Message notification method and apparatus for wearable device, device, and storage medium

Abstract

The present application relates to the technical field of wearable devices, and discloses a message notification method and apparatus for a wearable device, a device, and a storage medium. The message notification method for a wearable device comprises: acquiring user state information and environmental state information of a target user; determining state keywords of the target user on the basis of the user state information and the environmental state information; determining a message notification mode of the wearable device on the basis of the state keywords and an obtained message to be processed, wherein the message notification mode represents a message notification manner of the wearable device; and performing message notification for the target user according to the message notification mode. According to the present application, the message notification manner is switched on the basis of the user state information and the environmental state information, improving the user experience with wearable devices.

Description

Message prompt method, device, equipment and storage medium for wearable device

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application refers to Chinese patent application No. 202311619839.9, filed on November 29, 2023, entitled “Message prompt method, apparatus, device and storage medium for wearable device”, which is incorporated into this application in its entirety by reference. Technical Field

[0003] The present application relates to the technical field of wearable devices, and in particular to a message prompt method, apparatus, device, and storage medium for wearable devices. Background Art

[0004] With the popularization of mobile devices, the improvement of computing power and the advancement of sensor technology, augmented reality (AR) glasses are developing rapidly. The interaction between AR glasses and users is an important part of AR technology.

[0005] At present, the interaction between AR glasses and users includes visual interaction, gesture interaction, voice interaction and tactile feedback, among which visual interaction and voice interaction are the main ways for AR glasses to interact with users. For example, some AR glasses can provide various customized prompt methods and information displays in specific application scenarios, but the interactive switching capabilities in different environmental scenarios are insufficient. For example, when a user receives a message prompt while stationary, the half-screen display can be used for easy reading. However, if the user continues to display the half-screen display while exercising, it will affect the user's vision. In most cases, the user can only be prompted in a fixed form or the prompt method can be switched through instructions. The user's intervention is required to switch the prompt method, which affects the user's vision and leads to a poor user experience.

[0006] Summary of the Invention

[0007] In view of this, the present application provides a message prompt method, apparatus, device and storage medium for a wearable device to solve the problem of insufficient interactive switching function of wearable devices.

[0008] In a first aspect, the present application provides a message prompt method for a wearable device, comprising:

[0009] Obtain user status information and environmental status information of the target user; determine the status keyword of the target user based on the user status information and environmental status information; determine the message prompt mode of the wearable device based on the status keyword and the obtained pending message; wherein the pending message is a message waiting for the user to process, and the message prompt mode represents the message prompt method of the wearable device; and provide a message prompt to the target user according to the message prompt mode.

[0010] Beneficial effects: This application determines the status keywords of the target user based on the user status information that reflects the user's psychological state and movement state, and the environmental status information that reflects the conditions and characteristics in a specific environment or scene, determines the message prompt mode of the wearable device based on the status keywords and the pending messages, and provides message prompts to the target user based on the message prompt mode. This application uses the user status information and environmental status information as the basis for message prompts to the target user, determines the status keywords of the target user, classifies different states and environments, and standardizes them, thereby standardizing the user status information and environmental status information, obtaining status keywords, determining the message prompt mode based on the status keywords, and providing message prompts to the target user based on the message prompt mode. Compared with the related art of switching prompt modes through manual intervention, this application realizes automatic switching of message prompt modes according to user status and environmental status, and can switch the most suitable message prompt mode for the target user without the intervention of the target user, thereby improving the user experience and the efficiency of switching message prompt modes.

[0011] In some embodiments, obtaining user status information and environmental status information of a target user includes: collecting sensor data, where the sensor data is status data collected by the sensor; preprocessing the sensor data to obtain valid data, where the valid data is information that can be used to determine the user status and environmental status; inputting the valid data into a trained preset neural network model to obtain user status information and environmental status information; wherein the input of the preset neural network model is valid data, and the output of the preset neural network model is user status information and environmental status information.

[0012] Beneficial Effects: This application collects sensor data, preprocesses the sensor data, obtains valid data, improves the data quality of the sensor data, reduces data analysis costs, facilitates subsequent data processing, and improves the accuracy of the valid data. The valid data is input into a pre-trained neural network model. The pre-trained neural network is trained with a large amount of data, so the user status information and environmental status information obtained are more accurate.

[0013] In some embodiments, the status keywords of the target user are determined based on the user status information and the environmental status information, including: extracting information from the user status information and the environmental status information to obtain key information; wherein the key information is information representing the motion status and environmental characteristics of the target user; matching the key information with preset keywords, and obtaining status keywords based on the matching results.

[0014] In some embodiments, the message prompt mode of the wearable device is determined based on the status keywords and the obtained pending messages, including: analyzing the status keywords and the pending messages according to preset rules to determine the modality and paradigm of the wearable device; wherein the modality represents the message presentation mode, and the paradigm represents the form of the message presentation; the modality and paradigm are combined to determine the message prompt mode of the wearable device.

[0015] Beneficial effects: This application analyzes status keywords and pending messages according to preset rules, determines the message prompt mode of the wearable device, and comprehensively considers the influence of multiple factors to switch the message prompt mode that best suits the current scenario for the target user, thereby improving the user experience.

[0016] In some embodiments, the rule priority of the preset rule is set according to demand information; wherein the demand information is information indicating user demand.

[0017] Beneficial effects: This application sets the rule priority of the preset rules according to the demand information, and can set the rule priority according to the wishes of the target user. The message prompt mode obtained according to the preset rules will be more in line with the needs of the target user.

[0018] In some embodiments, the message prompt mode is sent to a data output module, and the data output module is used to provide a message prompt to the target user according to the message prompt mode.

[0019] In some embodiments, the user state information is information reflecting the user's psychological state and movement state, and the environmental state information is information about conditions and characteristics in a specific environment or scene.

[0020] In some embodiments, the state keyword is a keyword representing the target user's motion state and environmental characteristics.

[0021] In some embodiments, the message prompt pattern is evaluated based on the artificial intelligence confidence level to determine the accuracy of the message prompt pattern.

[0022] Beneficial effect: This application evaluates the message prompt pattern based on artificial intelligence confidence and determines the accuracy of the message prompt pattern, so that the preset rules can be adjusted based on the accuracy of the message prompt pattern in the future.

[0023] In some embodiments, device information is obtained, where the device information is information indicating the operating status of the wearable device; the operating status of the wearable device is determined based on the device information, and the message prompt mode is adjusted based on the operating status.

[0024] Beneficial effect: This application determines the operating status of the wearable device based on the device information of the wearable device, and determines the message prompt mode based on the operating status. For example, when the operating status is taken off, no message prompt is given, thereby reducing the power consumption of the wearable device.

[0025] In a second aspect, the present application provides a message prompt device for a wearable device, comprising:

[0026] An information acquisition module is used to obtain user status information and environmental status information of the target user; a status keyword determination module is used to determine the status keyword of the target user based on the user status information and environmental status information; a message prompt mode determination module is used to determine the message prompt mode of the wearable device based on the status keyword and the acquired pending message; wherein the pending message is a message waiting for the user to process, and the message prompt mode represents the message prompt method of the wearable device; a message prompt module is used to provide a message prompt to the target user according to the message prompt mode.

[0027] In a third aspect, the present application provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, computer instructions being stored in the memory, and the processor executing the computer instructions to thereby execute the message prompt method for a wearable device of the above-mentioned first aspect or any corresponding embodiment thereof.

[0028] In a fourth aspect, the present application provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the message prompt method for a wearable device of the above-mentioned first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0030] FIG1 is a schematic diagram of a flow chart of a message prompt method for a wearable device according to an embodiment of the present application;

[0031] FIG2 is a flow chart of a message prompt method for another wearable device according to an embodiment of the present application;

[0032] FIG3 is a flow chart of a message prompt method for another wearable device according to an embodiment of the present application;

[0033] FIG4 is a schematic diagram of a data status analysis structure according to an embodiment of the present application;

[0034] FIG5 is a structural block diagram of a message prompt method and apparatus for a wearable device according to an embodiment of the present application;

[0035] FIG6 is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] To make the purpose, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of this application.

[0037] An embodiment of the present application provides a message prompt method for a wearable device, which determines the message prompt mode of the wearable device according to user status information and environmental status information to achieve the effect of automatic switching of the message prompt mode.

[0038] According to an embodiment of the present application, an embodiment of a message prompt method for a wearable device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0039] In this embodiment, a message prompt method for a wearable device is provided, which can be used for the above-mentioned wearable device. FIG1 is a flow chart of the message prompt method for a wearable device according to an embodiment of the present application. As shown in FIG1 , the process includes the following steps:

[0040] Step S101: Acquire user status information and environment status information of a target user.

[0041] In some embodiments, the user state information is information reflecting the user's psychological state and movement state, and the environmental state information is information about conditions and characteristics in a specific environment or scene.

[0042] In some embodiments, user status information and environmental status information of a target user are collected through sensors, wherein a plurality of sensors are configured on a wearable device, and the wearable device may be augmented reality (AR) glasses.

[0043] Among them, the user state information includes the psychological state, physical state and motion state of the target user. For example, the psychological state includes happiness, anger, etc., the physical state includes illness, staring, etc., and the motion state includes riding, walking, stillness, etc.

[0044] The environmental status information includes the environment or scene where the target user is located. For example, the environmental status information includes a conference room, outdoors, a road, and a bedroom.

[0045] Step S102: determining the status keywords of the target user according to the user status information and the environment status information.

[0046] In some embodiments, the state keyword is a keyword representing the target user's motion state and environmental characteristics.

[0047] In some embodiments, user status information and environment status information are analyzed and extracted to obtain key information, the key information is matched with preset keywords, and status keywords are obtained based on the matching results.

[0048] Among them, key information is obtained based on user status information and environmental status information. The key information includes information that represents the user status and environmental status. For example, the key information may be "user is riding outdoors", "user is resting on a park bench", etc.

[0049] Preset keywords are pre-set keywords. Preset keywords include all status keywords of the target user. Preset keywords can also be customized. For example, preset keywords include but are not limited to outdoor, road, bedroom, park, stadium, cycling, walking, resting, stationary, sleeping, jogging, sprinting, driving, cooking, etc.

[0050] Match the key information with the preset keywords, and obtain the status keywords based on the matching results. For example, if the key information is "the user is riding outdoors", match it with the preset keywords to obtain the status keywords: outdoor, riding; if the key information is "the user is resting on a park bench", match it with the preset keywords to obtain the status keywords: park, rest.

[0051] Step S103: determining a message prompt mode of the wearable device according to the status keyword and the obtained pending message; wherein the pending message is a message waiting for the user to process, and the message prompt mode represents the message prompt method of the wearable device.

[0052] In some embodiments, the obtained status keywords and the message to be processed are analyzed to determine the message prompt mode of the wearable device.

[0053] The process analyzes the pending message to determine its word count, length, recipient, and content. The status keyword is then combined with the pending message to determine the wearable device's message notification mode. For example, if the status keyword is "outdoors" or "cycling," and the pending message is five lines long, the wearable device's message notification mode is determined to be: converting the text into a voice broadcast and playing it aloud.

[0054] Among them, there are multiple message prompt modes, which can be customized according to user needs. For example, the message prompt modes include: pop-up full-screen display, pop-up half-screen display, voice broadcast, delayed reminder, ignore, vibration without display, etc.

[0055] Step S104: Prompt a message to the target user according to the message prompt mode.

[0056] In some embodiments, the message prompt mode is sent to a data output module, and the data output module is used to provide a message prompt to the target user according to the message prompt mode.

[0057] Exemplarily, the data output module converts the text into a voice broadcast and plays it aloud.

[0058] In some embodiments, the method further includes: setting a rule priority of a preset rule according to demand information; wherein the demand information is information indicating user demand.

[0059] Among them, the demand information is the information set by the user to express the demand. The rule priority of the preset rules is set according to the demand information. The preset rules can be customized according to the demand information. For example, user safety is more important than user emotions.

[0060] In an embodiment of the present application, status keywords and pending messages are analyzed according to preset rules to determine the message prompt mode of the wearable device. Taking into account the influence of various factors, the message prompt mode that best suits the current scenario is switched for the target user to enhance the user experience.

[0061] The embodiment of the present application sets the rule priority of the preset rules according to the demand information, and can set the rule priority according to the wishes of the target user. The message prompt mode obtained according to the preset rules will better meet the needs of the target user.

[0062] In some embodiments, the method further includes: evaluating the message prompt pattern according to the artificial intelligence confidence level to determine the accuracy of the message prompt pattern.

[0063] AI confidence refers to the AI's assessment of the reliability and accuracy of the message notification mode. AI confidence can also be used as an option in data status analysis to assist in determining the message notification mode. For example, if a target user receives an insulting pending message while feeling happy, the message notification mode can be modified to a delayed one based on the AI ​​confidence.

[0064] In an embodiment of the present application, the message prompt pattern is evaluated based on the artificial intelligence confidence level to determine the accuracy of the message prompt pattern so that the preset rules can be adjusted based on the accuracy of the message prompt pattern.

[0065] In some embodiments, the method further includes: obtaining device information, where the device information is information indicating the operating status of the wearable device; determining the operating status of the wearable device based on the device information, and adjusting the message prompt mode based on the operating status.

[0066] Among them, the device information includes the operating status of the wearable device, the wearing condition of the wearable device, etc. For example, the device information can be worn, taken off, standby, charging, waiting to be charged, no network signal, etc.

[0067] Exemplarily, when the operating state of the wearable device is taken off, the message reminder mode is determined to be no message delayed reminder according to the operating state.

[0068] The embodiment of the present application determines the operating status of the wearable device based on the device information of the wearable device, and determines the message prompt mode according to the operating status. For example, when the operating status is taken off, no message prompt is performed, thereby reducing the power consumption of the wearable device.

[0069] In an embodiment of the present application, a message prompt mode has been confirmed according to the aforementioned embodiment. When a change in the device state of the wearable device is detected, the message prompt mode is updated to a new message prompt mode according to the device state of the wearable device.

[0070] The message prompt method for a wearable device provided in this embodiment determines the status keywords of the target user based on user status information reflecting the user's psychological state and movement state, and environmental status information reflecting the conditions and characteristics in a specific environment or scene, determines the message prompt mode of the wearable device based on the status keywords and the pending message, and performs a message prompt for the target user based on the message prompt mode. This application uses user status information and environmental status information as the basis for message prompting the target user, determines the status keywords of the target user, classifies different states and environments, and standardizes them, thereby standardizing the user status information and environmental status information to obtain status keywords, determines the message prompt mode based on the status keywords, and performs a message prompt for the target user based on the message prompt mode. Compared with the related art of switching prompt modes through manual intervention, this application realizes automatic switching of message prompt modes based on user status and environmental status. Without the intervention of the target user, the most suitable message prompt mode can be switched for the target user, thereby improving the user experience and the efficiency of switching message prompt modes.

[0071] In this embodiment, a message prompt method for a wearable device is provided, which can be used for the above-mentioned wearable device. FIG2 is a flow chart of the message prompt method for a wearable device according to an embodiment of the present application. As shown in FIG2 , the process includes the following steps:

[0072] Step S201: Obtain user status information and environment status information of the target user. Please refer to step S101 of the embodiment shown in FIG1 for details, which will not be repeated here.

[0073] In some embodiments, the above step S201 includes:

[0074] Step S2011: collecting sensor data, where the sensor data is status data collected by the sensor.

[0075] The wearable device is equipped with multiple sensors, and sensor data is collected based on the sensors on the wearable device.

[0076] Step S2012: pre-process the sensor data to obtain valid data, which is information that can be used to determine the user status and the environment status.

[0077] Among them, preprocessing includes operations such as noise reduction, filtering, and data calibration to ensure the validity and reliability of the data.

[0078] Step S2013: input the valid data into the trained preset neural network model to obtain user status information and environment status information.

[0079] The input of the preset neural network model is valid data, and the output of the preset neural network model is user status information and environment status information.

[0080] In some embodiments, the method also includes training a preset neural network model. The training method includes obtaining historical sensor data, preprocessing the historical sensor data to obtain historical valid information, inputting the historical valid information into the preset neural network model, training the preset neural network model, and evaluating the accuracy of the preset neural network model based on the training results.

[0081] Step S202: Determine the target user's status keyword based on the user status information and the environment status information. For details, please refer to step S102 of the embodiment shown in FIG1 , which will not be described in detail here.

[0082] In some embodiments, the above step S202 includes:

[0083] Step S2021 , extracting user status information and environmental status information to obtain key information; wherein the key information is information representing the target user's motion status and environmental characteristics.

[0084] Step S2022: Match the key information with the preset keywords, and obtain the status keywords based on the matching results.

[0085] In step S203, based on the status keyword and the obtained pending message, a message notification mode for the wearable device is determined. A pending message is a message waiting for user processing, and a message notification mode represents the message notification method of the wearable device. For details, please refer to step S103 of the embodiment shown in FIG1 , and will not be repeated here.

[0086] In some embodiments, the above step S203 includes:

[0087] Step S2031: Analyze the status keywords and the message to be processed according to preset rules to determine the modality and paradigm of the wearable device; wherein the modality represents the message presentation mode, and the paradigm represents the form of message presentation.

[0088] Among them, the modes include vision, voice, vibration, voice + vision, sleep, etc., and the paradigms include single-line scrolling at the top of the screen, semi-transparent screen, half screen, full screen display, arrows, pop-ups, low volume, high volume, etc.

[0089] Step S2032: Combine the modality and paradigm to determine the message prompt mode of the wearable device.

[0090] In some embodiments, the modality and paradigm are combined to determine the message prompt mode. For example, the message prompt mode can be voice, in a low voice; visual, in a single-line scrolling at the top of the screen, etc.

[0091] Step S204: Prompt the target user with a message according to the message prompt mode. Please refer to step S104 of the embodiment shown in FIG1 for details, which will not be repeated here.

[0092] In some embodiments, the above step S204 includes:

[0093] Step S2041: Send the message prompt mode to the data output module, and the data output module is used to provide a message prompt to the target user according to the message prompt mode.

[0094] The wearable device message notification method provided in this embodiment collects sensor data, preprocesses the sensor data, obtains valid data, improves the data quality of the sensor data, reduces data analysis costs, facilitates subsequent data processing, and improves the accuracy of the valid data. The valid data is input into a pre-trained neural network model. The pre-trained neural network is trained with a large amount of data, so the user status information and environmental status information obtained are more accurate.

[0095] In this embodiment, a message prompt method for a wearable device is provided, which can be used for the above-mentioned wearable device. FIG3 is a flow chart of a message prompt method for another wearable device according to an embodiment of the present application. As shown in FIG3 , the process includes:

[0096] User status information, environmental status information and device information are obtained according to sensors; data input information is obtained, wherein the data input information is the information to be processed received by the target user; data status analysis is performed on the user status information, environmental status information, device information and input information to obtain analysis results, and the modal paradigm of the wearable device is determined according to the analysis results. According to the modal paradigm data distributor, the modal paradigm is sent to the data output module or application, and the data output module or application is used to prompt the data input information to the target user according to the modal paradigm.

[0097] In an embodiment of the present application, as shown in Figure 4, which is a schematic diagram of the data state analysis structure according to an embodiment of the present application, user state information (user state), environmental state information (environmental state) and device information (device state) are obtained according to the sensor, and the data input includes images, audio and text, etc. The above information is input into the state analysis controller to obtain the modal and paradigm of the wearable device, and the modal and paradigm are sent to the distribution display module or application prompt to prompt the target user with the data input information according to the modal paradigm.

[0098] The wearable device can be an AR glasses. For example, if a target user receives a pending message while sitting on a bench outdoors, then starts cycling, and then receives another pending message during the cycle, AR glasses typically display the pending message content as a notification. The pending message may be a four- or five-line text notification. Receiving a text notification while the target user is sitting on a bench outdoors will not have a negative impact. However, once the target user starts cycling, displaying the pending message content as a notification will block the target user's view, posing a safety hazard.

[0099] In this embodiment of the application, the operational process is as follows: Using various AR sensors, the current environment state is determined to be "outdoors" and the user state is "resting." Based on the input data being long text and various state analyses, the appropriate modal paradigm types are determined to be visual, full screen, half screen, or semi-transparent. The analyzed modal paradigm is distributed to the message notification module, which then provides information prompts to the target user based on the appropriate modal paradigm, such as displaying text to the target user in full screen semi-transparent mode.

[0100] After the target user begins cycling, they receive a longer message to be processed. The state sensor determines that the environment is "outdoors" and the user is "cycling." Based on the long text input and various state analysis, the appropriate modal paradigm is likely to be voice and loud. The analyzed modal paradigm is distributed to the message notification module, which then prompts the target user's device based on the appropriate modal paradigm, such as converting the text into a voice broadcast and playing it loudly.

[0101] Another message prompt method for a wearable device provided in an embodiment of the present application obtains user status information, environmental status information, device information and messages to be processed in real time, determines the modal paradigm of the wearable device based on the above information, and prompts the target user with data input information based on the modal paradigm, thereby realizing the switching of the modal paradigm of the wearable device. Different effects can be obtained without user operation in different state and environmental conditions, thereby improving the user experience.

[0102] In this embodiment, a message prompt device for a wearable device is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceivable.

[0103] This embodiment provides a message prompt device for a wearable device, as shown in FIG5 , including:

[0104] The information acquisition module 501 is used to acquire the user status information and environment status information of the target user.

[0105] The status keyword determination module 502 is used to determine the status keyword of the target user according to the user status information and the environment status information.

[0106] The message prompt mode determination module 503 is used to determine the message prompt mode of the wearable device according to the status keyword and the obtained pending message; wherein the pending message is a message waiting for the user to process, and the message prompt mode represents the message prompt method of the wearable device.

[0107] The message prompt module 504 is configured to provide a message prompt to the target user according to the message prompt mode.

[0108] In some embodiments, the information acquisition module 501 includes:

[0109] The data collection unit is used to collect sensor data, where the sensor data is status data collected by the sensor.

[0110] The preprocessing unit is used to preprocess the sensor data to obtain valid data, which is information that can be used to determine the user status and environmental status.

[0111] The neural network output unit is used to input valid data into the trained preset neural network model to obtain user status information and environmental status information; wherein, the input of the preset neural network model is valid data, and the output of the preset neural network model is user status information and environmental status information.

[0112] In some embodiments, the status keyword determination module 502 includes:

[0113] The information extraction unit is used to extract user status information and environmental status information to obtain key information; wherein the key information is information representing the motion status of the target user and environmental characteristics.

[0114] The keyword matching unit is used to match the key information with the preset keywords and obtain the status keywords according to the matching results.

[0115] In some embodiments, the message prompt mode determination module 503 includes:

[0116] The information analysis unit is used to analyze the status keywords and the messages to be processed according to preset rules to determine the modality and paradigm of the wearable device; wherein the modality represents the message presentation mode, and the paradigm represents the form of message presentation.

[0117] The message prompt mode determination unit is used to combine the modality and paradigm to determine the message prompt mode of the wearable device.

[0118] In some embodiments, the message prompt module 504 includes:

[0119] The message prompt unit is used to send the message prompt mode to the data output module, and the data output module is used to provide a message prompt to the target user according to the message prompt mode.

[0120] In some embodiments, the apparatus further comprises:

[0121] The priority setting module is used to set the rule priority of the preset rule according to the demand information; wherein the demand information is information indicating the user's demand.

[0122] The evaluation module is used to evaluate the message prompt mode according to the artificial intelligence confidence level to determine the accuracy of the message prompt mode.

[0123] The operating status determination module is used to obtain device information, which is information indicating the operating status of the wearable device; determine the operating status of the wearable device based on the device information, and determine the message prompt mode based on the operating status.

[0124] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0125] The message prompt device of the wearable device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0126] An embodiment of the present application also provides a computer device having the message prompt device of the wearable device shown in FIG. 5 above.

[0127] Figure 6 is a structural diagram of a computer device provided by an optional embodiment of the present application. As shown in Figure 6, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In some embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 6 takes a processor 10 as an example.

[0128] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0129] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0130] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0131] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0132] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0133] The embodiments of the present application also provide a computer-readable storage medium. The above-mentioned method according to the embodiment of the present application can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0134] Although the embodiments of the present application have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations shall fall within the scope defined by the appended claims.

Claims

1. A message prompt method for a wearable device, wherein: The method comprises: Obtain user status information and environment status information of the target user; Determining a status keyword of the target user according to the user status information and the environment status information; Determine a message prompt mode of the wearable device according to the status keyword and the acquired pending message; wherein the pending message is a message waiting for a user to process, and the message prompt mode represents a message prompt mode of the wearable device; Providing a message prompt to the target user according to the message prompt mode.

2. The method according to claim 1, wherein: The step of obtaining the user status information and environment status information of the target user includes: Collecting sensor data, where the sensor data is status data collected by the sensor; Preprocessing the sensor data to obtain valid data, where the valid data is information that can be used to determine the user status and the environment status; The valid data is input into a trained preset neural network model to obtain the user status information and the environment status information; wherein the input of the preset neural network model is the valid data, and the output of the preset neural network model is the user status information and the environment status information.

3. The method according to claim 1 or 2, wherein: The determining the state keyword of the target user according to the user state information and the environment state information includes: Extracting the user status information and the environment status information to obtain key information; wherein the key information is information indicating the motion status and environment characteristics of the target user; The key information is matched with a preset keyword, and the status keyword is obtained according to the matching result.

4. The method according to any one of claims 1 to 3, wherein: The determining of the message prompt mode of the wearable device according to the state keyword and the acquired message to be processed includes: Analyze the state keywords and the to-be-processed messages according to preset rules to determine the mode and paradigm of the wearable device; wherein the mode represents the message presentation mode, and the paradigm represents the form of message presentation; The modality and the paradigm are combined to determine the message prompt mode of the wearable device.

5. The method according to claim 4, wherein: The method further comprises: The rule priority of the preset rule is set according to the demand information; wherein the demand information is information indicating the user demand.

6. The method according to any one of claims 1 to 5, wherein: Providing a message prompt to the target user according to the message prompt mode includes: The message prompt mode is sent to a data output module, and the data output module is used to provide a message prompt to the target user according to the message prompt mode.

7. The method according to any one of claims 1 to 6, wherein: The user state information is information reflecting the user's psychological state and movement state, and the environment state information is information about conditions and features in a specific environment or scene.

8. The method according to any one of claims 1 to 7, wherein: The state keywords are keywords representing the motion state and environmental characteristics of the target user.

9. The method according to any one of claims 1 to 8, wherein: The method further comprises: The message prompt mode is evaluated according to the artificial intelligence confidence level to determine the accuracy of the message prompt mode.

10. The method according to any one of claims 1 to 9, wherein: The method further comprises: Acquire device information, where the device information is information indicating the operating status of the wearable device; Determine the operating status of the wearable device according to the device information, and adjust the message prompt mode according to the operating status.

11. A message prompting device for a wearable device, wherein: The device comprises: An information acquisition module is used to acquire user status information and environment status information of a target user; A status keyword determination module, used to determine the status keyword of the target user according to the user status information and the environment status information; A message prompt mode determination module, used to determine the message prompt mode of the wearable device according to the state keyword and the acquired pending message; wherein the pending message is a message waiting for the user to process, and the message prompt mode represents the message prompt mode of the wearable device; A message prompt module is used to provide message prompts to the target user according to the message prompt mode.

12. A computer device, wherein: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the message prompt method of the wearable device according to any one of claims 1 to 10 by executing the computer instructions.

13. A computer-readable storage medium, wherein: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the message prompt method for a wearable device according to any one of claims 1 to 10.

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