Cabin unit control method, system, and storage medium

Abstract

The present application discloses a cabin unit control method, a system, and a computer storage medium, the cabin unit control method including the steps of: acquiring first image data, generating a target wireless network based on the first image data, identifying a target cabin unit corresponding to the first image data, and controlling the target cabin unit to start up based on the target wireless network, receiving a network access request sent by a client, the network access request including second feature data, and when determining that a feature association degree between the second feature data and the first feature data corresponding to the target wireless network is less than a preset threshold, sending a network access response to the client, so that the client is connected to the target cabin unit via the target wireless network.

Description

[Technical field]

[0001] This application is filed based on a Chinese patent application bearing application number 202210620482.5 and filing date June 2, 2022, and claims priority to the Chinese patent application, the entire contents of which are incorporated herein by reference.

[0002] The present application relates to the technical field of in-vehicle device control, and more particularly to a cabin unit control method, system, and computer storage medium. [Background technology]

[0003] In recent years, the automotive industry has entered an era of smart and electrified driving, and smart cabins have become a popular development trend. Compared with traditional automobile cabins, smart cabins can interact with mobile devices used by users, thereby realizing human-vehicle interaction and providing users with services such as smart display, smart voice, and smart driving.

[0004] However, when multiple users using multiple mobile devices in a smart cabin need to connect to a specific device in the smart cabin for interaction, the existing operations are complicated and cannot automatically perform connection, switching, or control smartly and conveniently. For example, when the user's location in the smart cabin changes, the user needs to manually use the mobile device to select the wireless network of the current cabin unit by network search, network selection, network click, etc., and manually enter the password to connect to the network of the cabin unit. This process makes the steps very cumbersome when the user wants to connect a cabin unit or switch the connected cabin unit, which negatively affects the user experience. Summary of the Invention [Problem to be solved by the invention]

[0005] SUMMARY OF THE DISCLOSURE Embodiments of the present application provide a method, system, apparatus, and computer storage medium for controlling a cabin unit. [Means for solving the problem]

[0006] In a first aspect, the present embodiment comprises: A cabin unit control method applied to a cabin, comprising: acquiring first image data and generating a target wireless network based on the first image data, the target wireless network having network connection data including first characteristic data generated based on the first image data; identifying a target cabin unit corresponding to the first image data and controlling the target cabin unit to wake up based on the target wireless network; receiving a network access request sent by a client, the network access request including second characteristic data; A method for controlling a cabin unit includes a step of sending a network access response to the client so that the client is connected to the target cabin unit via the target wireless network when it is determined that the feature relevance between the second feature data and the first feature data is less than a predetermined threshold.

[0007] In a second aspect, the present embodiment comprises: A method for controlling a cabin unit applied to a client, comprising: reading a network username of at least one wireless network; extracting first characteristic data of the network user name; determining, as a target wireless network, a wireless network having a feature relevance between the first feature data and a preset second feature data that is less than a relevance threshold; generating a network access request based on the second characteristic data and the first characteristic data; and transmitting the network access request to a target cabin unit corresponding to the target wireless network via the target wireless network, so as to control the target cabin unit.

[0008] In a third aspect, the present embodiment comprises: A computer program comprising: a memory; a processor; and a computer program stored in the memory and executable by the processor; When the processor executes the computer program, it provides a cabin unit control system that realizes the cabin unit control method described in any one of the first and second aspects.

[0009] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions for executing the cabin unit control method described in any of the embodiments of the first and second aspects. [Brief description of the drawings]

[0010] [Figure 1] 4 is a flowchart of a cabin unit control method according to an embodiment of the present application. [Diagram 2] 11 is a flowchart of a method for generating a target wireless network in a cabin unit control method according to another embodiment of the present application. [Diagram 3] 4 is a flowchart of a method for sending a network access response to a client according to another embodiment of the present application; [Figure 4] 13 is a flowchart of a method for determining a target cabin unit from among a plurality of cabin units in a cabin unit control method according to another embodiment of the present application. [Diagram 5]13 is a flowchart of another method for determining a target cabin unit from among a plurality of cabin units in a cabin unit control method according to another embodiment of the present application. [Figure 6] 13 is a flowchart of an additional method of controlling a cabin unit according to another embodiment of the present application; [Figure 7] 11 is a flowchart of a method for applying a cabin unit control method to a client according to another embodiment of the present application; [Figure 8] 11 is a flowchart of a method for determining, as a target wireless network, a wireless network corresponding to a network username whose feature relevance is less than a relevance threshold according to another embodiment of the present application; [Figure 9] 11 is a flowchart of a method for applying a cabin unit control method according to another embodiment of the present application to a smart cabin. [Figure 10] FIG. 11 is a diagram showing an example in which a cabin unit control method according to another embodiment of the present application is applied to a target cabin unit. [Figure 11] FIG. 13 is a diagram showing an example of applying a cabin unit control method according to another embodiment of the present application to a client. [Figure 12] FIG. 11 is a configuration diagram of a cabin unit control method system according to another embodiment of the present application. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be described in more detail below with reference to the drawings and examples. The specific examples described in this specification are only used to interpret the present application, and are not used to limit the present application.

[0012] In some embodiments, the division of functional modules is made in the schematic diagram of the system and a logical order is shown in the flowchart, but in some cases the division of modules in the system may differ, or the steps shown or described may be performed in a different order than in the flowchart. The terms first, second, etc. in the specification and claims and the above drawings are intended to distinguish between similar objects and are not intended to describe a particular order or priority.

[0013] The present application discloses a cabin unit control method, a system, and a computer storage medium. According to the cabin unit control method of the present application, first image data is acquired, and based on the first image data, a target wireless network having network connection data including first feature data generated based on the first image data is generated, a target cabin unit corresponding to the first image data is identified, and the target cabin unit is controlled to start up based on the target wireless network, and a network access request including second feature data sent by a client is received, and when it is determined that the feature association degree between the second feature data and the first feature data is less than a preset threshold, a network access response is sent to the client so that the client is connected to the target cabin unit through the target wireless network. Here, the first image data of a user is acquired, and a target wireless network is automatically generated in the target cabin unit based on the first image data, and the user's client can be automatically connected to the target wireless network, and after the cabin unit where the user is located is changed, the mobile terminal equipped with the client's application can be automatically connected to the target wireless network and the target cabin unit can be controlled through the target wireless network. This can simplify the user's operation, eliminate the need for the user to manually switch networks, and provide the user with a smarter interaction experience.

[0014] Hereinafter, the embodiments of the present application will be further described with reference to the drawings.

[0015] Referring to FIG. 1, an embodiment of the present application provides a cabin unit control method applied to a target cabin unit, and the cabin unit control method includes, but is not limited to, the following steps S110, S120, S130, and S140.

[0016] Step S110: Obtain first image data, and generate a target wireless network based on the first image data, where the target wireless network has network connection data including first characteristic data generated based on the first image data.

[0017] In one embodiment, the smart cabin is a whole vehicle system converted into a digitalization platform. While a traditional automobile cabin can only be used to display various driving situations, the key feature of the smart cabin is smartification. The smart cabin is equipped with multiple sensor devices, and also equipped with multiple controllable terminals and AI smart devices, which can give the user a more comfortable driving experience based on the user's habits and comfort. Here, the smart cabin includes multiple cabin units corresponding to the user's position in the smart cabin. The cabin unit includes independent sensors, and includes environmental control components such as an audio-video player, lighting and air conditioning, and a seat position adjustment component. When a user connects to the network generated by the cabin unit through a mobile terminal (e.g., a mobile phone, a tablet, etc.), the user can control each functional component of the cabin unit through the corresponding client on the mobile terminal to meet the user's needs.

[0018] In one embodiment, if user A is sitting in smart cabin seat No. 1 with cabin unit No. 1 corresponding to seat No. 1, when user A unlocks the mobile terminal and opens the smart cabin application on the mobile terminal, he needs to manually search through the mobile terminal to select the corresponding wireless network No. 1 and connect to cabin unit No. 1. If user A changes his seat in the smart cabin to smart cabin position No. 2, user A still needs to use the smart cabin application through the mobile terminal to manually search through the mobile terminal to select the corresponding wireless network No. 2 and connect to cabin unit No. 2 corresponding to the seat. This process is cumbersome and affects the user experience, so this application proposes to realize automatic connection between the user mobile terminal and the cabin unit in front of the user's seat by obtaining first image data representing the user, thus eliminating user operations and improving the user experience.

[0019] In some embodiments, when a user enters the smart cabin, the master controller of the smart cabin activates a camera to perform face recognition for each user, marks each user, obtains first image data having the user's face information, and transmits the first image data to the cabin unit, so that the cabin unit automatically generates a set of data for each face based on the user's face recognition data according to the first image data, and generates a target wireless network.

[0020] Step S120: Identify a target cabin unit corresponding to the first image data, and control the target cabin unit to wake up according to the target wireless network.

[0021] In one embodiment, a target wireless network is generated with the target cabin unit as a network hotspot, and the target wireless network includes network connection data, which enables a client to determine a target wireless network corresponding to the target cabin unit from among multiple wireless networks of the smart cabin through the network connection data when the client searches for a surrounding network, and further sends a network access request to the target cabin unit, so that the client controls the target cabin unit through the target wireless network.

[0022] In some embodiments, the first image data is the face image data of the user, and the first feature data is specific feature data obtained by performing feature extraction processing on the face image data representing the identity of the user through the face recognition function component built in the target cabin unit. For example, the target cabin unit defines a length reference unit through the built-in face recognition function component, obtains the binocular pupillary distance of the user, and defines it as eye-length. For example, the binocular pupillary center distance is 160 pixels, and defines the length reference unit as std-length, std-length=eye-length / n, where n is a coefficient for subdividing eye-length, for example, n=20 (or other numerical value), and std-length=8 pixels. In addition, the important feature positions of the face are measured in the standard unit std-length, and the width between the user's two ears is measured as 240 pixels, which is converted to a standard length of 30, and the feature data of the two ears is set to 30. Similarly, the distance between the center point of both eyes and the center point of the mouth can be set to, for example, 21 standard lengths, and the width of the mouth can be set to 12 standard lengths, and the data can be further combined as required to obtain the first feature data "302112". This data is related to the facial features of the user, and this data can be used in the subsequent process to automatically connect the terminal device carried by the user to the cabin unit through relevance analysis, thereby simplifying the user's operation.

[0023] Step S130: Receive a network access request sent by a client, the network access request including the second characteristic data.

[0024] In one embodiment, the network access request includes configuration information generated by the client according to the target wireless network and second characteristic data, where the configuration information is used to perform network interaction with a target cabin unit corresponding to the target wireless network, send the second characteristic data to the target cabin unit, and allow the target cabin unit to perform subsequent processing based on the second characteristic data. The second characteristic data is used to allow the target cabin unit to check whether a user corresponding to the terminal device that sent the second characteristic data is a user currently present in the cabin unit, and automatically access the network of the user to improve the user experience when it is determined that the user corresponding to the terminal device that sent the second characteristic data is a user currently present in the cabin unit.

[0025] In some embodiments, the second feature data is generated based on image information of the user previously acquired by the client, represents personal feature data of the user corresponding to the client, and represents personal information of the user. If the target cabin unit determines that the second feature data and the first feature data are associated with each other, the terminal device carried by the user is automatically accessed to the target wireless network. Thus, a step requiring manual operation by the user is omitted, and the user's operation is simplified.

[0026] Step S140: If it is determined that the feature relevance between the second feature data and the first feature data is less than a preset threshold, a network access response is sent to the client so that the client is connected to the target cabin unit via the target wireless network.

[0027] In one embodiment, the data analysis on the second feature data and the first feature data is analyzed in the target cabin unit. The data acquired in the smart cabin, i.e., the face data of a user, is the first feature data, and the data acquired in the user's mobile terminal is the second feature data. The second feature data and the first feature data are compared and analyzed to determine whether these two sets of data are closely related and whether they are from the same user's face. If it is determined that the two sets of data are from the same user's face, the smart cabin hotspot allows the device to access and sends a network access response to the client. Thereby, the client controls the target cabin unit through the target wireless network to automatically turn on the hotspot in front of the corresponding person in the seat, and automatically connect the user's mobile terminal to the unit hotspot corresponding to the user in the smart cabin.

[0028] In some embodiments, when a user enters the smart cabin, the master controller of the smart cabin will activate the camera to perform face recognition for each user and mark each user. Then, based on each face recognition data, it will automatically generate a set of data related to each face according to an algorithm. For example, when user A is in the smart cabin, the data generated by face recognition is denoted as A-CD. The user's mobile phone has a smart cabin application, which also has the same algorithm as the smart cabin, and a set of data related to his / her face is automatically generated. When user A is in the mobile phone, the data generated by face recognition is denoted as A-MD. Obviously, since they are the same person, A-CD and A-MD are related, and in the smart cabin, since there is already face recognition data, the master controller of the smart cabin will obtain the target cabin unit corresponding to the user's specific location in the smart cabin, thereby realizing the automatic connection between the user's mobile terminal and the unit in front of his / her seat.

[0029] In some embodiments, in a scenario where a user moves from a first cabin unit to a second cabin unit in a smart cabin, a method for controlling a smart cabin includes acquiring second image data by a master controller of the smart cabin, and if the second image data does not match the first image data, changing the first image data to the second image data, turning off a target wireless network corresponding to the first cabin unit, acquiring the first image data, generating a second wireless network based on the first image data, the second image data including network connection data including first feature data generated based on the first image data, receiving a network access request sent by a client, the second feature included, and if a feature relevance between the second feature data and the first feature data is less than an association threshold, sending a network access response to the client so that the client controls the cabin unit via the second wireless network. Thereby, in the smart cabin, when multiple users' mobile terminals connect to multiple cabin units, if the users change their positions or want to switch the cabin units to which their mobile terminals are connected, the problem that the network connection configuration of the mobile devices needs to be manually changed is solved; a password for the user's face recognition is automatically generated, the hotspot in front of the seat counterpart is automatically turned on, and the target cabin unit can be controlled through the target wireless network by the client used by the user, providing the user with a smart interactive experience.

[0030] Referring to FIG. 2, an embodiment of the present application provides a cabin unit control method applied to a target cabin unit, and the cabin unit control method includes, but is not limited to, the following steps S210, S220, and S230.

[0031] Step S210: Biometric feature data is extracted from the first image data to obtain first feature data.

[0032] Step S220: Generate network connection data, including a network user name and a network password, based on the first characteristic data.

[0033] Step S230: Generate a target wireless network based on a network user name and a network password.

[0034] In one embodiment, the biometric feature data in the first image data is face image data, and the face recognition component of the target cabin unit performs image recognition processing on the acquired face image data, analyzes and acquires a plurality of feature parameters representing the specific facial features of the user, and further performs data combination on the plurality of feature parameters to obtain the first feature data representing the individual of the user. For example, a length reference unit is defined, for example, the binocular pupillary distance of the user is acquired and defined as eye-length. For example, the binocular pupillary center distance is 160 pixels. The length reference unit std-length is defined as std-length=eye-length / n, where n is a coefficient for subdividing eye-length, for example, n=20 (or other numerical value), etc. std-length=8 pixels. In addition, the important feature positions of the face are measured in the standard unit std-length, for example, the width between the user's two ears is measured as 240 pixels, converted to a standard length of 30, and the feature data of both ears is set to 30. Similarly, the distance between the center of the eyes and the center of the mouth can be set to, for example, 21 standard lengths, the width of the mouth can be set to, for example, 12 standard lengths, and the data can be further combined in a predetermined manner to obtain data "302112." This data is related to the facial features of the user.

[0035] In some embodiments, in the above examples, length is described as a standard unit for ease of understanding, but in actual applications, those skilled in the art may select the standard unit according to the application scenario, or obtain the first feature data from the facial image data based on a specific facial recognition algorithm, and the specific selection does not limit the present application.

[0036] In some embodiments, specific recognition algorithms for obtaining the first feature data based on the facial image data include, but are not limited to, at least one of a facial feature point-based recognition algorithm, a facial image-based recognition algorithm, a template-based recognition algorithm, a neural network-based recognition algorithm, and a support vector machine-based recognition algorithm.

[0037] In some embodiments, the biometric feature data in the first image information may be face image data, iris or other image recognition data, and those skilled in the art may select specific image recognition data as the first image information according to the actual situation, and the specific selection does not limit the present application.

[0038] In some embodiments, the target cabin unit generates network connection data including a network user name and a network password based on the first characteristic data, and generates a target wireless network based on the network user name and the network password. When the client sends a network access request, it determines a target wireless network based on the network user name, and further determines a corresponding target cabin unit. When the target cabin unit receives the network access request, it performs a relevance analysis based on the characteristic information and the network password included in the network access request. If the target cabin unit detects that the characteristic information requesting access to the hotspot is related to the network password, it allows the access, and denies the access otherwise. Thereby, an automatic connection between the user's mobile terminal and the unit in front of his / her seat is realized.

[0039] In some embodiments, the network user name includes the first characteristic data, and the network password is the first characteristic data. For example, before performing the step of generating network connection data based on the first characteristic data, the first characteristic data "312011" has already been obtained. The target cabin unit executes the data application, associates the user's face data with the smart cabin hotspot's user name and password, determines the smart cabin where the user is located, adjusts and sets the hotspot user name corresponding to this smart cabin to "user302112", and sets the password to "302112". Thereby, the client obtains the target network's user name to obtain the network password of the target wireless network, and further includes the network password in the network access request. After sending the network access request to the target cabin unit, the target cabin unit directly obtains this network password, allows the device corresponding to this client to access, automatically generates a password for the user's face recognition, automatically turns on the hotspot in front of the seat's counterpart, and automatically connects.

[0040] Referring to FIG. 3, an embodiment of the present application provides a cabin unit control method applied to a target cabin unit, and the cabin unit control method includes, but is not limited to, the following steps S310 and S330.

[0041] Step S310: According to a preset condition, a plurality of first data feature values ​​are compared with corresponding second data feature values, and a feature relevance between the second feature data and the first feature data is obtained.

[0042] Step S320: If the feature relevance is less than the relevance threshold, send a network access response to the client.

[0043] In some embodiments, the first feature data includes a plurality of first data feature values ​​generated according to a preset condition, and the second feature data includes a plurality of second data feature values ​​generated according to the preset condition. When the feature relevance between the second feature data and the first feature data is less than a relevance threshold, the step of sending a network access response to the client includes the steps of: comparing the plurality of first data feature values ​​with corresponding second data feature values ​​according to the preset condition, respectively, to obtain a feature relevance between the second feature data and the first feature data; and, when the feature relevance is less than the relevance threshold, sending a network access response to the client.

[0044] In one embodiment, the first feature data includes a plurality of first data feature values ​​arranged according to a preset condition, and the second feature data includes a plurality of second data feature values ​​arranged according to a preset condition. For example, the face data of a user, i.e., a certain user, acquired by a cabin unit in a smart cabin is "302112", and the data acquired by the user's mobile phone is "312011". For example, each of the two-digit data of "30" and "31", "21" and "20", and "12" and "11" is compared and analyzed to obtain a plurality of feature difference values. If any of the feature difference values ​​is smaller than a preset association threshold value of "3", it is determined that the two sets of data are closely related data and are from the same user's face.

[0045] In some embodiments, in practical applications, the above-mentioned correlation threshold, preset conditions, and number of digits of comparison data may be selected by those skilled in the art according to application scenarios, or a judgment method for determining whether the two facial recognition data are related may be selected according to a specific facial recognition algorithm, but the specific selection does not limit the present application.

[0046] In some embodiments, a method for obtaining a feature relevance between second feature data and first feature data includes the steps of obtaining a plurality of data feature values ​​and an order of the feature values ​​based on the second feature data, dividing a target network password generated based on the first feature data into a plurality of feature fields according to the order of the feature values, and comparing the data feature values ​​and the feature fields to obtain a feature relevance.

[0047] 4, an embodiment of the present application provides a cabin unit control method applied to a smart cabin, the smart cabin includes a plurality of cabin units and a master controller, and the cabin units include a sub-controller. The cabin unit control method includes, but is not limited to, the following steps S410 and S420.

[0048] Step S410: Position information data is obtained based on the first image data.

[0049] Step S420: Determine a target cabin unit from among the multiple cabin units based on the position information data.

[0050] In one embodiment, the smart cabin applied in this embodiment obtains facial recognition data of the entire smart cabin through the main camera, and the master controller determines location information representing the specific cabin unit where the user is located from the facial recognition data through the built-in image recognition component based on the facial recognition data, and the data master controller determines a target cabin unit from the multiple cabin units based on the location information data, and performs subsequent operations.

[0051] 5, an embodiment of the present application provides a cabin unit control method applied to a smart cabin, the smart cabin includes a plurality of cabin units and a master controller, and the cabin units include a sub-controller. The cabin unit control method includes, but is not limited to, the following steps S510, S520, and S530.

[0052] Step S510: The sensing parameters of the sensor that generated the first image data are obtained.

[0053] Step S520: Obtain location information data based on the sensing parameters.

[0054] Step S530: Determine a target cabin unit from among the multiple cabin units based on the position information data.

[0055] In one embodiment, the smart cabin applied in this embodiment acquires facial recognition data of each corresponding cabin unit by a sensor installed in each cabin unit, and the master controller acquires sensing parameters of the sensor that generates the facial recognition data, acquires location information data based on the sensing parameters, determines a target cabin unit from among the multiple cabin units based on the location information data, and performs subsequent operations.

[0056] In some embodiments, the first image data includes facial image data, and the sub-controller of the target cabin unit generates the target wireless network based on the first image data, specifically, the sub-controller obtaining first feature data based on the facial image data, and the sub-controller generating the target wireless network based on the first feature data.

[0057] In some embodiments, the step of the sub-controller generating a target wireless network based on the first characteristic data includes the step of the sub-controller generating network connection data including a network username and a network password based on the first characteristic data, and the step of the sub-controller generating the target wireless network based on the network username and the network password.

[0058] In some embodiments, a network username comprises the first characteristic data and a network password is the first characteristic data.

[0059] In some embodiments, the first feature data includes a plurality of first data feature values ​​generated according to a preset condition, and the second feature data includes a plurality of second data feature values ​​generated according to a preset condition. If the feature relevance between the second feature data and the first feature data is less than a relevance threshold, the sub-controller transmits a network access response to the client. Specifically, the method includes the steps of: the sub-controller compares the plurality of first data feature values ​​with the corresponding second data feature values ​​according to the preset condition, respectively, to obtain a feature relevance between the second feature data and the first feature data; and the sub-controller transmits a network access response to the client if the feature relevance is less than the relevance threshold.

[0060] Referring to FIG. 6, an embodiment of the present application provides a control method for a cabin unit applied to a smart cabin, and the control method for the cabin unit includes, but is not limited to, the following steps S610 and S620.

[0061] Step S610: The second image data is obtained.

[0062] Step S620: If the second image data does not match the first image data, change the first image data to the second image data, and turn off the target wireless network.

[0063] In one embodiment, in a scenario where the second image data does not match the first image data, i.e., where a user moves from a first cabin unit to a second cabin unit in a smart cabin, a method for controlling a cabin unit includes the steps of: a master controller of the smart cabin acquiring the second image data; if the second image data does not match the first image data, the master controller changes the first image data to the second image data, turns off a target wireless network corresponding to the first cabin unit, and acquiring the first image data, generating a second wireless network based on the first image data, the second image data including network connection data including first feature data generated based on the first image data, receiving a network access request sent by a client, the second feature included, and if the feature relevance between the second feature data and the first feature data is less than a relevance threshold, sending a network access response to the client, so that the client controls the second cabin unit via the second wireless network. Thus, in the smart cabin, when multiple users' mobile terminals connect to multiple cabin units, if the users change their positions or want to switch the cabin units to which their mobile terminals are connected, the problem of needing to manually change the network connection configuration of the mobile devices is solved; a password for the user's face recognition is automatically generated, the hotspot in front of the seat's corresponding person is automatically turned on, and the target cabin unit can be controlled through the target wireless network by the client used by the user, so as to realize the automatic connection of the user's mobile terminal when the user switches cabin units.

[0064] Referring to FIG. 7, an embodiment of the present application provides a control method for a cabin unit applied to a client, and the control method for the cabin unit includes, but is not limited to, the following steps S710, S720, S730, S740, and S750.

[0065] Step S710: Read a network user name of at least one wireless network.

[0066] Step S720: Extract first characteristic data of the network user name.

[0067] Step S730: A wireless network in which a feature relevance, which is a relevance between the first feature data and a preset second feature data, is less than a relevance threshold is determined as a target wireless network.

[0068] Step S740: Generate a network access request based on the second characteristic data and the first characteristic data.

[0069] Step S750: Send a network access request to a target cabin unit corresponding to the target wireless network, so as to control the target cabin unit via the target wireless network.

[0070] In one embodiment, the above steps S710 to S750 are the method of the present application applied to the client. The client obtains the network user name, determines the target wireless network, and then sends a network access request to access the target network. Thereby, the client automatically inputs the network password, performs network access, and realizes automatic connection. For example, the data known to the user's mobile phone is "312011", the mobile phone searches for the hotspot user name and obtains the hotspot user name "user302112". After analyzing this user name, it is found that the data characteristics of this user name are closely related to the mobile phone data "312011", and the user's mobile phone automatically initiates an access request to this related user name and automatically inputs the password. In addition, the smart cabin hotspot also finds that there is an equipment access request, checks the user name and password, and confirms that it is indeed related to the known data "302112", then the smart cabin hotspot allows the equipment access.

[0071] In some embodiments, the client obtains a plurality of network user names, determines a wireless network corresponding to a network user name whose feature relevance, which is the relevance between the feature value of the network user name and the preset second feature data, is less than a relevance threshold, generates a network access request according to the second feature data and the first feature data, which is the feature value in the network user name of the target wireless network, and sends the network access request to the target cabin unit corresponding to the target wireless network, so as to control the target cabin unit through the target wireless network, thereby achieving the effects of automatically generating a password for the user's face recognition, automatically turning on the hotspot in front of the seat correspondent, and automatically connecting.

[0072] In some embodiments, the network user name of the target wireless network generated by the target cabin unit includes the first characteristic data, and the network password of the target wireless network is the first characteristic data. When the client determines the target wireless network, it obtains the network password from the network user name, and further includes the password information in the network access request. Thus, when the target cabin unit receives the network access request, it sends a network access response to the client based on the password information included in the network access request. When the client receives the network access response, it confirms that the target wireless network has been accessed, and further causes the cabin unit to automatically connect for the user, and allows the user to control the target cabin unit via the target wireless network by the client.

[0073] Referring to FIG. 8, an embodiment of the present application provides a control method for a cabin unit applied to a client, and the control method for the cabin unit includes, but is not limited to, the following steps S810 and S820.

[0074] Step S810: According to a preset condition, a plurality of first data feature values ​​are compared with corresponding second data feature values, and a feature relevance between the second feature data and the first feature data is obtained.

[0075] Step S820: If the feature relevance is less than the relevance threshold, determine the wireless network corresponding to the network username as the target wireless network.

[0076] In some embodiments, the first feature data includes a plurality of first data feature values ​​generated according to a preset condition, and the second feature data includes a plurality of second data feature values ​​generated according to a preset condition. The step of determining the wireless network corresponding to the network user name whose feature relevance is less than the relevance threshold as the target wireless network includes the steps of: respectively comparing the plurality of first data feature values ​​with the corresponding second data feature values ​​according to the preset condition to obtain a feature relevance between the second feature data and the first feature data; and determining the wireless network corresponding to the network user name as the target wireless network when the feature relevance is less than the relevance threshold. Thereby, a password for face authentication of the user is automatically generated, a hotspot in front of the seat correspondent is automatically turned on, and a target cabin unit is controlled through the target wireless network by a client used by the user, thereby providing the user with a smart interactive experience.

[0077] Referring to FIG. 9, an embodiment of the present application provides a cabin unit control method applied to a smart cabin, where the smart cabin includes a plurality of cabin units and a master controller, and the cabin units include sub-controllers. The master controller has authority to control each sub-controller, and may control all sub-controllers to display / play in a unified manner or operate the same content, but is not limited thereto, and may control a plurality of devices to receive, display, and operate independently. For example, in determining a target cabin unit according to a situation, the smart cabin may determine one cabin unit, or may determine to connect to a plurality of cabin units, such as a plurality of cabin units in the back row. Here, the cabin unit control method includes, but is not limited to, the following steps S910, S920, S930, S940, and S950.

[0078] Step S910: The master controller obtains the first image data.

[0079] Step S920: The master controller determines a target cabin unit from among the multiple cabin units according to the first image data.

[0080] Step S930: The sub-controller of the target cabin unit generates, based on the first image data, a target wireless network having network connection data including first characteristic data generated based on the first image data.

[0081] Step S940: The sub-controller receives a network access request sent by the client, the network access request including the second characteristic data.

[0082] Step S950: If the feature relevance between the second feature data and the first feature data is less than the relevance threshold, the sub-controller sends a network access response to the client, so that the client controls the target cabin unit via the target wireless network.

[0083] In one embodiment, the smart cabin includes a plurality of cabin units and a master controller, the cabin units include a sub-controller, the master controller is responsible for selecting a target cabin unit in the smart cabin, and the sub-controller is responsible for a specific network connection process of the target cabin unit. Here, the master controller obtains first image data and determines a target cabin unit from among the plurality of cabin units based on the first image data. The sub-controller generates a target wireless network based on the first image data, the target wireless network has network connection data, and the network connection data includes first feature data manufactured based on the first image data. The sub-controller receives a network access request sent by the client, the network access request including second feature data. If the feature association degree between the second feature data and the first feature data is less than an association threshold, the sub-controller sends a network access response to the client, so that the client controls the target cabin unit through the target wireless network. Thereby, in the smart cabin environment, the terminal device carried by the user and the cabin unit in front of the seat can be automatically connected, greatly facilitating the user's use.

[0084] Referring to FIG. 10, an embodiment of the present application provides a cabin unit control method applied to a target cabin unit, and the cabin unit control method includes, but is not limited to, the following steps S1001 to S1009.

[0085] Step S1001: Initialize and start.

[0086] Step S1002: The smart cabin starts face recognition, recognizes a person, and generates corresponding face data.

[0087] Step S1003: The smart cabin determines the user's location, activates the corresponding hotspot, and adjusts the user name and password of the hotspot.

[0088] Step S1004: The hotspot corresponding to the smart cabin waits for access from the user terminal.

[0089] Step S1005: Determine whether an access request has been received. If an access request has been received, the process jumps to step S1006, and if an access request has not been received, the process jumps to step S1005.

[0090] Step S1006: Determine whether the password is correct. If the password is correct, jump to step S1007, and if the password is incorrect, jump to step S1008.

[0091] Step S1007: The smart cabin allows the user terminal to access.

[0092] Step S1008: The smart cabin does not allow the user terminal to access.

[0093] Step S1009: End.

[0094] Referring to FIG. 11, an embodiment of the present application provides a control method for a cabin unit applied to a client, and the control method for the cabin unit includes, but is not limited to, the following steps S1101 to S1109.

[0095] Step S1101: Initialize and start.

[0096] Step S1102: The user terminal performs face input and generates corresponding face data.

[0097] Step S1103: The user terminal enters the smart cabin together with the user to search for hotspots.

[0098] Step S1104: The user terminal finds a corresponding hotspot and initiates access.

[0099] Step S1105: Determine whether or not to permit the access request. If YES, jump to step S1106, and if NO, jump to step S1105.

[0100] Step S1106: Determine whether the password is correct. If YES, jump to step S1107, and if NO, jump to step S1108.

[0101] Step S1107: The user terminal accesses the hotspot corresponding to the smart cabin.

[0102] Step S1108: The user terminal does not access the corresponding hotspot.

[0103] Step S1109: End.

[0104] Referring to FIG. 12, an embodiment of the present application also provides a control system 1200 for a cabin unit. The cabin unit control system 1200 includes a memory 1220, a processor 1210, and a computer program stored in the memory and executable by the processor, and when the processor 1210 executes the computer program, it executes the cabin unit control method of any of the above embodiments, for example, method steps S110 to S140 of FIG. 1, method steps S210 to S230 of FIG. 2, method steps S310 to S320 of FIG. 3, method steps S410 to S420 of FIG. 4, method steps S510 to S530 of FIG. 5, method steps S610 to S620 of FIG. 6, method steps S710 to S750 of FIG. 7, method steps S810 to S820 of FIG. 8, method steps S910 to S950 of FIG. 9, method steps S1001 to S1009 of FIG. 10, and method steps S1101 to S1109 of FIG. 11.

[0105] Further, an embodiment of the present application also provides a computer-readable storage medium having computer-executable instructions stored thereon which, when executed by one or more control processors, perform, for example, the above-mentioned method steps S110-S140 of Figure 1, method steps S210-S230 of Figure 2, method steps S310-S320 of Figure 3, method steps S410-S420 of Figure 4, method steps S510-S530 of Figure 5, method steps S610-S620 of Figure 6, method steps S710-S750 of Figure 7, method steps S810-S820 of Figure 8, method steps S910-S950 of Figure 9, method steps S1001-S1009 of Figure 10, and method steps S1101-S1109 of Figure 11.

[0106] The present application has at least the following beneficial effects. According to the cabin unit control method of the present application, first image data is acquired, and based on the first image data, a target wireless network having network connection data including first feature data generated based on the first image data is generated, a target cabin unit corresponding to the first image data is identified, and the target cabin unit is controlled to start up based on the target wireless network, and a network access request including second feature data sent by a client is received, and when it is determined that the feature association degree between the second feature data and the first feature data is less than a preset threshold, a network access response is sent to the client, so that the client is connected to the target cabin unit through the target wireless network. Here, the first image data of a user is acquired, and a target wireless network is automatically generated in the target cabin unit based on the first image data, and the user's client can be automatically connected to the target wireless network, and after the cabin unit where the user is located is changed, the mobile terminal equipped with the client's application can be automatically connected to the target wireless network and the target cabin unit can be controlled through the target wireless network. This can simplify the user's operation, eliminate the need for the user to manually switch networks, and provide the user with a smarter interaction experience.

[0107] All or part of the steps in the methods and systems disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processor, digital signal processor, microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer readable medium, which may include computer storage media (or non-transitory media) and communication media (or transitory media). As known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (e.g., computer readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridge, magnetic tape, magnetic disk storage or other magnetic storage device, or any other medium that can be used to store the desired information and that can be accessed by a computer. Additionally, communication media typically includes computer readable instructions, data structures, program modules or other data in a modulated data signal, such as a carrier wave or other transmission mechanism, and may include any information delivery media as known to those skilled in the art.

Claims

1. A cabin unit control method applied to a cabin, comprising: acquiring first image data and generating a target wireless network based on the first image data, the target wireless network having network connection data including first characteristic data generated based on the first image data; identifying a target cabin unit corresponding to the first image data and controlling the target cabin unit to wake up based on the target wireless network; receiving a network access request sent by a client, the network access request including second characteristic data; A method for controlling a cabin unit, comprising: when it is determined that the feature relevance between the second feature data and the first feature data is less than a predetermined threshold, sending a network access response to the client so that the client is connected to the target cabin unit via the target wireless network.

2. The step of generating a target wireless network includes: extracting biometric feature data from the first image data to obtain the first feature data; generating network connection data based on the first characteristic data, the network connection data including a network username and a network password; and generating a target wireless network based on a network username and a network password.

3. 3. The cabin unit control method of claim 2, wherein the network user name includes first characteristic data, and the network password is the first characteristic data.

4. the first feature data includes a plurality of first data feature values ​​generated in accordance with a preset condition, the second feature data includes a plurality of second data feature values ​​generated in accordance with a preset condition, and when a feature relevance between the second feature data and the first feature data is less than a relevance threshold, the step of transmitting a network access response to the client includes: comparing a plurality of the first data feature values ​​with the corresponding second data feature values ​​according to the preset condition to obtain a feature relevance between the second feature data and the first feature data; The cabin unit control method of claim 2 , further comprising the step of: sending a network access response to the client if the feature relevance is less than a relevance threshold.

5. The step of identifying a target cabin unit corresponding to the first image data includes: obtaining position information data based on the first image data; determining a target cabin unit from among the plurality of cabin units based on the position information data; or, acquiring sensing parameters of a sensor that generated the first image data; obtaining location information data based on the sensing parameters; The cabin unit control method according to any one of claims 1 to 4, further comprising a step of determining a target cabin unit from among the plurality of cabin units based on the position information data.

6. acquiring second image data; The cabin unit control method of any one of claims 1 to 4, further comprising the step of: if the second image data does not match the first image data, changing the first image data to the second image data and turning off the target wireless network.

7. A method for controlling a cabin unit applied to a client, comprising: reading a network username of at least one wireless network; extracting first characteristic data of the network user name; determining, as a target wireless network, a wireless network having a feature relevance between the first feature data and a preset second feature data that is less than a relevance threshold; generating a network access request based on the second characteristic data and the first characteristic data; and transmitting the network access request to a target cabin unit corresponding to the target wireless network via the target wireless network to control the target cabin unit.

8. The first feature data includes a plurality of first data feature values ​​generated according to a preset condition, and the second feature data includes a plurality of second data feature values ​​generated according to a preset condition. The step of determining, as a target wireless network, a wireless network corresponding to the network user name whose feature relevance is less than a relevance threshold, includes: comparing a plurality of the first data feature values ​​with the corresponding second data feature values ​​according to the preset condition to obtain a feature relevance between the second feature data and the first feature data; and determining the wireless network corresponding to the network username as a target wireless network if the feature relevance is less than a relevance threshold.

9. A cabin unit control system including a memory, a processor, and a computer program stored in the memory and executable by the processor, the processor executing the computer program, which realizes the cabin unit control method described in any one of claims 1 to 8.

10. A computer-readable storage medium storing computer-executable instructions for carrying out the cabin unit control method according to any one of claims 1 to 8.

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