Vehicle recommendation system, method, device and storage medium

Abstract

The application discloses a vehicle-mounted recommendation system, method, device and storage medium, and belongs to the technical field of vehicles. In the system, a wearable device collects physiological data of a driver, and then sends the collected physiological data to a vehicle-mounted terminal; the vehicle-mounted terminal collects behavior data of the driver, and then sends the physiological data and the behavior data to a cloud server; the cloud server determines information to be recommended according to the physiological data and the behavior data, and finally recommends the information to the driver through the vehicle-mounted terminal. Therefore, the information is determined based on the physiological data and the behavior data of the driver, so that the information can be accurately recommended to the driver, thereby meeting the demand of the driver.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to an in-vehicle recommendation system, method, device and storage medium. Background Technology

[0002] With rapid economic and technological development, cars are being owned and used by an increasing number of people. Currently, cars are no longer just a means of transportation; they have become a third space for people to work, entertain, and relax. Within this space, cars can recommend information to users. Therefore, how to accurately recommend information to users to meet their needs has become a pressing issue. Summary of the Invention

[0003] This application provides an in-vehicle recommendation system, method, device, and storage medium that can recommend information to drivers based on their physiological and behavioral data, thereby meeting the drivers' needs. The technical solution is as follows:

[0004] On the one hand, an in-vehicle recommendation system is provided, the system comprising: a wearable device, an in-vehicle terminal, and a cloud server, wherein the wearable device and the cloud server are both electrically connected to the in-vehicle terminal;

[0005] The wearable device is a device worn by the driver, and the wearable device is used to collect the driver's physiological data and send the physiological data to the vehicle terminal;

[0006] The vehicle-mounted terminal is used to collect the driver's behavioral data and send the physiological data and behavioral data to the cloud server;

[0007] The cloud server is used to determine the information to be recommended based on the physiological data and the behavioral data, and send the information to the vehicle terminal.

[0008] The vehicle-mounted terminal is also used to recommend the information to the driver.

[0009] In one possible implementation, the cloud server is configured to extract features from the physiological data and the behavioral data respectively to obtain physiological features and behavioral features; determine the driver's health attributes based on the physiological features; determine the driver's behavioral attributes based on the behavioral features; and determine the information based on the health attributes and the behavioral attributes.

[0010] In another possible implementation, the cloud server is used to classify the driver based on the health attributes and the behavioral attributes; and to determine the information based on the classification results.

[0011] In another possible implementation, the cloud server is configured to: determine a first information list based on the health attribute, the first information list including multiple first information items; determine a second information list based on the behavior attribute, the second information list including multiple second information items; and determine the information from the multiple first information items and the multiple second information items.

[0012] In another possible implementation, the cloud server is further configured to determine, based on the health attributes, whether the driver is fit to drive the current vehicle; and, if the driver is not fit to drive the current vehicle, to send a first control command to the vehicle terminal.

[0013] The vehicle-mounted terminal is also used to control the current vehicle to stop driving and issue a warning based on the first control command.

[0014] In another possible implementation, the cloud server is further configured to: determine the current location of the vehicle if the information includes dietary information; determine the location of a target location based on the current location of the vehicle, wherein the target location is a place that provides the diet corresponding to the dietary information; and send the dietary information and the location of the target location to the vehicle terminal.

[0015] On the other hand, an in-vehicle recommendation method is provided, the method comprising:

[0016] Wearable devices collect the driver's physiological data and send the physiological data to the vehicle terminal;

[0017] The vehicle-mounted terminal collects the driver's behavioral data and sends the physiological data and behavioral data to the cloud server.

[0018] Based on the physiological data and the behavioral data, the cloud server determines the information to be recommended and sends the information to the vehicle terminal.

[0019] The in-vehicle terminal recommends the information to the driver.

[0020] In one possible implementation, the cloud server determines the information to be recommended based on the physiological data and the behavioral data, including:

[0021] The cloud server performs feature extraction on the physiological data and the behavioral data respectively to obtain physiological features and behavioral features;

[0022] The driver's health attributes are determined based on the aforementioned physiological characteristics;

[0023] The driver's behavioral attributes are determined based on the behavioral characteristics;

[0024] The information is determined based on the health attributes and the behavioral attributes.

[0025] In another possible implementation, the cloud server determines the information based on the health attribute and the behavioral attribute, including:

[0026] The cloud server classifies the drivers based on the health attributes and the behavioral attributes; and determines the information based on the classification results.

[0027] In another possible implementation, the cloud server determines the information based on the health attribute and the behavioral attribute, including:

[0028] The cloud server determines a first information list based on the health attribute, and the first information list includes multiple pieces of first information;

[0029] Based on the aforementioned behavioral attributes, a second information list is determined, which includes multiple pieces of second information.

[0030] The information is determined from the plurality of first information and the plurality of second information.

[0031] In another possible implementation, the method further includes:

[0032] Based on the health attributes, the cloud server determines whether the driver is suitable to drive the current vehicle; if the driver is not suitable to drive the current vehicle, the cloud server sends a first control command to the vehicle terminal.

[0033] Based on the first control command, the vehicle terminal controls the current vehicle to stop driving and issues a warning.

[0034] In another possible implementation, the cloud server sends the information to the vehicle terminal, including:

[0035] If the information includes dietary information, the cloud server determines the current location of the vehicle;

[0036] Based on the current location of the vehicle, the location of the target location is determined, wherein the target location is a place that provides the food corresponding to the food information.

[0037] The food information and the location of the target location are sent to the vehicle-mounted terminal.

[0038] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one piece of program code, which is loaded and executed by the processor to implement the steps performed by the wearable device, the vehicle terminal, or the cloud server in any of the above-described vehicle recommendation methods.

[0039] On the other hand, a computer-readable storage medium is provided, wherein at least one piece of program code is stored therein, the at least one piece of program code being loaded and executed by a processor to implement the in-vehicle recommendation method described in any of the preceding claims.

[0040] On the other hand, a computer program product is provided, wherein at least one piece of program code is stored therein, the at least one piece of program code being loaded and executed by a processor to implement the in-vehicle recommendation method described in any of the preceding claims.

[0041] This application provides an in-vehicle recommendation system. In this system, a wearable device collects the driver's physiological data and sends it to an in-vehicle terminal. The in-vehicle terminal collects the driver's behavioral data and sends both physiological and behavioral data to a cloud server. The cloud server determines the information to be recommended based on the physiological and behavioral data and finally recommends the information to the driver through the in-vehicle terminal. Therefore, the information is determined based on the driver's physiological and behavioral data, thus accurately recommending information to the driver and meeting their needs.

[0042] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this disclosure. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of an in-vehicle recommendation system provided in an embodiment of this application;

[0044] Figure 2 This is a flowchart of an in-vehicle recommendation method provided in an embodiment of this application;

[0045] Figure 3 This is a schematic diagram illustrating the interaction between a wearable device, an in-vehicle terminal, and a cloud server, as provided in an embodiment of this application.

[0046] Figure 4 This is a structural block diagram of a vehicle-mounted terminal provided in an embodiment of this application;

[0047] Figure 5 This is a structural block diagram of a cloud server provided in an embodiment of this application. Detailed Implementation

[0048] To make the technical solution and advantages of this application clearer, the embodiments of this application will be described in further detail below.

[0049] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0050] It should be noted that all information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the physiological data, behavioral data, and information to be recommended involved in this application were all obtained with full authorization.

[0051] Figure 1 This is a schematic diagram of an in-vehicle recommendation system provided in an embodiment of this application. See also... Figure 1 The system includes: a wearable device 101, an in-vehicle terminal 102, and a cloud server 103, both of which are electrically connected to the in-vehicle terminal 102.

[0052] Wearable device 101 is a device worn by the driver. Wearable device 101 is used to collect the driver's physiological data and send the physiological data to the vehicle terminal 102.

[0053] The vehicle-mounted terminal 102 is used to collect driver behavior data and send physiological and behavioral data to the cloud server 103.

[0054] The cloud server 103 is used to determine the information to be recommended based on physiological and behavioral data and send the information to the vehicle terminal 102.

[0055] The vehicle terminal 102 is also used to recommend information to the driver.

[0056] In the embodiments of this application, the electrical connection can be a circuit connection or a wireless connection, and there is no specific limitation on the latter. If the electrical connection is a circuit connection, the connection method can be a cable connection; if the electrical connection is a wireless connection, the connection method can be a Bluetooth connection, an infrared connection, a wireless local area network, or a WiFi (Wireless Fidelity) network connection.

[0057] The wearable device 101 can be a smartwatch, smart bracelet, or other smart wearable device that can be worn by the driver. In this embodiment, the wearable device 101 is not specifically limited. The cloud server 103 can be at least one of a single server, a server cluster consisting of multiple servers, a cloud computing platform, and a virtualization center.

[0058] For wearable device 101, it can connect to vehicle terminal 102 via Bluetooth or WiFi. However, WiFi connection has high power consumption and cannot guarantee the battery life of wearable device 101. Bluetooth has low power consumption and good anti-interference ability. Therefore, Bluetooth has become the preferred connection method for wearable device 101 to connect to vehicle terminal 102.

[0059] In one possible implementation, cloud server 103 is used to extract features from physiological data and behavioral data respectively to obtain physiological features and behavioral features; determine the driver's health attributes based on the physiological features; determine the driver's behavioral attributes based on the behavioral features; and determine information based on the health attributes and behavioral attributes.

[0060] In another possible implementation, cloud server 103 is used to classify drivers based on health and behavioral attributes; and to determine information based on the classification results.

[0061] In another possible implementation, cloud server 103 is used to determine a first information list based on health attributes, the first information list including multiple first information items; determine a second information list based on behavioral attributes, the second information list including multiple second information items; and determine information from the multiple first information items and the multiple second information items.

[0062] In another possible implementation, the cloud server 103 is also used to determine whether the driver is suitable to drive the current vehicle based on health attributes; if the driver is not suitable to drive the current vehicle, a first control command is sent to the vehicle terminal 102.

[0063] The vehicle terminal 102 is also used to control the current vehicle to stop driving and issue a warning based on the first control command.

[0064] In another possible implementation, the cloud server 103 is also used to determine the current location of the vehicle when the information includes food information; based on the current location of the vehicle, determine the location of the target location, which is the place that provides the food information; and send the food information and the location of the target location to the vehicle terminal 102.

[0065] This application provides an in-vehicle recommendation system. In this system, a wearable device collects the driver's physiological data and sends it to an in-vehicle terminal. The in-vehicle terminal collects the driver's behavioral data and sends both physiological and behavioral data to a cloud server. The cloud server determines the information to be recommended based on the physiological and behavioral data and finally recommends the information to the driver through the in-vehicle terminal. Therefore, the information is determined based on the driver's physiological and behavioral data, thus accurately recommending information to the driver and meeting their needs.

[0066] Figure 2 This is a flowchart of an in-vehicle recommendation method provided in an embodiment of this application. See also... Figure 2 The method includes:

[0067] Step 201: The wearable device collects the driver's physiological data and sends the physiological data to the vehicle terminal.

[0068] Wearable devices are devices worn by drivers and run on health applications to collect the driver's physiological data.

[0069] Wearable devices primarily use multiple sensors, such as accelerometers, gyroscopes, magnetometers, heart rate sensors, and others, to collect the driver's physiological data in real time or periodically, with the driver's authorization. This data includes the driver's heart rate, blood pressure, blood sugar, blood oxygen saturation, muscle oxygen, BMI (Body Mass Index), sleep duration, and other physiological data.

[0070] In one possible implementation, the wearable device sends all collected physiological data to the vehicle terminal. In another possible implementation, the wearable device displays the collected physiological data, and the driver selects the physiological data to be uploaded from the displayed data; accordingly, the wearable device sends the selected physiological data to the vehicle terminal.

[0071] The driver can enable Bluetooth on their wearable device, select the device to connect to (i.e., the in-vehicle terminal), and wait for the pairing process to complete. Once paired, the wearable device can then transmit data with the in-vehicle terminal.

[0072] Step 202: The vehicle terminal collects the driver's behavior data and sends physiological and behavioral data to the cloud server.

[0073] The in-vehicle terminal runs a recommendation application. This application has two main functions: one is to communicate with wearable devices to obtain physiological data from them; the other is to transmit data with a cloud server, sending behavioral data collected by the in-vehicle terminal and physiological data sent by the wearable devices to the cloud server, and receiving recommendation information from the cloud server, displaying the information according to a pre-set display method. (See [link to relevant documentation]). Figure 3 .

[0074] In one possible implementation, the driver's behavior data includes driving behavior data, such as making or receiving phone calls, smoking, and driving while fatigued. In this implementation, the in-vehicle terminal can collect the driver's behavior data through a camera inside the vehicle. The process is as follows: the in-vehicle terminal sends a collection command to the camera; based on the collection command, the camera captures an image of the driver and sends the captured image back to the in-vehicle terminal. The in-vehicle terminal then identifies the image to determine the driver's driving behavior, thereby obtaining the driver's behavior data.

[0075] The in-vehicle terminal can perform facial recognition on the images and, based on the recognition results, determine whether the driver is making or receiving phone calls, smoking, or driving while fatigued. Furthermore, the number of images can be one frame or multiple frames, without specific limitation.

[0076] In another possible implementation, the driver's behavioral data includes browsing and click data of applications within the vehicle. In this implementation, the in-vehicle terminal can obtain the browsing and click records of each installed application, and based on these records, retrieve browsing and click data.

[0077] It should be noted that behavioral data can include both the driver's driving behavior data and the driver's browsing and clicking data inside the vehicle; there are no specific limitations on this.

[0078] In one possible implementation, the vehicle terminal can send physiological data to the cloud server after receiving physiological data, and then send behavioral data to the cloud server after obtaining behavioral data, that is, send physiological data and behavioral data separately.

[0079] In another possible implementation, the vehicle terminal can encapsulate the physiological and behavioral data after acquiring them, and then send the encapsulated physiological and behavioral data together to the cloud server.

[0080] Step 203: Based on physiological and behavioral data, the cloud server determines the information to be recommended and sends the information to the vehicle terminal.

[0081] The process by which the cloud server determines the information to be recommended in this step can be achieved through the following steps (1) to (4):

[0082] (1) The cloud server extracts features from physiological data and behavioral data respectively to obtain physiological features and behavioral features.

[0083] Cloud servers can use feature extraction algorithms to extract features from physiological and behavioral data separately, obtaining physiological and behavioral characteristics. The feature extraction algorithm can be configured and modified as needed, and no specific limitations are imposed.

[0084] It should be noted that before performing feature extraction, the cloud server can preprocess the physiological and behavioral data, such as data cleaning, noise reduction, and normalization.

[0085] (2) The cloud server determines the driver’s health attributes based on physiological characteristics.

[0086] Physiological characteristics include multiple physiological sub-characteristics, and the cloud server determines at least one health indicator that is satisfied by multiple physiological sub-characteristics. Specifically, one physiological sub-characteristic corresponds to one health indicator, or multiple physiological sub-characteristics correspond to one health indicator.

[0087] For example, physiological characteristics include blood pressure. Based on blood pressure, the cloud server determines whether the blood pressure meets the health indicators of hypertension, hypotension, or normal blood pressure.

[0088] The cloud server determines the driver's health attributes based on at least one health indicator, which represents the driver's health status. Specifically, the cloud server combines at least one health indicator to form the driver's health attributes.

[0089] (3) The cloud server determines the driver’s behavioral attributes based on behavioral characteristics.

[0090] The behavioral characteristics include multiple behavioral sub-characteristics. The cloud server determines at least one behavioral indicator that each of the multiple behavioral sub-characteristics satisfies. One behavioral sub-characteristic corresponds to one behavioral indicator, or multiple behavioral sub-characteristics correspond to one behavioral indicator. Based on at least one behavioral indicator, the driver's behavioral attributes are determined, and these attributes represent the driver's behavioral status. The cloud server combines at least one behavioral indicator to form the driver's behavioral attributes.

[0091] The process by which cloud servers determine behavioral attributes based on behavioral characteristics is similar to the process by which health attributes are determined based on physiological characteristics, and will not be repeated here.

[0092] (4) The cloud server determines the information to be recommended based on health attributes and behavioral attributes.

[0093] In one possible implementation, the cloud server categorizes drivers based on health and behavioral attributes; based on the categorization results, it determines the information to be recommended.

[0094] In this implementation, the cloud server can determine the health category corresponding to the health attribute based on the health attribute; determine the behavior category corresponding to the behavior attribute based on the behavior attribute; and determine the driver's classification result based on the health category and the behavior category.

[0095] The cloud server can pre-store the mapping between health attributes and health categories. During this step, the health category corresponding to a health attribute is determined based on this mapping. Similarly, the cloud server can also pre-store the mapping between behavioral attributes and behavioral categories. During this step, the behavioral category corresponding to a behavioral attribute is determined based on this mapping. After obtaining the health category and behavioral category, they are combined to form the driver's classification result.

[0096] Alternatively, cloud servers can classify drivers based on health and behavioral attributes using machine learning algorithms to obtain classification results. The machine learning algorithm can be configured and modified as needed; for example, it can be a decision tree, random forest, neural network, etc., without specific limitations.

[0097] Alternatively, the cloud server can also acquire the driver's basic attributes. Based on health, behavioral, and basic attributes, it can classify drivers using machine learning algorithms to obtain classification results. Specifically, before sending physiological and behavioral data to the cloud server, the in-vehicle terminal can also acquire and send the driver's basic data. The cloud server extracts features from the basic data to obtain basic features, and determines basic attributes based on these features. Basic data may include the driver's gender, age, location, and other data, without specific limitations.

[0098] In this embodiment, the cloud server categorizes drivers to obtain classification results, and determines information to be recommended based on these results. Specifically, the cloud server can determine the information to be recommended using a first recommendation algorithm based on the classification results.

[0099] The first recommendation algorithm can be a collaborative filtering algorithm, a content-based recommendation algorithm, a knowledge-based recommendation algorithm, a hybrid recommendation algorithm, or other algorithms, without specific limitations. Content-based recommendation algorithms recommend related items based on item characteristics (such as tags, categories, etc.). Knowledge-based recommendation algorithms utilize the knowledge of domain experts for recommendations. Hybrid recommendation algorithms combine several algorithms to improve recommendation performance.

[0100] In another possible implementation, the cloud server determines a first information list based on health attributes, which includes multiple pieces of first information; determines a second information list based on behavioral attributes, which includes multiple pieces of second information; and determines the information to be recommended from the multiple pieces of first information and the multiple pieces of second information.

[0101] In this implementation, the cloud server determines multiple pieces of first information that match the health attributes based on the health attributes; and determines multiple pieces of second information that match the behavior attributes based on the behavior attributes.

[0102] Specifically, the cloud server can determine multiple pieces of first information based on health attributes, where the matching degree with the health attributes is greater than a first matching threshold; or, based on health attributes, determine a first preset number of pieces of first information that match the health attributes. Similarly, the cloud server can determine multiple pieces of second information based on behavioral attributes, where the matching degree with the behavioral attributes is greater than a second matching threshold; or, based on behavioral attributes, determine a second preset number of pieces of second information that match the behavioral attributes.

[0103] Alternatively, the cloud server can determine multiple pieces of first information that match the health attributes using a second recommendation algorithm, and determine multiple pieces of second information that match the behavioral attributes using a third recommendation algorithm.

[0104] The first recommendation algorithm, the second recommendation algorithm, and the third recommendation algorithm can be the same or different, and there are no specific restrictions on this.

[0105] In the embodiments of this application, the information to be recommended can be one or more pieces, and there is no specific limitation on this.

[0106] For example, if there is only one piece of information to be recommended, the cloud server can randomly select one piece of information from multiple pieces of first information and multiple pieces of second information as the recommended information. As another example, if there are multiple pieces of information to be recommended, the cloud server can select a third preset number of first information pieces from multiple pieces of first information and a fourth preset number of second information pieces from multiple pieces of second information, combining the third preset number of first information pieces and the fourth preset number of second information pieces to form the recommended information.

[0107] The cloud server can randomly determine a third preset number of first information items from multiple first information items, or determine a third preset number of first information items with a high degree of matching. Similarly, the cloud server can also randomly determine a fourth preset number of second information items from multiple second information items, or determine a fourth preset number of second information items with a high degree of matching.

[0108] In the embodiments of this application, the information to be recommended may include dietary information, exercise information, health information, or other information, and there is no specific limitation thereto.

[0109] For example, if the information to be recommended includes food information, the cloud server will also determine the current location of the vehicle; based on the current location of the vehicle, determine the location of the target location, which is the place that provides the food information; and send the food information and the location of the target location to the vehicle terminal.

[0110] In this implementation, the vehicle-mounted terminal also obtains the current location of the vehicle. When sending physiological and behavioral data to the cloud server, it also sends the current location of the vehicle. Correspondingly, the cloud server obtains the current location of the vehicle. Using the current location of the vehicle as the center, the cloud server determines the target location within a preset range that provides the food information corresponding to the dietary information, and sends the location of the target location when sending the dietary information to the vehicle-mounted terminal.

[0111] For example, if the information to be recommended is coffee information, the cloud server determines the location of coffee shops around the current vehicle location and sends the coffee information and coffee shop location to the vehicle terminal.

[0112] For example, if the information to be recommended includes sports information, the cloud server determines the current location of the vehicle; based on the current location of the vehicle, it determines the location of the sports venue, which is the venue that provides the sports information corresponding to the sports activities; and sends the sports information and the location of the sports venue to the vehicle terminal.

[0113] For example, if the information to be recommended is exercise information, the cloud server determines the locations of gyms around the current vehicle location and sends the exercise information and gym locations to the in-vehicle terminal.

[0114] It should be noted that after receiving physiological and behavioral data, the cloud server can first store the physiological and behavioral data in a database to prevent data loss.

[0115] Step 204: The in-vehicle terminal recommends this information to the driver.

[0116] The in-vehicle terminal may display recommended information to the driver through a recommended application, or the in-vehicle terminal may play recommended information to the driver via voice; there are no specific limitations on this.

[0117] When the information includes dietary information, the in-vehicle terminal also recommends the location of the target location to the driver. Based on the location of the target location, the in-vehicle terminal can generate a first navigation route to facilitate the driver's journey to the target location. Similarly, when the information includes exercise information, the in-vehicle terminal also recommends the location of exercise venues to the driver. Based on the location of the exercise venues, the in-vehicle terminal can generate a second navigation route to facilitate the driver's journey to the exercise venues.

[0118] The in-vehicle terminal can recommend information to the driver when the vehicle starts or while the vehicle is in motion, without any specific limitation.

[0119] It should be noted that in step 203, after determining the driver's health attributes, the cloud server can determine whether the driver is suitable to drive the current vehicle based on these attributes. If the driver is unsuitable to drive the current vehicle, a first control command is sent to the vehicle terminal. Based on the first control command, the vehicle terminal controls the current vehicle to stop driving and issues a warning.

[0120] In this implementation, the cloud server determines the driver's physical condition based on their health attributes, and then determines whether the driver is fit to drive the vehicle. If the driver is fit, the subsequent steps continue. If the driver is unfit, a first control command is sent to the vehicle terminal. Accordingly, the vehicle terminal, based on the first control command, stops the vehicle and issues a warning.

[0121] The warning method can be set and changed as needed. For example, if the warning method is voice warning, the vehicle terminal will play a voice message through the voice device. The voice message could be "Your current physical condition is not suitable for driving. Please stop and rest."

[0122] In step 203, after determining the driver's behavioral attributes, the cloud server can also determine whether the driver is suitable to drive the current vehicle based on these attributes. If the driver is not suitable to drive the current vehicle, a second control command is sent to the vehicle terminal. The vehicle terminal then outputs a prompt message based on the second control command.

[0123] In this implementation, the cloud server determines whether the driver exhibits a preset driving behavior based on the driver's behavioral attributes. If the driver does not exhibit the preset driving behavior, the subsequent steps continue. However, if the preset driving behavior is observed, it is determined that the driver is unsuitable to drive the current vehicle. In this case, a second control command is sent to the vehicle terminal. The vehicle terminal then outputs a prompt message based on the second control command.

[0124] The in-vehicle terminal displays prompts via an in-vehicle screen or plays them aloud via a voice device; there are no specific limitations on this. Preset driving behaviors can include making or receiving phone calls, smoking, driving while fatigued, or other behaviors that affect safe driving; there are no specific limitations on this either.

[0125] This application provides an in-vehicle recommendation method. In this method, a wearable device collects the driver's physiological data and then sends the collected physiological data to an in-vehicle terminal. The in-vehicle terminal collects the driver's behavioral data and then sends both the physiological and behavioral data to a cloud server. The cloud server determines the information to be recommended based on the physiological and behavioral data, and finally recommends the information to the driver through the in-vehicle terminal. Therefore, the information is determined based on the driver's physiological and behavioral data, thus accurately recommending information to the driver and meeting the driver's needs.

[0126] refer to Figure 4 , Figure 4 The diagram illustrates a structural block diagram of an in-vehicle terminal 400 provided in an exemplary embodiment of this application. Typically, the in-vehicle terminal 400 includes a processor 401 and a memory 402.

[0127] Processor 401 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 401 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 401 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 401 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 401 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0128] The memory 402 may include one or more computer-readable storage media, which may be non-transitory. The memory 402 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 402 are used to store at least one piece of program code, which is executed by the processor 401 to implement the operations performed by the vehicle terminal in the vehicle recommendation method provided in the method embodiments of this application.

[0129] In some embodiments, the vehicle terminal 400 may optionally include a peripheral device interface 403 and at least one peripheral device. The processor 401, memory 402, and peripheral device interface 403 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 403 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of the following: a radio frequency circuit 404, a display screen 405, a camera assembly 406, an audio circuit 407, and a power supply 408.

[0130] Peripheral device interface 403 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 401 and memory 402. In some embodiments, processor 401, memory 402 and peripheral device interface 403 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 401, memory 402 and peripheral device interface 403 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0131] The radio frequency (RF) circuit 404 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 404 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 404 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 404 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 404 can communicate with other vehicle terminals via at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 404 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0132] Display screen 405 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 405 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 401 for processing. In this case, display screen 405 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 405, disposed on the front panel of the vehicle terminal 400; in other embodiments, there may be at least two display screens, disposed on different surfaces of the vehicle terminal 400 or in a folded design; in still other embodiments, display screen 405 may be a flexible display screen, disposed on a curved or folded surface of the vehicle terminal 400. Furthermore, display screen 405 may be configured as a non-rectangular irregular shape, i.e., a non-rectangular screen. Display screen 405 may be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0133] The camera assembly 406 is used to acquire images or videos. Optionally, the camera assembly 406 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the vehicle terminal, and the rear-facing camera is located on the back of the vehicle terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 406 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cool light flash, which can be used for light compensation at different color temperatures.

[0134] The audio circuit 407 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting them into electrical signals that are input to the processor 401 for processing, or to the radio frequency circuit 404 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each positioned at a different location on the vehicle terminal 400. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from the processor 401 or the radio frequency circuit 404 into sound waves. The speaker may be a traditional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 407 may also include a headphone jack.

[0135] Power supply 408 is used to power the various components in the vehicle terminal 400. Power supply 408 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 408 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, and a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0136] In some embodiments, the vehicle terminal 400 further includes one or more sensors 409. The one or more sensors 409 include, but are not limited to, an acceleration sensor 410, a gyroscope sensor 411, a pressure sensor 412, an optical sensor 413, and a proximity sensor 414.

[0137] Accelerometer 410 can detect the magnitude of acceleration along the three axes of a coordinate system established by the vehicle terminal 400. For example, accelerometer 410 can be used to detect the components of gravitational acceleration along the three axes. Processor 401 can control display screen 405 to display the user interface in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 410. Accelerometer 410 can also be used for games or for acquiring user motion data.

[0138] The gyroscope sensor 411 can detect the orientation and rotation angle of the vehicle terminal 400. The gyroscope sensor 411 can work in conjunction with the accelerometer sensor 410 to collect 3D motion data from the user on the vehicle terminal 400. Based on the data collected by the gyroscope sensor 411, the processor 401 can perform the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0139] The pressure sensor 412 can be disposed on the side bezel of the vehicle terminal 400 and / or the lower layer of the display screen 405. When the pressure sensor 412 is disposed on the side bezel of the vehicle terminal 400, it can detect the user's grip signal on the vehicle terminal 400, and the processor 401 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 412. When the pressure sensor 412 is disposed on the lower layer of the display screen 405, the processor 401 can control the operable controls on the UI interface based on the user's pressure operation on the display screen 405. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0140] Optical sensor 413 is used to collect ambient light intensity. In one embodiment, processor 401 can control the display brightness of display screen 405 based on the ambient light intensity collected by optical sensor 413. Specifically, when the ambient light intensity is high, the display brightness of display screen 405 is increased; when the ambient light intensity is low, the display brightness of display screen 405 is decreased. In another embodiment, processor 401 can also dynamically adjust the shooting parameters of camera assembly 406 based on the ambient light intensity collected by optical sensor 413.

[0141] The proximity sensor 414, also known as a distance sensor, is typically installed on the front panel of the vehicle terminal 400. The proximity sensor 414 is used to detect the distance between the user and the front of the vehicle terminal 400. In one embodiment, when the proximity sensor 414 detects that the distance between the user and the front of the vehicle terminal 400 is gradually decreasing, the processor 401 controls the display screen 405 to switch from a screen-on state to a screen-off state; when the proximity sensor 414 detects that the distance between the user and the front of the vehicle terminal 400 is gradually increasing, the processor 401 controls the display screen 405 to switch from a screen-off state to a screen-on state.

[0142] Those skilled in the art will understand that Figure 4 The structure shown does not constitute a limitation on the vehicle terminal 400, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0143] For a structural diagram of a cloud server, please refer to [link / reference]. Figure 5The cloud server 500 can vary significantly due to differences in configuration or performance. It may include a central processing unit (CPU) 501 and a memory 502. The memory 502 stores at least one line of program code, which is loaded and executed by the processor 501 to implement the operations performed by the cloud server in the aforementioned vehicle-mounted recommended method. Of course, the cloud server 500 may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The cloud server 500 may also include other components for implementing device functions, which will not be elaborated upon here.

[0144] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one piece of program code that is loaded and executed by a processor to implement the in-vehicle recommendation method in the above embodiments.

[0145] In an exemplary embodiment, a computer program product is also provided, which stores at least one piece of program code that is loaded and executed by a processor to implement the in-vehicle recommendation method in the above embodiments.

[0146] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0147] The above description is only for the purpose of enabling those skilled in the art to understand the technical solution of this application, and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. An in-vehicle recommendation system, characterized by, The system includes: a wearable device, an in-vehicle terminal, and a cloud server, wherein the wearable device and the cloud server are both electrically connected to the in-vehicle terminal; The wearable device is a device worn by the driver, and the wearable device is used to collect the driver's physiological data and send the physiological data to the vehicle terminal; The vehicle-mounted terminal is used to collect the driver's behavioral data and send the physiological data and behavioral data to the cloud server; The cloud server is used to determine information to be recommended based on the physiological data and the behavioral data, and send the information to the vehicle terminal. The information is determined from multiple first pieces of information and multiple pieces of second information. The multiple first pieces of information are information whose matching degree with health attributes is greater than a first matching threshold, and the multiple pieces of second information are information whose matching degree with behavioral attributes is greater than a second matching threshold. The health attributes are determined based on the physiological data, and the behavioral attributes are determined based on the behavioral data. The vehicle-mounted terminal is also used to recommend the information to the driver; The cloud server is further configured to: determine the current location of the vehicle if the information includes dietary information; determine the location of a target location based on the current location of the vehicle, wherein the target location is a place that provides the diet corresponding to the dietary information; and send the dietary information and the location of the target location to the vehicle terminal.

2. The system of claim 1, wherein, The cloud server is used to extract features from the physiological data and the behavioral data respectively to obtain physiological features and behavioral features. The health attributes are determined based on the aforementioned physiological characteristics; The behavioral attributes are determined based on the behavioral characteristics; The information is determined based on the health attributes and the behavioral attributes.

3. The system of claim 2, wherein, The cloud server is used to classify the drivers based on the health attributes and the behavioral attributes; and to determine the information based on the classification results.

4. The system according to claim 2, characterized in that, The cloud server is configured to: determine a first information list based on the health attribute, the first information list including multiple first information items; determine a second information list based on the behavior attribute, the second information list including multiple second information items; and determine the information from the multiple first information items and the multiple second information items.

5. The system according to claim 2, characterized in that, The cloud server is also used to determine whether the driver is suitable to drive the current vehicle based on the health attributes; and to send a first control command to the vehicle terminal if the driver is not suitable to drive the current vehicle. The vehicle-mounted terminal is also used to control the current vehicle to stop driving and issue a warning based on the first control command.

6. A vehicle-mounted recommendation method, characterized in that, The method includes: Wearable devices collect the driver's physiological data and send the physiological data to the vehicle terminal; The vehicle-mounted terminal collects the driver's behavioral data and sends the physiological data and behavioral data to the cloud server. The cloud server determines the information to be recommended based on the physiological data and the behavioral data, and sends the information to the vehicle terminal. The information is determined from multiple pieces of first information and multiple pieces of second information. The multiple pieces of first information are information whose matching degree with health attributes is greater than a first matching threshold, and the multiple pieces of second information are information whose matching degree with behavioral attributes is greater than a second matching threshold. The health attributes are determined based on the physiological data, and the behavioral attributes are determined based on the behavioral data. The in-vehicle terminal recommends the information to the driver; The information recommended by the vehicle terminal to the driver includes: If the information includes dietary information, the cloud server determines the current location of the vehicle. Based on the current location of the vehicle, the location of the target location is determined, wherein the target location is a place that provides the food corresponding to the food information. The food information and the location of the target location are sent to the vehicle-mounted terminal.

7. An electronic device, characterized in that, The electronic device includes a processor and a memory, wherein the memory stores at least one piece of program code, which is loaded and executed by the processor to implement the steps performed by the wearable device, vehicle terminal, or cloud server in the vehicle recommendation method as described in claim 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to implement the in-vehicle recommendation method as described in claim 6.

9. A computer program product, characterized in that, The computer program product stores at least one piece of program code, which is loaded and executed by a processor to implement the in-vehicle recommendation method as described in claim 6.

Images