Screensaver determination method and device, electronic equipment, storage medium and vehicle

Abstract

The invention provides a screensaver determination method and device, electronic equipment, a storage medium and a vehicle. The method comprises the steps that a driving label of a vehicle and an emotion label of a monitoring object are determined, the driving label represents the driving state of the vehicle, and the emotion label represents the emotion state of the monitoring object; classifying and marking the driving labels and the emotion labels according to a mapping relation between pre-trained labels and screensaver content types, and determining screensaver contents corresponding to the driving labels and the emotion labels in a screensaver library; according to the embodiment of the invention, the screensaver content is displayed on the vehicle screen, so that personalized screensaver content can be provided in real time according to the emotional state of the monitored object and the driving state of the vehicle, the driving comfort and safety are improved, and more intelligent and humanized driving experience can be provided for the monitored object.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle technology, and in particular to a screen saver determination method, device, electronic device, storage medium, and vehicle. Background Technology

[0002] With the development of automotive intelligence, improving driving experience and safety has become increasingly important requirements. As part of the human-machine interaction within the vehicle, screensavers need to be more intelligent and personalized to meet the increasingly diverse needs of drivers and passengers.

[0003] Currently, car screensavers in related technologies typically use static or fixed content, failing to personalize based on the driver's or passenger's real-time emotional state and driving safety factors. Since the driver's or passenger's emotional state and driving behavior significantly impact driving safety—for example, driver tension, fatigue, or distraction can lead to driving errors and increase the risk of traffic accidents—the screensaver determination methods in related technologies lack personalization and adaptability, thus affecting driving safety. Summary of the Invention

[0004] This disclosure provides a screensaver determination method, apparatus, electronic device, storage medium, and vehicle.

[0005] According to a first aspect of this disclosure, a screensaver determination method is provided, the method comprising: determining a vehicle's driving label and a monitored object's emotion label, wherein the driving label represents the vehicle's driving state and the emotion label represents the monitored object's emotional state; classifying and labeling the driving label and emotion label according to a mapping relationship between pre-trained labels and screensaver content types; determining the screensaver content corresponding to the driving label and emotion label in the screensaver library; and displaying the screensaver content on the vehicle screen.

[0006] In some embodiments of this disclosure, determining the vehicle's driving label and the monitoring object's emotion label includes: collecting vehicle data and monitoring object's physiological data; extracting vehicle features from the vehicle data and physiological features from the physiological data; and analyzing the vehicle features and physiological features based on the mapping relationship between pre-trained features and labels to determine the driving label corresponding to the vehicle features and the emotion label corresponding to the physiological features.

[0007] In some embodiments of this disclosure, classifying and labeling driving tags and emotion tags according to pre-trained mapping relationships, and determining the screensaver content corresponding to driving tags and emotion tags in the screensaver library includes: classifying and labeling driving tags and emotion tags according to pre-trained mapping relationships between tags and screensaver content types, determining the screensaver content types corresponding to driving tags and emotion tags; and determining the screensaver content corresponding to the screensaver content types in the screensaver library.

[0008] In some embodiments of this disclosure, after classifying and labeling driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, and determining the screensaver content corresponding to driving tags and emotion tags in the screensaver library, the method includes: analyzing driving tags and emotion tags to determine the screensaver display method of the screensaver content; and displaying the screensaver content on the vehicle screen, including: displaying the screensaver content on the vehicle screen according to the screensaver display method.

[0009] In some embodiments of this disclosure, before classifying and labeling driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, and determining the screensaver content corresponding to driving tags and emotion tags in the screensaver library, the method includes: detecting network data; if the network data does not meet the target network indicators, determining that the network environment corresponding to the network data is a weak network environment; in the case of a weak network environment, classifying and labeling driving tags and emotion tags according to the historical habit data of the detected object, and determining the screensaver content corresponding to driving tags and emotion tags in the cached screensaver resources in the screensaver library.

[0010] In some embodiments of this disclosure, after classifying and labeling driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, and determining the screensaver content corresponding to driving tags and emotion tags in the screensaver library, the method includes: analyzing the physiological data of the monitored object and / or the vehicle data of the vehicle to determine the interaction level of the screensaver content; and pushing the screensaver content to the monitored object according to the interaction method corresponding to the interaction level.

[0011] In some embodiments of this disclosure, after displaying screen saver content on a vehicle screen, the method includes: receiving screen saver content type or screen saver content feedback from the monitoring object; adjusting the screen saver content to the screen saver content corresponding to the screen saver content type feedback from the monitoring object, or adjusting the screen saver content to the screen saver content feedback from the monitoring object.

[0012] According to a second aspect of this disclosure, a screen saver determination device is provided, the device comprising:

[0013] The first determining unit is used to determine the vehicle's driving label and the monitoring object's emotional label. The driving label indicates the vehicle's driving status, and the emotional label indicates the monitoring object's emotional status.

[0014] The second determining unit is used to classify and label driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, and to determine the screensaver content corresponding to driving tags and emotion tags in the screensaver library.

[0015] The display unit is used to display the screensaver content on the vehicle screen.

[0016] According to a third aspect of this disclosure, an electronic device is provided, comprising:

[0017] At least one processor; and

[0018] A memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0020] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0021] According to a fifth aspect of this disclosure, a vehicle is provided, including an area determining device as described in the second aspect above or an electronic device as described in the third aspect above.

[0022] According to a sixth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0023] The screensaver determination method, device, electronic device, storage medium, and vehicle disclosed herein determine the vehicle's driving tag and the monitored object's emotion tag. The driving tag represents the vehicle's driving state, and the emotion tag represents the monitored object's emotional state. Based on the mapping relationship between pre-trained tags and screensaver content types, the driving tag and emotion tag are classified and labeled to determine the screensaver content corresponding to the driving tag and emotion tag in the screensaver library. The screensaver content is then displayed on the vehicle screen, enabling the provision of personalized screensaver content in real time based on the monitored object's emotional state and the vehicle's driving state. This not only improves driving comfort and safety but also provides a more intelligent and humanized driving experience for the monitored object.

[0024] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0025] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0026] Figure 1 A schematic flowchart illustrating a screen saver determination method provided in an embodiment of this disclosure;

[0027] Figure 2 A schematic flowchart illustrating a screen saver determination method provided in an embodiment of this disclosure;

[0028] Figure 3 This is a schematic diagram of a specific screen saver system provided in an embodiment of the present disclosure;

[0029] Figure 4 A schematic diagram illustrating a specific screen saver determination method provided in an embodiment of this disclosure;

[0030] Figure 5 This is a schematic diagram of a screen saver determination device provided in an embodiment of the present disclosure;

[0031] Figure 6 A schematic block diagram of an example electronic device 600 provided for embodiments of this disclosure. Detailed Implementation

[0032] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0033] To address the problems in related technologies, this disclosure automatically provides personalized screensaver content by monitoring the emotional state of the monitored object and the driving status of the vehicle in real time. This helps reduce the risk of accidents caused by distraction or fatigue, improves the driver's emotional experience and driving safety, and effectively protects driving safety.

[0034] The following description, with reference to the accompanying drawings, describes a screen saver determination method, apparatus, electronic device, storage medium, and vehicle according to embodiments of the present disclosure.

[0035] Figure 1 This is a flowchart illustrating a screen saver determination method provided in an embodiment of this disclosure. Figure 1 As shown, this method can be applied to vehicles, specifically to vehicle screen saver systems. The method includes:

[0036] Step 101: Determine the vehicle's driving status and the monitoring subject's emotional status. The driving status indicates the vehicle's driving status, and the emotional status indicates the monitoring subject's emotional status.

[0037] In some embodiments, the present disclosure utilizes sensors and related equipment on the vehicle to monitor and analyze its driving status, thereby obtaining the driving tag. The vehicle sensors may include speed sensors, steering sensors, acceleration sensors, etc., which can collect vehicle data in real time. The screensaver system of the present disclosure can identify and determine the driving tag based on this vehicle data, such as "normal driving," "accelerating," "decelerating," and "turning." These driving tags accurately reflect the vehicle's driving status, providing the screensaver system with necessary driving information.

[0038] The monitored subjects can be drivers or passengers in vehicles, depending on the actual situation, and are not limited in this embodiment. Regarding the determination of emotion labels, this disclosure can utilize a camera to capture the facial expressions of the monitored subject, or use voice recognition technology to analyze the physiological data such as the subject's voice and emotions, to monitor and analyze the subject's emotional state, thereby obtaining emotion labels.

[0039] Furthermore, this disclosure can also combine vehicle data and the physiological data of the monitored object to infer the emotional state of the monitored object. For example, if the system detects that the vehicle suddenly accelerates or brakes, and the driver's heart rate is too fast, or their voice is tense or rapid, then the screen saver system can determine that the driver is in a tense or excited emotional state, thereby determining the emotion label as tense or excited.

[0040] Step 102: Classify and label the driving tag and the emotion tag according to the mapping relationship between the pre-trained tags and the screensaver content types, and determine the screensaver content corresponding to the driving tag and the emotion tag in the screensaver library.

[0041] In some embodiments, after determining the driving and emotion tags, the screensaver system can select appropriate screensaver content based on the obtained driving and emotion tags. The pre-trained mapping relationship is trained on a large amount of historical data and can accurately map different driving and emotion tags to the corresponding screensaver content types.

[0042] After completing the classification and tagging, the screensaver system can obtain the categorized screensaver content types and search for the corresponding screensaver content in the screensaver library based on these types. The screensaver library is a database storing various screensaver content, each associated with specific driving and mood tags. By searching the library, the screensaver system can find the screensaver content that best matches the current driving and mood tags.

[0043] In this disclosure, the selection of screen saver content takes into account the driver's emotional state and the vehicle's driving status to ensure that the screen saver content can meet the personalized needs of the monitored subject without affecting driving safety.

[0044] Step 103: Display the screensaver content on the vehicle screen.

[0045] In some embodiments, the screensaver system can display specific screensaver content on the vehicle's in-vehicle screen, providing a personalized screensaver experience for the monitored subject. This screensaver content not only matches the vehicle's driving status but can also be dynamically adjusted based on the monitored subject's emotional state, thereby creating a more comfortable and safer driving environment.

[0046] In summary, the technical solution provided in this disclosure determines the vehicle's driving status and the monitored object's emotional status by identifying the driving status of the vehicle and the emotional status of the monitored object. Based on the mapping relationship between pre-trained tags and screensaver content types, the driving and emotional tags are classified and labeled to determine the corresponding screensaver content in the screensaver library. The screensaver content is then displayed on the vehicle screen, enabling personalized screensaver content to be provided in real time based on the monitored object's emotional status and the vehicle's driving status. This not only improves driving comfort and safety but also provides a more intelligent and user-friendly driving experience for the monitored object.

[0047] Figure 2 This is a flowchart illustrating a screen saver determination method provided in an embodiment of the present disclosure. Figure 2 based on Figure 1 The illustrated embodiment further defines steps 101 and 102. Figure 2 In the illustrated embodiment, step 101 includes steps 201, 202, and 203, and step 102 includes steps 204 and 205. For example... Figure 2 As shown, the method includes the following steps.

[0048] Step 201: Collect vehicle data and physiological data of the monitored objects.

[0049] In some embodiments, vehicle data and physiological data of the monitored object can be collected through the data acquisition device in the screen saver system.

[0050] Data acquisition devices typically include an emotion perception module and a driving safety perception module. The emotion perception module is primarily responsible for monitoring the physiological data of the monitored object to infer its emotional state. This module may include devices such as cameras and infrared sensors. Cameras can capture the driver's facial expressions, while infrared sensors can monitor physiological parameters such as body temperature and heart rate. By analyzing this physiological data, the screensaver system can make a preliminary judgment about the driver's emotional state, such as calmness, excitement, tension, or fatigue.

[0051] The driving safety perception module is primarily responsible for collecting vehicle data. This module can include various vehicle sensors, such as cameras, radar, and ultrasonic sensors. Cameras capture information about the vehicle's surroundings, while radar and ultrasonic sensors monitor dynamic data such as speed, acceleration, and steering angle. By comprehensively analyzing this vehicle data, the screensaver system can accurately determine the vehicle's driving status, such as normal driving, acceleration, deceleration, and turning.

[0052] After the data acquisition device collects vehicle data and physiological data, it will transmit this data to the data processing module of the screen saver system for analysis and processing.

[0053] Step 202: Extract vehicle features from vehicle data and physiological features from physiological data.

[0054] In some embodiments, the data processing module can use predefined emotion models and driving safety models to analyze and evaluate the physiological data of the monitored object and the vehicle data of the vehicle. Specifically, vehicle features in the vehicle data and physiological features in the physiological data can be extracted first.

[0055] Vehicle characteristics and physiological characteristics can reflect the current driving status of the vehicle and the emotional state of the monitored object.

[0056] After collecting vehicle and physiological data, the data processing module first extracts features from this data. For vehicle data, the module extracts features such as vehicle speed, acceleration, steering angle, and braking status. These features reflect the vehicle's driving state, such as normal driving, acceleration, deceleration, and turning.

[0057] Similarly, for physiological data, the data processing module extracts physiological characteristics such as facial tags, heart rate, blood pressure, and respiratory rate. These physiological characteristics can reflect the emotional state of the monitored subject, such as calmness, excitement, tension, or fatigue.

[0058] Through these steps, the system can determine the driving tags corresponding to vehicle characteristics and the emotion tags corresponding to physiological characteristics.

[0059] Step 203: Based on the mapping relationship between pre-trained features and labels, analyze vehicle features and physiological features to determine the driving labels corresponding to vehicle features and the emotion labels corresponding to physiological features.

[0060] In some embodiments, by analyzing vehicle characteristics and physiological characteristics, the screen saver system's data processing module can accurately determine the vehicle's current driving status and the emotional state of the monitored object, providing a basis for the subsequent determination of driving tags and emotional tags.

[0061] After extracting vehicle and physiological features, the data processing module can further analyze and evaluate these features using predefined emotion models and driving safety models. Specifically, it utilizes the mapping relationship between physiological features and emotion labels in the predefined emotion model, and the mapping relationship between vehicle features and driving labels in the driving safety model, to analyze and evaluate the vehicle and physiological features. The emotion model can determine the emotional state of the monitored object based on physiological features and map it to corresponding emotion labels, such as "excitement" or "nervousness." The driving safety model can determine the vehicle's driving state based on vehicle features and map it to corresponding driving labels, such as "high-speed driving" or "emergency braking."

[0062] Vehicle tags and emotion tags provide a basis for subsequent screensaver content selection and driving assistance functions, enabling the screensaver system to provide personalized screensaver displays and driving assistance to the monitored object based on real-time driving status and emotional state, thereby improving the driving experience and ensuring driving safety.

[0063] Step 204: Classify and label the driving tag and the emotion tag according to the mapping relationship between the pre-trained tags and the screen saver content type, and determine the screen saver content type corresponding to the driving tag and the emotion tag.

[0064] In some embodiments, the screen saver display control module in the screen saver system selects an appropriate screen saver content type from the mapping relationship based on the emotion tag and driving tag of the monitored object, so as to determine the appropriate screen saver content according to the screen saver content type.

[0065] Specifically, the screensaver display control module can classify and label driving and emotion tags using a pre-trained mapping relationship between tags and screensaver content types. This mapping relationship is based on extensive historical data and machine learning algorithms, accurately mapping different driving and emotion tags to specific screensaver content types. Driving tags reflect the vehicle's driving status, such as acceleration, deceleration, and turning; while emotion tags reflect the emotional state of the monitored object, such as calm, excitement, and tension.

[0066] After obtaining the driving and emotion tags, the screensaver display control module determines the corresponding screensaver content type based on these tags and a pre-trained mapping relationship. This mapping relationship, trained on a large amount of historical data, maps different driving and emotion tags to corresponding screensaver content types.

[0067] The screensaver content type is determined based on the monitored subject's emotional state and the vehicle's driving status, aiming to provide screensaver content that matches the current situation. For example, when the vehicle is accelerating and the driver is tense, the screensaver system can choose to display relaxing or calming content to help alleviate tension; while when the vehicle is driving smoothly and the driver is calm, the system can choose to display scenic or artistic content to provide a pleasant driving experience.

[0068] Through this process, intelligent car screensaver systems can provide drivers with personalized screensaver displays based on real-time driving and mood tags, thereby enhancing the driving experience and improving driving safety.

[0069] Step 205: Determine the screensaver content corresponding to the screensaver content type in the screensaver library.

[0070] In some embodiments, the screensaver display control module can select appropriate screensaver content from the screensaver library for display based on a determined screensaver content type. The screensaver library is a database that stores various types of screensaver content to meet the display needs of different driving states and emotional states.

[0071] The screensaver display module in a screensaver system can integrate Natural Language Processing (NLP) and recommendation system technologies to further improve the personalization and intelligence of screensaver content. NLP technology helps the system analyze the voice and text information of monitored subjects to understand their needs and preferences; while the recommendation system can filter the most suitable screensaver content based on its type and recommend it to the monitored subjects. This process can utilize machine learning algorithms to continuously learn and adapt to the preferences of the monitored subjects, thereby improving the quality of recommendations.

[0072] The screensaver display module disclosed herein can also utilize advanced generative modeling techniques, such as Generative Adversarial Networks (GANs), to customize and generate screensaver content optimized specifically for in-vehicle scenarios. This screensaver content not only matches driving and emotional states but also dynamically adjusts based on changes in time and location. For example, during long-distance night driving, the screensaver system might play more upbeat music to help the driver stay alert and conscious; while on short morning trips, it might play relaxing and pleasant music to create a pleasant atmosphere.

[0073] In this disclosure, the screensaver content corresponding to driving tags and mood tags in the screensaver library is determined. Then, this disclosure also includes: analyzing driving tags and mood tags to determine the screensaver display method of the screensaver content; and displaying the screensaver content on the vehicle screen according to the screensaver display method.

[0074] In one optional embodiment of this disclosure, by analyzing driving tags and emotion tags, a comprehensive understanding of the current driving environment and the psychological state of the monitored object can be achieved. The screensaver display control module can determine the screensaver display method based on the analysis results. The display method may include adjustments to display parameters such as brightness, contrast, color saturation, and dynamic effects; it may also include the display method of the screensaver content, such as video display, image display, or voice display. Furthermore, the screensaver display method can be set according to the driver's personal preferences. The screensaver system can record the driver's historical choices and continuously optimize the screensaver display method through machine learning algorithms to meet the driver's personalized needs.

[0075] In this disclosure, after classifying and labeling driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, and determining the screensaver content corresponding to driving tags and emotion tags in the screensaver library, this disclosure includes: analyzing the physiological data of the monitored object and / or the vehicle data of the vehicle to determine the interaction level of the screensaver content; and pushing the screensaver content to the monitored object according to the interaction method corresponding to the interaction level.

[0076] In one optional embodiment of this disclosure, after determining the screensaver content corresponding to driving and emotion tags in the screensaver library, this disclosure can further comprehensively analyze the physiological data of the monitored subject and the vehicle data to determine the interaction level of the screensaver content. For example, when the monitored subject's physiological data indicates tension and the vehicle data shows high-speed driving, the interaction level of the screensaver content can be determined to be high. In this case, the screensaver content can be interacted with the monitored subject using the voice interaction method corresponding to the high interaction level. This achieves dynamic adjustment of the interaction level and method of the screensaver content to ensure the safety and convenience of the driving process.

[0077] First, when the monitored object is the driver, the screensaver system can dynamically optimize the interaction method using environmental awareness control technology and context-aware technology. When vehicle data indicates that the vehicle has come to a complete stop, the screensaver system allows for richer touch and gesture operations, providing the driver with a more flexible and convenient interactive experience. Conversely, when vehicle data indicates that the vehicle is moving, the screensaver system automatically switches to an interaction mode primarily based on voice and simplified gestures to minimize driver distraction and ensure driving safety.

[0078] Furthermore, the screensaver system can utilize in-car cameras and sensors to monitor the driver's state, such as gaze and hand position, thereby intelligently adjusting the interactivity level of the screensaver content. Based on changes in the driver's gaze and hand position, the screensaver system can determine the driver's attention and operational intentions, and then dynamically adjust the interaction method and level of the screensaver content.

[0079] Meanwhile, the screen saver system also incorporates advanced gesture recognition algorithms, allowing drivers to control the screen saver function with simple and intuitive gestures such as waving or tapping in the air, without touching the screen. This gesture recognition function uses a camera or a dedicated infrared sensor to provide high-precision and responsive gesture recognition, offering drivers a more convenient and natural interaction method.

[0080] In addition, the screensaver system incorporates emotion analysis algorithms to adjust content interaction based on the driver's emotional state. When the system detects that the driver is under significant stress, it proactively reduces voice and touch input, instead using soothing visual and audio content to help relieve stress and improve the driving experience.

[0081] By comprehensively considering the physiological data of the monitored object and the vehicle's data, and employing technologies such as environmental perception control, gesture recognition, and emotional feedback mechanisms, the screensaver system can intelligently determine the interaction level of the screensaver content and dynamically adjust the interaction method and level according to real-time conditions. This not only enhances the driver's interactive experience but also ensures the safety and convenience of the driving process.

[0082] In this disclosure, before classifying and labeling driving tags and emotion tags based on the mapping relationship between pre-trained tags and screensaver content types to determine the screensaver content corresponding to driving tags and emotion tags in the screensaver library, this disclosure also includes: detecting network data; if the network data does not meet the target network indicators, then determining that the network environment corresponding to the network data is a weak network environment; in the case of a weak network environment, classifying and labeling driving tags and emotion tags based on the historical habit data of the detected object to determine the screensaver content corresponding to driving tags and emotion tags in the cached screensaver resources in the screensaver library.

[0083] In one optional embodiment of this disclosure, in order to ensure that the driver can be provided with appropriate screensaver content in various network environments, a screensaver content selection mechanism in weak network environments is specifically considered.

[0084] The screensaver system can detect network data to determine whether the current network environment meets target network metrics. If the network data does not meet the target network metrics, the system determines that the current network environment is a weak network environment. The target network metrics are set according to the actual situation and are not limited in this embodiment. In a weak network environment, due to network connection limitations, the screensaver system cannot obtain screensaver content from the online resource library in real time. Therefore, the screensaver system will classify and label driving tags and emotion tags based on the historical habit data of the monitored object (such as the driver). This historical habit data may include information such as the driver's screensaver content preferences and usage frequency under different emotions and driving states.

[0085] Next, the screensaver system will use this historical habit data to filter screensaver content corresponding to driving and mood tags from the cached screensaver resources in the screensaver library. These cached screensaver resources are pre-downloaded and stored by the screensaver system under good network conditions to ensure that suitable screensaver content can still be provided in weak network environments.

[0086] In weak network environments, the screensaver system will also pay special attention to driving safety-related information. For example, when the screensaver system detects that the driver is driving at high speed, it will prioritize displaying screensaver content related to driving safety, such as current speed, the next highway exit, turns, and weather warnings. This helps remind the driver to pay attention to driving safety and reduce the risk of accidents.

[0087] Furthermore, in weak network environments, a preset decision-making mechanism can assist in selecting appropriate screensaver content. For example, the appropriate screensaver content can be selected based on the screen location (driver, passenger, or rear seat). When the screen location is the driver's position, screensavers with driving-related content (such as navigation assistant, navigation information, instrument status, etc.) can be provided. When the screen location is the passenger or rear seat, screensavers with entertainment-related content (such as popular movies, popular videos, music, games, scenic pictures, introductions to famous attractions along the way, etc.) can be provided.

[0088] In contrast, when the network environment is good, the screensaver system can enter online mode. In online mode, the screensaver system can use the process described in steps 201 to 205 above to determine appropriate screensaver content, which will not be repeated here.

[0089] Step 206: Display the screensaver content on the vehicle screen.

[0090] In some embodiments, the screensaver display control module can send determined screensaver content and display mode to the user interface for display on the in-vehicle display screen. In this way, the monitored individual can not only see screensaver content that matches their current driving and emotional state, but also enjoy a personalized screensaver display, thereby enhancing the driving experience.

[0091] The disclosure further includes, after displaying the screen saver content on the vehicle screen, receiving feedback from the monitoring subject regarding the screen saver content type or screen saver content; adjusting the screen saver content to the screen saver content corresponding to the screen saver content type provided by the monitoring subject, or adjusting the screen saver content to the screen saver content provided by the monitoring subject.

[0092] In other words, this disclosure can introduce a user feedback mechanism, allowing monitored subjects to choose their preferred screensaver content type and content based on their interests. For recommended content, users can indicate whether they like it or not via screen or voice. Monitored subjects can also select their preferred screensaver content or type on mobile devices (e.g., mobile phones) for subsequent display.

[0093] In summary, the technical solution provided in this disclosure employs advanced deep learning technology to analyze real-time physiological data such as user voice, facial expressions, and physiological signals captured by in-vehicle cameras and sensors, accurately determining the current emotional state of the monitored subject. Simultaneously, it intelligently adjusts screensaver content based on real-time vehicle data, including speed, location, weather conditions, and in-vehicle temperature and humidity, to match the driving environment and enhance the comfort of the monitored subject. Utilizing sophisticated recommendation system algorithms, combined with emotion and driving tags, it personalizes screensaver content, improving the driving experience and safety of the monitored subject. Adaptive content generation technologies, such as GANs, can also be introduced, allowing the screensaver system to instantly generate and customize screensaver content after determining the monitored subject's emotional state and priorities. Furthermore, it provides multimodal interaction methods based on touch, voice, and gestures, allowing the monitored subject to easily and naturally interact with the screensaver system and adjust the screensaver content output to meet personalized needs. The screensaver system can also continuously optimize content recommendation accuracy through monitored subject feedback and long-term behavioral pattern learning, providing a more precise, dynamic, and emotionally resonant screensaver experience.

[0094] As one possible implementation, based on the above embodiments, such as Figure 3 As shown, this disclosure provides a schematic diagram of a specific screen saver system, and, as... Figure 4 As shown in the diagram, this disclosure provides a specific method for determining a screen saver.

[0095] In some embodiments, refer to Figure 3 The screensaver system disclosed herein can be applied to various types of vehicles and driving scenarios, and may include a data acquisition module, a data processing module, a screensaver display control module, and a user interface. The data acquisition module is used to collect vehicle data and physiological data of the monitored object. The data acquisition module may include an emotion perception module and a driving safety perception module. The emotion perception module may include cameras and infrared sensors to acquire physiological data of the monitored object. The driving safety perception module may include vehicle sensors, such as cameras, radar, and ultrasonic sensors, to acquire vehicle data.

[0096] The data processing module can use predefined emotion models and driving safety models to analyze and evaluate the physiological data of the monitored subjects and the vehicle data of the vehicles, and obtain the emotion tags and driving tags of the monitored subjects.

[0097] The screensaver display control module selects appropriate screensaver content and display methods based on the monitored object's emotion and driving tags, and provides personalized driving assistance functions.

[0098] The user interface allows drivers or passengers to personalize settings and adjustments, including selecting and adjusting screen saver content, as well as enabling or disabling driving assistance functions.

[0099] In some embodiments, refer to Figure 4 This disclosure can be based on the above-mentioned screensaver system to execute the screensaver determination method for an object.

[0100] In response to the monitored object activating the screensaver function, the emotion perception module and driving safety perception module in the data acquisition module can acquire vehicle data and physiological data of the monitored object in real time (such as facial tags of the driver or passenger and driving environment). The data processing module can extract driving features and physiological features from the vehicle data and physiological data, and perform emotion classification based on the physiological features to determine the emotion tag corresponding to the current physiological feature. Similarly, for driving features, driving status classification can be performed to determine the driving tag corresponding to the current driving feature. The data processing module takes the driving tag and emotion tag as input to the screensaver display control module, so that the screensaver display control module can select appropriate screensaver content from the screensaver library based on the driving tag and emotion tag, and display the screensaver content on the vehicle screen. Furthermore, after displaying the screensaver content on the vehicle screen, this disclosure can also adjust the displayed screensaver content based on the screensaver content or screensaver content type reported by the monitored object.

[0101] Corresponding to the screen saver determination method described above, this invention also proposes a screen saver determination device. Since the device embodiments of this invention correspond to the method embodiments described above, details not disclosed in the device embodiments can be referred to in the method embodiments described above, and will not be repeated here.

[0102] Figure 5 This is a schematic diagram of a screen saver determination device provided in an embodiment of the present disclosure, as shown below. Figure 5 As shown, the device includes:

[0103] The first determining unit 510 is used to determine the vehicle's driving label and the monitoring object's emotion label. The driving label indicates the vehicle's driving status, and the emotion label indicates the monitoring object's emotional status.

[0104] The second determining unit 520 is used to classify and label driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, and to determine the screensaver content corresponding to driving tags and emotion tags in the screensaver library.

[0105] Display unit 530 is used to display screen saver content on the vehicle screen.

[0106] In some embodiments of this disclosure, the first determining unit 510 is used to: collect vehicle data and physiological data of the monitored object; extract vehicle features from the vehicle data and physiological features from the physiological data; and analyze the vehicle features and physiological features based on the mapping relationship between pre-trained features and labels to determine the driving label corresponding to the vehicle features and the emotion label corresponding to the physiological features.

[0107] In some embodiments of this disclosure, the second determining unit 520 is used to: classify and label driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, determine the screensaver content types corresponding to driving tags and emotion tags, and determine the screensaver content corresponding to the screensaver content types in the screensaver library.

[0108] In some embodiments of this disclosure, the second determining unit 520 is further configured to: classify and label driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, determine the screensaver content corresponding to driving tags and emotion tags in the screensaver library, and then analyze driving tags and emotion tags to determine the screensaver display method of the screensaver content; display the screensaver content on the vehicle screen, including: displaying the screensaver content on the vehicle screen according to the screensaver display method.

[0109] In some embodiments of this disclosure, the second determining unit 520 is further configured to: classify and label driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, and determine the screensaver content corresponding to driving tags and emotion tags in the screensaver library, before detecting network data; if the network data does not meet the target network indicators, then determine that the network environment corresponding to the network data is a weak network environment; in the case of a weak network environment, classify and label driving tags and emotion tags according to the historical habit data of the detected object, and determine the screensaver content corresponding to driving tags and emotion tags in the cached screensaver resources in the screensaver library.

[0110] In some embodiments of this disclosure, the second determining unit 520 is further configured to: classify and label driving tags and emotion tags according to the mapping relationship between pre-trained tags and screensaver content types, determine the screensaver content corresponding to driving tags and emotion tags in the screensaver library, then analyze the physiological data of the monitored object and / or the vehicle data of the vehicle to determine the interaction level of the screensaver content; and push the screensaver content to the monitored object according to the interaction method corresponding to the interaction level.

[0111] In some embodiments of this disclosure, the display unit 530 is further configured to: display screen saver content on the vehicle screen, and then receive screen saver content type or screen saver content feedback from the monitoring object; adjust the screen saver content to the screen saver content corresponding to the screen saver content type feedback from the monitoring object, or adjust the screen saver content to the screen saver content feedback from the monitoring object.

[0112] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and the principle is the same, so it is not limited in this embodiment.

[0113] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a vehicle.

[0114] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0115] like Figure 6 As shown, device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 602 or a computer program loaded from storage unit 608 into RAM (Random Access Memory) 603. RAM 603 may also store various programs and data required for the operation of device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. I / O (Input / Output) interface 605 is also connected to bus 604.

[0116] Multiple components in device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0117] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as the screen saver determination method. For example, in some embodiments, the screen saver determination method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the aforementioned screen saver determination method by any other suitable means (e.g., by means of firmware).

[0118] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0119] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0120] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0121] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0122] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0123] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service ecosystem, addressing the shortcomings of traditional physical hosts and VPS (Virtual Private Server, or simply "VPS") services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0124] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0125] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0126] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for determining a screensaver, characterized in that, The method includes: Determine the vehicle's driving status and the monitored object's emotional status, whereby the driving status indicates the vehicle's driving state and the emotional status indicates the monitored object's emotional state. Based on the mapping relationship between pre-trained tags and screensaver content types, the driving tags and the emotion tags are classified and labeled to determine the screensaver content corresponding to the driving tags and the emotion tags in the screensaver library; The screensaver content will be displayed on the vehicle screen.

2. The method according to claim 1, characterized in that, The determination of the vehicle's driving tags and the monitoring subjects' emotional tags includes: Collect vehicle data and physiological data of the monitored objects; Extract vehicle features from the vehicle data and physiological features from the physiological data; Based on the mapping relationship between pre-trained features and labels, the vehicle features and physiological features are analyzed to determine the driving label corresponding to the vehicle features and the emotion label corresponding to the physiological features.

3. The method according to claim 1, characterized in that, The step of classifying and labeling the driving tag and the emotion tag based on the mapping relationship between pre-trained tags and screensaver content types, and determining the screensaver content corresponding to the driving tag and the emotion tag in the screensaver library, includes: The driving tag and the emotion tag are classified and labeled according to the mapping relationship between the pre-trained tags and the screen saver content type, and the screen saver content type corresponding to the driving tag and the emotion tag is determined. Determine the screen saver content corresponding to the screen saver content type in the screen saver library.

4. The method according to claim 1, characterized in that, After classifying and labeling the driving tag and the emotion tag according to the mapping relationship between pre-trained tags and screensaver content types, and determining the screensaver content corresponding to the driving tag and the emotion tag in the screensaver library, the method includes: Analyze the driving tags and the emotion tags to determine the screensaver display method for the screensaver content; The step of displaying the screensaver content on the vehicle screen includes: The screensaver content is displayed on the vehicle screen according to the screensaver display method described above.

5. The method according to claim 2, characterized in that, Before classifying and labeling the driving tag and the emotion tag according to the mapping relationship between pre-trained tags and screensaver content types, and determining the screensaver content corresponding to the driving tag and the emotion tag in the screensaver library, the method includes: Detect network data; If the network data does not meet the target network indicators, then the network environment corresponding to the network data is determined to be a weak network environment; In the case of a weak network environment, the driving tag and the emotion tag are classified and marked according to the historical habit data of the detected object, and the screensaver content corresponding to the driving tag and the emotion tag in the cached screensaver resources in the screensaver library is determined.

6. The method according to claim 2, characterized in that, After classifying and labeling the driving tag and the emotion tag according to the mapping relationship between pre-trained tags and screensaver content types, and determining the screensaver content corresponding to the driving tag and the emotion tag in the screensaver library, the method includes: Analyze the physiological data of the monitored object and / or the vehicle data of the vehicle to determine the interaction level of the screensaver content; The screensaver content is pushed to the monitored object according to the interaction method corresponding to the interaction level.

7. The method according to claim 1, characterized in that, After displaying the screensaver content on the vehicle screen, the method includes: Receive the screen saver content type or screen saver content reported by the monitored object; Adjust the screensaver content to the screensaver content type reported by the monitored object, or adjust the screensaver content to the screensaver content reported by the monitored object.

8. A screen saver determination device, characterized in that, The device includes: The first determining unit is used to determine the vehicle's driving tag and the monitoring object's emotion tag, wherein the driving tag represents the vehicle's driving status and the emotion tag represents the monitoring object's emotional state. The second determining unit is used to classify and label the driving tag and the emotion tag according to the mapping relationship between the pre-trained tags and the screen saver content type, and determine the screen saver content corresponding to the driving tag and the emotion tag in the screen saver library; The display unit is used to display the screensaver content on the vehicle screen.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 7.

11. A vehicle, characterized in that, Includes the screen saver determination device as described in claim 8 or the electronic device as described in claim 9.

12. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 7.

Images