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 filed on June 2, 2022, and claims priority to that 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 control method, system, and Bi-ki Related to storage media. [Background technology]

[0003] In recent years, the automotive industry has entered an era of smart and electrified vehicles, and smart cabins have become a common development trend. Compared with traditional car cabins, smart cabins can interact with users' mobile devices, 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 specific devices in the smart cabin for interaction, existing operations are complicated and do not allow for automatic, smart, and convenient connection, switching, or control. For example, when a user's location in the smart cabin changes, the user must 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 a password to connect to the cabin unit network. This process makes the steps very cumbersome when a user wants to connect a cabin unit or switch connected cabin units, negatively affecting the user experience. Summary of the Invention [Problem to be solved by the invention]

[0005] The present invention relates to a cabin unit control method and system. , and Provide a storage medium. [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, 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; 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; 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 is provided.

[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, which is a relevance between the first feature data and a predetermined 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 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 first and second aspects. [Brief explanation of the drawings]

[0010] [Figure 1] 3 is a flowchart of a cabin unit control method according to an embodiment of the present application. [Figure 2] 10 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; [Figure 3] 10 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] 10 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. [Figure 5]10 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] 10 is a flowchart of an additional method of controlling a cabin unit according to another embodiment of the present application; [Figure 7] 10 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] 10 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] 10 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. 10 is a diagram illustrating 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. 10 is a diagram illustrating an example in which a cabin unit control method according to another embodiment of the present application is applied to a client. [Figure 12] FIG. 10 is a configuration diagram of a cabin unit control method system according to another embodiment of the present application. DETAILED DESCRIPTION OF THE INVENTION

[0011] In order to clarify the purpose, technical solution and advantages of the present application, 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, a division of functional modules is made in the system schematic and a logical order is shown in the flowchart, but in some cases the division of modules within the system may differ, or the steps shown or described may be performed in a different order than shown in the flowchart. Terms such as first, second, etc. in the specification and claims and in the 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, system, and computer storage medium. The cabin unit control method includes: 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; controlling the target cabin unit to activate based on the target wireless network; receiving a network access request sent by a client, the network access request including second feature data; and, if it is determined that the feature association between the second feature data and the first feature data is less than a predetermined threshold, transmitting a network access response to the client so that the client connects to the target cabin unit via the target wireless network. The method acquires first image data of a user, automatically generates a target wireless network in the target cabin unit based on the first image data, and automatically connects the user's client to the target wireless network. Furthermore, after the user's cabin unit is changed, a mobile terminal running a client application automatically connects to the target wireless network and can control the target cabin unit through the target wireless network. This simplifies user operations, eliminates the need for the user to manually switch networks, and provides the user with a smarter interaction experience.

[0014] Hereinafter, the embodiments of the present invention 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, a smart cabin is a vehicle system that has been fully digitized. While a traditional automobile cabin can only be used to display various driving situations, a key feature of a smart cabin is its smartness. The smart cabin is equipped with multiple sensor devices, controllable terminals, and AI smart devices, which can provide a more comfortable driving experience for the user based on the user's habits and comfort. Here, the smart cabin includes multiple cabin units corresponding to the user's location in the smart cabin. The cabin units include independent sensors, environmental control components such as an audio / video player, lighting, and air conditioning, and seat position adjustment components. When a user connects to the network generated by the cabin units through a mobile device (e.g., a mobile phone, tablet, etc.), the user can control each functional component of the cabin unit through the corresponding client on the mobile device to meet the user's needs.

[0018] In one embodiment, if User A is sitting in smart cabin seat No. 1, which has cabin unit No. 1 corresponding to seat No. 1, User A unlocks his / her mobile device and opens the smart cabin application on the mobile device. After unlocking his / her mobile device and opening the smart cabin application on the mobile device, User A must manually search for and select the corresponding wireless network No. 1 to connect to cabin unit No. 1. If User A changes his / her seat in the smart cabin to smart cabin No. 2, User A must manually search for and select the corresponding wireless network No. 2 to connect to cabin unit No. 2, while still using the smart cabin application on his / her mobile device. This process is cumbersome and impacts the user experience. Therefore, this application proposes to automatically connect the user's mobile device to the cabin unit in front of the user's seat by obtaining first image data representative of the user, thereby 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 facial recognition for each user, marks each user, obtains first image data having the user's facial information, and transmits the first image data to the cabin unit, so that the cabin unit automatically generates multiple sets of data for each face based on the user's facial 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 searching for a surrounding network, and further transmits a network access request to the target cabin unit so that the client can control the target cabin unit via the target wireless network.

[0022] In some embodiments, the first image data is facial image data of the user, and the first feature data is specific feature data obtained by performing feature extraction processing on facial image data representing the user's identity through a facial recognition function component built into the target cabin unit. For example, the target cabin unit defines a length reference unit through the built-in facial recognition function component, obtains the user's interocular distance, and defines it as eye-length. For example, the interocular 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 value), and std-length = 8 pixels. Furthermore, the positions of important facial features are measured in the standard unit std-length, and the width between the user's ears is measured as 240 pixels and converted to a standard length of 30, and the feature data of the ears is set to 30. Similarly, the distance between the center of both eyes and the center 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 in a predetermined manner 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 with 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 based on the target wireless network and second feature 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 feature data to the target cabin unit, and have the target cabin unit perform subsequent processing based on the second feature data. The second feature data is used to enable the target cabin unit to verify whether a user corresponding to the terminal device that sent the second feature data is a user currently present in the cabin unit, and automatically allow the user to access the network if it is determined that the user corresponding to the terminal device that sent the second feature data is a user currently present in the cabin unit, thereby improving the user experience.

[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, the terminal device carried by the user automatically accesses the target wireless network, thereby eliminating steps requiring manual user operation and simplifying user operation.

[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 target cabin unit performs data analysis on the second feature data and the first feature data. Data acquired by the smart cabin, i.e., a user's face data, is the first feature data, and data acquired by the user's mobile device is the second feature data. The second feature data and the first feature data are compared and analyzed to determine whether the two sets of data are closely related and whether they represent the same user's face. If it is determined that the two sets of data represent the same user's face, the smart cabin hotspot grants access to the device and sends a network access response to the client. The client then controls the target cabin unit via the target wireless network to automatically turn on the hotspot in front of the seated person and automatically connect the user's mobile device 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 activates a camera to recognize each user's face and assigns a mark to each user. Then, based on each facial recognition data, a set of data related to each face is automatically generated according to an algorithm. For example, when user A is in the smart cabin, the data generated by facial recognition is referred to 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 the user's face is automatically generated. When user A is on his / her mobile phone, the data generated by facial recognition is referred to as A-MD. Obviously, since they are the same person, A-CD and A-MD are related. Furthermore, since the smart cabin already has facial recognition data, the master controller of the smart cabin obtains the target cabin unit corresponding to the user's specific location in the smart cabin, thereby realizing automatic connection between the user's mobile device 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 within 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 wireless network 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 network access request including the second feature, 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 cabin unit via the second wireless network. This solves the problem that when multiple users' mobile terminals connect to multiple cabin units, if a user changes location or wants to switch the cabin unit to which the mobile terminal is connected, the user needs to manually change the network connection configuration of the mobile device in the smart cabin. The smart cabin automatically generates a password for the user's face recognition, automatically turns on the hotspot in front of the seat correspondent, and further allows the user to control the target cabin unit through the target wireless network via 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 the network username and the network password.

[0034] In one embodiment, the biometric feature data in the first image data is facial image data. The facial recognition component of the target cabin unit performs image recognition processing on the acquired facial image data, analyzes and acquires multiple feature parameters representing the user's specific facial features, and then performs data combination on the multiple feature parameters to obtain first feature data representing the user's individuality. For example, a length reference unit is defined, such as the user's interocular distance, which is acquired and defined as eye-length. For example, the interocular distance is 160 pixels. The length reference unit is defined as std-length = eye-length / n, where n is a coefficient for subdividing eye-length, such as n = 20 (or other numerical value). std-length = 8 pixels. Furthermore, important facial feature positions are measured using the standard unit std-length. For example, the width between the user's ears is measured as 240 pixels, converted to a standard length of 30, and the feature data for both ears is set to 30. Similarly, the distance between the center of both eyes and the center 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 in a predetermined manner to obtain the data "302112." This data is related to the facial features of the user.

[0035] In some embodiments, the above examples describe length as a standard unit for ease of understanding, but in actual applications, those skilled in the art may select a 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 username and a network password based on the first characteristic data, and generates a target wireless network based on the network username and the network password. When the client sends a network access request, it determines the target wireless network based on the network username and further determines the 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 grants access; otherwise, it denies access. This realizes automatic connection between the user's mobile terminal and the unit in front of his or her seat.

[0039] In some embodiments, the network username includes the first feature data, and the network password is the first feature data. For example, the first feature data "312011" has already been acquired before performing the step of generating network connection data based on the first feature data. The target cabin unit executes a data application, associates the user's facial data with the smart cabin hotspot username and password, determines the smart cabin where the user is located, adjusts and sets the hotspot username corresponding to this smart cabin to "user302112" and sets the password to "302112." Thus, the client acquires the target network username and the network password of the target wireless network, and 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 acquires the network password, authorizes access for the device corresponding to this client, automatically generates a password for the user's facial recognition, automatically turns on the hotspot in front of the seat correspondent, 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, which 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 predetermined condition, and the second feature data includes a plurality of second data feature values ​​arranged according to a predetermined condition. For example, the face data of a 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, two-digit data sets, such as "30" and "31," "21" and "20," and "12" and "11," are compared and analyzed to obtain a plurality of feature difference values. If any of these feature difference values ​​is smaller than a predetermined correlation threshold of "3," the two sets of data are determined to be closely related and to represent the same user's face.

[0045] In some embodiments, in actual 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 the application scenario, 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, where the smart cabin includes multiple cabin units and a master controller, and the cabin units include sub-controllers. The cabin unit control method includes, but is not limited to, the following steps S410 and S420.

[0048] Step S410: Obtain position information data 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 among 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, where the smart cabin includes multiple cabin units and a master controller, and the cabin units include sub-controllers. 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 acquired.

[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 location information data.

[0055] In one embodiment, the smart cabin applied in this embodiment acquires facial recognition data of each corresponding cabin unit using 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 the 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 in accordance with a preset condition, and the second feature data includes a plurality of second data feature values ​​generated in accordance with the 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 comparing each of the plurality of first data feature values ​​with a corresponding second data feature value in accordance with the preset condition to obtain a feature relevance between the second feature data and the first feature data; and the sub-controller transmitting 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 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 wireless network 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 data 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 location or want to switch the cabin unit to which their mobile terminals are connected, the problem of having to manually change the network connection configuration of the mobile device is solved; a password for the user's face recognition is automatically generated, the hotspot in front of the seat correspondent is automatically turned on, and the target cabin unit can be controlled through the target wireless network by the client used by the user, realizing 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 a cabin unit includes, but is not limited to, the following steps S710, S720, S730, S740, and S750.

[0065] Step S710: Read the network username of at least one wireless network.

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

[0067] Step S730: A wireless network having a feature relevance, which is a relevance between the first feature data and a preset second feature data, that 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, steps S710 to S750 are performed by a client in accordance with the method of the present application. The client acquires a network username, determines a target wireless network, and then sends a network access request to access the target network. The client then automatically inputs a network password, accesses the network, and automatically connects to the network. For example, the known data in the user's mobile phone is "312011." The mobile phone searches for the hotspot's username and obtains the hotspot's username "user302112." After analyzing this username, the mobile phone finds that the username's data characteristics are closely related to the mobile phone's data "312011." The user's mobile phone then automatically initiates an access request for this associated username and automatically inputs the password. Furthermore, the smart cabin hotspot then finds a device access request, checks the username and password, and, if it is indeed related to the known data "302112," allows the device to access the device.

[0071] In some embodiments, the client acquires a plurality of network usernames, determines a wireless network corresponding to a network username whose feature relevance, which is the relevance between the feature value of the network username and a predetermined second feature data, is less than a relevance threshold, generates a network access request based on the second feature data and the first feature data, which is the feature value of the network username 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 via the target wireless network, thereby achieving the effects of automatically generating a password for user facial recognition, automatically turning on the hotspot in front of the seat correspondent, and automatically connecting.

[0072] In some embodiments, the network username 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 username and further includes this 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 it has accessed the target wireless network and further causes the cabin unit to automatically connect for the user, allowing the user to control the target cabin unit via the target wireless network through 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 a 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 predetermined condition, and the second feature data includes a plurality of second data feature values ​​generated according to a predetermined condition. The step of determining, as the target wireless network, a wireless network corresponding to a network username whose feature relevance is less than a relevance threshold includes: comparing, according to the predetermined condition, the plurality of first data feature values ​​with corresponding second data feature values ​​to obtain a feature relevance between the second feature data and the first feature data; and, if the feature relevance is less than the relevance threshold, determining the wireless network corresponding to the network username as the target wireless network. This automatically generates a password for face authentication for the user, automatically turns on a hotspot in front of the seat correspondent, and further controls a target cabin unit via the target wireless network via 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. The smart cabin includes multiple cabin units and a master controller, and the cabin units include sub-controllers. The master controller has authority to control each sub-controller, including, but not limited to, controlling all sub-controllers to unify display / playback or operate the same content. The master controller may also control multiple devices to independently receive, display, and operate. For example, when determining a target cabin unit according to a situation, the smart cabin may determine one cabin unit or may determine to connect to multiple cabin units, such as multiple cabin units in the rear 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 based on 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, a smart cabin includes multiple 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 specific network connection processing of the target cabin unit. Here, the master controller acquires first image data and determines a target cabin unit from among the multiple 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 created based on the first image data. The sub-controller receives a network access request sent by a 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, allowing the client to control the target cabin unit via the target wireless network. This allows the smart cabin environment to automatically connect a terminal device carried by a user to the cabin unit in front of the seat, greatly facilitating user 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 username 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 a 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 inputs a face 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 the 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 cabin unit control system 1200. Cabin unit control system 1200 includes memory 1220, processor 1210, and a computer program stored in the memory and executable by the processor, which, when executed by processor 1210, performs 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] Furthermore, an embodiment of the present application also provides a computer-readable storage medium having computer-executable instructions stored thereon that, when executed by one or more control processors, perform, for example, the above-described 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: A cabin unit control method according to the present application includes acquiring first image data, generating a target wireless network based on the first image data, the target wireless network having network connection data including first feature 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 activate based on the target wireless network. A network access request sent by a client, the network access request including second feature data, is received. If it is determined that the feature correlation between the second feature data and the first feature data is less than a predetermined threshold, a network access response is sent to the client so that the client connects to the target cabin unit via the target wireless network. Here, the method acquires first image data of a user, automatically generates a target wireless network in the target cabin unit based on the first image data, and automatically connects the user's client to the target wireless network. Furthermore, after the user's cabin unit is changed, a mobile terminal running a client application automatically connects to the target wireless network and can control the target cabin unit through the target wireless network. This simplifies user operations, eliminates the need for the user to manually switch networks, and provides 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 any suitable combination 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, or 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 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, 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; identifying a target cabin unit corresponding to the first image data and controlling the target cabin unit to activate 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 including a network username and a network password based on the first characteristic data; and generating a target wireless network based on a network username and a network password.

3. The cabin unit control method of claim 2 , wherein the network username 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: a step of comparing a plurality of the first data feature values ​​with the corresponding second data feature values ​​according to the preset condition, and obtaining a feature relevance between the second feature data and the first feature data; 3. 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 changing the first image data to the second image data and turning off the target wireless network if the second image data does not match the first image data.

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, which is a relevance between the first feature data and a predetermined 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, and the step of determining, as a target wireless network, a wireless network corresponding to the network username whose feature relevance is less than a relevance threshold, a step of comparing a plurality of the first data feature values ​​with the corresponding second data feature values ​​according to the preset condition, and obtaining 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 comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor, when executing the computer program, realizes the cabin unit control method described in any one of claims 1 to 4, 7, and 8.

10. A computer-readable storage medium storing computer-executable instructions for executing the cabin unit control method according to any one of claims 1 to 4, 7 and 8.

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