WO2023202161A1 - 设备连接方法、装置、第一设备及计算机可读存储介质 - Google Patents

设备连接方法、装置、第一设备及计算机可读存储介质 Download PDF

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Publication number
WO2023202161A1
WO2023202161A1 PCT/CN2022/144306 CN2022144306W WO2023202161A1 WO 2023202161 A1 WO2023202161 A1 WO 2023202161A1 CN 2022144306 W CN2022144306 W CN 2022144306W WO 2023202161 A1 WO2023202161 A1 WO 2023202161A1
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Prior art keywords
connection
information
historical
target
scene
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PCT/CN2022/144306
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English (en)
French (fr)
Inventor
谭维
王鹏德
姜成专
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Oppo广东移动通信有限公司
零束科技有限公司
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Publication of WO2023202161A1 publication Critical patent/WO2023202161A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/48—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for in-vehicle communication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
    • H04M1/724—User interfaces specially adapted for cordless or mobile telephones
    • H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
    • H04M1/72409—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality by interfacing with external accessories
    • H04M1/724098—Interfacing with an on-board device of a vehicle
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/005—Discovery of network devices, e.g. terminals
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present application relates to the field of artificial intelligence technology, and in particular to a device connection method, device, first device and computer-readable storage medium.
  • the embodiments of the present application are expected to provide a device connection method, device, first device and computer-readable storage medium, which can determine the accuracy of the target device for connection from multiple devices.
  • the embodiment of this application provides a device connection method, including:
  • the scene information represents the usage scene of the first device
  • device connection prediction is performed in combination with historical connection information, and a target device is determined from the at least one second device;
  • the historical connection information includes at least one connection to which the first device is connected under at least one historical scene information.
  • Second device in history
  • the embodiment of the present application provides a device connection device, including:
  • a determining part configured to determine at least one second device that has connection conditions with the first device
  • the scene collection part is configured to obtain scene information; the scene information represents the usage scene of the first device;
  • connection prediction part is configured to perform device connection prediction based on the scene information and historical connection information, and determine the target device from the at least one second device;
  • the historical connection information includes the first device in at least one historical connection At least one historical second device connected under scene information;
  • Communication connection module used to connect the target device.
  • the embodiment of the present application provides a first device, including:
  • the memory is used to store executable instructions
  • the processor is configured to implement the device connection method provided by the embodiment of the present application by executing executable instructions stored in the memory.
  • Embodiments of the present application provide a computer-readable storage medium that stores executable instructions for causing the processor to implement the device connection method provided by the embodiments of the present application.
  • An embodiment of the present application provides a computer program product, which includes a computer program or instructions.
  • the computer program or instructions are executed by a processor, the device connection method provided by the embodiment of the present application is implemented.
  • the first device can obtain at least one prediction result corresponding to at least one historical second device by obtaining scene information and combining it with the historical connection information of at least one historical second device that has been connected under at least one historical scene information, so that the first device can obtain at least one prediction result corresponding to the at least one historical second device.
  • At least one prediction result determines a target device for connection from at least one second device. Therefore, in the device interconnection scenario, it is possible to perceive the scenario factors in various dimensions that affect the device connection, realize the addition of scenario information to the prediction process, improve the accuracy of the prediction results, and further improve the ability to determine the target device for connection based on the prediction results. accuracy.
  • Figure 1 is an optional structural schematic diagram of a vehicle-mounted interconnection system provided by an embodiment of the present application
  • Figure 2 is an optional flow diagram of the device connection method provided by the embodiment of the present application.
  • Figure 3 is an optional flow diagram of the device connection method provided by the embodiment of the present application.
  • Figure 4 is an optional flow diagram of the device connection method provided by the embodiment of the present application.
  • Figure 5 is an optional flow diagram of the device connection method provided by the embodiment of the present application.
  • Figure 6 is an optional flow diagram of the device connection method provided by the embodiment of the present application.
  • Figure 7 is an optional functional module framework diagram of a vehicle-mounted device provided by an embodiment of the present application.
  • Figure 8 is an optional flowchart of applying the device connection method provided by the embodiment of the present application to an actual scenario
  • Figure 9 is an optional flow diagram of applying the device connection method provided by the embodiment of the present application to an actual scenario
  • Figure 10 is an optional structural schematic diagram of the equipment connection device provided by the embodiment of the present application.
  • Figure 11 is an optional structural schematic diagram of the first device provided by the embodiment of the present application.
  • first ⁇ second ⁇ third are only used to distinguish similar objects and do not represent a specific ordering of objects. It is understandable that “first ⁇ second ⁇ third” is used in Where appropriate, the specific order or sequence may be interchanged so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein.
  • a and/or B can mean: A exists alone, A and B exist simultaneously, and they exist alone. B these three situations.
  • at least one herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, and C, which can mean including from A, Any one or more elements selected from the set composed of B and C.
  • In-vehicle interconnection software Carplay, Carlife, Android Auto At present, the operating systems of smartphones are usually divided into: IOS system and Android system of Apple mobile phones. Correspondingly, in-vehicle interconnection applications can also be divided into applications running on IOS systems (such as Apple Carplay) and applications running on Android systems (such as Android Auto, Carlife, etc.).
  • the in-vehicle interconnection application is embedded in the in-vehicle multimedia system and is used to connect a compatible mobile phone to the car, and the mobile phone screen is mapped on the central control screen of the in-vehicle multimedia system, so that it can be controlled through the buttons or voice control on the central control screen of the in-vehicle multimedia system , to control functions on your phone.
  • the relevant technology usually selects a target device among multiple mobile devices to connect to the vehicle-mounted device for interactive use based on preset rules customized by the developer.
  • related technology will also train a neural network based on the user's historical behavioral data, and use the trained neural network to predict the device the user wants to connect to, and then connect to the vehicle-mounted device.
  • selecting the device connection method according to the preset rules depends on whether the developer has comprehensively formulated the selection rules, which limits the applicability in multiple scenarios. When applied in scenarios not covered by the preset rules, it will greatly reduce the selection of devices for connection. accuracy.
  • the method of prediction using a neural network trained based on historical behavioral data has a relatively single source of data, which also reduces the accuracy of selecting devices for connection.
  • the vehicle-mounted interconnection system 100 includes: a first device 200 and a plurality of second devices 400 (400-1 to 400-4 are shown as examples).
  • the second device 400 includes a second device that has connection conditions with the first device, such as Bluetooth, Wireless Local Area Network (WLAN) direct connection, and Near Field Communication (NFC) turned on in the car. Secondary device with functions and more.
  • the first device can discover the second device that meets the connection conditions through functions such as Bluetooth search, such as 400-1 to 400-3 shown in Figure 1.
  • the first device provided by the embodiment of the present application can be implemented as a vehicle-mounted terminal, an intelligent voice interaction device, a smart home appliance, a notebook computer, a tablet computer, a desktop computer, a set-top box, and other types of terminals or user terminals.
  • the second device may be implemented as various types of terminals or user terminals such as smartphones, smart watches, mobile devices (eg, mobile phones, portable music players, personal digital assistants, dedicated messaging devices, portable gaming devices). The specific selection is made according to the actual situation, and is not limited by the embodiments of this application.
  • the first device 200 is used to determine at least one second device that has connection conditions with the first device; obtain scene information; the scene information represents the usage scene of the first device; based on the scene information, combined with historical connection information Perform device connection prediction and determine a target device from the at least one second device; historical connection information includes at least one historical second device connected by the first device under at least one historical scene information; connect the target device.
  • the target device, 400-3 shown in Figure 1 is used to share the currently running application interface, such as application A interface, to the first device 200, and display the application A interface through the first device 200.
  • application A interface such as application A interface
  • the first device 200 is also configured to receive user operations initiated by the user on the application A interface, and based on the user operations, operate application A running on the target device 400-3, and update and display the operations of application A on the application A interface. Responsive interface. In this way, device interconnection and data interaction between the first device and the target device are achieved.
  • a first device such as a vehicle-mounted device can automatically make decisions from multiple second devices based on scene information and connect to a target device suitable for the usage scenario of the first device. And use the application interconnection with the target device, thereby improving the accuracy of determining the target device from multiple devices for connection use.
  • FIG. 2 is an optional flow chart of the device connection method provided by the embodiment of the present application, which will be described in conjunction with the steps shown in FIG. 2 .
  • S101 Determine at least one second device that has connection conditions with the first device.
  • the embodiments of this application are applicable to the scenario where a first device selects a target device from multiple second devices for connection, thereby performing data interaction and functional interconnection with the target device.
  • the vehicle-mounted device selects a target device from multiple mobile devices in the vehicle for connection, and functionally interacts with the vehicle-mounted device through the target device; or, the smart home device selects a target device from multiple mobile devices in the room. Select the target device to connect to the device, and control the smart home device through the target device.
  • the specific selection is made according to the actual situation, and is not limited by the embodiments of this application.
  • the first device can search in a preset communication method, such as Bluetooth search, WLAN, NFC, etc., and find at least one second device that has connection conditions with itself.
  • a preset communication method such as Bluetooth search, WLAN, NFC, etc.
  • the second device that meets the connection conditions may have the preset communication mode currently turned on, and the distance to the first device is less than or equal to the preset distance threshold corresponding to the preset communication mode, so that it can be searched and discovered by the first device. of the second device.
  • the first device can collect scene data that affects the selection of the mobile device in the current usage scenario as scene information.
  • the scene information represents the usage scene of the first device, and the scene information may include scene data of at least one dimension in the usage scene of the first device that affects the first device to select the second device for connection.
  • S102 can be implemented by executing the process of S1021-S1024, which will be described in combination with each step.
  • the current time information can represent the different usage intentions of the user in using the first device in different time periods.
  • the current time information can include: whether it is a holiday, what day of the week, morning, afternoon or evening time period, etc. .
  • Different usage intentions may affect the first device's selection of the connection device. Therefore, the first device can obtain the current time information to use the usage intention information contained in the current time information, such as travel intentions such as going to work, going to school, traveling, etc., to predict device connection.
  • the second device generates broadcast information based on its respective device status information, and broadcasts it to the outside world through a preset communication method.
  • the first device performs device search in a preset communication mode, it can obtain the device status information of the second device by receiving the broadcast information of the second device.
  • the status information includes software information and/or hardware information used to characterize the connection condition on the second device.
  • the status information may include at least one of the second device power level and preset interconnection software information.
  • the preset interconnection software information is software information currently running on the second device and used to implement device interconnection.
  • the default interconnection software may include vehicle-machine interconnection software, smart home appliance control software in a smart home scenario, etc.
  • the default interconnection software information may include the software name, version, and operation of the default interconnection software.
  • Situation, etc. the specific selection is made according to the actual situation, and is not limited by the embodiments of this application.
  • different operators of the first device may affect the first device's selection of the connection device.
  • the first device can collect images of the preset operation position corresponding to the first device through a built-in or externally connected image acquisition device to obtain an image of the operator at the preset operation position. Furthermore, the first device can obtain the operator information corresponding to the first device by performing image recognition, such as face recognition, on the operator image.
  • At least one operator information corresponding to at least one operator image may be pre-recorded on the first device.
  • the first device may determine a matching operator image from the at least one operator image based on the result of image recognition.
  • the target operator image is used, and the operator information corresponding to the target operator image is used as the operator information corresponding to the first device.
  • the operator information may include at least one of operator identity information and operator equipment information.
  • the operator device information includes second device information corresponding to the pre-registered or recorded operator identity information.
  • the preset operating position may include: the main driving position of the vehicle where the vehicle-mounted device is located.
  • the vehicle-mounted device can collect the image of the operator in the main driving position through the camera, and perform face recognition on the operator image to obtain the identity information of the user in the main driving position, and obtain the pre-registered user equipment information corresponding to the user identity information.
  • User identity information and user equipment information are used as operator information.
  • S1021, S1022 and S1023 may be parallel method steps. In actual applications, one or more of the steps may be selected to be executed to obtain at least the current time information, equipment status information and operator information accordingly. one. The specific selection is made according to the actual situation, and is not limited by the embodiments of this application.
  • S1024. Use at least one of current time information, device status information, and operator information as scene information.
  • the first device can obtain at least one of current time information, device status information, and operator information by executing at least one process in S1021-S1023, thereby combining the current time information, device status information, and operator information. At least one of the information is used as scene information.
  • the scene information may further include: at least one of schedule information and navigation information.
  • at least one of schedule information and navigation information on the first device and/or the second device can be used to further identify the user's travel intention, so as to obtain scene information that affects device connection selection in more dimensions.
  • other types of scene information can also be obtained according to different scenes, such as weather information, distance information between each second device and the first device, etc. The specific selection is based on the actual situation, and is not limited by the embodiments of this application. .
  • S103 Perform device connection prediction based on the scene information and historical connection information, and determine the target device from at least one second device.
  • the first device may record at least one historical second device that has been connected under at least one historical scene information during the historical device connection process, and obtain the historical scene information.
  • the first device can obtain the historical second device that meets the user's connection intention under different historical scene information according to the historical second device that is actually connected or used under each historical scene information, so that it can correspond to the historical second device based on the historical scene information.
  • the historical second device performs device connection prediction on the currently collected scene information, and obtains at least one historical second device's connection probability with the first device under the scene information, that is, at least one prediction result.
  • At least one second device includes at least part of the historical second device.
  • at least one historical second device may include: device A, device B, device C, and device D; at least one second device may include: device A, device B, and device C.
  • the first device may determine, from at least part of the historical second devices included in the at least one second device, a second device that meets the user's current connection intention as the target device based on at least one connection probability corresponding to the at least one historical second device.
  • the target device when the target device cannot be determined based on at least one connection probability, for example, the at least one connection probability predicted based on the scene information is lower than a preset probability threshold, or at least one second device does not include at least one In the case of any of the historical second devices, it may be caused by factors such as the first device being in new scene information, or at least one second device being a new device that has not been connected to the first device.
  • the first device can generate corresponding information for information prompts to remind the user that the connection probability predicted based on the scene information is low, and it is recommended that the user make a manual selection.
  • the first device is connected to the target device for further functional interconnection applications.
  • screen mapping technology can be used to display applications on the mobile phone, such as navigation, itineraries, and audio and video playback.
  • applications on the mobile phone such as navigation, itineraries, and audio and video playback.
  • messaging and other applications are projected to the multimedia playback device of the vehicle-mounted device, such as the car central control screen. And operate the applications on the mobile phone through the vehicle-mounted device.
  • the first device determines the target device from at least one second device through device connection prediction, and may also push device information of the target device to the first device. For example, the device information of the target device is pushed on the preset connection interface of the first device to recommend the user to connect to the target device.
  • the first device obtains the scene information and predicts the historical connection information of at least one historical second device that the first device has connected to under at least one historical scene information, so as to obtain the information corresponding to the at least one historical second device. At least one prediction result, so that the target device can be determined from at least one second device to connect according to the at least one prediction result.
  • the scenario information is added to the prediction process to improve the accuracy of the prediction results, thereby improving the ability to determine the target device for connection based on the prediction results. accuracy.
  • S103 can be implemented through S1031, as follows:
  • S1031. Use the device to connect to the network, perform device connection prediction based on scene information, and determine at least one connection probability corresponding to at least one historical second device.
  • the device connection network is obtained by training the initial device connection network through historical connection information. Since the historical connection information includes at least one historical second device that the first device has connected to under at least one historical scene information, the first device uses the device connection network obtained by training with the historical connection information, performs device connection prediction on the scene information, and can obtain the scene Under the information, at least one connection probability corresponding to at least one historical second device.
  • the process of training the initial device connection network using historical connection information can be executed on the first device; it can also be executed on other devices, and the trained device connection network is deployed on the first device.
  • the specific selection is made according to the actual situation, and is not limited by the embodiments of this application.
  • the first device may determine the target device based on the target historical second device with the highest connection probability among at least part of the historical second devices.
  • the first device may determine the target historical second device with the highest connection probability among at least some of the historical second devices as the target device.
  • the first device can also combine the preset probability threshold and use the historical second device with the highest connection probability and higher than the preset probability threshold as the target historical second device as the target device; here, at least one first The second device contains the target history of the second device.
  • the device connection network trained by historical connection information is used to perform device connection prediction on scene information, which can make full use of the complex nonlinear mapping ability, self-learning ability and generalization ability of the neural network to improve Accuracy of predicting target devices via neural networks.
  • the first device can also perform further network training on the device connection network by performing S105-S107 to further optimize the device connection network based on user feedback.
  • the prediction performance as shown in Figure 5, is as follows:
  • the first device when the first device automatically selects and connects to the target device through the method of S101-S104, it can determine the second device that the first device is currently actually connected to as the connecting device.
  • S105 can be implemented by executing S1051 or S1052, which will be described in combination with each step.
  • the target device and the first device when the target device and the first device generate data interaction, it means that the user has started to use the device interconnection through the target device, that is, the user agrees that the first device automatically selects the connected target device.
  • the first device uses the target device as the connected device.
  • the first device when receiving a switching instruction for the target device, it means that the user did not use the currently automatically selected target device, but manually selected another second device for connection.
  • the first device obtains the target switching device specified by the switching instruction for connection, and uses the target switching device as the connecting device.
  • connection device and scene information as incremental connection information in historical connection information.
  • the first device when the first device determines the connected device, it records the connected device and scene information as incremental connection information in the historical connection information. That is, the connection device and scene information corresponding to the current device interconnection are added to the historical connection information.
  • the first device can train and update the device connection network based on incremental connection information.
  • the first device can use the incremental connection information to perform incremental training on the device connection network, and update network parameters of the device connection network through incremental training, so that the device connection network with updated parameters can be used for the next device connection.
  • Connection prediction enables continuous optimization of the device network model through user feedback.
  • the first device can also use part or all of the historical connection information including incremental connection information to train the device connection network and update network parameters.
  • the specific selection is based on the actual situation. The embodiments of this application do not limited.
  • the connected device in the case where the connected device does not belong to at least one historical second device, it means that the user manually selected the second device that was connected to the first device for the first time.
  • the predictable categories included in the device connection network trained based on historical connection information do not include the connection device that the user intends to select.
  • at least one historical second device includes device A, device B, device C, and device D; the device connection network trained according to the historical connection information can predict device A, device B, device C, and device D corresponding to Connection probability.
  • the connecting device actually connected to the first device is device E.
  • the first device may use scene information and device E as incremental information.
  • the first device obtains at least part of the information from historical connection information, and combines at least part of the information with the incremental connection information to retrain the device connection network, and retrain the device connection network. Training updates the predicted categories and network parameters of the device connection network. In this way, the retrained device connection network can predict the connection probability of device E.
  • the first device can further optimize the device connection network based on the user's selection and feedback of the connected device, forming a virtuous cycle that can gradually optimize the accuracy of network prediction based on usage. As user connection data continues to enrich, The accuracy of device connection network prediction will also gradually improve, giving users a better connection experience.
  • the first device may also perform S108 to implement application recommendations for the connected device, as follows:
  • the target application is used to perform data interaction with the first device on the connected device.
  • the connected device can share and interact with the first device through the target application.
  • the target application may be a multimedia application, such as music, radio, video, listening to books, or an information prompt application, such as travel prompts, short message prompts, advertising prompts, or a navigation application, such as itinerary sharing, map Navigation, etc., are specifically selected according to the actual situation, and are not limited by the embodiments of this application.
  • a music application can be run on the mobile phone currently connected to the vehicle device to share songs played in the music application to the vehicle device for playback.
  • the target application information may include one or more of the application name, logo, version, current application data of the music application, such as the navigation address set in the navigation application, etc. The specific selection is based on the actual situation. In the embodiment of this application Not limited.
  • the first device can push the target application to the connected device connected to it through the application recommendation network.
  • the application recommendation network is obtained by training the initial application recommendation network through the application usage information collection.
  • the application usage information set includes: at least one historical connection device to which the first device has been connected, and at least one historical target application information corresponding to at least one historical target application that has been run on the at least one historical connection device.
  • the first device may record historical connected devices and historical target application information running on the historically connected devices in an application usage information set; use the application usage information set to train to obtain the application Recommended Network.
  • the first device before the first device uses the application recommendation network to push the target application to the connected device, for a historical device interconnection on the first device, can combine the historical connected device and the application running on the historical connected device.
  • the target application information of the target application is recorded as an application usage information.
  • an application usage information set including at least one piece of application usage information can be obtained.
  • the first device uses the application usage information collection to train the initial application recommendation network until the preset network training conditions are met to obtain the application recommendation network.
  • the application recommendation network can be included in the device connection network and trained as part of the device connection network, or it can be an independent network model. The specific selection is based on the actual situation, which is not limited by the embodiments of this application.
  • the first device can not only automatically make decisions from multiple second devices and determine the applicable target device under the scene information for connection, but can also further utilize the application recommendation network to make connections on the target device.
  • Recommend runnable applications such as recommending users to open commonly used navigation addresses, or recommending users to open music playing software, etc., thus realizing application recommendation based on the target device, providing greater convenience for users and improving device interconnection. User experience of use.
  • the first device may be a vehicle-mounted device
  • the second device may be a mobile device.
  • Figure 7 shows a functional module framework diagram of a vehicle-mounted device provided by an embodiment of the present application, including a communication connection module 700, Scene awareness module 701, historical information storage module 702 and connection decision module 703. in,
  • the communication connection module 700 is configured to collect a list of connectable mobile devices in real time after the vehicle is started, which is equivalent to at least one second device; the communication connection module 700 is also configured to manage the communication connection between the vehicle and the mobile device, such as connecting Optimal device, new device connection detection, or connecting to other devices manually switched by the user, etc.
  • the scene sensing module 701 is configured to collect scene information by sensing the influencing factors in various dimensions that affect the selection of the mobile device in the usage scenario of the first device.
  • Scene information can include: current time information, such as the current time period, whether it is a holiday, day of the week, morning, evening, etc., to identify travel intentions such as going to work, school, traveling, etc.; mobile device status information, such as device battery, whether Carlife is turned on, etc.
  • Vehicle-machine interconnection software is equivalent to the above-mentioned device status information; driver information: who is the current main driver and which mobile device is it, which is equivalent to the above-mentioned operator information.
  • the historical information storage module 702 is configured to store and retrieve historical connection information of mobile devices connected to the vehicle. It not only includes which historical mobile devices are connected, that is, historical second devices, but also includes what the scene sensing module 701 sensed.
  • the multi-dimensional scene information is equivalent to at least one historical second device connected under the at least one historical scene information mentioned above. And based on the connection device detected by the communication connection module 700, the connection device and the connection scene are stored in the historical connection information.
  • the connection decision-making module 703 is configured to input the scene information collected by the scene sensing module 701 into the decision-making model of the fully connected neural network, which is equivalent to the above-mentioned device connection network, and integrates the list of connectable mobile devices of the communication connection module 700 to make a decision.
  • Optimally connected mobile devices Based on the actual connection results and user feedback of optimally connected mobile devices, the decision-making model is trained and optimized online, and the device connection network is completely retrained in the event that the user manually switches to a new mobile device, so that each vehicle and machine can The device connection network can form a unique personalized model, which continuously improves the accuracy of device connection prediction for the device connection network.
  • the communication connection module 700 collects a list of connectable mobile devices.
  • the scene sensing module 701 collects scene information.
  • connection decision module 703 predicts at least one connection probability corresponding to at least one historical mobile device according to the scene information through the decision model.
  • connection decision module 703 outputs the optimal device based on at least one connection probability and a list of connectable mobile devices.
  • the communication connection module 700 connects to the optimal device.
  • the vehicle-mounted device further trains the decision-making model based on user feedback, as shown in Figure 9, as follows:
  • the communication connection module 700 detects that the user has not switched to the optimal device and starts using it.
  • the historical information storage module 702 stores the optimal device and scene information in the historical connection information.
  • the historical information storage module 702 stores the optimal device and scene information; and then executes S811.
  • the communication connection module 700 detects the user's manual switching, connects to and obtains the target switching device.
  • the historical information storage module 702 stores the target switching device and scene information in the historical connection information.
  • connection decision module 703 performs incremental training and network parameter update on the decision module based on the optimal device and scene information.
  • the historical information storage module 702 inputs the optimal device and scene information into the online training module in the connection decision module 703 for incremental training, and updates and optimizes the network parameters of the decision model.
  • connection decision module 703 performs incremental training on the decision module based on the target switching device and scene information.
  • the historical information storage module 702 inputs the target switching device and scene information into the online training module for incremental training, and performs incremental training on the network parameters of the decision model. Updates and optimizations.
  • connection decision module 703 obtains at least part of the historical connection information within the preset time period; and performs the decision-making module on the basis of at least part of the historical connection information, the target switching device and the scene information. Retrain.
  • the connection decision module 703 retrieves at least part of the historical connection information within the preset time period in the historical information storage module 702, and adds The target switches equipment and scene information, adds new equipment to the output of the model, and retrains the decision-making module.
  • each mobile device can be connected to each other, with the optimal device connected to the vehicle as the main mobile device, and an interconnection network is established between the mobile devices so that the vehicle and the device Each mobile device can establish a connection, allowing the vehicle to connect to multiple mobile devices at the same time.
  • the device connection method provided by the embodiments of the present application greatly improves the scalability of the solution compared with the method of selecting device connection based on preset rules in related technologies. Compared with the method of predicting connected devices based only on user usage data, This method fully considers the influencing factors of various dimensions in the device interconnection scenario, and proposes to use a fully connected neural network for decision-making, establish a user personalized model based on user feedback, continuously optimize the model effect, and achieve better model generalization, thus improving the Accuracy of predicted optimal equipment.
  • FIG. 10 is a schematic structural diagram of the equipment connection device provided by the embodiment of the present application; as shown in Figure 10, the equipment connection device 1 includes:
  • the determining part 11 is configured to determine at least one second device that has connection conditions with the first device
  • the scene collection part 12 is configured to obtain scene information; the scene information represents the usage scene of the first device;
  • connection prediction part 13 is configured to perform device connection prediction based on the scene information and historical connection information, and determine the target device from the at least one second device;
  • the historical connection information includes the first device in at least one At least one historical second device connected under historical scene information;
  • the communication connection part 14 is configured to connect the target device.
  • the scene collection part 12 is also configured to obtain current time information
  • the device status information of the second device is obtained; and/or, by performing image recognition on the operator image collected at the preset operating position of the first device, the obtained Operator information corresponding to the first device; use at least one of the current time information, the device status information and the operator information as the scene information.
  • the device status information includes: at least one of the second device power level and preset interconnection software information; the preset interconnection software information is currently running on the second device and is used to implement Software information for device interconnection.
  • connection prediction part 13 is also configured to utilize the device connection network, perform device connection prediction based on the scene information, and determine at least one connection probability corresponding to the at least one historical second device;
  • the device connection network is obtained by training the initial device connection network through the historical connection information;
  • the target device is determined from the at least one second device according to the at least one connection probability.
  • the device connection device further includes: a training part configured to determine the connection device of the first device after connecting the target device; and combine the connection device with The scene information is recorded in the historical connection information as incremental connection information; based on the incremental connection information, the device connection network is trained.
  • the training part is further configured to use the target device as the connected device when the target device generates application data interaction with the first device; In the case of a switching instruction of the target device, the target switching device specified by the switching instruction is obtained for connection, and the target switching device is determined as the connecting device.
  • the training part is further configured to use the incremental connection information to perform incremental training on the device connection network.
  • the training part is further configured to obtain at least part of the information from the historical connection information when the connected device does not belong to the at least one historical second device; combined with the at least The partial information is combined with the incremental connection information to retrain the device connection network.
  • the device connection device further includes: an application recommendation part, the application recommendation part is configured to use an application recommendation network to push a target application to the connected device of the first device; the target application uses Performing data interaction with the first device on the connecting device; wherein the application recommendation network is obtained by training an initial application recommendation network through a collection of application usage information; the collection of application usage information includes: At least one historical connection device that the first device has connected to, and at least one historical target application information corresponding to at least one historical target application that has run on the at least one historical connection device.
  • the at least one second device includes at least part of the historical second devices in the at least one historical second device
  • the connection prediction part 13 is further configured to calculate the at least part of the historical second device according to the at least part of the historical second device.
  • the second device with the highest connection probability in target history determines the target device.
  • the device connection device further includes: a device push part, the device push part is configured to perform device connection prediction based on the scene information and historical connection information, from the at least one After the target device is determined in the second device, the device information of the target device is pushed to the first device.
  • the first device includes: a vehicle-mounted device
  • the second device includes: a mobile device
  • the preset operating position includes: the main driving position of the vehicle where the vehicle-mounted device is located; the scene
  • the information also includes: at least one of schedule information and navigation information.
  • FIG. 11 is an optional structural schematic diagram of the first device provided by embodiments of the present application.
  • the first device 2 includes: a memory 22 and a processor 23 .
  • the memory 22 and the processor 23 are connected through the communication bus 24; the memory 22 is used to store executable instructions; the processor 23 is used to implement the method provided by the embodiment of the present application when executing the executable instructions stored in the memory 22, For example, the device connection method provided by the embodiment of this application.
  • Embodiments of the present application provide a computer-readable storage medium that stores executable device connection instructions, which are used to cause the processor 23 to implement the method provided by the embodiment of the present application when executed, for example, the device connection method provided by the embodiment of the present application. .
  • the storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; it may also include one or any combination of the above memories.
  • Various equipment may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; it may also include one or any combination of the above memories.
  • executable device connection instructions may take the form of a program, software, software module, script or code, in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages) and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
  • executable device connection instructions may, but do not necessarily correspond to, files in the file system and may be stored as part of a file holding other programs or data, for example, in Hyper Text Markup Language (HTML). ) document, in one or more scripts, stored in a single file specific to the program in question, or, stored in multiple collaborative files (e.g., files storing one or more modules, subroutines, or portions of code) middle.
  • HTML Hyper Text Markup Language
  • executable device connection instructions may be deployed to execute on one computing device, or on multiple computing devices located at one location, or on multiple computing devices distributed across multiple locations and interconnected by a communications network. executed on the computing device.
  • embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, magnetic disk storage and optical storage, etc.) embodying computer-usable program code therein.
  • a computer-usable storage media including, but not limited to, magnetic disk storage and optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions
  • the device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.
  • These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device.
  • Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.
  • the first device can obtain at least one historical second device corresponding to the at least one historical second device by obtaining scene information and making predictions based on the historical connection information of at least one historical second device that has been connected under at least one historical scene information. Prediction results, so that the target device can be determined from at least one second device to connect according to the at least one prediction result. Therefore, in the device interconnection scenario, it is possible to perceive the scenario factors in various dimensions that affect the device connection, realize the addition of scenario information to the prediction process, improve the accuracy of the prediction results, and further improve the ability to determine the target device for connection based on the prediction results. accuracy.
  • the first device can further optimize the device connection network based on the user's selection and feedback of the connected device, forming a virtuous cycle that can gradually optimize the network prediction accuracy according to usage.
  • the device connection network The accuracy of predictions will also gradually improve, giving users a better connection experience.

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Abstract

本申请实施例公开了一种设备连接方法、装置、第一设备及计算机可读存储介质，能够提高从多个设备中确定目标设备以进行连接的准确性。方法包括：确定与第一设备具备连接条件的至少一个第二设备；获取场景信息；场景信息表征第一设备的使用场景；基于场景信息，结合历史连接信息进行设备连接预测，从至少一个第二设备中确定目标设备；历史连接信息包含第一设备在至少一个历史场景信息下连接的至少一个历史第二设备；连接目标设备。

Description

设备连接方法、装置、第一设备及计算机可读存储介质
相关申请的交叉引用
本申请基于申请号为202210419405.3、申请日为2022年04月20日、发明名称为“设备连接方法、装置、第一设备及计算机可读存储介质”的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本发明作为参考。
技术领域
本申请涉及人工智能技术领域，尤其涉及一种设备连接方法、装置、第一设备及计算机可读存储介质。
背景技术
目前，手机等移动设备与车载设备相互连接，以进行功能互联和应用已成为常见的使用场景。对于多个用户或多个移动设备同时在车内的情况，相关技术通常是根据开发者定制的预设规则，在多个移动设备中选择一个目标设备与车载设备连接并进行交互使用。这种方法依赖于开发者对选择规则制定的全面性，限制了在多场景下应用的广泛性，对于预设规则未覆盖到的场景，降低了选择设备进行连接的准确性。
发明内容
本申请实施例期望提供一种设备连接方法、装置、第一设备及计算机可读存储介质，能够从多个设备中确定目标设备以进行连接的准确性。
本申请的技术方案是这样实现的：
本申请实施例提供了一种设备连接方法，包括：
确定与第一设备具备连接条件的至少一个第二设备；
获取场景信息；所述场景信息表征所述第一设备的使用场景；
基于所述场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备；所述历史连接信息包含所述第一设备在至少一个历史场景信息下连接的至少一个历史第二设备；
连接所述目标设备。
本申请实施例提供了一种设备连接装置，包括：
确定部分，被配置为确定与第一设备具备连接条件的至少一个第二设备；
场景采集部分，被配置为获取场景信息；所述场景信息表征所述第一设备的使用场景；
连接预测部分，被配置为基于所述场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备；所述历史连接信息包含所述第一设备在至少一个历史场景信息下连接的至少一个历史第二设备；
通信连接模块，用于连接所述目标设备。
本申请实施例提供一种第一设备，包括：
所述存储器，用于存储可执行指令；
所述处理器，用于通过执行所述存储器中存储的可执行指令，实现本申请实施例提供的设备连接方法。
本申请实施例提供一种计算机可读存储介质，存储有可执行指令，用于引起处理器执行时，实现本申请实施例提供的设备连接方法。
本申请实施例提供一种计算机程序产品，包括计算机程序或指令，所述计算机程序或指令被处理器执行时，实现本申请实施例提供的设备连接方法。
本申请实施例具有以下有益效果：
第一设备通过获取场景信息，结合在至少一个历史场景信息下连接过的至少一个历史第二设备的历史连接信息进行预测，可以得到至少一个历史第二设备对应的至少一个预测结果，从而可以根据至少一个预测结果从至少一个第二设备中确定目标设备进行连接。从而在设备互连场景下，能够对影响设备连接的各个维度的场景因素进行感知，实现了将场景信息加入预测过程，提高了预测结果的准确性，进而提高了根据预测结果确定目标设备进行连接的准确性。
附图说明
图1是本申请实施例提供的车载互联系统的一种可选的结构示意图；
图2是本申请实施例提供的设备连接方法的一种可选的流程示意图；
图3是本申请实施例提供的设备连接方法的一种可选的流程示意图；
图4是本申请实施例提供的设备连接方法的一种可选的流程示意图；
图5是本申请实施例提供的设备连接方法的一种可选的流程示意图；
图6是本申请实施例提供的设备连接方法的一种可选的流程示意图；
图7是本申请实施例提供的一种车载设备的一种可选的功能模块框架图；
图8是本申请实施例提供的设备连接方法应用于实际场景的一种可选的流程示意图；
图9是本申请实施例提供的设备连接方法应用于实际场景的一种可选的流程示意图；
图10是本申请实施例提供的设备连接装置的一种可选的结构示意图；
图11是本申请实施例提供的第一设备的一种可选的结构示意图。
具体实施方式
为了使本申请的目的、技术方案和优点更加清楚，下面将结合附图对本申请作进一步地详细描述，所描述的实施例不应视为对本申请的限制，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本申请保护的范围。
在以下的描述中，涉及到“一些实施例”，其描述了所有可能实施例的子集，但是可以理解，“一些实施例”可以是所有可能实施例的相同子集或不同子集，并且可以在不冲突的情况下相互结合。
在以下的描述中，所涉及的术语“第一\第二\第三”仅仅是区别类似的对象，不代表针对对象的特定排序，可以理解地，“第一\第二\第三”在允许的情况下可以互换特定的顺序或先后次序，以使这里描述的本申请实施例能够以除了在这里图示或描述的以外的顺序实施。
本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中术语“至少一种”表示多种中的任意一种或多种中的至少两种的任意组合，例如，包括A、B、C中的至少一种，可以表示包括从A、B和C构成的集合中选择的任意一个或多个元素。
除非另有定义，本文所使用的所有的技术和科学术语与属于本申请的技术领域的技术人员通常理解的含义相同。本文中所使用的术语只是为了描述本申请实施例的目的，不是旨在限制本申请。
对本申请实施例进行进一步详细说明之前，对本申请实施例中涉及的名词和术语进行说明，本申请实施例中涉及的名词和术语适用于如下的解释。
车载互联软件Carplay、Carlife、Android Auto：目前，智能手机的操作系统通常分为：苹果手机的IOS系统和安卓系统，相应地，车载互联应用可也分为在IOS系统上运行的应用(如Apple Carplay)与安卓系统上运行的应用(如Android Auto、Carlife等)。车载互联应用植入在车载多媒体系统中，用于将兼容的手机与汽车连接，并手机屏幕映射在车载多媒体系统的中控屏幕上，从而可以通过车载多媒体系统的中控屏幕上的按键或者声控，来控制手机上的功能。
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述。
目前，对于多个用户或多个移动设备同时在车内的情况，相关技术通常是根据开发者定制的预设规则，在多个移动设备中选择一个目标设备与车载设备连接并进行交互使用。或者，相关技术也会基于用户的历史行为数据训练神经网络，利用训练得到的神经网络预测用户想要连接的设备，进而与车载设备连接。其中，根据预设规则选择设备连接方法依赖于开发者对选择规则的制定是否全面，限制了在多场景下适用性，在预设规则未覆盖的场景下应用时，会大大降低选择设备进行连接的准确性。而利用基于历史行为数据训练的神经网络进行预测的方法数据来源较为单一，同样降低了选择设备进行连接的准确性。
本申请实施例提供一种设备连接方法、装置、第一设备及计算机可读存储介质，能够提高设备连接的准确性。下面，以车载场景为例，说明本申请实施例提供的第一设备的示例性应用。如图1所示，本申请实施例提供的车载互联系统100包括：第一设备200与多个第二设备400(示例性示出了400-1至400-4)。其中，第二设备400中包含与第一设备具备连接条件的第二设备，如车内开启了蓝牙、无线局域网(Wireless Local Area Network，WLAN)直连、近场通信(Near Field Communication，NFC)功能等等的第二设备。相应地，第一设备可以通过蓝牙搜索等功能，发现具备连接条件的第二设备，如图1中示出的400-1至400-3。
本申请实施例提供的第一设备可以实施为车载终端、智能语音交互设备、智能家电和笔记本电脑，平板电脑，台式计算机，机顶盒等各种类型的终端或用户终端。第二设备可以实施为智能手机、智能手表、移动设备(例如，移动电话，便携式音乐播放器，个人数字助理，专用消息设备，便携式游戏设备)等各种类型的终端或用户终端。具体的根据实际情况进行选择，本申请实施例不作限定。
本申请实施例中，第一设备200，用于确定与第一设备具备连接条件的至少一个第二 设备；获取场景信息；场景信息表征第一设备的使用场景；基于场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备；历史连接信息包含所述第一设备在至少一个历史场景信息下连接的至少一个历史第二设备；连接目标设备。
目标设备，如图1中示出的400-3，用于将当前运行的应用界面，如应用A界面，共享至第一设备200，通过第一设备200显示应用A界面。
第一设备200，还用于接收用户针对应用A界面发起的用户操作，并基于用户操作，对目标设备400-3上运行的应用A进行操作，并在应用A界面上更新显示应用A的操作响应界面。如此，实现了第一设备与目标设备之间的设备互联与数据交互。
可以看出，通过本申请实施例提供的车载互联系统，第一设备如车载设备可以根据场景信息，从多个第二设备中自动决策并连接至适用于第一设备的使用场景的目标设备，并与目标设备进行应用互联使用，从而提高了从多个设备中确定目标设备以进行连接使用的准确性。
下面，以第一设备为执行主体，介绍本申请实施例的设备连接方法。图2是本申请实施例提供的设备连接方法的一个可选的流程图，将结合图2示出的步骤进行说明。
S101、确定与第一设备具备连接条件的至少一个第二设备。
本申请实施例适用于第一设备从多个第二设备中选择目标设备进行连接，从而与目标设备进行数据交互与功能互联的场景。示例性地，车载场景或自动驾驶场景下，车载设备从车内的多个移动设备中选择目标设备进行连接，通过目标设备与设备车载设备进行功能交互；或者，智能家居设备从室内的多个设备中选择目标设备进行连接，通过目标设备对智能家居设备进行操控的应用场景。具体的根据实际情况进行选择，本申请实施例不作限定。
本申请实施例中，第一设备可以以预设通信方式进行搜索，如通过蓝牙搜索，WLAN、NFC等方式进行搜索，发现与自身具备连接条件的至少一个第二设备。
这里，具备连接条件的第二设备可以是当前开启了预设通信方式，且与第一设备之间的距离小于或等于预设通信方式对应的预设距离阈值，从而可以被第一设备搜索发现的第二设备。
S102、获取场景信息；场景信息表征第一设备的使用场景。
本申请实施例中，第一设备可以当前的使用场景中，采集影响移动设备选择的场景数据，作为场景信息。
本申请实施例中，场景信息表征第一设备的使用场景，场景信息可以包含第一设备的使用场景中，影响第一设备选择第二设备进行连接的至少一个维度的场景数据。
在一些实施例中，基于图2，如图3所示，S102可以通过执行S1021-S1024的过程来实现，将结合各步骤进行说明。
S1021、获取当前时间信息。
本申请实施例中，当前时间信息可以表征用户在不同时间段使用第一设备的不同使用意图，示例性地，当前时间信息可以包括：是否假期、星期几、上午、下午或晚上的时间段等。而不同使用意图可能影响第一设备对连接设备的选择。从而，第一设备可以获取当前时间信息，以利用当前时间信息包含的使用意图信息，如上班、上学、出游等出行意图进行设备连接预测。
S1022、通过接收第二设备的广播信息，获取第二设备的设备状态信息。
本申请实施例中，第二设备根据各自的设备状态信息，生成广播信息，并通过预设通信方式对外进行广播。这样，第一设备在以预设通信方式进行设备搜索的情况下，可以通过接收第二设备的广播信息，获取第二设备的设备状态信息。
这里，状态信息包含用于表征第二设备上连接条件的软件信息和/或硬件信息。在一些实施例中，状态信息可以包括第二设备电量与预设互联软件信息中的至少一种。其中，预设互联软件信息为在第二设备上当前运行的，用于实现设备互联的软件信息。
在一些实施例中，预设互联软件可以包括车机互联软件，也可以包括智能家居场景下的智能家电操控软件等等，预设互联软件信息可以包括预设互联软件的软件名称、版本、运行情况等等，具体的根据实际情况进行选择，本申请实施例不作限定。
S1023、通过对第一设备的预设操作位置上采集的操作者图像进行图像识别，得到第一设备对应的操作者信息。
本申请实施例中，第一设备的不同操作者，如不同的车辆驾驶员可能影响第一设备对连接设备的选择。第一设备可以通过内置或外部连接的图像采集设备，对第一设备对应的预设操作位置进行图像采集，得到预设操作位置上的操作者图像。并且，第一设备可以通过对操作者图像进行图像识别，如人脸识别，得到第一设备对应的操作者信息。
在一些实施例中，第一设备上可以预先记录有至少一个操作者图像对应的至少一个操作者信息，这样，第一设备可以根据图像识别的结果，从至少一个操作者图像中确定出匹配的目标操作者图像，进而将目标操作者图像对应的操作者信息作为第一设备对应的操作 者信息。
在一些实施例中，操作者信息可以包括操作者身份信息，以及操作者设备信息中的至少一个。其中，操作者设备信息包含预先注册或记录的操作者身份信息对应的第二设备信息。
示例性地，对于第一设备为车载设备的情况，预设操作位置可以包括：车载设备所在车辆的主驾驶位置。车载设备可以通过摄像头采集主驾驶位置上的操作者图像，并通过对操作者图像进行人脸识别，得到主驾驶位置上用户身份信息，并获取用户身份信息对应的预先注册的用户设备信息，将用户身份信息和用户设备信息作为操作者信息。
需要说明的是，S1021、S1022与S1023可以是并列的方法步骤，实际应用中可以选择其中的一个或多个步骤来执行，以相应地得到当前时间信息、设备状态信息与操作者信息中的至少一个。具体的根据实际情况进行选择，本申请实施例不作限定。
S1024、将当前时间信息、设备状态信息与操作者信息中的至少一个，作为场景信息。
本申请实施例中，第一设备可以通过执行S1021-S1023中的至少一个过程，得到当前时间信息、设备状态信息与操作者信息中的至少一个，从而将当前时间信息、设备状态信息与操作者信息中的至少一个，作为场景信息。
在一些实施例中，对于车载应用场景，也即第一设备包括：车载设备，第二设备包括：移动设备的场景，场景信息还可以包括：日程信息与导航信息中的至少一个。这里，可以利用第一设备和/或第二设备上的日程信息与导航信息中的至少一个，进一步识别出用户的出行意图，以得到更多维度下影响设备连接选择的场景信息。实际应用中也可以根据场景不同获取其他类型的场景信息，如天气信息、每个第二设备与第一设备之间的距离信息等等，具体的根据实际情况进行选择，本申请实施例不作限定。
可以理解的是，通过引入车机状态、移动设备状态、驾驶员状态、环境状态等多种影响因素作为场景信息，以基于场景信息进行设备连接预测，能够大大提高设备连接预测的准确性。
S103、基于场景信息，结合历史连接信息进行设备连接预测，从至少一个第二设备中确定目标设备。
本申请实施例中，第一设备可以在历史设备连接过程中，记录在至少一个历史场景信息下连接过的至少一个历史第二设备，得到历史场景信息。如此，第一设备可以根据每个历史场景信息下，对应实际连接或使用过的历史第二设备，得到不同历史场景信息下符合 用户连接意图的历史第二设备，从而，可以基于历史场景信息对应的历史第二设备，对当前采集到的场景信息进行设备连接预测，得到至少一个历史第二设备在场景信息下与第一设备的连接概率，也即至少一个预测结果。
本申请实施例中，至少一个第二设备中包含至少部分历史第二设备。示例性地，至少一个历史第二设备可以包括：设备A、设备B、设备C、与设备D；至少一个第二设备可以包括：设备A、设备B、与设备C。第一设备可以根据至少一个历史第二设备对应的至少一个连接概率，在至少一个第二设备包含的至少部分历史第二设备中，确定符合用户当前连接意图的第二设备，作为目标设备。
在一些实施例中，在根据至少一个连接概率无法确定出目标设备，示例性地，根据场景信息预测的至少一个连接概率均低于预设概率阈值，或者，至少一个第二设备不包含至少一个历史第二设备中的任一历史第二设备的情况下，可能是第一设备处于新的场景信息中，或者至少一个第二设备均为未与第一设备连接过的新设备等因素导致。第一设备可以生成相应的信息进行信息提示，以提醒用户根据场景信息预测的连接概率较低，建议用户进行手动选择。
S104、连接目标设备。
本申请实施例中，第一设备与目标设备连接，以进行进一步的功能互联应用。
在一些实施例中，以第一设备为车载设备，目标设备为手机等移动设备为例，车载设备与手机连接后，可以利用屏幕映射技术，将手机上应用，如导航、行程、音视频播放、消息等应用的多媒体内容投射到车载设备的多媒体播放设备，如汽车中控屏上。并通过车载设备对手机上的应用进行操作。
在一些实施例中，第一设备通过设备连接预测，从至少一个第二设备中确定目标设备，也可以将目标设备的设备信息推送至第一设备。示例性地，在第一设备的预设连接界面上推送目标设备的设备信息，以推荐用户连接至目标设备。
可以理解的是，第一设备通过获取场景信息，结合第一设备在至少一个历史场景信息下连接过的至少一个历史第二设备的历史连接信息进行预测，可以得到至少一个历史第二设备对应的至少一个预测结果，从而可以根据至少一个预测结果从至少一个第二设备中确定目标设备进行连接。从而实现了在设备互连场景下，通过对影响设备连接的各个维度的场景因素进行感知，将场景信息加入预测过程，提高预测结果的准确性，进而提高了根据预测结果确定目标设备进行连接的准确性。
本申请实施例中，基于图2或图3，S103可以通过S1031来实现，如下：
S1031、利用设备连接网络，基于场景信息进行设备连接预测，确定至少一个历史第二设备对应的至少一个连接概率。
本申请实施例中，设备连接网络是通过历史连接信息，对初始设备连接网络进行训练得到的。由于历史连接信息包含第一设备在至少一个历史场景信息下连接过的至少一个历史第二设备，第一设备利用历史连接信息训练得到的设备连接网络，对场景信息进行设备连接预测，可以得到场景信息下，至少一个历史第二设备对应的至少一个连接概率。
本申请实施例中，利用历史连接信息对初始设备连接网络进行训练的过程可以在第一设备上执行；也可以在其他设备上执行，并将训练完成的设备连接网络部署在第一设备上。具体的根据实际情况进行选择，本申请实施例不作限定。
S1032、根据至少一个连接概率，从至少一个第二设备中确定目标设备。
本申请实施例中，第一设备可以根据至少部分历史第二设备中，最高连接概率的目标历史第二设备，确定目标设备。
在一些实施例中，第一设备可以将至少部分历史第二设备中，最高连接概率的目标历史第二设备，确定为目标设备。
在一些实施例中，第一设备也可以结合预设概率阈值，将连接概率最高，且高于预设概率阈值的历史第二设备作为目标历史第二设备，作为目标设备；这里，至少一个第二设备包含目标历史第二设备。
可以理解的是，本申请实施例中，利用历史连接信息训练得到的设备连接网络对场景信息进行设备连接预测，可以充分利用神经网络的复杂非线性映射能力、自学习能力和泛化能力，提高通过神经网络预测目标设备的准确性。
在一些实施例中，基于图2、图3或图4，S104之后，第一设备还可以通过执行S105-S107，对设备连接网络进行进一步网络训练，以根据用户使用的反馈进一步优化设备连接网络的预测性能，如图5所示，如下：
S105、确定第一设备的连接设备。
本申请实施例中，第一设备在通过S101-S104的方法，自动选择并连接至目标设备的情况下，可以确定第一设备当前实际连接的第二设备，作为连接设备。
在一些实施例中，基于图5，如图6所示，S105可以通过执行S1051或S1052来实现，将结合各步骤进行说明。
S1051、在目标设备与第一设备产生数据交互的情况下，将目标设备作为连接设备。
本申请实施例中，在目标设备与第一设备产生数据交互的情况下，说明用户已经开始通过目标设备进行设备互联的使用了，也即用户认同第一设备自动选择连接的目标设备。第一设备将目标设备作为连接设备。
S1052、在接收到针对目标设备的切换指令的情况下，连接目标切换设备，并获取切换指令指定的目标切换设备作为连接设备。
本申请实施例中，在接收到针对目标设备的切换指令的情况下，说明用户并未使用当前自动选择得到的目标设备，而是手动选择了其他的第二设备进行连接。第一设备获取切换指令指定的目标切换设备进行连接，并将目标切换设备作为连接设备。
S106、将连接设备与场景信息作为增量连接信息，记录在历史连接信息中。
本申请实施例中，第一设备在确定连接设备的情况下，将连接设备与场景信息作为增量连接信息，记录在历史连接信息中。也即在历史连接信息中新增了当前次设备互联对应的连接设备与场景信息。
S107、基于增量连接信息，对设备连接网络进行训练。
本申请实施例中，第一设备可以基于增量连接信息，对设备连接网络进行训练与更新。
在一些实施例中，第一设备可以利用增量连接信息，对设备连接网络进行增量训练，通过增量训练更新设备连接网络的网络参数，从而可以利用更新参数的设备连接网络进行下一次设备连接预测，实现通过用户的使用反馈对设备网络模型进行持续优化。
在一些实施例中，第一设备也可以利用包含了增量连接信息的部分或全部历史连接信息，对设备连接网络进行训练与网络参数更新，具体的根据实际情况进行选择，本申请实施例不作限定。
在一些实施例中，在连接设备不属于至少一个历史第二设备的情况下，说明用户手动选择了首次连接到第一设备的第二设备。而根据历史连接信息训练得到的设备连接网络包含的可预测类别并不包含用户意向选择的该连接设备。示例性地，至少一个历史第二设备包括设备A、设备B、设备C、与设备D；根据历史连接信息训练得到的设备连接网络可预测设备A、设备B、设备C、与设备D对应的连接概率。而第一设备实际连接的连接设备为设备E。第一设备可以将场景信息与设备E作为增量信息，第一设备从历史连接信息中获取至少部分信息，并结合至少部分信息与增量连接信息，对设备连接网络进行重新训练，并通过重新训练对设备连接网络的预测类别与网络参数进行更新。这样，重新训练的 设备连接网络可以对设备E的连接概率进行预测。
可以理解的是，第一设备可以根据用户对连接设备的选择与反馈进一步优化用于设备连接网络，形成能够根据使用情况逐步优化网络预测准确度的良性循环，随着用户连接数据的不断丰富，设备连接网络预测的准确度也会逐步提高，给用户带来更优质的连接体验。
在一些实施例中，确定连接设备之后，第一设备还可以执行S108，以实现对连接设备的应用推荐，如下：
S108、利用应用推荐网络，向第一设备的连接设备推送目标应用；目标应用用于在连接设备上，与第一设备进行数据交互。
本申请实施例中，目标应用用于在连接设备上，与第一设备进行数据交互。连接设备可以通过目标应用，与第一设备进行应用功能共享与交互。
在一些实施例中，目标应用可以是多媒体应用，如音乐、电台、视频、听书，或者信息提示类应用，如旅游提示、短消息提示、广告提示、或者导航类应用，如行程分享、地图导航等等，具体的根据实际情况进行选择，本申请实施例不作限定。
示例性地，车载场景下，车载设备当前连接的手机上可以运行有音乐应用，以将音乐应用中播放的歌曲共享至车载设备进行播放。则目标应用信息可以包含音乐应用的应用名称、标识、版本、当前应用数据，如导航应用中设置的导航地址等等信息中的一个或多个，具体的根据实际情况进行选择，本申请实施例不作限定。
本申请实施例中，第一设备可以通过应用推荐网络，向其连接的连接设备推送目标应用。其中，应用推荐网络是通过应用使用信息集合，对初始应用推荐网络进行训练得到的。应用使用信息集合包括：第一设备连接过的至少一个历史连接设备，以及至少一个历史连接设备上运行过的至少一个历史目标应用对应的至少一个历史目标应用信息。
在一些实施例中，在S108之前，第一设备可以将历史连接过的历史连接设备以及历史连接设备上运行的历史目标应用信息，记录在应用使用信息集合中；利用应用使用信息集合训练得到应用推荐网络。
在一些实施例中，在第一设备利用应用推荐网络，向连接设备推送目标应用之前，对于第一设备上的一次历史设备互联，第一设备可以将历史连接设备以及该历史连接设备上运行的目标应用的目标应用信息，记录为一条应用使用信息。这样，通过至少一次历史设备互联，可以得到包含至少一条应用使用信息的应用使用信息集合。第一设备利用应用使用信息集合，对初始应用推荐网络进行训练，直至满足预设网络训练条件的情况下，得到 应用推荐网络。
在一些实施例中，应用推荐网络可以包含在设备连接网络中，作为设备连接网络的一部分进行训练，也可以是独立的网络模型，具体的根据实际情况进行选择，本申请实施例不作限定。
可以理解的是，本申请实施例中，第一设备不仅可以从多个第二设备中自动决策并确定出场景信息下适用的目标设备进行连接，还可以进一步利用应用推荐网络，对目标设备上可运行的应用进行推荐，如推荐用户打开常用的导航地址，或者推荐用户打开音乐播放软件等等，从而实现了基于目标设备进行应用推荐，为用户使用提供了更大的便利，提高了设备互联使用的用户体验。
下面，结合图7-图8，介绍本申请实施例在实际场景，如车载设备互联场景下的应用。
车载设备互联场景下，上述第一设备可以是车载设备，第二设备可以是移动设备，图7示出了本申请实施例提供的一种车载设备的功能模块框架图，包括通信连接模块700、场景感知模块701、历史信息存储模块702与连接决策模块703。其中，
通信连接模块700，被配置为在车机启动后，实时采集可连接移动设备列表，相当于至少一个第二设备；通信连接模块700还被配置为管理车机和移动设备的通信连接，如连接最优设备、新设备连接检测，或者连接到用户手动切换的其他设备等等。
场景感知模块701，被配置为通过感知第一设备的使用场景下的各维度的影响移动设备选择的影响因子，采集场景信息。场景信息可包括：当前时间信息，如当前时间段，是否假期、星期几、早上、晚上等，以识别出上班、上学、出游等出行意图；移动设备状态信息，如设备电量、是否打开Carlife等车机互联软件，相当于上述的设备状态信息；驾驶员信息：当前主驾驶是哪一位，其移动设备是哪个，相当于上述的操作者信息。
历史信息存储模块702，被配置为存储和调取车机连接过的移动设备的历史连接信息，不仅包含连接了哪些历史移动设备，也即历史第二设备，同时也包含场景感知模块701感知到的多维度的场景信息，相当于上述的至少一个历史场景信息下连接过的至少一个历史第二设备。并基于通信连接模块700检测到的连接设备，将连接设备和连接场景存储在历史连接信息中。
连接决策模块703，被配置为场景感知模块701采集的场景信息输入到全连接神经网络的决策模型，相当于上述的设备连接网络，并综合通信连接模块700的可连接移动设备列表，决策出最优连接的移动设备。根据最优连接的移动设备的实际连接结果和用户反馈， 在线训练和优化决策模型，并在用户手动切换到新移动设备的情况下对设备连接网络进行完全重新训练，从而使得每个车机上的设备连接网络可以形成独特的个性化模型，不断提高设备连接网络进行设备连接预测的准确性。
本申请实施例中，基于图7示出的功能模块框架，车载设备选择移动设备进行连接的过程可以如图8所示，如下：
S801、车机启动。
S802、通信连接模块700采集可连接移动设备列表。
S802与上述S101的过程描述一致，此处不再赘述。
S803、场景感知模块701采集场景信息。
S803与上述S102的过程描述一致，此处不再赘述。
S804、连接决策模块703通过决策模型，根据场景信息，预测至少一个历史移动设备对应的至少一个连接概率。
S804与上述S1031的过程描述一致，此处不再赘述。
S805、连接决策模块703根据至少一个连接概率与可连接移动设备列表，输出最优设备。
S805中，最优设备相当于目标设备。S805的过程与上述S1032描述一致，此处不再赘述。
S806、通信连接模块700连接最优设备。
S806的过程与上述S104描述一致，此处不再赘述。
本申请实施例中，基于图7示出的功能模块框架，车载设备根据用户使用反馈，对决策模型进行进一步训练的过程可以如图9所示，如下：
S807、通信连接模块700检测到用户未切换最优设备并开始使用。
S808、历史信息存储模块702在历史连接信息中存储最优设备与场景信息。
S807-S808中，用户连接成功后未切换设备并开始使用，则历史信息存储模块702存储最优设备与场景信息；进而执行S811。
S809、通信连接模块700检测到用户手动切换，连接并获取目标切换设备。
S810、历史信息存储模块702在历史连接信息中存储目标切换设备与场景信息。
S809-S810中，用户如手动切换到目标切换设备，则通信连接模块700连接至目标切换设备，历史信息存储模块存储目标切换设备和场景信息，进而执行S812或S813。
S807-S808的过程以及S809-S810的过程与上述的S105-S106描述一致，此处不再赘述。
S811、连接决策模块703根据最优设备与场景信息，对决策模块进行增量训练与网络参数更新。
S811中，历史信息存储模块702将最优设备与场景信息输入到连接决策模块703中的在线训练模块进行增量训练，对决策模型的网络参数进行更新与优化。
S812、在目标切换设备属于历史移动设备的情况下，连接决策模块703根据目标切换设备与场景信息，对决策模块进行增量训练。
S812中，在目标切换设备属于历史连接信息中包含的历史移动设备的情况下，历史信息存储模块702将目标切换设备和场景信息输入到在线训练模块进行增量训练，对决策模型的网络参数进行更新与优化。
S813、在目标切换设备不属于历史移动设备的情况下，连接决策模块703获取预设时间段内的至少部分历史连接信息；根据至少部分历史连接信息、目标切换设备与场景信息，对决策模块进行重新训练。
S812中，在目标切换设备不属于历史移动设备的情况下，连接决策模块703调取历史信息存储模块702中，预设时间段内的至少部分历史连接信息，根据至少部分历史连接信息，加上目标切换设备与场景信息，增加新设备增加到模型的输出上，对决策模块进行重新训练。
上述S811-S813的过程以及S809-S810的过程与上述的S107描述一致，此处不再赘述。
需要说明的是，若连接至最优设备后未检测到用户使用，也即未检测到最优设备与车载设备之间产生应用数据交互，则保持车载设备与最优设备的连接。
在一些实施例中，在车载设备连接至最优设备之后，可以将各个移动设备相互连接，以车机连接的最优设备作为主移动设备，通过各移动设备间建立互联网络，使得车机和各个移动设备都可以建立连接，实现车机可同时连接多个移动设备。
可以理解的是，本申请实施例提供的设备连接方法相较于相关技术中根据预设规则选择设备连接的方法，大大提高了方案的扩展性，相较于仅根据用户使用数据进行连接设备预测的方法，充分考虑了设备互联场景下各维度影响因素，并提出采用全连接神经网络进行决策，根据用户使用反馈建立用户个性化模型，不断优化模型效果，模型泛化形成更好，从而提高了预测得到的最优设备的准确性。
本申请还提供一种设备连接装置，应用于第一设备。图10为本申请实施例提供的设备 连接装置的结构示意图；如图10所示，设备连接装置1包括：
确定部分11，被配置为确定与第一设备具备连接条件的至少一个第二设备；
场景采集部分12，被配置为获取场景信息；所述场景信息表征所述第一设备的使用场景；
连接预测部分13，被配置为基于所述场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备；所述历史连接信息包含所述第一设备在至少一个历史场景信息下连接的至少一个历史第二设备；
通信连接部分14，被配置为连接所述目标设备。
在一些实施例中，所述场景采集部分12，还被配置为获取当前时间信息；
以及/或者，通过接收第二设备的广播信息，获取第二设备的设备状态信息；以及/或者，通过对所述第一设备的预设操作位置上采集的操作者图像进行图像识别，得到所述第一设备对应的操作者信息；将所述当前时间信息、所述设备状态信息与所述操作者信息中的至少一个，作为所述场景信息。
在一些实施例中，所述设备状态信息包括：第二设备电量与预设互联软件信息中的至少一种；所述预设互联软件信息为所述第二设备上当前运行的，用于实现设备互联的软件信息。
在一些实施例中，所述连接预测部分13，还被配置为利用设备连接网络，基于所述场景信息进行设备连接预测，确定所述至少一个历史第二设备对应的至少一个连接概率；所述设备连接网络是通过所述历史连接信息对初始设备连接网络进行训练得到的；根据所述至少一个连接概率，从所述至少一个第二设备中确定所述目标设备。
在一些实施例中，所述设备连接装置还包括：训练部分，所述训练部分，被配置为所述连接所述目标设备之后，确定所述第一设备的连接设备；将所述连接设备与所述场景信息作为增量连接信息，记录在所述历史连接信息中；基于所述增量连接信息，对所述设备连接网络进行训练。
在一些实施例中，所述训练部分，还被配置为在所述目标设备与所述第一设备产生应用数据交互的情况下，将所述目标设备作为所述连接设备；在接收到针对所述目标设备的切换指令的情况下，获取所述切换指令指定的目标切换设备进行连接，并将所述目标切换设备确定为所述连接设备。
在一些实施例中，所述训练部分，还被配置为利用所述增量连接信息，对所述设备连 接网络进行增量训练。
在一些实施例中，所述训练部分，还被配置为在所述连接设备不属于所述至少一个历史第二设备的情况下，从所述历史连接信息中获取至少部分信息；结合所述至少部分信息与所述增量连接信息，对所述设备连接网络进行重新训练。
在一些实施例中，所述设备连接装置还包括：应用推荐部分，所述应用推荐部分，被配置为利用应用推荐网络，向所述第一设备的连接设备推送目标应用；所述目标应用用于在所述连接设备上，与所述第一设备进行数据交互；其中，所述应用推荐网络是通过应用使用信息集合，对初始应用推荐网络进行训练得到的；所述应用使用信息集合包括：所述第一设备连接过的至少一个历史连接设备，以及所述至少一个历史连接设备上运行过的至少一个历史目标应用对应的至少一个历史目标应用信息。
在一些实施例中，所述至少一个第二设备包含所述至少一个历史第二设备中的至少部分历史第二设备，所述连接预测部分13，还被配置为根据所述至少部分历史第二设备中，最高连接概率的目标历史第二设备，确定所述目标设备。
在一些实施例中，所述设备连接装置还包括：设备推送部分，所述：设备推送部分，被配置为所述基于所述场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备之后，将所述目标设备的设备信息推送至所述第一设备。
在一些实施例中，所述第一设备包括：车载设备，所述第二设备包括：移动设备，其中，所述预设操作位置包括：所述车载设备所在车辆的主驾驶位置；所述场景信息还包括：日程信息与导航信息中的至少一个。
需要说明的是，以上装置实施例的描述，与上述方法实施例的描述是类似的，具有同方法实施例相似的有益效果。对于本申请装置实施例中未披露的技术细节，请参照本申请方法实施例的描述而理解。
在一些实施例中，本申请实施例还提供一种第一设备，图11为本申请实施例提供的第一设备的一种可选的结构示意图。如图11所示，第一设备2包括：存储器22与处理器23。其中，存储器22和处理器23通过通信总线24连接；存储器22，用于存储可执行指令；处理器23，用于执行存储器22中存储的可执行指令时，实现本申请实施例提供的方法，例如，本申请实施例提供的设备连接方法。
本申请实施例提供一种计算机可读存储介质，存储有可执行设备连接指令，用于引起处理器23执行时，实现本申请实施例提供的方法，例如，本申请实施例提供的设备连接方 法。
在本申请的一些实施例中，存储介质可以是FRAM、ROM、PROM、EPROM、EEPROM、闪存、磁表面存储器、光盘、或CD-ROM等存储器；也可以是包括上述存储器之一或任意组合的各种设备。
在本申请的一些实施例中，可执行设备连接指令可以采用程序、软件、软件模块、脚本或代码的形式，按任意形式的编程语言(包括编译或解释语言，或者声明性或过程性语言)来编写，并且其可按任意形式部署，包括被部署为独立的程序或者被部署为模块、组件、子例程或者适合在计算环境中使用的其它单元。
作为示例，可执行设备连接指令可以但不一定对应于文件系统中的文件，可以可被存储在保存其它程序或数据的文件的一部分，例如，存储在超文本标记语言(HTML，Hyper Text Markup Language)文档中的一个或多个脚本中，存储在专用于所讨论的程序的单个文件中，或者，存储在多个协同文件(例如，存储一个或多个模块、子程序或代码部分的文件)中。
作为示例，可执行设备连接指令可被部署为在一个计算设备上执行，或者在位于一个地点的多个计算设备上执行，又或者，在分布在多个地点且通过通信网络互连的多个计算设备上执行。
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请可采用硬件实施例、软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框 中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
以上所述，仅为本申请的较佳实施例而已，并非用于限定本申请的保护范围。
工业实用性
本申请实施例中，第一设备通过获取场景信息，结合在至少一个历史场景信息下连接过的至少一个历史第二设备的历史连接信息进行预测，可以得到至少一个历史第二设备对应的至少一个预测结果，从而可以根据至少一个预测结果从至少一个第二设备中确定目标设备进行连接。从而在设备互连场景下，能够对影响设备连接的各个维度的场景因素进行感知，实现了将场景信息加入预测过程，提高了预测结果的准确性，进而提高了根据预测结果确定目标设备进行连接的准确性。并且，第一设备可以根据用户对连接设备的选择与反馈进一步优化用于设备连接网络，形成能够根据使用情况逐步优化网络预测准确度的良性循环，随着用户连接数据的不断丰富，设备连接网络预测的准确度也会逐步提高，给用户带来更优质的连接体验。

Claims (15)

  1. 一种设备连接方法，包括：
    确定与第一设备具备连接条件的至少一个第二设备；
    获取场景信息；所述场景信息表征所述第一设备的使用场景；
    基于所述场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备；所述历史连接信息包含所述第一设备在至少一个历史场景信息下连接的至少一个历史第二设备；
    连接所述目标设备。
  2. 根据权利要求1所述的方法，其中，所述获取场景信息，包括：
    获取当前时间信息；
    以及/或者，
    通过接收第二设备的广播信息，获取第二设备的设备状态信息；
    以及/或者，
    通过对所述第一设备的预设操作位置上采集的操作者图像进行图像识别，得到所述第一设备对应的操作者信息；
    将所述当前时间信息、所述设备状态信息与所述操作者信息中的至少一个，作为所述场景信息。
  3. 根据权利要求2所述的方法，其中，所述设备状态信息包括：第二设备电量与预设互联软件信息中的至少一种；所述预设互联软件信息为所述第二设备上当前运行的，用于实现设备互联的软件信息。
  4. 根据权利要求1-3任一项所述的方法，其中，所述基于所述场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备，包括：
    利用设备连接网络，基于所述场景信息进行设备连接预测，确定所述至少一个历史第二设备对应的至少一个连接概率；所述设备连接网络是通过所述历史连接信息对初始设备连接网络进行训练得到的；
    根据所述至少一个连接概率，从所述至少一个第二设备中确定所述目标设备。
  5. 根据权利要求4所述的方法，其中，所述连接所述目标设备之后，所述方法还包括：
    确定所述第一设备的连接设备；
    将所述连接设备与所述场景信息作为增量连接信息，记录在所述历史连接信息中；
    基于所述增量连接信息，对所述设备连接网络进行训练。
  6. 根据权利要求5所述的方法，其中，所述确定所述第一设备的连接设备，包括：
    在所述目标设备与所述第一设备产生应用数据交互的情况下，将所述目标设备作为所述连接设备；
    在接收到针对所述目标设备的切换指令的情况下，获取所述切换指令指定的目标切换设备进行连接，并将所述目标切换设备确定为所述连接设备。
  7. 根据权利要求5所述的方法，其中，所述基于所述增量连接信息，对所述设备连接网络进行训练与更新，包括：
    利用所述增量连接信息，对所述设备连接网络进行增量训练。
  8. 根据权利要求5所述的方法，其中，所述基于所述增量连接信息，对所述设备连接网络进行训练与更新，包括：
    在所述连接设备不属于所述至少一个历史第二设备的情况下，从所述历史连接信息中获取至少部分信息；
    结合所述至少部分信息与所述增量连接信息，对所述设备连接网络进行重新训练。
  9. 根据权利要求1-3中任一项、或5-8中任一项所述的方法，其中，所述方法还包括：
    利用应用推荐网络，向所述第一设备的连接设备推送目标应用；所述目标应用用于在所述连接设备上，与所述第一设备进行数据交互；其中，
    所述应用推荐网络是通过应用使用信息集合，对初始应用推荐网络进行训练得到的；所述应用使用信息集合包括：所述第一设备连接过的至少一个历史连接设备，以及所述至少一个历史连接设备上运行过的至少一个历史目标应用对应的至少一个历史目标应用信息。
  10. 根据权利要求4所述的方法，其中，所述至少一个第二设备包含所述至少一个历史第二设备中的至少部分历史第二设备，所述根据所述至少一个连接概率，从所述至少一个第二设备中确定所述目标设备，包括：
    根据所述至少部分历史第二设备中，最高连接概率的目标历史第二设备，确定所述目标设备。
  11. 根据权利要求2所述的方法，其中，所述第一设备包括：车载设备，所述第二设备包括：移动设备，其中，
    所述预设操作位置包括：所述车载设备所在车辆的主驾驶位置；
    所述场景信息还包括：日程信息与导航信息中的至少一个。
  12. 根据权利要求1-3、5-8、10、11中任一项所述的方法，其中，所述基于所述场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备之后，所述方法还包括：
    将所述目标设备的设备信息推送至所述第一设备。
  13. 一种设备连接装置，包括：
    确定部分，被配置为确定与第一设备具备连接条件的至少一个第二设备；
    场景采集部分，被配置为获取场景信息；所述场景信息表征所述第一设备的使用场景；
    连接预测部分，被配置为基于所述场景信息，结合历史连接信息进行设备连接预测，从所述至少一个第二设备中确定目标设备；所述历史连接信息包含所述第一设备在至少一个历史场景信息下连接的至少一个历史第二设备；
    通信连接模块，被配置为连接所述目标设备。
  14. 一种第一设备，包括：
    存储器，用于存储可执行指令；
    处理器，用于通过执行所述存储器中存储的可执行指令，实现权利要求1至11任一项所述的方法。
  15. 一种计算机可读存储介质，存储有可执行指令，用于引起处理器执行时，实现权利要求1至11任一项所述的方法。
PCT/CN2022/144306 2022-04-20 2022-12-30 设备连接方法、装置、第一设备及计算机可读存储介质 WO2023202161A1 (zh)

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