoning based on the retrieved information, the basic information, and the preset first prompt using a large language model.

[0085] Retrieval-Augmented Generation (RAG) is an innovative artificial intelligence technique that combines retrieval and generation technologies. It is primarily used in natural language processing and artificial intelligence, particularly in dialogue systems, text generation, and question-answering systems. The core idea of ​​RAG is to leverage external knowledge or information to enhance the model's generative capabilities, thereby improving the accuracy and richness of the answers provided.

[0086] By analyzing user behavior logs, we can understand users' usage habits. The longer a user uses a product, the better we understand them, allowing us to make recommendations based on usage scenarios that are more closely aligned with their needs.

[0087] The process whitelist can include a list of mainstream software currently on the market. This can accurately determine the user's usage scenario in some cases, thus serving as an auxiliary support for large model inference.

[0088] For example, the preset knowledge base may also include a knowledge base in the field of notebook computers (hereinafter referred to as the notebook computer knowledge base).

[0089] For example, the first prompt could be "Determine the current usage scenario of the electronic device based on basic information, user behavior logs, and / or process whitelists".

[0090] For example, the preset first prompt could be "Please determine the current usage scenario of the electronic device based on basic information, user behavior logs, and / or process whitelists".

[0091] In step 13, in one exemplary embodiment, determining the current recommended settings information of the electronic device based on the current usage scenario may include:

[0092] The recommended settings information for the electronic device are determined based on the correspondence between the current usage scenario, the preset usage scenario, and the recommended settings information.

[0093] In one exemplary embodiment, determining the current recommended settings information of the electronic device based on the current usage scenario may include:

[0094] The recommended settings information of the electronic device are determined based on the current usage scenario, the preset second prompt, and multiple preset recommended settings information; the preset second prompt includes a statement that instructs the determination of the recommended settings information of the electronic device.

[0095] In one exemplary embodiment, the statement instructing the determination of recommended settings information for the electronic device may include a statement instructing the determination of recommended settings information for the electronic device based on the usage scenario;

[0096] Determining the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and multiple preset recommended settings information may include:

[0097] The current usage scenario and the preset second prompt are input into the large language model, and the recommended settings information of the electronic device are determined by the large language model through reasoning.

[0098] The recommended setting information that best matches the recommended setting information of the electronic device determined by the large language model among multiple preset recommended setting information is determined as the current recommended setting information of the electronic device.

[0099] In this embodiment, a large language model infers recommended settings information based on the current usage scenario. Then, it selects the recommended settings information that best matches the recommended settings information of the electronic device determined by the large language model from a plurality of preset recommended settings information as the current recommended settings information of the electronic device.

[0100] For example, existing text similarity calculation methods can be used to calculate the similarity between the recommended settings information of the electronic device determined by the large language model and the preset recommended settings information, and the recommended settings information with the highest similarity can be used as the most matching recommended settings information.

[0101] Methods for calculating text similarity may include, but are not limited to, the following:

[0102] 1) String matching-based methods, such as calculating the minimum number of single-character edits required to convert between two texts, where the similarity is equal to 1 - edit distance / max(len(str1), len(str2)); or calculating similarity using the Jaccard similarity coefficient, etc.

[0103] 2) Based on word vectors and statistical models, such as calculating similarity through cosine similarity or word shift distance.

[0104] 3) Based on deep learning and pre-trained models, such as sentence vector averaging or Sentence-BERT.

[0105] In one exemplary embodiment, the statement instructing the determination of recommended settings information for an electronic device includes a statement instructing the determination of recommended settings information for an electronic device from a plurality of preset recommended settings information based on the usage scenario;

[0106] Determining the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and multiple preset recommended settings information may include:

[0107] The current usage scenario, the preset second prompt, and the preset recommended settings information are input into the large language model. After reasoning by the large language model, the recommended settings information that best matches the current usage scenario of the electronic device among the preset recommended settings information is determined as the current recommended settings information of the electronic device. The second prompt is a statement that instructs the determination of the recommended settings information of the electronic device based on the usage scenario and the preset recommended settings information.

[0108] In one exemplary embodiment, the statement instructing the determination of recommended settings information for an electronic device may include a statement instructing the determination of recommended settings information for an electronic device from a plurality of preset recommended settings information based on user behavior preferences in a usage scenario;

[0109] Determining the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and multiple preset recommended settings information may include:

[0110] The enhanced generation algorithm retrieves information from a preset knowledge base based on the basic information and the preset second prompt; wherein, the preset knowledge base stores user behavior logs.

[0111] Based on the retrieved information, the current usage scenario, the preset second prompt, and the preset recommended settings information, the large language model infers and determines the recommended settings information that best matches the current usage scenario of the electronic device from among multiple preset recommended settings information as the current recommended settings information of the electronic device.

[0112] For example, the second prompt could be "Determine the recommended settings information for the electronic device based on the usage scenario." Alternatively, the second prompt could be "Determine the recommended settings information for the electronic device based on the usage scenario and multiple preset recommended settings," etc.

[0113] For example, the second prompt could be "Please determine the recommended settings for your electronic device based on your usage scenario".

[0114] In one exemplary embodiment, prior to adjusting the current system settings and / or resource configuration of the electronic device according to the recommended setting information, the following may also be included:

[0115] The recommended settings information is processed to match the information format of the tool that performs the recommended settings.

[0116] In one exemplary embodiment, adjusting the current system settings and / or resource configuration of the electronic device according to the recommended setting information includes:

[0117] The recommended settings are executed using robotic process automation tools to adjust the current system settings and resource configuration of the electronic device.

[0118] Robotic Process Automation (RPA) is a technology that uses software robots or artificial intelligence workers to automate repetitive, rule-based daily office tasks. The goal of RPA is to improve work efficiency, reduce error rates, and lower costs by simulating human actions in applications, such as data entry, information retrieval, document processing, and report generation.

[0119] In one exemplary embodiment, adjusting the current system settings of the electronic device may include one or more of the following:

[0120] Adjust the hardware parameters of the current electronic device; adjust the current system settings of the electronic device.

[0121] Adjusting system settings can include, but is not limited to, adjusting screen brightness, contrast, color temperature, volume, fan speed, keyboard backlight, and battery usage mode.

[0122] In one exemplary embodiment, adjusting the current resource configuration of the electronic device includes:

[0123] Adjust the current process resource configuration of electronic devices.

[0124] In one exemplary embodiment, adjusting the current process resource configuration of the electronic device may include:

[0125] Close processes that are irrelevant to the described use case, run them in the background, or reduce their resource allocation priority.

[0126] Alternatively, close processes or third-party programs that have not been used for a long time.

[0127] In one exemplary embodiment, the electronic device can be a computer; in other embodiments, the electronic device can also be a tablet or a mobile phone, provided that computing power allows or the large language model is placed in the cloud.

[0128] Figure 2 An example of electronic device management is shown, such as Figure 2As shown, the basic information of the electronic device includes information obtained through the hardware interface and currently running processes obtained through the process list, including desktop third-party processes: P_1 large game, P_2 music player, P_3 chat software, and P_4 translation software; and background third-party processes: B_1 antivirus software update and scan program, B_2 wallpaper program, and B_3 a local service. Based on the obtained basic information, it is determined that the device is currently in a game scenario. The recommended settings are inferred using RAG combined with a large language model and process whitelist. The recommended settings corresponding to the game scenario are sent to RPA for execution. The operations performed by RPA include: switching the electronic device to high-performance mode; closing background third-party processes (B_1 antivirus software update and scan program, B_2 wallpaper program, and B_3 a local service); reducing the thread priority of P_3 / P_4 processes; adjusting the screen brightness to 90%; adjusting the contrast to 50%; adjusting the color temperature to 7500K; adjusting the volume to 60%; adjusting the fan speed to 4000 RPM; and adjusting the keyboard backlight to RGB neon mode, etc.

[0129] This application discloses an electronic device management device, such as... Figure 3 As shown, it includes memory and processor.

[0130] The memory 100 is used to store programs for electronic device management methods;

[0131] The processor 200 is configured to read the program that executes the electronic device management method and execute the method described in any of the above embodiments.

[0132] This application also provides an electronic device readable storage medium storing electronic device executable instructions, wherein the electronic device executable instructions are used to cause the electronic device to perform the methods described in any of the above embodiments.

[0133] This application also provides an electronic device management apparatus, including:

[0134] The data acquisition module is configured to collect basic information of the current electronic device. The basic information includes one or more of the following: the operating status of the underlying hardware of the current electronic device, the current foreground process information, the background process information, the environment information of the current electronic device, and the current screen snapshot.

[0135] The main control module is configured to call the large language model and the robotic process automation tool module.

[0136] The large language model is configured to determine the current usage scenario of the electronic device based on the basic information and a preset first prompt; and to determine the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and preset recommended settings information; the preset first prompt includes a statement indicating the determination of the current usage scenario of the electronic device; the preset second prompt includes a statement indicating the determination of the recommended settings information of the electronic device.

[0137] The robotic process automation tool module includes a robotic process automation tool configured to adjust the current system settings and / or resource configuration of the electronic device based on the recommended settings information.

[0138] In one exemplary embodiment, the electronic device management device further includes a retrieval enhancement generation algorithm module;

[0139] The main control module is also configured to call the retrieval enhancement generation algorithm module;

[0140] The retrieval enhancement generation algorithm module is configured to perform retrieval in a preset knowledge base based on the basic information and the preset first prompt; and to perform retrieval in the preset knowledge base based on the basic information and the preset second prompt.

[0141] The large language model is further configured to infer the current usage scenario of the electronic device based on the retrieved information, the basic information, and the preset first prompt; and to determine the current recommended settings information of the electronic device based on the retrieved information, the current usage scenario, the preset second prompt, and multiple preset recommended settings information.

[0142] This application describes several embodiments, but these descriptions are exemplary and not restrictive, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0143] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application can also be combined with any conventional features or elements to form unique inventive solutions. Any feature or element of any embodiment can also be combined with features or elements from other inventive solutions to form another unique inventive solution. Therefore, it should be understood that any feature shown and / or discussed in this application can be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes can be made within the scope of the appended claims.

[0144] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0145] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on an electronic device readable medium, which may include electronic device storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term "electronic device storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as electronic device readable instructions, data structures, program modules, or other data). Electronic device storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by the electronic device. Furthermore, it is well known to those skilled in the art that communication media typically contain readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0146] Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include at least one of those features.

[0147] In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise expressly and specifically limited.

[0148] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," "fixing," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0149] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can mean that the first and second features are in direct contact, or that the first and second features are in indirect contact through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0150] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0151] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for managing electronic devices, comprising: Obtain basic information about electronic devices; The basic information includes one or more of the following: the current operating status of the underlying hardware of the electronic device, the current foreground process information, the current background process information, the current environment information of the electronic device, and the current screen snapshot. The current usage scenario of the electronic device is determined based on the basic information and the preset first prompt; the preset first prompt includes a statement indicating the determination of the current usage scenario of the electronic device. Determine the recommended settings for the electronic device based on the current usage scenario; Adjust the current system settings and / or resource configuration of the electronic device according to the recommended settings information.

2. The electronic device management method as described in claim 1, characterized in that, The statement indicating the current usage scenario of the electronic device includes a statement indicating the current usage scenario of the electronic device based on basic information; Determining the current usage scenario of the electronic device based on the basic information and the preset first prompt includes: The basic information and the preset first prompt are input into the large language model, and the current usage scenario of the electronic device is obtained through the reasoning of the large language model.

3. The electronic device management method as described in claim 1, characterized in that, The statement indicating the current usage scenario of the electronic device includes a statement indicating the determination of the current usage scenario of the electronic device based on basic information, user behavior logs, and / or process whitelists. Determining the current usage scenario of the electronic device based on the basic information and the preset first prompt includes: The enhanced generation algorithm performs a search in a preset knowledge base based on the basic information and the preset first prompt; wherein, the preset knowledge base stores user behavior logs and / or process whitelists; The current usage scenario of the electronic device is obtained by reasoning based on the retrieved information, the basic information, and the preset first prompt using a large language model.

4. The electronic device management method as described in claim 1, characterized in that, Determining the recommended settings for the electronic device based on the current usage scenario includes: The recommended settings information for the electronic device are determined based on the correspondence between the current usage scenario, the preset usage scenario, and the recommended settings information.

5. The electronic device management method as described in claim 1, characterized in that, Determining the recommended settings for the electronic device based on the current usage scenario includes: The recommended settings information of the electronic device are determined based on the current usage scenario, the preset second prompt, and multiple preset recommended settings information; the preset second prompt includes a statement that instructs the determination of the recommended settings information of the electronic device.

6. The electronic device management method as described in claim 5, characterized in that, The statement indicating the recommended settings information for the electronic device includes a statement indicating the recommended settings information for the electronic device based on the usage scenario; The step of determining the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and multiple preset recommended settings includes: The current usage scenario and the preset second prompt are input into the large language model, and the recommended settings information of the electronic device are determined by the large language model through reasoning. The recommended setting information that best matches the recommended setting information of the electronic device determined by the large language model among multiple preset recommended setting information is determined as the current recommended setting information of the electronic device.

7. The electronic device management method as described in claim 5, characterized in that, The statement instructing the determination of recommended settings information for an electronic device includes a statement instructing the determination of recommended settings information for the electronic device from a plurality of preset recommended settings information based on the usage scenario; the determination of the current recommended settings information for the electronic device based on the current usage scenario, a preset second prompt, and the plurality of preset recommended settings information includes: The current usage scenario, the preset second prompt, and the preset recommended settings information are input into the large language model. After reasoning by the large language model, the recommended settings information that best matches the current usage scenario of the electronic device among the preset recommended settings information is determined as the current recommended settings information of the electronic device. The second prompt is a statement that instructs the determination of the recommended settings information of the electronic device based on the usage scenario and the preset recommended settings information.

8. The electronic device management method as described in claim 5, characterized in that, The statement instructing the determination of recommended settings information for an electronic device includes a statement instructing the determination of recommended settings information for an electronic device from a plurality of preset recommended settings information based on user behavior preferences in the usage scenario; The step of determining the current recommended settings information of the electronic device based on the current usage scenario, a preset second prompt, and multiple preset recommended settings includes: The enhanced generation algorithm retrieves information from a preset knowledge base based on the basic information and the preset second prompt; wherein, the preset knowledge base stores user behavior logs. Based on the retrieved information, the current usage scenario, the preset second prompt, and the preset recommended settings information, the large language model infers and determines the recommended settings information that best matches the current usage scenario of the electronic device from among multiple preset recommended settings information as the current recommended settings information of the electronic device.

9. The electronic device management method as described in claim 1, characterized in that, Before adjusting the current system settings and / or resource configuration of the electronic device according to the recommended setting information, the method further includes: The recommended settings information is processed to match the information format of the tool that performs the recommended settings.

10. The electronic device management method as described in claim 1, characterized in that, The step of adjusting the current system settings and / or resource configuration of the electronic device according to the recommended setting information includes: The recommended settings are executed using robotic process automation tools to adjust the current system settings and / or resource configuration of the electronic device.

11. The electronic device management method as described in claim 3, characterized in that, The electronic device is a computer.

12. An electronic device management apparatus, comprising a memory and a processor, characterized in that, The memory is used to store programs for electronic device management methods; The processor is configured to read the program that executes the electronic device management method and execute the method according to any one of claims 1 to 11.

13. An electronically readable storage medium storing electronically executable instructions, wherein, The electronic device can execute instructions to cause the electronic device to perform the method of any one of claims 1 to 11.

14. An electronic device management apparatus, characterized in that, include: The data acquisition module is configured to collect basic information about the current electronic device. The basic information includes one or more of the following: the current operating status of the underlying hardware of the electronic device, the current foreground process information, the background process information, the current environment information of the electronic device, and the current screen snapshot. The main control module is configured to call the large language model and the robotic process automation tool module. The large language model is configured to determine the current usage scenario of the electronic device based on the basic information and a preset first prompt. The recommended settings information for the electronic device are determined based on the current usage scenario, the preset second prompt, and the preset recommended settings information. The robotic process automation tool module includes a robotic process automation tool configured to adjust the current system settings and / or resource configuration of the electronic device based on the recommended settings information.

15. The electronic device management device as claimed in claim 14, characterized in that, It also includes a retrieval enhancement generation algorithm module; The main control module is also configured to call the retrieval enhancement generation algorithm module; The retrieval enhancement generation algorithm module is configured to retrieve information from a preset knowledge base based on the basic information and the preset first prompt. The search is performed in the preset knowledge base based on the basic information and the preset second prompt; The large language model is further configured to infer the current usage scenario of the electronic device based on the retrieved information, the basic information, and the preset first prompt; and to determine the current recommended settings information of the electronic device based on the retrieved information, the current usage scenario, the preset second prompt, and multiple preset recommended settings information.

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