Method and device for adjusting contextual model of mobile terminal, equipment and medium

Abstract

The embodiment of the invention provides a method and device for adjusting a scene mode of a mobile terminal, equipment and a medium. The method comprises the following steps: acquiring geographical location information of the location of the mobile terminal; acquiring associated data of the geographical location information, wherein the associated data comprises pictures and videos; determining the area type of the location of the mobile terminal according to the associated data of the geographical location information; and setting a contextual model of the mobile terminal according to the area type of the position where the mobile terminal is located. According to the technical scheme, region division can be performed on the position of the mobile terminal according to the position of the mobile terminal, the contextual model of the mobile terminal is set according to the divided region type, the mobile terminal can be automatically adjusted according to the change of the surrounding environment and the position, the use requirement of a user is further met, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of device control, and in particular to a method for adjusting a scenario mode of a mobile terminal, a device for adjusting a scenario mode of a mobile terminal, an electronic device and a computer-readable storage medium. Background Art

[0002] With the popularization of mobile Internet and the maturity of GPS (Global Positioning System) positioning technology, users can easily obtain the geographic location information of themselves or the target location. However, only knowing the latitude and longitude information of the geographic location information of yourself or the target location is often not enough to intuitively understand the specific environment, topography or area type of the location. For example, if the area where the location is located is a quiet environment, such as a library or a conference room, a loud mobile phone ringtone that suddenly rings will have an impact, while in noisy cafeterias, buses, etc., the mobile phone ringtone is often not heard, resulting in missed calls or text messages. In general, user mobile devices are pre-defined scenario modes, which cannot be automatically adjusted according to the noise level of the surrounding environment and changes in the user's location, and thus cannot meet the user's usage needs. Summary of the invention

[0003] In view of the above problems, embodiments of the present invention are proposed to provide a method for adjusting the scenario mode of a mobile terminal, an apparatus for adjusting the scenario mode of a mobile terminal, an electronic device and a computer-readable storage medium that overcome the above problems or at least partially solve the above problems.

[0004] In order to solve the above problem, a first aspect of an embodiment of the present invention provides a method for adjusting a scenario mode of a mobile terminal, the method comprising:

[0005] Obtaining geographical location information of the mobile terminal;

[0006] Acquire the associated data of the geographic location information, the associated data including pictures and videos;

[0007] Determining the area type of the location of the mobile terminal according to the associated data of the geographical location information;

[0008] The scenario mode of the mobile terminal is set according to the area type where the mobile terminal is located.

[0009] Optionally, the acquiring the associated data of the geographic location information includes:

[0010] The search engine is used to search according to the geographical location information and the reference information to obtain related data.

[0011] Optionally, the acquiring of the associated data of the geographic location information further includes:

[0012] The mobile terminal is queried for associated data corresponding to the geographic location information.

[0013] Optionally, determining the area type of the location of the mobile terminal according to the associated data of the geographical location information includes:

[0014] Preprocessing the associated data corresponding to the geographic location information;

[0015] Extracting features from the preprocessed associated data to obtain feature data of the associated data;

[0016] The characteristic data of the associated data is input into a preset area type determination model to obtain the area type of the location where the mobile terminal is located.

[0017] Optionally, the area type includes: a noisy area and a quiet area;

[0018] The step of setting the device scenario mode of the mobile terminal according to the area type of the location of the mobile terminal includes:

[0019] When the area type of the location of the mobile terminal is the noisy area, setting the mobile terminal to a high volume mode;

[0020] When the area type of the location of the mobile terminal is the quiet area, the mobile terminal is set to a vibration mode.

[0021] Optionally, the preset area type determination model can be trained in the following manner:

[0022] Acquire sample data and a label corresponding to the sample data; the sample data includes picture data and video data; the label indicates the type of region to which the position corresponding to the sample data belongs;

[0023] Extracting features from the sample data to obtain feature data of the sample data;

[0024] Training a deep learning model according to the feature data of the sample data and the annotations corresponding to the sample data, and adjusting model parameters according to the training results;

[0025] After the deep learning model training is completed, the preset area type determination model is obtained.

[0026] Optionally, the method further comprises:

[0027] When the location of the mobile terminal cannot be determined, the area type of the location of the mobile terminal is classified as the quiet area, and the mobile terminal is set to a vibration mode.

[0028] According to a second aspect of the present invention, there is provided a device for adjusting a scenario mode of a mobile terminal, the device comprising:

[0029] A location information acquisition module, used to acquire the geographical location information of the mobile terminal;

[0030] A related data acquisition module, used to acquire the related data of the geographic location information, wherein the related data includes pictures and videos;

[0031] An area type determination module, used to determine the area type of the location of the mobile terminal according to the associated data of the geographical location information;

[0032] The scenario mode setting module is used to set the scenario mode of the mobile terminal according to the area type where the mobile terminal is located.

[0033] Optionally, the associated data acquisition module includes:

[0034] The information search submodule is used to search according to the geographical location information and reference information through a search engine to obtain related data.

[0035] Optionally, the associated data acquisition module further includes:

[0036] The information query submodule is used to query the associated data corresponding to the geographical location information from the mobile terminal.

[0037] Optionally, the region type determination module includes:

[0038] A data preprocessing submodule, used to preprocess the associated data corresponding to the geographic location information;

[0039] A feature extraction submodule is used to extract features from the preprocessed associated data to obtain feature data of the associated data;

[0040] The location determination submodule is used to input the characteristic data of the associated data into a preset area type determination model to obtain the area type of the location of the mobile terminal.

[0041] Optionally, the area types include: noisy area and quiet area; the scene mode setting module includes:

[0042] A first setting submodule, configured to set the mobile terminal to a high volume mode when the area type of the location of the mobile terminal is the noisy area;

[0043] The second setting submodule is used to set the mobile terminal to a vibration mode when the area type of the location of the mobile terminal is the quiet area.

[0044] Optionally, the preset area type determination model can be obtained by training the following modules:

[0045] A sample acquisition module, used to acquire sample data and annotations corresponding to the sample data; the sample data includes picture data and video data; the annotation indicates the type of region to which the position corresponding to the sample data belongs;

[0046] A feature data acquisition module, used to extract features from the sample data to obtain feature data of the sample data;

[0047] A model training module, used to train a deep learning model according to the feature data of the sample data and the annotations corresponding to the sample data, and adjust the model parameters according to the training results;

[0048] The model determination module is used to obtain the preset area type determination model after the deep learning model training is completed.

[0049] Optionally, the device further comprises:

[0050] The mode setting module is used for classifying the area type of the location of the mobile terminal as the quiet area and setting the mobile terminal to the vibration mode when the location of the mobile terminal cannot be determined.

[0051] According to a third aspect of the present invention, there is provided an electronic device comprising: a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the steps of a method for adjusting a scenario mode of a mobile terminal as described above.

[0052] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method for adjusting the scenario mode of a mobile terminal as described above are implemented.

[0053] The technical solution provided by the embodiments of the present invention may have the following beneficial effects:

[0054] The embodiment of the present invention provides a method, apparatus, device and medium for adjusting the scenario mode of a mobile terminal, the method comprising: obtaining geographic location information of the location of the mobile terminal; obtaining associated data of the geographic location information, the associated data comprising pictures and videos; determining the area type of the location of the mobile terminal according to the associated data of the geographic location information; and setting the scenario mode of the mobile terminal according to the area type of the location of the mobile terminal. The location of the mobile terminal can be divided into regions according to the location of the mobile terminal, and the scenario mode of the mobile terminal can be set according to the region type obtained by the division, so that the mobile terminal can automatically adjust according to the changes in the surrounding environment and the location, further meeting the user's usage needs and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is a flowchart of a method for adjusting a scenario mode of a mobile terminal provided by an embodiment of the present invention;

[0056] Figure 2 is a flowchart of another method for adjusting a scene mode of a mobile terminal provided by an embodiment of the present invention;

[0057] Figure 3 It is a flow chart of a method for adjusting a scenario mode of a mobile terminal provided by an embodiment of the present invention;

[0058] Figure 4 The present invention is a structural block diagram of a device for adjusting a scenario mode of a mobile terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0060] In general, user mobile phones have pre-defined scenario modes, which cannot be automatically adjusted according to the noise level of the surrounding environment and changes in the user's location, and thus cannot meet the user's usage needs.

[0061] One of the core concepts of the embodiments of the present invention is to obtain the geographical location information of the location of the mobile terminal, and obtain the associated data corresponding to the geographical location information, wherein the associated data includes pictures and videos. According to the associated data of the geographical location information, the area type of the location of the mobile terminal is determined, and the scenario mode of the mobile terminal is set according to the area type of the location of the mobile terminal. The location of the mobile terminal can be divided into regions according to the location of the mobile terminal, and the scenario mode of the mobile terminal can be set according to the area type obtained by the division, so that the mobile terminal can automatically adjust according to the changes in the surrounding environment and the location, further meet the user's usage needs, and improve the user experience.

[0062] Reference Figure 1 , shows a flowchart of a method for adjusting a scenario mode of a mobile terminal provided by an embodiment of the present invention, wherein the method may specifically include the following steps:

[0063] Step 101, obtaining geographical location information of the mobile terminal;

[0064] Mobile Terminal usually refers to a portable device that can transmit and communicate data through wireless communication technology. These devices usually have portability, wireless connection capabilities and multiple functions, and are widely used in personal communication, entertainment, work and other fields. It mainly refers to mobile devices such as mobile phones.

[0065] Geolocation Information refers to data related to geographic location, usually including longitude, latitude, altitude, direction, speed and other information.

[0066] In this embodiment, the mobile terminal receives signals from the global positioning system (GPS) satellite. The GPS module on the mobile terminal obtains the longitude and latitude through data traffic based on the received signals. The user's location can be calculated based on the longitude and latitude obtained from the geographical location information. Alternatively, the base station positioning technology of the mobile communication network is used to determine the location of the device by calculating the distance between the device and the surrounding base stations. After the mobile terminal obtains information such as longitude and latitude and address names, the system on the mobile terminal uses geocoding technology to convert them into specific geographical locations, thereby obtaining the current location information of the mobile terminal.

[0067] Step 102, obtaining the associated data of the geographic location information, the associated data including pictures and videos;

[0068] Many map services on mobile terminals (such as Google Maps, Amap, Baidu Maps, etc.) provide pictures and video data related to geographic locations. The terminal database or user-uploaded content can also obtain pictures and videos related to geographic location information.

[0069] In this embodiment, based on the acquired geographic location information, the system of the mobile device sends requests to multiple network search engines (such as Baidu Pictures, WeChat Video, and AutoNavi) to retrieve pictures and videos related to the location. In order to improve the retrieval efficiency, filtering can be performed in combination with timestamps and keywords (such as "city landscape", "natural scenery", "noon time", "August", etc.). Combined with the time and weather conditions at that time, the network is searched for relevant text, pictures and videos of the location (approximate time point, weather conditions).

[0070] If there are some pictures and videos related to the geographic location in the mobile terminal and stored locally or in a database, these related data can be obtained by querying the database.

[0071] Step 103, determining the area type of the location of the mobile terminal according to the associated data of the geographical location information;

[0072] The area type of the mobile terminal location can be classified according to different standards, and common classification methods include geographical features, functional use, network coverage, etc. This embodiment mainly involves classifying the area environment of the location into noisy areas and quiet areas.

[0073] In this embodiment, the type of region where the mobile terminal is located can be inferred based on the associated data of the geographic location information (such as pictures, videos, etc.). Use the preset region type determination model to analyze the image and video content, and identify features such as buildings, roads, and natural landscapes. For example: if the image mainly contains high-rise buildings and commercial billboards, it may be a commercial area; if the image mainly contains residential buildings and green belts, it may be a residential area; if the image mainly contains natural landscapes (such as mountains, water, and trees), it may be a nature reserve or suburb. Use a pre-trained image classification model (such as ResNet, EfficientNet) to classify the image, and infer the region type based on the classification results.

[0074] Step 104: setting a scenario mode of the mobile terminal according to the area type where the mobile terminal is located.

[0075] Scenario Mode is a function that automatically adjusts device settings based on the user's environment or needs. It can help users optimize device performance, save power, improve efficiency or enhance user experience in different scenarios. Scenario Mode is widely used in mobile terminals and electronic devices such as smartphones, tablets, laptops, and smart home devices.

[0076] In this embodiment, the scenario mode of the mobile terminal can be dynamically set according to the type of area where the mobile terminal is located (such as commercial area, residential area, industrial area, leisure area, etc.). The scenario mode usually includes the adjustment of parameters such as volume, brightness, notification settings, and network connection. For example, in a commercial area with a large flow of people and a noisy environment, you may need to make calls or receive notifications frequently, so you need to set the volume to medium or high. In an office area with a relatively quiet environment, you can set the volume to low or vibration mode.

[0077] This embodiment can divide the location of the mobile terminal into regions according to the location of the mobile terminal, and set the scenario mode of the mobile terminal according to the region type obtained by the division, so that the mobile terminal can automatically adjust according to the changes in the surrounding environment and the location, further meet the user's usage needs and improve the user experience. It can be used in noisy scenes such as shopping malls and supermarkets, where the main call is missed because the ringtone of the mobile terminal is too small. Or in quiet places such as libraries or parks. Because the incoming call ringtone of the mobile device is too loud, it affects others.

[0078] Reference Figure 2 , shows a flowchart of another method for adjusting a scenario mode of a mobile terminal provided by an embodiment of the present invention, wherein the method may specifically include the following steps:

[0079] Step 201, obtaining geographical location information of the mobile terminal;

[0080] In this embodiment, the mobile terminal receives signals from the global positioning system (GPS) satellite. The GPS module on the mobile terminal obtains the longitude and latitude through data traffic based on the received signals. The user's location can be calculated based on the longitude and latitude obtained from the geographical location information. Alternatively, the base station positioning technology of the mobile communication network is used to determine the location of the device by calculating the distance between the device and the surrounding base stations. After the mobile terminal obtains information such as longitude and latitude and address names, the system on the mobile terminal uses geocoding technology to convert them into specific geographical locations, thereby obtaining the current location information of the mobile terminal.

[0081] Step 202, obtaining the associated data of the geographic location information, the associated data including pictures and videos;

[0082] In this embodiment, based on the acquired geographic location information, the system of the mobile device sends requests to multiple network search engines (such as Baidu Pictures, WeChat Video, and AutoNavi) to retrieve pictures and videos related to the location. In order to improve the retrieval efficiency, filtering can be performed in combination with timestamps and keywords (such as "city landscape", "natural scenery", "noon time", "August", etc.). Combined with the time and weather conditions at that time, the network is searched for relevant text, pictures and videos of the location (approximate time point, weather conditions).

[0083] If there are some pictures and videos related to the geographic location in the mobile terminal and stored locally or in a database, these related data can be obtained by querying the database.

[0084] In some embodiments, step 202 includes the following sub-steps:

[0085] Sub-step S11, searching by a search engine according to the geographical location information and the reference information to obtain related data.

[0086] A search engine is a tool used to find information on the Internet. It helps users quickly find the information they need by crawling, indexing, and retrieving web page content. This includes Baidu Images, WeChat Videos, and Amap on mobile terminals.

[0087] Reference information is information associated with a geographic location, including timestamps, keywords (such as "city landscape", "natural scenery", "what time at noon", "August", etc.).

[0088] In this embodiment, the search engine searches based on the geographic location information and reference information to obtain associated data (such as pictures, videos, articles, comments, etc.) related to the location. Based on the geographic location information such as longitude and latitude, place names, etc., and the reference information corresponding to the geographic location such as time, scenic spots, etc., the search engine searches based on the geographic location information, and filters the searched content based on the reference information, obtains the corresponding picture data from the picture search results, and extracts the corresponding video data from the video search results, and further processes the data based on the search results.

[0089] Sub-step S21, querying the associated data corresponding to the geographical location information from the mobile terminal.

[0090] In this embodiment, if the mobile terminal has stored data related to the geographic location information (such as pictures, videos, logs, etc.), it can be directly queried from the local storage. The mobile terminal's file system API (such as Android's MediaStore or iOS's Photos framework) is used to query pictures and videos related to the geographic location information, and the geographic location is matched through the metadata of the pictures and videos (such as GPS information).

[0091] If the mobile terminal stores logs or database records related to the geographic location, the associated data can be obtained by querying the database. The cloud API can be used to query data related to the geographic location information, and query pictures and videos related to the geographic location.

[0092] If a mobile terminal user shares data related to a geographic location on social media, the social media API can be used to query pictures and videos related to the geographic location.

[0093] Step 203, determining the area type of the location of the mobile terminal according to the associated data of the geographical location information;

[0094] In this embodiment, the type of area where the mobile terminal is located can be inferred based on the associated data of the geographic location information (such as pictures, videos, etc.). Use image recognition technology (such as deep learning models) to analyze the content of pictures and videos to identify features such as buildings, roads, and natural landscapes. For example: if the picture mainly contains high-rise buildings and commercial billboards, it may be a commercial area; if the picture mainly contains residential buildings and green belts, it may be a residential area; if the picture mainly contains natural landscapes (such as mountains, water, and trees), it may be a nature reserve or suburb. Use a pre-trained image classification model (such as ResNet, EfficientNet) to classify the pictures, and infer the area type based on the classification results.

[0095] In some embodiments, step 203 includes the following sub-steps:

[0096] Sub-step S31, pre-processing the associated data corresponding to the geographic location information;

[0097] Preprocessing refers to a series of operations to clean, transform, and optimize raw data in the fields of data analysis, machine learning, natural language processing (NLP), image processing, etc. The purpose of preprocessing is to improve the quality and usability of data for subsequent analysis and application.

[0098] In this embodiment, the retrieved pictures and videos are preprocessed (such as resizing, denoising, key frame extraction, etc.).

[0099] Including: Data cleaning: Check whether there are duplicates in the data and delete the duplicate data; Check whether there are missing values ​​in the data and fill or delete them as appropriate; Delete data that does not meet the requirements (such as invalid image data, video data, etc.). Data formatting: Convert data into a unified format for subsequent processing. Data standardization: Convert data into a standardized form for easy comparison and analysis. Data filtering: Filter data according to specific conditions. Through these preprocessing steps, the quality and availability of data can be improved.

[0100] Sub-step S32, extracting features from the pre-processed associated data to obtain feature data of the associated data;

[0101] Feature extraction is a key step in data processing and machine learning, which aims to extract useful features from raw data in order to better represent the data and improve the performance of the model. The goal of feature extraction is to reduce the complexity of the data while retaining the most important information.

[0102] Feature data refers to the attributes or characteristics used to describe and represent data in the fields of data analysis, machine learning, and artificial intelligence. Feature data is extracted from raw data, can reflect the key information of the data, and is used for subsequent analysis, modeling, or decision-making.

[0103] In this embodiment, feature extraction is performed on the preprocessed associated data to obtain feature data of the associated data. Feature extraction is the process of converting raw data into a more representative and analyzable feature vector. Image recognition and video analysis technology are used to extract key features, including but not limited to color distribution, texture features, object recognition (such as buildings, trees, crowds, etc.) and dynamic features in the video.

[0104] Sub-step S33, inputting the characteristic data of the associated data into a preset area type determination model to obtain the area type of the location of the mobile terminal.

[0105] The preset region type determination model is a model used to automatically identify and classify region types according to specific standards or rules. This model can be applied to the fields of geographic information system (GIS), urban planning, traffic management, environmental monitoring, etc.

[0106] The preset region type determination model is a system based on rules, statistical methods or machine learning algorithms, which is used to automatically identify and classify region types based on input geographic data (such as location, environmental characteristics, population density, etc.). Region types can be urban, suburban, rural, industrial, commercial, etc.

[0107] Automatically identifying region types based on input data can reduce the workload of manual classification and improve classification efficiency.

[0108] The preset area type determination model is obtained through deep learning model training, which can be a convolutional neural network (CNN), a recurrent neural network (RNN), a Transformer, etc., which is not limited in this embodiment of the present invention.

[0109] In this embodiment, before inputting feature data into the model, it is necessary to ensure that the feature data has been preprocessed and feature extracted and meets the input requirements of the model. Ensure that the image features have been extracted through the pre-trained model, and ensure that the video features have extracted frame features or motion features. If there is already a pre-trained region type determination model, the model can be loaded directly; otherwise, the model needs to be trained first. Input the feature data into the model to obtain the region type of the mobile terminal. The feature data can be effectively used to predict the region type of the mobile terminal.

[0110] In some embodiments, the preset area type determination model can be trained in the following manner:

[0111] Obtain sample data and annotations corresponding to the sample data; the sample data includes image data and video data; the annotations indicate the type of area to which the position corresponding to the sample data belongs; perform feature extraction on the sample data to obtain feature data of the sample data; train a deep learning model based on the feature data of the sample data and the annotations corresponding to the sample data, and adjust model parameters based on the training results; after the deep learning model training is completed, obtain the preset area type determination model.

[0112] Sample data refers to a part of the data extracted from the population to represent the characteristics of the population. Sample data is usually used in statistical analysis to infer the properties of the population. The selection and analysis of sample data is crucial to draw accurate conclusions.

[0113] Sample data annotation refers to marking or classifying sample data for subsequent analysis, processing or training of machine learning models. The purpose of annotation is to give clear meaning or labels to data so that the data is interpretable or can be used for specific tasks (such as classification, regression, clustering, etc.).

[0114] Deep learning models are a subfield of machine learning that mainly use multi-layer neural networks to process complex data patterns and features. Deep learning models have achieved remarkable results in image recognition, natural language processing, speech recognition, recommendation systems, etc. The core of deep learning models is a neural network, which consists of multiple layers, each of which contains multiple neurons (or nodes).

[0115] Model training is a core step in deep learning. Its purpose is to optimize model parameters so that it can learn useful patterns or features from data and complete specific tasks (such as classification, regression, generation, etc.).

[0116] In this embodiment, a deep learning model is used to automatically classify the region types based on the extracted features. The model is trained with a large amount of annotated data (i.e., a collection of pictures and videos of known region types) to learn the features of different region types. Different regions are classified based on the features.

[0117] Obtain sample data and annotations. The sample data includes image data and video data. The annotations indicate the location of the target object in the sample data and the type of area to which it belongs. For image data, the annotation is usually the category label of the target location. For video data, the annotation can be the type of area to which the motion trajectory of the target object belongs.

[0118] Perform feature extraction on sample data. Feature extraction is to extract useful features from images or videos for subsequent model training. For image feature extraction, a convolutional neural network (CNN) is used to extract local and global features of the image. For video feature extraction, a 3D convolutional network (3D CNN) or a temporal convolutional network (Temporal CNN) is used to extract the temporal and spatial features of the video. For example, image features extract the visual features of each target (such as color, texture, and shape), and video features extract the motion features of the target (such as speed and direction).

[0119] The deep learning model is trained based on the feature data and annotations. The feature data and annotation data are input into the training model, the output of the model (such as the category of the target location) is calculated, the classification loss is calculated to measure the difference between the predicted category and the true category and the model parameters are updated. The above steps are repeated until the model converges and the model parameters are adjusted according to the training results.

[0120] After the training is completed, the preset area type determination model is obtained, the performance of the training model is evaluated using the test set, and the trained model is deployed in practical applications.

[0121] Step 204: setting a scenario mode of the mobile terminal according to the area type where the mobile terminal is located.

[0122] In this embodiment, the scenario mode of the mobile terminal can be dynamically set according to the type of area where the mobile terminal is located (such as commercial area, residential area, industrial area, leisure area, etc.). The scenario mode usually includes the adjustment of parameters such as volume, brightness, notification settings, and network connection. For example, in a commercial area with a large flow of people and a noisy environment, you may need to make calls or receive notifications frequently, so you need to set the volume to medium or high. In an office area with a relatively quiet environment, you can set the volume to low or vibration mode.

[0123] In some embodiments, the area types include: noisy area and quiet area; step 204 includes the following sub-steps:

[0124] Sub-step S41, when the area type of the location of the mobile terminal is the noisy area, setting the mobile terminal to a high volume mode;

[0125] The area type classification may include a noisy area and a quiet area, and the location of the mobile terminal may be divided into a noisy area or a quiet area.

[0126] In this embodiment, the area type of the mobile terminal is identified by an area type determination model (such as a classification model or a deep learning model). If the area type is a "noisy area", subsequent operations are performed. The current volume setting is obtained, the volume is set to a high-end mode, and the current setting is saved (optional) so that it can be restored when leaving the noisy area. The volume setting of the mobile terminal can be dynamically adjusted according to the area type to improve the user experience.

[0127] Sub-step S42: When the area type where the mobile terminal is located is the quiet area, setting the mobile terminal to a vibration mode.

[0128] In this embodiment, the area type of the mobile terminal is identified by an area type determination model (such as a classification model or a deep learning model). If the area type is a "quiet area", subsequent operations are performed. The current ringtone mode is obtained, the ringtone mode is set to a vibration mode, and the current setting is saved (optional) so that it can be restored when leaving the quiet area.

[0129] Step 205: When the location of the mobile terminal cannot be determined, the area type of the location of the mobile terminal is classified as the quiet area, and the mobile terminal is set to a vibration mode.

[0130] In this embodiment, when the location of the mobile terminal cannot be determined, the area type of the location of the mobile terminal can be classified as a "quiet area" by default, and the mobile terminal can be set to vibration mode. In the case where the location of the mobile terminal cannot be determined, there are usually several situations: the GPS signal is lost and the current longitude and latitude information cannot be obtained, the network positioning fails and the positioning cannot be performed through Wi-Fi or base stations, and the user turns off the positioning service. The user manually turns off the positioning permission. If the location cannot be determined, the area type is set to "quiet area" by default. You can determine whether the location cannot be determined by checking the status of the positioning service.

[0131] Set the ringtone mode to vibration mode. If you need to restore the ringtone mode after restoring the location, you can save the current ringtone mode and restore the previous ringtone mode after restoring the location.

[0132] This embodiment can significantly improve the user experience by dynamically adjusting the scenario mode (such as volume, vibration mode, etc.) according to the area type where the mobile terminal is located. In noisy areas, the volume is set to high mode to ensure that users can clearly hear notifications and sounds in noisy environments; in quiet areas, the ringtone mode is set to vibration mode to avoid disturbing others, especially in places such as libraries and conference rooms; when the location cannot be determined, it is set to quiet area and vibration mode by default to ensure that the device does not make noise when positioning services are not available.

[0133] Reference Figure 3, showing a flow chart of a method for adjusting a scenario mode of a mobile terminal provided by an embodiment of the present invention,

[0134] In this embodiment, by obtaining the geographical location information of the mobile terminal, and judging the region of the mobile terminal according to the geographical location information, the mobile terminal's adjustment device scene mode is turned on and the corresponding scene mode is adjusted. According to the user's geographical location, the system can automatically switch to a scene mode suitable for the area to improve the user experience.

[0135] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0136] Reference Figure 4 , shows a structural block diagram of a device for adjusting a scenario mode of a mobile terminal provided by an embodiment of the present invention, which may specifically include the following modules:

[0137] The location information acquisition module 401 is used to acquire the geographical location information of the mobile terminal;

[0138] In this embodiment, the location information acquisition module 401 obtains the longitude and latitude through the data flow according to the received signal through the GPS module on the mobile terminal, and the user's location can be calculated based on the longitude and latitude to obtain the geographical location information. Or the base station positioning technology of the mobile communication network is used to determine the location of the device by calculating the distance between the device and the surrounding base stations. After the mobile terminal obtains the longitude and latitude, address name, the system on the mobile terminal uses the geocoding technology to convert it into a specific geographical location, thereby obtaining the current location information of the mobile terminal.

[0139] The associated data acquisition module 402 is used to acquire the associated data of the geographic location information, wherein the associated data includes pictures and videos;

[0140] In this embodiment, the associated data acquisition module 402 sends a search request to multiple network search engines based on the acquired geographic location information to retrieve pictures and videos related to the location. In order to improve the search efficiency, filtering can be performed in combination with timestamps and keywords. In combination with the time and weather conditions at that time, the network is searched for relevant text, pictures and videos of the location (approximate time point, weather conditions). If there are some pictures and videos related to the geographic location stored locally or in a database in the mobile terminal, these associated data can be obtained by querying the database.

[0141] An area type determination module 403, configured to determine the area type of the location of the mobile terminal according to the associated data of the geographical location information;

[0142] In this embodiment, the area type determination module 403 can infer the area type of the location of the mobile terminal based on the associated data of the geographic location information (such as pictures, videos, etc.). The preset area type determination model is used to analyze the image and video content to identify the features of the location, such as buildings, roads, and natural landscapes. For example: if the picture mainly contains high-rise buildings and commercial billboards, it may be a commercial area; if the picture mainly contains residential buildings and green belts, it may be a residential area; if the picture mainly contains natural landscapes (such as mountains, water, and trees), it may be a nature reserve or suburb. Use a pre-trained image classification model (such as ResNet, EfficientNet) to classify the picture, and infer the area type based on the classification results.

[0143] The scenario mode setting module 404 is used to set the scenario mode of the mobile terminal according to the area type where the mobile terminal is located.

[0144] In this embodiment, the scenario mode setting module 404 can dynamically set the scenario mode of the mobile terminal according to the type of area where the mobile terminal is located (such as commercial area, residential area, industrial area, leisure area, etc.). The scenario mode usually includes the adjustment of parameters such as volume, brightness, notification settings, and network connection. For example, in a commercial area with a large flow of people and a noisy environment, you may need to make calls or receive notifications frequently, so you need to set the volume to medium or high. In an office area with a relatively quiet environment, you can set the volume to low or vibration mode.

[0145] Optionally, the associated data acquisition module 402 includes:

[0146] The information search submodule is used to search according to the geographical location information and reference information through a search engine to obtain related data.

[0147] Optionally, the associated data acquisition module 402 further includes:

[0148] The information query submodule is used to query the associated data corresponding to the geographical location information from the mobile terminal.

[0149] Optionally, the region type determination module 403 includes:

[0150] A data preprocessing submodule, used to preprocess the associated data corresponding to the geographic location information;

[0151] A feature extraction submodule is used to extract features from the preprocessed associated data to obtain feature data of the associated data;

[0152] The location determination submodule is used to input the characteristic data of the associated data into a preset area type determination model to obtain the area type of the location of the mobile terminal.

[0153] Optionally, the area type includes: a noisy area and a quiet area; the scene mode setting module 404 includes:

[0154] A first setting submodule, configured to set the mobile terminal to a high volume mode when the area type of the location of the mobile terminal is the noisy area;

[0155] The second setting submodule is used to set the mobile terminal to a vibration mode when the area type of the location of the mobile terminal is the quiet area.

[0156] Optionally, the preset area type determination model can be obtained by training the following modules:

[0157] A sample acquisition module, used to acquire sample data and annotations corresponding to the sample data; the sample data includes picture data and video data; the annotation indicates the type of region to which the position corresponding to the sample data belongs;

[0158] A feature data acquisition module, used to extract features from the sample data to obtain feature data of the sample data;

[0159] A model training module, used to train a deep learning model according to the feature data of the sample data and the annotations corresponding to the sample data, and adjust the model parameters according to the training results;

[0160] The model determination module is used to obtain the preset area type determination model after the deep learning model training is completed.

[0161] Optionally, the device further comprises:

[0162] The mode setting module is used for classifying the area type of the location of the mobile terminal as the quiet area and setting the mobile terminal to the vibration mode when the location of the mobile terminal cannot be determined.

[0163] The location information acquisition module of this embodiment is used to acquire the location information of the mobile terminal; the associated data acquisition module is used to acquire the associated data of the location information, and the associated data includes pictures and videos; the area type determination module is used to determine the area type of the mobile terminal according to the associated data of the location information; the scene mode setting module is used to set the scene mode of the mobile terminal according to the area type of the mobile terminal. By acquiring the associated data of the location information (such as pictures and videos), the system can more accurately determine the area type of the mobile terminal. The location information is combined with the picture and video data to avoid the misjudgment that may be caused by a single location information, and can provide users with more personalized scene mode settings to meet the needs of different scenarios.

[0164] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0165] An embodiment of the present invention also provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned method embodiment for adjusting the scenario mode of a mobile terminal are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0166] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned method embodiment for adjusting the scenario mode of a mobile terminal are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0167] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0168] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0169] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0170] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0171] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0172] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0173] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0174] The method for adjusting the scene mode of a mobile terminal and the device for adjusting the scene mode of a mobile terminal provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for adjusting a scenario mode of a mobile terminal, characterized in that: The method comprises: Obtaining geographical location information of the mobile terminal; Acquire the associated data of the geographic location information, the associated data including pictures and videos; Determining the area type of the location of the mobile terminal according to the associated data of the geographical location information; The scenario mode of the mobile terminal is set according to the area type where the mobile terminal is located.

2. The method for adjusting the scenario mode of a mobile terminal according to claim 1, characterized in that: The step of obtaining the associated data of the geographic location information includes: The search engine is used to search according to the geographical location information and the reference information to obtain related data.

3. The method for adjusting the scenario mode of a mobile terminal according to claim 2, characterized in that: The step of acquiring the associated data of the geographic location information further includes: The mobile terminal is queried for associated data corresponding to the geographic location information.

4. The method for adjusting the scenario mode of a mobile terminal according to claim 1, characterized in that: The determining, according to the associated data of the geographical location information, the area type of the location of the mobile terminal includes: Preprocessing the associated data corresponding to the geographic location information; Extracting features from the preprocessed associated data to obtain feature data of the associated data; The characteristic data of the associated data is input into a preset area type determination model to obtain the area type of the location where the mobile terminal is located.

5. The method for adjusting the scenario mode of a mobile terminal according to claim 1, characterized in that: The area types include: noisy area and quiet area; The step of setting the device scenario mode of the mobile terminal according to the area type of the location of the mobile terminal includes: When the area type of the location of the mobile terminal is the noisy area, setting the mobile terminal to a high volume mode; When the area type of the location of the mobile terminal is the quiet area, the mobile terminal is set to a vibration mode.

6. The method for adjusting the scenario mode of a mobile terminal according to claim 4, characterized in that: The preset area type determination model can be trained in the following way: Acquire sample data and a label corresponding to the sample data; the sample data includes picture data and video data; the label indicates the type of region to which the position corresponding to the sample data belongs; Extracting features from the sample data to obtain feature data of the sample data; Training a deep learning model according to the feature data of the sample data and the annotations corresponding to the sample data, and adjusting model parameters according to the training results; After the deep learning model training is completed, the preset area type determination model is obtained.

7. The method for adjusting the scenario mode of a mobile terminal according to claim 1, characterized in that: The method further comprises: When the location of the mobile terminal cannot be determined, the area type of the location of the mobile terminal is classified as the quiet area, and the mobile terminal is set to a vibration mode.

8. A device for adjusting a scene mode of a mobile terminal, characterized in that: The device comprises: A location information acquisition module, used to acquire the geographical location information of the mobile terminal; A related data acquisition module, used to acquire the related data of the geographic location information, wherein the related data includes pictures and videos; An area type determination module, used to determine the area type of the location of the mobile terminal according to the associated data of the geographical location information; The scenario mode setting module is used to set the scenario mode of the mobile terminal according to the area type where the mobile terminal is located.

9. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of a method for adjusting a scenario mode of a mobile terminal as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of a method for adjusting a scenario mode of a mobile terminal according to any one of claims 1 to 7 are implemented.

Images