WO2020168929A1 - 对特定路线上的特定位置进行识别的方法及电子设备 - Google Patents

对特定路线上的特定位置进行识别的方法及电子设备 Download PDF

Info

Publication number
WO2020168929A1
WO2020168929A1 PCT/CN2020/074592 CN2020074592W WO2020168929A1 WO 2020168929 A1 WO2020168929 A1 WO 2020168929A1 CN 2020074592 W CN2020074592 W CN 2020074592W WO 2020168929 A1 WO2020168929 A1 WO 2020168929A1
Authority
WO
WIPO (PCT)
Prior art keywords
electronic device
wireless network
route
specific
information
Prior art date
Application number
PCT/CN2020/074592
Other languages
English (en)
French (fr)
Inventor
杨锐
金辉
窦凤辉
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to EP20758903.7A priority Critical patent/EP3923634B1/en
Priority to US17/432,807 priority patent/US11871328B2/en
Publication of WO2020168929A1 publication Critical patent/WO2020168929A1/zh

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/16—Discovering, processing access restriction or access information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/34—Modification of an existing route
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/18—Selecting a network or a communication service
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/20—Selecting an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/56—Provisioning of proxy services
    • H04L67/568—Storing data temporarily at an intermediate stage, e.g. caching
    • H04L67/5681—Pre-fetching or pre-delivering data based on network characteristics
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/24—Reselection being triggered by specific parameters
    • H04W36/32—Reselection being triggered by specific parameters by location or mobility data, e.g. speed data
    • H04W36/322—Reselection being triggered by specific parameters by location or mobility data, e.g. speed data by location data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • 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

  • This application relates to the field of electronic technology, and in particular to a method for identifying a specific location on a specific route, a method for optimizing terminal performance, and electronic equipment.
  • a good network environment is often required.
  • not all base stations can provide a better network environment for electronic devices.
  • multiple base stations may provide network services for the user, and the multiple base stations may include base stations with good signal quality and base stations with poor signal quality.
  • users pass through a base station with poor signal quality, they may not be able to use network services normally.
  • the present application provides a method and electronic device for identifying a specific location on a specific route.
  • the method can remind users to deal with network abnormalities, so that network abnormalities will not affect user operations and improve user experience.
  • a method for optimizing performance is provided, which is applied to a terminal device.
  • the terminal device saves a specific route determination model.
  • the specific route determination model includes information of multiple specific routes.
  • the method includes: obtaining information of the current route,
  • the current route information includes information about a first wireless network set, the first wireless network set includes a first wireless network and a second wireless network, the communication quality of the first wireless network is greater than the first threshold, and the communication quality of the second wireless network Less than or equal to the first threshold; determine the current route as the first specific route according to the specific route determination model and the information of the current route; perform a first specific action related to the first specific route, the first specific action Including at least one of the following: changing the network search interval; or searching for different network signals according to changes in network standards; or generating a first message when it is determined that the application currently running on the terminal device is the first application.
  • To instruct the terminal device to send a cache request to the server corresponding to the first application, and/or the first message is used
  • the route information refers to the information of the wireless network on the route, such as the information of the base station.
  • This application will take a base station as an example to specifically introduce methods for optimizing terminal performance.
  • the first wireless network corresponds to a normal base station, which is a base station that can provide normal network services for terminal equipment;
  • the second wireless network corresponds to an abnormal base station, which may be a base station that cannot provide network services for terminal equipment.
  • the terminal equipment will be disconnected within the coverage of the abnormal base station, or the download rate will be lower than a certain threshold and/or the business will be stuck.
  • acquiring the information of the current route by the electronic device means acquiring the information of all base stations on the current route or recording the location information of multiple base stations.
  • the information of the base station includes identification information of the base station or cell identification information, which is not limited in this application.
  • the foregoing first wireless network set may include at least one base station, and the at least one base station may correspond to the normal base station and the abnormal base station described in the embodiment.
  • the number of base stations is not limited.
  • the specific route identification method provided in this application can be used to optimize terminal performance.
  • users can be reminded of the network conditions in different ways, or audio and video can be cached in advance to improve user experience.
  • the reminding method may include a dynamic method such as a pop-up window, or a static method such as a configuration switch.
  • the method further includes: displaying a first message on a first interface, where the first interface is the running interface of the game application, and the first message is used for The time at which the terminal device performs a specific action related to the specific route.
  • the method further includes: determining the moment when the terminal device performs a specific action related to the specific route; and executing a specific action related to the specific route according to the terminal device. At the moment of the action, the terminal device sends a cache request to the server corresponding to the audio or video application, and the cache request is used to cache audio data or video data from the server.
  • terminal performance can also be optimized in other ways.
  • optimizing terminal performance may refer to optimizing power consumption of the terminal device.
  • the terminal device can predict the time when the terminal device enters the coverage area of the abnormal base station and the time when it leaves the coverage area of the abnormal base station on the specific route based on the result of specific route identification, so that any of the following can be performed Possible actions:
  • the network search frequency of the terminal device is searched every 2 minutes, and in the coverage area of an abnormal base station, the network search frequency of the terminal device is changed to search every 4 minutes.
  • the power consumption of the terminal equipment is reduced.
  • the time interval for the terminal device to search the network can be shortened, so that the terminal device can start the network search in advance, so as to quickly access the network when it enters the coverage of the normal base station, providing users with a network service.
  • the first time period may refer to the time period between the time when the terminal device enters the coverage area of the abnormal base station and the time when it leaves the coverage area of the abnormal base station. It should be understood that the first time period may not include the time when the terminal device leaves the abnormal base station, or the first time period may include the time when the terminal device leaves the abnormal base station. This application does not limit this.
  • the first period is the period between 8:30:60-8:35:60. Then, the first period does not include the time 08:35:60 when the terminal device leaves the abnormal base station, and the terminal device predicts to enter the normal base station at 8:35:60, the terminal device can start the network search function at 8:35:60. Or start the network search function in the first n seconds of 8:35:60 (for example, 8:35:50). When the terminal device leaves the abnormal base station, it can access other wireless networks, shorten the disconnection time and improve user experience .
  • the first period may also mean that the terminal device does not have wireless network coverage in the process.
  • the duration of the covered area may be
  • the terminal device 8:30:60-8:35:60 is within the coverage of base station A
  • 8:35:60-8:38:60 is within the coverage of no wireless network
  • 8:38:60 -8:40:60 is within the coverage of base station B.
  • the first period refers to 8:35:60-8:38:60.
  • the network search function of the terminal device can be turned off, thereby reducing the power consumption of the terminal device.
  • optimizing terminal performance may also refer to quickly enabling terminal devices to obtain network services.
  • the terminal device when the terminal device enters the coverage area of the abnormal base station and the network is dropped, the terminal device will continuously search the network, for example, search for accessible wireless network (2G/3G/4G) signals.
  • the terminal device can obtain the information of the base station on the specific route according to the result of the identification of the specific route.
  • the terminal device can know what kind of network standard changes will occur. For example, the switching of high and low network standards, from 2G to 3G, or 3G to 4G, or 5G in the future.
  • the terminal equipment can know that base station A provides 4G network for terminal equipment on the specific route, and base station B can only provide 3G network for terminal equipment.
  • the terminal equipment determines that base station A is switched to base station B, it directly searches for 3G network signals. , Instead of searching for network signals provided by other different network standards, such as 2G/4G/5G and other network signals.
  • the terminal device may also predict the time when it enters the coverage area of the abnormal base station from the coverage area of the normal base station and the time it leaves the coverage area of the abnormal base station on the specific route, and the terminal device may know that the normal base station can provide the terminal equipment.
  • abnormal base stations can only provide 2G networks for terminal equipment. Therefore, when the terminal equipment enters the coverage area of the abnormal base station from the normal base station, it directly searches for the 2G network signal that the abnormal base station can provide, and does not need to search for the network signals provided by other different network standards at the same time, such as prohibiting the terminal equipment from searching for 4G/ Network signals under network standards such as 3G/5G networks, so that terminal devices can quickly obtain network services.
  • the method further includes: determining the specific route determination model, each of the plurality of specific routes includes information of the second wireless network set, and The second set of wireless networks includes at least one wireless network.
  • determining the specific route determination model includes: acquiring information about wireless networks included in a second wireless network set on the multiple specific routes; The acquired information of the wireless networks included in the second wireless network set on the multiple specific routes is used to construct a first feature matrix of the multiple specific routes; according to the first feature matrix, the multiple specific routes are classified to obtain The second feature matrix; according to the second feature matrix, determine the specific route decision model.
  • constructing the first feature matrix of the plurality of specific routes includes: calculating any two specific routes of the plurality of specific routes by sliding correlation coefficients.
  • the matching characteristic curve of the route; the first characteristic matrix is constructed according to the matching characteristic curve; wherein the sliding correlation coefficient calculation includes hard decision calculation or soft decision calculation.
  • the method further includes: classifying any one of the plurality of specific routes according to the K nearest neighbor algorithm and the first feature matrix.
  • determining that the current route is the first specific route based on the specific route determination model and the current route information includes: obtaining the specific route determination Information of the wireless networks included in the second wireless network set included on each specific route in the model; determine the information of the wireless networks included in the second wireless network set and the information of the wireless networks included in the first wireless network set When the matching degree of is greater than or equal to the second threshold, it is determined that the current route is the first specific route.
  • acquiring the wireless network information included in the second wireless network set included in the specific route determination model includes: periodically acquiring the second wireless network set Information about the wireless networks included in the wireless network collection.
  • down-sampling is a way to periodically obtain the information of a specific route that has been learned, and at the same time, down-sampling can reduce the amount of calculation of the electronic device.
  • general sampling may be sampling once per second, and down sampling may be sampling once every 2 seconds. Without affecting the recognition accuracy, reducing the sampling frequency can reduce the amount of calculation of the electronic device, thereby reducing power consumption.
  • the information of the wireless network includes identification information of the base station and/or cell identification information.
  • an electronic device including: one or more processors; a memory; a plurality of application programs; and one or more programs, wherein the one or more programs are stored in the memory, when the When one or more programs are executed by the processor, the electronic device is caused to perform the following steps: obtain information of the current route, the information of the current route includes information of the first wireless network set, and the first wireless network set includes the first wireless network And a second wireless network, the communication quality of the first wireless network is greater than a first threshold, and the communication quality of the second wireless network is less than or equal to the first threshold; the current route is determined according to the specific route determination model and the information of the current route The route is a first specific route; a first specific action related to the first specific route is performed, and the first specific action includes at least one of the following: changing the network search interval; or searching for different network signals according to changes in the network standard; Or when it is determined that the application currently running on the terminal device is the first application, a first message is generated, the first message is
  • the electronic device when the one or more programs are executed by the processor, the electronic device is caused to perform the following steps: determine the specific route determination model, and the multiple specific routes Each specific route in includes information of a second wireless network set, and the second wireless network set includes at least one wireless network.
  • the electronic device when the one or more programs are executed by the processor, the electronic device is caused to perform the following steps: obtain the first on the multiple specific routes 2.
  • Information of the wireless networks included in the wireless network set ; construct the first feature matrix of the multiple specific routes according to the acquired information of the wireless networks included in the second wireless network set on the multiple specific routes;
  • the feature matrix is used to classify the multiple specific routes to obtain a second feature matrix; according to the second feature matrix, the specific route determination model is determined.
  • the electronic device when the one or more programs are executed by the processor, the electronic device is caused to perform the following steps: calculating the plurality of programs by sliding correlation coefficients Matching characteristic curves of any two specific routes in a specific route; construct the first characteristic matrix according to the matching characteristic curve; wherein, the sliding correlation coefficient calculation includes hard decision calculation or soft decision calculation.
  • the electronic device when the one or more programs are executed by the processor, the electronic device is caused to perform the following steps: according to the K nearest neighbor algorithm and the first A feature matrix classifies any one of the multiple specific routes.
  • the electronic device when the one or more programs are executed by the processor, the electronic device is caused to perform the following steps: obtain each specific route determination model Information of wireless networks included in the second wireless network set included on a specific route; determining the degree of matching between the information of the wireless networks included in the second wireless network set and the information of the wireless networks included in the first wireless network set When it is greater than or equal to the second threshold, it is determined that the current route is the first specific route.
  • the electronic device when the one or more programs are executed by the processor, the electronic device is caused to perform the following steps: periodically acquiring the second wireless network Information about the wireless networks included in the collection.
  • the information of the wireless network includes identification information of the base station and/or cell identification information.
  • the present application provides a device included in an electronic device, and the device has the function of realizing the behavior of the electronic device in the foregoing aspect and possible implementation manners of the foregoing aspect.
  • the function can be realized by hardware, or by hardware executing corresponding software.
  • the hardware or software includes one or more modules or units corresponding to the above-mentioned functions. For example, display module or unit, detection module or unit, processing module or unit, etc.
  • the present application provides an electronic device, including: a touch display screen, wherein the touch display screen includes a touch-sensitive surface and a display; a camera; one or more processors; one or more memories; and multiple applications ; And one or more computer programs.
  • one or more computer programs are stored in the memory, and the one or more computer programs include instructions.
  • the electronic device is caused to execute the method in any one of the possible implementations of the foregoing aspects.
  • the present application provides an electronic device including one or more processors and one or more memories.
  • the one or more memories are coupled with one or more processors, and the one or more memories are used to store computer program codes.
  • the computer program codes include computer instructions.
  • the electronic device executes A possible implementation method of any of the above aspects.
  • this application provides a computer storage medium, including computer instructions, which when the computer instructions run on an electronic device, cause the electronic device to execute any one of the possible methods in any of the foregoing aspects.
  • the present application provides a computer program product, which when the computer program product runs on an electronic device, causes the electronic device to execute any one of the possible methods in any of the foregoing aspects.
  • FIG. 1 is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the application.
  • FIG. 2 is a schematic diagram of the software structure of an electronic device provided by an embodiment of the application.
  • Fig. 3 is a schematic diagram of an example of route recognition provided by this application.
  • Figure 4 is a schematic diagram of multiple possible application scenarios provided by this application.
  • Fig. 5 is an example of a flow chart of an electronic device identifying a route.
  • Fig. 6 is a schematic diagram of an example route provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of an example of an identification method for starting a specific route provided by an embodiment of the present application.
  • FIG. 8 is a schematic diagram of an algorithm flow chart provided by an embodiment of the present application.
  • FIG. 9 is a schematic diagram of an example of calculation process of sliding correlation coefficient provided by an embodiment of the present application.
  • FIG. 10 is a flowchart of an example of a sliding calculation process provided by an embodiment of the present application.
  • FIG. 11 is a schematic diagram of an example of a characteristic curve provided by an embodiment of the present application.
  • FIG. 12 is a flowchart of another example of a sliding calculation process provided by an embodiment of the present application.
  • FIG. 13 is a flowchart of an example of an autonomous clustering process provided by an embodiment of the present application.
  • FIG. 14 is a flowchart of an example of the KNN clustering process provided by an embodiment of the present application.
  • FIG. 15 is a schematic flowchart of an example of a specific route identification method provided by an embodiment of the present application.
  • FIG. 16 is a schematic flowchart of a method for identifying a specific route provided by an embodiment of the present application.
  • FIG. 17 is a schematic diagram of the composition of a possible electronic device provided by an embodiment of the present application.
  • first and second are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features.
  • the features defined with “first” and “second” may explicitly or implicitly include one or more of these features.
  • the first feature matrix and the second feature matrix in this application are only used to characterize different processing results obtained in different stages of the feature matrix processing.
  • “plurality” means two or more.
  • the embodiment of the application provides a method for identifying a specific location on a specific route, which can be applied to an electronic device or a separate application program, which can realize the identification of a specific location on a specific route in this application Methods.
  • the electronic device can predict the user's daily specific route according to the user's daily behavior habits, and determine the user's daily specific route and information about multiple base stations that the electronic device accesses in the specific route.
  • the electronic device can first predict the time to reach such a base station, and then combine the characteristics of the APP running on the electronic device to send a cache request to the server in advance to prevent the electronic device from accessing the signal.
  • a bad base station may affect the user's use, or inform the user of the time to reach such a base station in the form of a message to remind the user to deal with network abnormalities.
  • the method for identifying a specific location on a specific route provided by the embodiments of this application can be applied to mobile phones, tablets, wearable devices, vehicle-mounted devices, augmented reality (AR)/virtual reality (VR) devices
  • AR augmented reality
  • VR virtual reality
  • electronic devices such as laptops, ultra-mobile personal computers (UMPC), netbooks, and personal digital assistants (PDAs)
  • UMPC ultra-mobile personal computers
  • PDAs personal digital assistants
  • FIG. 1 shows a schematic structural diagram of an electronic device 100.
  • the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, and an antenna 2.
  • Mobile communication module 150 wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, earphone jack 170D, sensor module 180, buttons 190, motor 191, indicator 192, camera 193, display screen 194, and Subscriber identification module (subscriber identification module, SIM) card interface 195, etc.
  • SIM Subscriber identification module
  • the sensor module 180 may include pressure sensor 180A, gyroscope sensor 180B, air pressure sensor 180C, magnetic sensor 180D, acceleration sensor 180E, distance sensor 180F, proximity light sensor 180G, fingerprint sensor 180H, temperature sensor 180J, touch sensor 180K, ambient light Sensor 180L, bone conduction sensor 180M, etc.
  • the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the electronic device 100.
  • the electronic device 100 may include more or fewer components than shown, or combine certain components, or split certain components, or arrange different components.
  • the illustrated components can be implemented in hardware, software, or a combination of software and hardware.
  • the processor 110 may include one or more processing units.
  • the processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), and an image signal processor. (image signal processor, ISP), controller, memory, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural-network processing unit (NPU) Wait.
  • AP application processor
  • modem processor modem processor
  • GPU graphics processing unit
  • image signal processor image signal processor
  • ISP image signal processor
  • controller memory
  • video codec digital signal processor
  • DSP digital signal processor
  • NPU neural-network processing unit
  • the different processing units may be independent devices or integrated in one or more processors.
  • the controller may be the nerve center and command center of the electronic device 100.
  • the controller can generate operation control signals according to the instruction operation code and timing signals to complete the control of fetching and executing instructions.
  • a memory may also be provided in the processor 110 to store instructions and data.
  • the memory in the processor 110 is a cache memory.
  • the memory can store instructions or data that have just been used or recycled by the processor 110. If the processor 110 needs to use the instruction or data again, it can be directly called from the memory. Repeated accesses are avoided, the waiting time of the processor 110 is reduced, and the efficiency of the system is improved.
  • the processor 110 may include one or more interfaces.
  • the interface may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, and a universal asynchronous transmitter (universal asynchronous transmitter) interface.
  • I2C integrated circuit
  • I2S integrated circuit built-in audio
  • PCM pulse code modulation
  • PCM pulse code modulation
  • UART universal asynchronous transmitter
  • MIPI mobile industry processor interface
  • GPIO general-purpose input/output
  • SIM subscriber identity module
  • USB Universal Serial Bus
  • the processor 110 may be used to determine a specific route determination model, and determine which specific route the current route is based on the specific route determination model, so as to predict the location of the base station on the specific route and the connection of the electronic device. Enter the time of multiple base stations included on the specific route.
  • the processor 110 may also be used to determine the type of application currently running on the electronic device, and determine whether it is necessary to request the server to cache audio and video data, and so on.
  • the I2C interface is a two-way synchronous serial bus, including a serial data line (SDA) and a serial clock line (SCL).
  • the processor 110 may include multiple sets of I2C buses.
  • the processor 110 may be coupled to the touch sensor 180K, charger, flash, camera 193, etc. through different I2C bus interfaces.
  • the processor 110 may couple the touch sensor 180K through an I2C interface, so that the processor 110 and the touch sensor 180K communicate through an I2C bus interface to realize the touch function of the electronic device 100.
  • the I2S interface can be used for audio communication.
  • the processor 110 may include multiple sets of I2S buses.
  • the processor 110 may be coupled with the audio module 170 through an I2S bus to realize communication between the processor 110 and the audio module 170.
  • the audio module 170 may transmit audio signals to the wireless communication module 160 through an I2S interface, so as to realize the function of answering calls through a Bluetooth headset.
  • the PCM interface can also be used for audio communication to sample, quantize and encode analog signals.
  • the audio module 170 and the wireless communication module 160 may be coupled through a PCM bus interface.
  • the audio module 170 may also transmit audio signals to the wireless communication module 160 through the PCM interface, so as to realize the function of answering calls through the Bluetooth headset. Both the I2S interface and the PCM interface can be used for audio communication.
  • the UART interface is a universal serial data bus used for asynchronous communication.
  • the bus can be a two-way communication bus. It converts the data to be transmitted between serial communication and parallel communication.
  • the UART interface is generally used to connect the processor 110 and the wireless communication module 160.
  • the processor 110 communicates with the Bluetooth module in the wireless communication module 160 through the UART interface to implement the Bluetooth function.
  • the audio module 170 may transmit audio signals to the wireless communication module 160 through a UART interface, so as to realize the function of playing music through a Bluetooth headset.
  • the MIPI interface can be used to connect the processor 110 with the display screen 194, the camera 193 and other peripheral devices.
  • the MIPI interface includes camera serial interface (camera serial interface, CSI), display serial interface (display serial interface, DSI), etc.
  • the processor 110 and the camera 193 communicate through a CSI interface to implement the shooting function of the electronic device 100.
  • the processor 110 and the display screen 194 communicate through a DSI interface to realize the display function of the electronic device 100.
  • the GPIO interface can be configured through software.
  • the GPIO interface can be configured as a control signal or as a data signal.
  • the GPIO interface can be used to connect the processor 110 with the camera 193, the display screen 194, the wireless communication module 160, the audio module 170, the sensor module 180, and so on.
  • GPIO interface can also be configured as I2C interface, I2S interface, UART interface, MIPI interface, etc.
  • the USB interface 130 is an interface that complies with the USB standard specification, and specifically may be a Mini USB interface, a Micro USB interface, a USB Type C interface, and so on.
  • the USB interface 130 can be used to connect a charger to charge the electronic device 100, and can also be used to transfer data between the electronic device 100 and peripheral devices. It can also be used to connect headphones and play audio through the headphones. This interface can also be used to connect other electronic devices, such as AR devices.
  • the interface connection relationship between the modules illustrated in the embodiment of the present application is merely a schematic description, and does not constitute a structural limitation of the electronic device 100.
  • the electronic device 100 may also adopt different interface connection modes in the foregoing embodiments, or a combination of multiple interface connection modes.
  • the charging management module 140 is used to receive charging input from the charger.
  • the charger can be a wireless charger or a wired charger.
  • the charging management module 140 may receive the charging input of the wired charger through the USB interface 130.
  • the charging management module 140 may receive the wireless charging input through the wireless charging coil of the electronic device 100. While the charging management module 140 charges the battery 142, it can also supply power to the electronic device through the power management module 141.
  • the power management module 141 is used to connect the battery 142, the charging management module 140 and the processor 110.
  • the power management module 141 receives input from the battery 142 and/or the charge management module 140, and supplies power to the processor 110, the internal memory 121, the external memory, the display screen 194, the camera 193, and the wireless communication module 160.
  • the power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle times, and battery health status (leakage, impedance).
  • the power management module 141 may also be provided in the processor 110.
  • the power management module 141 and the charging management module 140 may also be provided in the same device.
  • the wireless communication function of the electronic device 100 can be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor, and the baseband processor.
  • the antenna 1 and the antenna 2 are used to transmit and receive electromagnetic wave signals.
  • Each antenna in the electronic device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization.
  • antenna 1 can be multiplexed as a diversity antenna of a wireless local area network.
  • the antenna can be used in combination with a tuning switch.
  • the mobile communication module 150 can provide a wireless communication solution including 2G/3G/4G/5G and the like applied to the electronic device 100.
  • the mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), etc.
  • the mobile communication module 150 can receive electromagnetic waves by the antenna 1, and perform processing such as filtering, amplifying and transmitting the received electromagnetic waves to the modem processor for demodulation.
  • the mobile communication module 150 can also amplify the signal modulated by the modem processor, and convert it into electromagnetic waves for radiation via the antenna 1.
  • at least part of the functional modules of the mobile communication module 150 may be provided in the processor 110.
  • at least part of the functional modules of the mobile communication module 150 and at least part of the modules of the processor 110 may be provided in the same device.
  • the mobile communication module 150 may send a request message to the server to request the cache.
  • the mobile communication module 110 can also be used to detect base station signals and the like.
  • the modem processor may include a modulator and a demodulator.
  • the modulator is used to modulate the low frequency baseband signal to be sent into a medium and high frequency signal.
  • the demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. Then the demodulator transmits the demodulated low-frequency baseband signal to the baseband processor for processing.
  • the low-frequency baseband signal is processed by the baseband processor and then passed to the application processor.
  • the application processor outputs a sound signal through an audio device (not limited to the speaker 170A, the receiver 170B, etc.), or displays an image or video through the display screen 194.
  • the modem processor may be an independent device.
  • the modem processor may be independent of the processor 110 and be provided in the same device as the mobile communication module 150 or other functional modules.
  • the wireless communication module 160 can provide applications on the electronic device 100 including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), bluetooth (BT), and global navigation satellites.
  • WLAN wireless local area networks
  • BT wireless fidelity
  • GNSS global navigation satellite system
  • FM frequency modulation
  • NFC near field communication technology
  • infrared technology infrared, IR
  • the wireless communication module 160 may be one or more devices integrating at least one communication processing module.
  • the wireless communication module 160 receives electromagnetic waves via the antenna 2, frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110.
  • the wireless communication module 160 can also receive the signal to be sent from the processor 110, perform frequency modulation, amplify it, and convert it into electromagnetic wave radiation via the antenna 2.
  • the antenna 1 of the electronic device 100 is coupled with the mobile communication module 150, and the antenna 2 is coupled with the wireless communication module 160, so that the electronic device 100 can communicate with the network and other devices through wireless communication technology.
  • the wireless communication technologies may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), broadband Code division multiple access (wideband code division multiple access, WCDMA), time-division code division multiple access (TD-SCDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC , FM, and/or IR technology, etc.
  • the GNSS may include global positioning system (GPS), global navigation satellite system (GLONASS), Beidou navigation satellite system (BDS), quasi-zenith satellite system (quasi -zenith satellite system, QZSS) and/or satellite-based augmentation systems (SBAS).
  • GPS global positioning system
  • GLONASS global navigation satellite system
  • BDS Beidou navigation satellite system
  • QZSS quasi-zenith satellite system
  • SBAS satellite-based augmentation systems
  • the electronic device 100 implements a display function through a GPU, a display screen 194, and an application processor.
  • the GPU is a microprocessor for image processing, connected to the display 194 and the application processor.
  • the GPU is used to perform mathematical and geometric calculations for graphics rendering.
  • the processor 110 may include one or more GPUs, which execute program instructions to generate or change display information.
  • the display screen 194 is used to display images, videos, etc.
  • the display screen 194 includes a display panel.
  • the display panel can adopt liquid crystal display (LCD), organic light-emitting diode (OLED), active-matrix organic light-emitting diode or active-matrix organic light-emitting diode (active-matrix organic light-emitting diode).
  • LCD liquid crystal display
  • OLED organic light-emitting diode
  • active-matrix organic light-emitting diode active-matrix organic light-emitting diode
  • AMOLED flexible light-emitting diode (FLED), Miniled, MicroLed, Micro-oLed, quantum dot light-emitting diode (QLED), etc.
  • the electronic device 100 may include one or N display screens 194, and N is a positive integer greater than one.
  • the electronic device 100 can implement a shooting function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, and an application processor.
  • the ISP is used to process the data fed back from the camera 193. For example, when taking a picture, the shutter is opened, the light is transmitted to the photosensitive element of the camera through the lens, the light signal is converted into an electrical signal, and the photosensitive element of the camera transfers the electrical signal to the ISP for processing and is converted into an image visible to the naked eye.
  • ISP can also optimize the image noise, brightness, and skin color. ISP can also optimize the exposure, color temperature and other parameters of the shooting scene.
  • the ISP may be provided in the camera 193.
  • the camera 193 is used to capture still images or videos.
  • the object generates an optical image through the lens and projects it to the photosensitive element.
  • the photosensitive element may be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor.
  • CMOS complementary metal-oxide-semiconductor
  • the photosensitive element converts the optical signal into an electrical signal, and then transmits the electrical signal to the ISP to convert it into a digital image signal.
  • ISP outputs digital image signals to DSP for processing.
  • DSP converts digital image signals into standard RGB, YUV and other formats.
  • the electronic device 100 may include 1 or N cameras 193, and N is a positive integer greater than 1.
  • Digital signal processors are used to process digital signals. In addition to digital image signals, they can also process other digital signals. For example, when the electronic device 100 selects the frequency point, the digital signal processor is used to perform Fourier transform on the energy of the frequency point.
  • Video codecs are used to compress or decompress digital video.
  • the electronic device 100 may support one or more video codecs. In this way, the electronic device 100 can play or record videos in a variety of encoding formats, such as: moving picture experts group (MPEG) 1, MPEG2, MPEG3, MPEG4, and so on.
  • MPEG moving picture experts group
  • NPU is a neural-network (NN) computing processor.
  • NN neural-network
  • the NPU can realize applications such as intelligent cognition of the electronic device 100, such as image recognition, face recognition, voice recognition, text understanding, and so on.
  • the external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100.
  • the external memory card communicates with the processor 110 through the external memory interface 120 to realize the data storage function. For example, save music, video and other files in an external memory card.
  • the internal memory 121 may be used to store computer executable program code, where the executable program code includes instructions.
  • the processor 110 executes various functional applications and data processing of the electronic device 100 by running instructions stored in the internal memory 121.
  • the internal memory 121 may include a storage program area and a storage data area.
  • the storage program area can store an operating system, at least one application program (such as a sound playback function, an image playback function, etc.) required by at least one function.
  • the data storage area can store data (such as audio data, phone book, etc.) created during the use of the electronic device 100.
  • the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, a universal flash storage (UFS), etc.
  • UFS universal flash storage
  • the electronic device 100 can implement audio functions through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the earphone interface 170D, and the application processor. For example, music playback, recording, etc.
  • the audio module 170 is used to convert digital audio information into an analog audio signal for output, and is also used to convert an analog audio input into a digital audio signal.
  • the audio module 170 can also be used to encode and decode audio signals.
  • the audio module 170 may be provided in the processor 110, or part of the functional modules of the audio module 170 may be provided in the processor 110.
  • the speaker 170A also called a “speaker” is used to convert audio electrical signals into sound signals.
  • the electronic device 100 can listen to music through the speaker 170A, or listen to a hands-free call.
  • the receiver 170B also called “earpiece” is used to convert audio electrical signals into sound signals.
  • the electronic device 100 answers a call or voice message, it can receive the voice by bringing the receiver 170B close to the human ear.
  • the microphone 170C also called “microphone”, “microphone”, is used to convert sound signals into electrical signals.
  • the user can approach the microphone 170C through the mouth to make a sound, and input the sound signal to the microphone 170C.
  • the electronic device 100 may be provided with at least one microphone 170C. In other embodiments, the electronic device 100 may be provided with two microphones 170C, which can implement noise reduction functions in addition to collecting sound signals. In some other embodiments, the electronic device 100 can also be provided with three, four or more microphones 170C to collect sound signals, reduce noise, identify sound sources, and realize directional recording functions.
  • the earphone interface 170D is used to connect wired earphones.
  • the earphone interface 170D may be a USB interface 130, or a 3.5mm open mobile terminal platform (OMTP) standard interface, or a cellular telecommunications industry association (cellular telecommunications industry association of the USA, CTIA) standard interface.
  • OMTP open mobile terminal platform
  • CTIA cellular telecommunications industry association
  • the pressure sensor 180A is used to sense the pressure signal and can convert the pressure signal into an electrical signal.
  • the pressure sensor 180A may be provided on the display screen 194.
  • the capacitive pressure sensor may include at least two parallel plates with conductive material. When a force is applied to the pressure sensor 180A, the capacitance between the electrodes changes.
  • the electronic device 100 determines the intensity of the pressure according to the change in capacitance.
  • the electronic device 100 detects the intensity of the touch operation according to the pressure sensor 180A.
  • the electronic device 100 may also calculate the touched position according to the detection signal of the pressure sensor 180A.
  • touch operations that act on the same touch location but have different touch operation strengths may correspond to different operation instructions. For example: when a touch operation whose intensity of the touch operation is less than the first pressure threshold is applied to the short message application icon, an instruction to view the short message is executed. When a touch operation with a touch operation intensity greater than or equal to the first pressure threshold acts on the short message application icon, an instruction to create a new short message is executed.
  • the gyro sensor 180B may be used to determine the movement posture of the electronic device 100.
  • the angular velocity of the electronic device 100 around three axes ie, x, y, and z axes
  • the gyro sensor 180B can be used for image stabilization.
  • the gyro sensor 180B detects the shake angle of the electronic device 100, calculates the distance that the lens module needs to compensate according to the angle, and allows the lens to counteract the shake of the electronic device 100 through reverse movement to achieve anti-shake.
  • the gyro sensor 180B can also be used for navigation and somatosensory game scenes.
  • the air pressure sensor 180C is used to measure air pressure.
  • the electronic device 100 calculates the altitude based on the air pressure value measured by the air pressure sensor 180C to assist positioning and navigation.
  • the magnetic sensor 180D includes a Hall sensor.
  • the electronic device 100 can use the magnetic sensor 180D to detect the opening and closing of the flip holster.
  • the electronic device 100 can detect the opening and closing of the flip according to the magnetic sensor 180D.
  • features such as automatic unlocking of the flip cover are set.
  • the acceleration sensor 180E can detect the magnitude of the acceleration of the electronic device 100 in various directions (generally three axes). When the electronic device 100 is stationary, the magnitude and direction of gravity can be detected. It can also be used to identify the posture of electronic devices, and used in applications such as horizontal and vertical screen switching, pedometers and so on.
  • the electronic device 100 can measure the distance by infrared or laser. In some embodiments, when shooting a scene, the electronic device 100 can use the distance sensor 180F to measure the distance to achieve fast focusing.
  • the proximity light sensor 180G may include, for example, a light emitting diode (LED) and a light detector such as a photodiode.
  • the light emitting diode may be an infrared light emitting diode.
  • the electronic device 100 emits infrared light to the outside through the light emitting diode.
  • the electronic device 100 uses a photodiode to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it can be determined that there is an object near the electronic device 100. When insufficient reflected light is detected, the electronic device 100 can determine that there is no object near the electronic device 100.
  • the electronic device 100 can use the proximity light sensor 180G to detect that the user holds the electronic device 100 close to the ear to talk, so as to automatically turn off the screen to save power.
  • the proximity light sensor 180G can also be used in leather case mode, and the pocket mode will automatically unlock and lock the screen.
  • the ambient light sensor 180L is used to sense the brightness of the ambient light.
  • the electronic device 100 can adaptively adjust the brightness of the display screen 194 according to the perceived brightness of the ambient light.
  • the ambient light sensor 180L can also be used to automatically adjust the white balance when taking pictures.
  • the ambient light sensor 180L can also cooperate with the proximity light sensor 180G to detect whether the electronic device 100 is in the pocket to prevent accidental touch.
  • the fingerprint sensor 180H is used to collect fingerprints.
  • the electronic device 100 can use the collected fingerprint characteristics to realize fingerprint unlocking, access application locks, fingerprint photographs, fingerprint answering calls, etc.
  • the temperature sensor 180J is used to detect temperature.
  • the electronic device 100 uses the temperature detected by the temperature sensor 180J to execute a temperature processing strategy. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold value, the electronic device 100 executes to reduce the performance of the processor located near the temperature sensor 180J, so as to reduce power consumption and implement thermal protection.
  • the electronic device 100 when the temperature is lower than another threshold, the electronic device 100 heats the battery 142 to avoid abnormal shutdown of the electronic device 100 due to low temperature.
  • the electronic device 100 boosts the output voltage of the battery 142 to avoid abnormal shutdown caused by low temperature.
  • Touch sensor 180K also called “touch panel”.
  • the touch sensor 180K may be disposed on the display screen 194, and the touch screen is composed of the touch sensor 180K and the display screen 194, which is also called a “touch screen”.
  • the touch sensor 180K is used to detect touch operations applied on or near it.
  • the touch sensor can pass the detected touch operation to the application processor to determine the type of touch event.
  • the visual output related to the touch operation can be provided through the display screen 194.
  • the touch sensor 180K may also be disposed on the surface of the electronic device 100, which is different from the position of the display screen 194.
  • the bone conduction sensor 180M can acquire vibration signals.
  • the bone conduction sensor 180M can obtain the vibration signal of the vibrating bone mass of the human voice.
  • the bone conduction sensor 180M can also contact the human pulse and receive the blood pressure pulse signal.
  • the bone conduction sensor 180M may also be provided in the earphone, combined with the bone conduction earphone.
  • the audio module 170 can parse the voice signal based on the vibration signal of the vibrating bone block of the voice obtained by the bone conduction sensor 180M, and realize the voice function.
  • the application processor may analyze the heart rate information based on the blood pressure beat signal obtained by the bone conduction sensor 180M, and realize the heart rate detection function.
  • the button 190 includes a power button, a volume button, and so on.
  • the button 190 may be a mechanical button. It can also be a touch button.
  • the electronic device 100 may receive key input, and generate key signal input related to user settings and function control of the electronic device 100.
  • the motor 191 can generate vibration prompts.
  • the motor 191 can be used for incoming call vibration notification, and can also be used for touch vibration feedback.
  • touch operations applied to different applications can correspond to different vibration feedback effects.
  • Acting on touch operations in different areas of the display screen 194, the motor 191 can also correspond to different vibration feedback effects.
  • Different application scenarios for example: time reminding, receiving information, alarm clock, games, etc.
  • the touch vibration feedback effect can also support customization.
  • the indicator 192 may be an indicator light, which may be used to indicate the charging status, power change, or to indicate messages, missed calls, notifications, and so on.
  • the SIM card interface 195 is used to connect to the SIM card.
  • the SIM card can be inserted into the SIM card interface 195 or pulled out from the SIM card interface 195 to achieve contact and separation with the electronic device 100.
  • the electronic device 100 may support 1 or N SIM card interfaces, and N is a positive integer greater than 1.
  • the SIM card interface 195 can support Nano SIM cards, Micro SIM cards, SIM cards, etc.
  • the same SIM card interface 195 can insert multiple cards at the same time. The types of the multiple cards can be the same or different.
  • the SIM card interface 195 can also be compatible with different types of SIM cards.
  • the SIM card interface 195 may also be compatible with external memory cards.
  • the electronic device 100 interacts with the network through the SIM card to implement functions such as call and data communication.
  • the electronic device 100 adopts an eSIM, that is, an embedded SIM card.
  • the eSIM card can be embedded in the electronic device 100 and cannot be separated from the electronic device 100.
  • the software system of the electronic device 100 may adopt a layered architecture, an event-driven architecture, a microkernel architecture, a microservice architecture, or a cloud architecture.
  • the embodiment of the present application takes a layered Android system as an example to illustrate the software structure of the electronic device 100.
  • FIG. 2 is a block diagram of the software structure of the electronic device 100 according to an embodiment of the present application.
  • the layered architecture divides the software into several layers, and each layer has a clear role and division of labor. Communication between layers through software interface.
  • the Android system is divided into four layers, from top to bottom, the application layer, the application framework layer, the Android runtime and system library, and the kernel layer.
  • the application layer can include a series of application packages.
  • the application package can include applications such as camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, short message, etc.
  • the application framework layer provides application programming interfaces (application programming interface, API) and programming frameworks for applications in the application layer.
  • the application framework layer includes some predefined functions.
  • the application framework layer can include a window manager, a content provider, a view system, a phone manager, a resource manager, and a notification manager.
  • the window manager is used to manage window programs.
  • the window manager can obtain the size of the display, determine whether there is a status bar, lock the screen, take a screenshot, etc.
  • the content provider is used to store and retrieve data and make these data accessible to applications.
  • the data may include video, image, audio, phone calls made and received, browsing history and bookmarks, phone book, etc.
  • the view system includes visual controls, such as controls that display text and controls that display pictures.
  • the view system can be used to build applications.
  • the display interface can be composed of one or more views.
  • a display interface that includes a short message notification icon may include a view that displays text and a view that displays pictures.
  • the phone manager is used to provide the communication function of the electronic device 100. For example, the management of the call status (including connecting, hanging up, etc.).
  • the resource manager provides various resources for the application, such as localized strings, icons, pictures, layout files, video files, etc.
  • the notification manager enables the application to display notification information in the status bar, which can be used to convey notification-type messages, and it can disappear automatically after a short stay without user interaction.
  • the notification manager is used to notify the download completion, message reminder, etc.
  • the notification manager can also be a notification that appears in the status bar at the top of the system in the form of a chart or scroll bar text, such as a notification of an application running in the background, or a notification that appears on the screen in the form of a dialog window. For example, text messages are prompted in the status bar, prompt sounds, electronic devices vibrate, and indicator lights flash.
  • the electronic device first determines the time to access the abnormal base station, and then can display the time of accessing the abnormal base station in the form of notification information in the status bar to remind the user to deal with network abnormalities and other situations.
  • Android runtime includes core libraries and virtual machines. Android runtime is responsible for the scheduling and management of the Android system.
  • the core library consists of two parts: one part is the function functions that the java language needs to call, and the other part is the core library of Android.
  • the application layer and the application framework layer run in a virtual machine.
  • the virtual machine executes the java files of the application layer and the application framework layer as binary files.
  • the virtual machine is used to perform functions such as object life cycle management, stack management, thread management, security and exception management, and garbage collection.
  • the system library can include multiple functional modules. For example: surface manager (surface manager), media library (media libraries), 3D graphics processing library (for example: OpenGL ES), 2D graphics engine (for example: SGL), etc.
  • surface manager surface manager
  • media library media libraries
  • 3D graphics processing library for example: OpenGL ES
  • 2D graphics engine for example: SGL
  • the surface manager is used to manage the display subsystem and provides a combination of 2D and 3D layers for multiple applications.
  • the media library supports playback and recording of a variety of commonly used audio and video formats, as well as still image files.
  • the media library can support multiple audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.
  • the 3D graphics processing library is used to realize 3D graphics drawing, image rendering, synthesis, and layer processing.
  • the 2D graphics engine is a drawing engine for 2D drawing.
  • the kernel layer is the layer between hardware and software.
  • the kernel layer contains at least display driver, camera driver, audio driver, and sensor driver.
  • FIG. 3 is a schematic diagram of an example of specific route identification provided by this application.
  • the route from home to company includes 6 different base stations, such as the base stations shown by the small triangles in the figure.
  • the base stations 1, 3, 4, and 6 shown by the small white triangles are normal base stations.
  • the electronic equipment can normally access the base station, and the base station can provide network services for the user;
  • the small black triangles show Base stations 2 and 5 are abnormal base stations.
  • the electronic device cannot access the base station normally, and the network is disconnected or the network signal is weak, and the network service is abnormal.
  • the user cannot normally use the online service of a certain application, for example, using online applications such as online audio and online video.
  • electronic equipment can predict the user’s daily specific route based on the user’s daily behavior and habits, and determine the user’s daily specific route and the specific route that the electronic device accesses.
  • Information for multiple base stations When there is a base station with poor signal in a specific daily route, the electronic device can first predict the time to reach such a base station, and then combine the characteristics of the APP running on the electronic device to send a cache request to the server in advance to prevent the electronic device from accessing the signal.
  • a bad base station may affect the user's use, or inform the user of the time to reach such a base station in the form of a message to remind the user to deal with network abnormalities.
  • the foregoing process may include the following steps: S301, the electronic device predicts the time to access the abnormal base station; S302, the electronic device sends a request to the server before the time to access the abnormal base station arrives for buffering data in advance.
  • audio and video applications are taken as examples to introduce a mechanism for an electronic device to predict a user's route and cache data in advance.
  • the display interface of the electronic device in Figure 3 is a schematic diagram of a possible display interface during audio playback.
  • the electronic device can also run other applications, such as video and other applications that need to cache data, or other online applications Types of.
  • the electronic device can predict the user's route, and predict the time to access the abnormal base station in the route, and send a request to the server in advance to buffer audio data or video data before the time arrives.
  • the electronic device accesses the abnormal base station, the audio or video data buffered in advance is available for the user to use, so that the network abnormality will not affect the user's operation, and this method can improve the user experience.
  • the interface of the electronic device shown in FIG. 3 is an audio playback interface, which is used to indicate that the electronic device is currently playing an audio file.
  • the user starts from home. Within the coverage area of base station 1, the electronic device predicts that the specific route selected by the user is the route from home to company. During this period, it will access abnormal base station 2 and base station 5, and determine to access abnormal base station 2 and base station 5. time. Before reaching the coverage area of the base station 2, the electronic device sends a request to the server for buffering more audio data.
  • the aforementioned mechanism for predicting routes and network conditions in advance may also be applied to other application scenarios.
  • FIG. 4 is a schematic diagram of multiple possible application scenarios provided by this application. Specifically, (a) in FIG. 4 shows a schematic diagram of a scene in which an electronic device runs a game application.
  • the electronic device predicts the time to access a base station with poor communication quality on the specific route based on the user’s current travel speed, and generates a message in advance to inform the user that the network will be in a certain period of time Then it becomes worse, so that the user can take corresponding countermeasures.
  • the message can remind the user in the form of a message pop-up window 401 shown in Figure (a).
  • the content of the message pop-up window 401 can be: "The network quality is poor in 10 minutes", etc., or more used to remind the user that the network quality has deteriorated This application does not limit the content of the message pop-up window.
  • the notification message can be changed accordingly.
  • the user starts to be in driving mode, and the electronic device reminds the user "the network quality is poor in 10 minutes" at 08:30.
  • the electronic device determines that the user is in walking mode and the time to access a base station with poor communication quality From the original prediction of 08:40 to 8:55, the notification message can be changed to "Poor network quality after 20 minutes" and displayed again in the form of a message pop-up window.
  • the electronic device predicts the time to access a base station with poor communication quality on the specific route, and the electronic device can send a request to the server , Request to cache video data, and more cache progress can be displayed on the playback progress bar in the video display interface.
  • the black solid line is the content of the movie that the user has watched, and the black solid dot is used to indicate the current playback position.
  • the cache progress of the movie can reach the position shown by the hollow circle.
  • the duration between the playback position identified by the black solid dot and the playback position identified by the hollow circle is greater than or equal to the time from the current moment to the moment when the user leaves the coverage area of the abnormal base station duration. This ensures that when a user accesses an abnormal base station, it will not affect the user's online video viewing.
  • the electronic device may also generate a message in advance, such as a message pop-up window 402, and the content of the message pop-up window 402 is used to notify the user that the network will deteriorate after a certain period of time, so that the user can take corresponding countermeasures.
  • a message pop-up window 402 is used to notify the user that the network will deteriorate after a certain period of time, so that the user can take corresponding countermeasures. This application does not limit this.
  • the specific route recognition method provided in this application can be used to optimize terminal performance. Combining the two application scenarios listed in Figure 4, in the process of executing different user services, remind users of the network conditions in different ways, or buffer audio and video in advance, etc. Improve user experience. Among them, the reminding method may include a dynamic method such as a pop-up window, or a static method such as a configuration switch. In addition, in other application scenarios, terminal performance can also be optimized in other ways.
  • optimizing terminal performance may refer to optimizing power consumption of the terminal device.
  • the terminal device can predict the time when the terminal device enters the coverage area of the abnormal base station and the time when it leaves the coverage area of the abnormal base station on the specific route based on the result of specific route identification, so that any of the following can be performed Possible actions:
  • the network search frequency of the terminal device is searched every 2 minutes, and in the coverage area of an abnormal base station, the network search frequency of the terminal device is changed to search every 4 minutes.
  • the power consumption of the terminal equipment is reduced.
  • the time interval for the terminal device to search the network can be shortened, so that the terminal device can start the network search in advance, so as to quickly access the network when it enters the coverage of the normal base station, providing users with a network service.
  • the first time period may refer to the time period between the time when the terminal device enters the coverage area of the abnormal base station and the time when it leaves the coverage area of the abnormal base station. It should be understood that the first time period may not include the time when the terminal device leaves the abnormal base station, or the first time period may include the time when the terminal device leaves the abnormal base station. This application does not limit this.
  • the first period is the period between 8:30:60-8:35:60. Then, the first period does not include the time 08:35:60 when the terminal device leaves the abnormal base station, and the terminal device predicts to enter the normal base station at 8:35:60, the terminal device can start the network search function at 8:35:60. Or start the network search function in the first n seconds of 8:35:60 (for example, 8:35:50). When the terminal device leaves the abnormal base station, it can access other wireless networks, shorten the disconnection time and improve user experience .
  • the first period may also mean that the terminal device does not have wireless network coverage in the process.
  • the duration of the covered area may be
  • the terminal device 8:30:60-8:35:60 is within the coverage of base station A
  • 8:35:60-8:38:60 is within the coverage of no wireless network
  • 8:38:60 -8:40:60 is within the coverage of base station B.
  • the first period refers to 8:35:60-8:38:60.
  • the network search function of the terminal device can be turned off, thereby reducing the power consumption of the terminal device.
  • optimizing terminal performance may also refer to quickly enabling terminal devices to obtain network services.
  • the terminal device when the terminal device enters the coverage area of the abnormal base station and the network is dropped, the terminal device will continuously search the network, for example, search for accessible wireless network (2G/3G/4G) signals.
  • the terminal device can obtain the information of the base station on the specific route according to the result of the identification of the specific route.
  • the terminal device can know what kind of network standard changes will occur. For example, the switching of high and low network standards, from 2G to 3G, or 3G to 4G, or 5G in the future.
  • the terminal equipment can know that base station A provides 4G network for terminal equipment on the specific route, and base station B can only provide 3G network for terminal equipment.
  • the terminal equipment determines that base station A is switched to base station B, it directly searches for 3G network signals. , Instead of searching for network signals provided by other different network standards, such as 2G/4G/5G and other network signals.
  • the terminal device may also predict the time when it enters the coverage area of the abnormal base station from the coverage area of the normal base station and the time it leaves the coverage area of the abnormal base station on the specific route, and the terminal device may know that the normal base station can provide the terminal equipment.
  • abnormal base stations can only provide 2G networks for terminal equipment. Therefore, when a terminal device enters the coverage area of an abnormal base station from a normal base station, it directly searches for the 2G network signal that the abnormal base station can provide, and does not need to search for network signals provided by other different network standards at the same time, such as prohibiting the terminal device from searching for 4G/ Network signals under network standards such as 3G/5G, so that terminal devices can quickly obtain network services.
  • the electronic device first needs to accurately predict the specific route the user will take. In the process of determining the route of the user, the electronic device needs to learn the specific route information that the user passes through, and recognize the route where the current user is located, so as to select a corresponding prediction model for the route.
  • FIG. 5 is an example of a flow chart of an electronic device identifying a route.
  • the scene is judged according to the time information of the electronic device accessing the base station, which is mainly divided into the base station near the home and the base station near the company.
  • Figure 5 (a) is a process for the electronic device to determine a base station near the home, and (b) is a process for the electronic device to determine a base station near the company.
  • the electronic device identifies the base station connected for a long time at night as the base station near home, and records the time stamp information of the base station near the home at night; the base station connected for a long time during the day is identified as the base station near the company.
  • the device records the time stamp information of the base stations near the access company during the day. Therefore, the electronic device can determine the route to and from get off work based on the timestamp information and combined with the information of the base station, and identify the route that leaves the base station near home during the day as the work route, and the route that leaves the base station near the company at night as the off-get off work route.
  • Fig. 6 is a schematic diagram of an example route provided by an embodiment of the present application. As shown in Figure 6, taking the route between the user's home, company, and the most frequent shopping mall as an example, there may be multiple routes or different round-trip routes. For different multiple routes, the base stations passing by each route are different, and the distribution of abnormal base stations and normal base stations is also different. In the above method of identifying routes based on timestamp information, the electronic device can only identify base stations near home and base stations near the company, and cannot accurately identify the route from home to company or the route from company to home.
  • This method can only roughly estimate that the user is on the way to or from get off work based on time information, and cannot accurately determine the user's route and whether there is a base station with poor communication quality in the estimated route.
  • This method has the problems of poor robustness and sensitivity, such as the limited types of recognized routes, and the inability to recognize turn-back routes.
  • GPS positioning method can use satellites with known positions to calculate the current position through the GPS receiver of the electronic device.
  • the WI-FI network positioning method mainly uses the physical address information of WI-FI to calculate the position information of the electronic device through the triangulation method or the fingerprint positioning method.
  • GPS global positioning system
  • Wi-Fi wireless fidelity
  • the present application provides a method for identifying a specific location on a specific route, which can realize the classification and recognition of the specific route, realize the route recognition in real time and with high accuracy, and meet the requirements of low power consumption.
  • the specific location on the specific route mentioned in this application may refer to the locations of multiple base stations included on the specific route.
  • the method for identifying a specific route provided in this application can be activated through a setting application.
  • FIG. 7 is a schematic diagram of an example of an identification method for starting a specific route provided by an embodiment of the present application.
  • the screen display system of the mobile phone displays a current possible interface content
  • the interface content is the main interface 701 of the mobile phone.
  • the main interface 701 can display a variety of third-party applications (applications, App), such as Alipay, task card store, Weibo, settings, WeChat, card package, photo album, camera, etc. It should be understood that the interface content 701 may also include other more application programs, which is not limited in this application.
  • the user performs the click operation on the setting application shown in (a).
  • the mobile phone enters the main interface 702 of the setting application, and the main interface 702 of the setting application can display as shown in Fig. 7(b) content.
  • the interface 702 may specifically include flight mode setting controls, Wi-Fi setting controls, Bluetooth controls, personal hotspot controls, mobile network controls, battery controls, display and brightness setting controls, Huawei account controls, sound setting controls, privacy controls, and the like. It should be understood that the main interface 702 of the setting application may also include other more or less display content, which is not limited in this application.
  • the desktop and wallpaper setting interface 703 includes a local theme setting control, a local wallpaper setting control, a local lock screen setting control, a local font setting control, and a smart assistant control.
  • the user performs the opening operation of the smart assistant control shown in (c), and in response to the opening operation, the mobile phone starts the smart assistant, as shown in (d), the smart assistant has been opened.
  • the mobile phone activates the specific route recognition function provided in the embodiment of the present application.
  • the smart assistant may also include more other functions, or there may be other possible shortcuts for starting the specific route recognition function, for example, starting by setting options of the application running on the electronic device.
  • the electronic device runs a video playback application, it can be activated through a setting option of the video playback application, which is not limited in this application.
  • the specific route identification method provided in this application can be activated by default, that is, when it is monitored that the user’s current route may be one of the multiple specific routes recorded by the electronic device and the When there is an abnormal base station on a specific route, detect the application currently running on the electronic device, and when it is determined to run an audio application, request a cache from the server in advance, or remind the user to access the abnormal base station by means of a message notification when the user is running an application such as a game At any time, so that users can make other preparations to prevent adverse effects caused by abnormal base station disconnection. When it is detected that the current route of the user is not any of the multiple specific routes recorded by the electronic device, the electronic device does not take subsequent operations such as requesting buffering or generating a time reminder message for access to an abnormal base station.
  • the method may include two stages: a learning stage and a prediction stage.
  • the learning phase mainly calculates related matching features based on the route information collected by electronic devices, constructs the matching feature matrix of the learning database, searches for initial autonomous clustering points, and uses the K-nearest neighbor (KNN) algorithm to return Classify multiple specific route information.
  • the prediction phase mainly performs down-sampling operations based on the data records completed by clustering, and matches with the base station sequence read in real time, and uses the route with the highest matching degree in the classification set as the predicted output to realize route recognition.
  • the electronic device After outputting the predicted specific route, the electronic device can obtain the communication status of the base station on the specific route, and predict the time when the user arrives at the base station with poor network quality. The electronic device then determines whether it needs to send a request to the server in advance to request more data cache according to the currently running application.
  • the specific route identification method provided by this application, the specific implementation process and algorithm principle will be introduced below.
  • the electronic device can collect multiple specific route information, for example, record information of all base stations on multiple routes or record the locations of multiple points.
  • the electronic device obtains a feature matrix for each specific route by calculating the sliding correlation coefficient, and classifies each specific route according to the feature matrix to classify multiple specific routes.
  • the method flow in the learning phase can be performed offline or online.
  • the electronic device can periodically perform route learning. For example, for the route from the user's home to the company, the electronic device learns once every 10 days to update the information in the route database to improve the accuracy of route recognition. This application does not limit this.
  • Feature extraction is to find the most effective features from the original features, and obtain a set of features with obvious physical or statistical significance through feature conversion.
  • the process of feature extraction needs to obtain the original data first, and transform the original data into training data of the model.
  • the feature extraction process of a specific route is a process of obtaining information of multiple base stations included in the specific route, and converting the obtained information of the base stations into a feature matrix.
  • the construction of the feature matrix is the process of constructing the mapping matrix with the feature vectors corresponding to the first N largest feature values of the original data covariance matrix, and then performing related processing on the feature matrix.
  • it can specifically include two parts: calculating route cell matching features and constructing route matching feature matrix.
  • FIG. 8 is a schematic diagram of an algorithm flow chart provided by an embodiment of the present application.
  • the specific processing flow includes: S801, sliding correlation coefficient to calculate the matching characteristic curve of any two base station records; S802, detecting the correlation peak as the matching characteristic of the two records; S803, constructing the matching characteristic of the learning database Matrix; S804, return the characteristic matrix.
  • S801 and S802 are the process of calculating the matching feature of the route cell
  • S803 is the process of constructing the route matching feature matrix.
  • FIG. 9 is a schematic diagram of a calculation process of a sliding correlation coefficient provided by an embodiment of the present application.
  • S801 first slide the matching characteristic curves recorded by any two base stations, as shown in the schematic diagram of FIG. 9, for the two routes, record them as route 1 and route 2, respectively.
  • Route 1 includes five base stations A1 to E1
  • route 2 includes five base stations A2 to E2.
  • each base station information of route 1 is used to match each base station information of route 2.
  • slide 1 means that route 2 and route 1 slide once, and calculate the matching degree between the A1 base station of route 1 and the E2 base station of route 2; similarly, slide 2 means that route 2 and route 1 slide twice to calculate route 1.
  • the degree of matching between the A1 base station and the D2 base station of route 2, the B1 base station of route 1 and the E2 base station of route 2; slide 5 means that route 2 and route 1 slide five times, calculate the A1 base station of route 1 and the A2 base station of route 2, The matching degree between the B1 base station of route 1 and the B2 base station of route 2, the C1 base station of route 1 and the C2 base station of route 2, the D1 base station of route 1 and the D2 base station of route 2, the E1 base station of route 1 and the E2 base station of route 2 ; Sliding 8 means that route 2 and route 1 slide eight times, and calculate the matching degree between route 1 D1 base station and route 2 A2 base station, route 1 E1 base station and route 2 B2 base station.
  • the characteristics of the base station in route 1 are used to match the characteristics of the base station in route 2. If the matching degree of the characteristics of the base station in route 1 and the characteristic of the base station in route 2 is greater than or equal to the first threshold TH, Then it is judged that the base station in route 1 and the base station of route 2 are the same base station, which is recorded as 1; if the characteristics of A1 and A2 match below the first threshold TH, it is judged that A1 and A2 are not the same base station, recorded as 0 , And so on to calculate the degree of matching between each base station in the two routes.
  • FIG. 10 is a flowchart of an example of a sliding calculation process provided by an embodiment of the present application.
  • the calculation of the sliding correlation coefficient can adopt a correlation calculation method based on hard decision, where the hard decision rule is the identification ID (identification) of two base stations or the cell identification (CID) under the base station. If they are the same, the statistical information is accumulated by 1, otherwise it is not accumulated.
  • the hard decision rule is the identification ID (identification) of two base stations or the cell identification (CID) under the base station. If they are the same, the statistical information is accumulated by 1, otherwise it is not accumulated.
  • any two collected and recorded route sequences which are the A sequence corresponding to route 1 and the B sequence corresponding to route 2, when the A sequence
  • add 1 to the sum otherwise the sum remains unchanged, and then normalize the sum by dividing the number of comparisons to obtain the correlation coefficient.
  • shift the B sequence and calculate the correlation coefficient again. The calculation process until the B sequence shift reaches the maximum value. When the number of slides reaches the maximum number of times, the sequence reaches the maximum shift.
  • each shift corresponds to a sum value.
  • a summation sequence is obtained, as shown in Table 1 below. The sequence is normalized to obtain the corresponding correlation coefficient, that is, the correlation coefficient between each base station of route 1 and each base station of route 2 is calculated.
  • FIG. 11 is a schematic diagram of an example of a characteristic curve provided by an embodiment of the present application. Among them, the horizontal axis of the characteristic curve in FIG. 11 is the sampling point offset value, and the vertical axis is the obtained correlation coefficient.
  • the correlation peak is detected as the matching characteristic of the two records, and the matching characteristic matrix of the learning database is constructed. This matrix is the upper triangular matrix, as shown in Table 2 below.
  • each item of the upper triangular matrix is a correlation coefficient between two routes, which is used to characterize the degree of matching between the two routes.
  • the constructed matching feature matrix is an upper triangular matrix. Because the correlation coefficient between the A1 base station of route 1 and the A2 base station of route 2 corresponds to only one value, the A2 base station of route 2 and the A1 base station of route 1 will be characterized Each item in the lower triangular part of the matrix of correlation coefficients is recorded as 0. Such an upper triangular matrix can simplify the calculation and improve the detection efficiency.
  • FIG. 12 is a flowchart of another example of a sliding calculation process provided by an embodiment of the present application.
  • the calculation of the sliding correlation coefficient adopts the correlation calculation method based on soft decision.
  • the soft decision takes into account the operator’s network
  • the adjacent base stations will be assigned adjacent CIDs, so in the correlation calculation
  • the statistical information is accumulated by 1. If the difference of the CID is within M, the position is considered adjacent, and the statistical information is accumulated by 0.5, except that the statistical information is not accumulated. Where M is 1-20.
  • the soft decision method introduced above is based on the aforementioned hard decision sliding calculation, taking into account the operator’s networking factors. For adjacent cells and the CIDs are also adjacent, it can ensure that the adjacent cells are specific due to the difference in CID. The error of route recognition further improves the robustness of route recognition.
  • a feature matrix for line matching can be constructed. For example, take the initial feature matrix listed in Table 2 above, and then process the initial feature matrix to filter the initial autonomous clustering points.
  • FIG. 13 is a flowchart of an example of an autonomous clustering process provided by an embodiment of the present application.
  • the process shown in Figure 13 includes: S1301, judging whether the feature matrix is an all-zero matrix; S1302, when the feature matrix is an all-zero matrix, end the screening process; S1303, finding the upper triangular feature matrix that satisfies the matching feature>TH Take the corresponding row coordinates as the initial autonomous clustering point; S1304, search for records that meet the matching feature of the row record> TH1, where the value of TH can be 0-0.55; S1305, update the feature matrix, will satisfy Set the row and column of the required record to 0; S1306, continue to search and check until the feature matrix is all zeros.
  • the maximum value of the correlation coefficient is 0.958711 first, and all the items satisfying the matching feature>0.5 in the row corresponding to the maximum value 0.958711 are reset to zero, for example, Correlation coefficients greater than 0.5 in the row where the maximum value 0.958711 in Table 2 is located are all zeroed; then the records that meet the matching characteristics of the row and the records are greater than TH, and the corresponding rows and columns are all zeroed.
  • routes 4 and 7 are two completely different routes.
  • routes 4 and 7 are the two types of routes with the greatest difference among all the acquired specific routes. .
  • routes 4 and 7 are completely different routes.
  • the route can be classified into either a specific route 4 or a specific route 7.
  • the remaining routes are classified based on the K nearest neighbor algorithm (KNN algorithm).
  • KNN algorithm K nearest neighbor algorithm
  • FIG. 14 is a flowchart of an example of the KNN clustering process provided by an embodiment of the present application.
  • the process includes: S1401, randomly fetching a record point in the remaining route; S1402, under the condition that the matching feature is greater than TH, find the matching class of the point based on the KNN algorithm; S1403, the Points are included in the matching class set; S1404, judge whether the number of records in the remaining routes is 0; S1406, when the number of records in the remaining routes is 0, end the clustering, otherwise the loop continues to read the record points in the remaining routes for judgment and Matching class.
  • the electronic device completes the learning process of the user's specific route. After the processing of the learning phase, the electronic device obtains multiple specific routes from home to the company, as well as base station information on each specific route, etc., which are electronic devices The basis for route recognition and matching. It should be understood that the learning of the specific route can be performed periodically, and the user's specific route can be updated in time to improve the accuracy of route recognition.
  • Phase 2 Forecasting Phase
  • the prediction phase can realize the online recognition of the user's route based on the classified specific route.
  • Fig. 15 is a flowchart of an example of a route identification process provided by an embodiment of the present application.
  • the process shown in Figure 15 includes: S1501, down-sampling the marked database records; S1502, sliding and storing the cell sequence within T seconds from the current moment; S1503, obtaining matching features with the down-sampling database; S1504 , Judge whether the maximum matching feature value Max is greater than TH; S1505, when the maximum matching feature value Max is greater than or equal to TH3, determine the corresponding route; S1506, when the maximum matching feature value Max is less than TH3, give up this prediction and continue to cycle The database is downsampled.
  • a route is first selected from the remaining records.
  • the electronic device samples the data set of the classified routes to obtain the information of the specific route that has been learned.
  • the sampling frequency can be appropriately reduced, for example, the information of the learned specific route can be periodically obtained by down-sampling.
  • the electronic device stores the cell sequence within T seconds from the current moment, matches the real-time read route information with the sampled specific route information, obtains the matching feature with the down-sampling database, and selects the class with the largest matching feature and greater than TH3 as
  • the down-sampling period T is less than or equal to 120s, and the value of TH3 is 0-0.55.
  • the value of TH3 and the above-mentioned TH2 or TH1 may be the same or different, which is not limited in this application.
  • down-sampling is a way to periodically obtain the information of a specific route that has been learned, and at the same time, down-sampling can reduce the amount of calculation of the electronic device. For example, general sampling may be sampling once per second, and down sampling may be sampling once every 2 seconds. Without affecting the recognition accuracy, reducing the sampling frequency can reduce the amount of calculation of the electronic device, thereby reducing power consumption.
  • the electronic device can complete the learning and recognition of a specific route. Sliding to match the CID of the base station to construct characteristic information to provide guarantee for line optimization.
  • this process does not require any prior information of the path, and based on the search method of the matching feature matrix, the initial autonomous clustering points are divided, and the route classification effect can be achieved through autonomous clustering. Then use the KNN algorithm to calculate the attribution category of the remaining lines, and achieve fast line prediction through downsampling.
  • this application also provides a soft-judgment sliding algorithm, which takes into account the characteristics of the existing network, and realizes the correlation matching of line cell sequence features based on soft-judgment, further improves the robustness of line recognition, and improves the line prediction stage Detection real-time and sensitivity.
  • the method for identifying specific routes greatly reduces the power consumption of electronic devices compared to existing methods for identifying routes such as GPS and Wi-Fi; compared to identifying routes through the time dimension
  • the method is more robust and improves the real-time and sensitivity of route detection.
  • a consensus is reached with the source application development end to provide an interface within the source application, which can be used by the user to set whether to activate the specific route identification function.
  • the user activates the identification function of a specific route on this interface, in the subsequent process of identifying the specific route, when the electronic device detects that there is an abnormal base station on the specific route that is judged to be output, it can determine whether to access the abnormal base station according to the type of the application. Cache before, or notify the user of the time of access to the abnormal base station by means of a message reminder.
  • the identification function of a specific route is not enabled in an application, the electronic device does not perform the subsequent above operations.
  • a switch control is provided in the setting menu in the video playback application, and the function of the switch control is similar to the smart assistant control shown in (d) in FIG. 7.
  • the switch control When the switch control is turned on, the identification function of a specific route is activated.
  • the electronic device may send a cache request to the server of the video playback application, requesting to cache more video data.
  • This application provides a set of software development kit (SDK), so that the electronic device has the specific route identification before leaving the factory.
  • SDK software development kit
  • the software runs in the system library of the electronic device software architecture in Figure 2, and provides the electronic device with a function to identify a specific location on a specific route.
  • the electronic device can directly form a functional agent inside the electronic device without relying on the video development terminal, and can realize the control of sending and receiving video data packets when the user is insensitive. For example, to communicate with the server and request the cache of video data packets in advance. When it is judged that the electronic device will access the abnormal base station on the specific route currently identified, the obtained video data packet is sent to the video application in advance. When it is judged that the electronic device will have no abnormal base station on the specific route currently identified , Send requests and accept video data packets at the rate at which the electronic device normally obtains video data packets.
  • FIG. 16 is a schematic flowchart of a method for identifying a specific route provided by an embodiment of the present application. As shown in FIG. 16, the method may include the following steps:
  • the electronic device obtains the current route information.
  • the information of the current route includes information of a first wireless network set, the first wireless network set includes a first wireless network and a second wireless network, the communication quality of the first wireless network is greater than a first threshold, so The communication quality of the second wireless network is less than or equal to the first threshold, and the information of the current route includes information of the first wireless network and information of the second wireless network.
  • the route information refers to the information of the wireless network on the route, such as the information of the base station.
  • This application will take a base station as an example to specifically introduce methods for optimizing terminal performance.
  • the first wireless network corresponds to a normal base station, which may be a base station that provides normal network services for terminal equipment;
  • the second wireless network corresponds to an abnormal base station, which may be a base station that cannot provide network services for terminal equipment.
  • the terminal equipment will be disconnected within the coverage of the abnormal base station, or the download rate will be lower than a certain threshold and/or the business will be stuck.
  • acquiring the information of the current route by the electronic device means acquiring the information of all base stations on the current route or recording the location information of multiple base stations.
  • the information of the base station includes identification information of the base station or cell identification information, which is not limited in this application.
  • the foregoing first wireless network set may include at least one base station, and the at least one base station may correspond to the normal base station and the abnormal base station described in the embodiment.
  • the number of base stations is not limited.
  • the electronic device collects information about the base stations that the current route passes through in real time.
  • the electronic device determines that the current route is the first specific route according to the specific route determination model and the current route information.
  • the electronic device may first determine the specific route determination model.
  • the specific route determination model includes information of a plurality of specific routes, and each of the plurality of specific routes includes a second wireless network set.
  • the electronic device may obtain information on multiple specific routes, construct the first feature matrix of the multiple specific routes according to the obtained information on the multiple specific routes, and then according to all the information on the specific routes.
  • a second feature matrix is obtained by classifying the multiple specific routes, and the specific route determination model is determined according to the second feature matrix.
  • the electronic device calculates the matching characteristic curves of any two of the multiple specific routes by sliding correlation coefficients, and constructs the first characteristic matrix according to the matching characteristic curves.
  • the sliding correlation coefficient calculation includes hard decision calculation or soft decision calculation.
  • any one of the multiple specific routes may be classified according to the K nearest neighbor algorithm and the first feature matrix.
  • the K nearest neighbor algorithm For the process, please refer to FIG. 14 and related descriptions, which will not be repeated here.
  • the above process corresponds to the learning phase of the recognition process of the specific route.
  • the detailed process of the learning phase please refer to the related introductions in FIG. 8 to FIG. 14, and will not be repeated here.
  • the electronic device may obtain information of base stations in the second wireless network set included on each specific route in the specific route determination model, and determine the information and information of the base stations in the second wireless network set.
  • the matching degree of the information of the base stations in the first wireless network set is greater than or equal to a second threshold, it is determined that the current route is the first specific route.
  • first threshold and second threshold may be configured in advance, and the size and configuration of the first threshold and second threshold are not limited in this application.
  • the electronic device may periodically obtain information about base stations in the second wireless network set included in the specific route determination model.
  • down-sampling is a way to periodically obtain the information of a specific route that has been learned, and at the same time, down-sampling can reduce the amount of calculation of the electronic device.
  • general sampling may be sampling once per second, and down sampling may be sampling once every 2 seconds. Without affecting the recognition accuracy, reducing the sampling frequency can reduce the amount of calculation of the electronic device, thereby reducing power consumption.
  • the first specific action includes at least one of the following: changing the network search interval; or searching for different network signals according to changes in network standards; or when determining the When the application currently running on the terminal device is the first application, a first message is generated, and the first message is used to instruct the terminal device to send a cache request to the server corresponding to the first application, and/or the first message Used to indicate the moment when the terminal device accesses the second wireless network.
  • the electronic device displays the first message on a first interface, and the first interface is the running interface of the game application, and The first message is used to indicate the moment when the electronic device accesses the abnormal base station.
  • a pop-up reminder as shown in (a) or (b) in FIG. 4.
  • the electronic device when the first application is an audio or video application, the electronic device sends a cache request to the server corresponding to the audio or video application according to the first message, so The cache request is used to cache audio data or video data from the server.
  • the electronic device can send a request to the server to request video data to be cached, and more cache progress can be displayed on the playback progress bar in the video display interface .
  • terminal performance can also be optimized in other ways. Participate in the relevant description in the foregoing embodiment, which will not be repeated here.
  • the electronic device can predict the user's daily specific route according to the user's daily behavior habits, determine the user's daily specific route and information about multiple base stations connected to the electronic device in the specific route.
  • the electronic device can first predict the time to reach such a base station, and then combine the characteristics of the APP running on the electronic device to send a cache request to the server in advance to prevent the electronic device from accessing the signal.
  • a bad base station may affect the user's use, or inform the user of the time to reach such a base station in the form of a message to remind the user to deal with network abnormalities. Therefore, network abnormalities will not affect user operations, and this method can improve user experience.
  • the performance of the terminal is optimized through the above-mentioned method of identifying a specific location on a specific route. For example, by changing the time interval for searching the network of the terminal device, or turning off the network searching function of the terminal device in an area without wireless network service, so that the terminal device will not always search and detect available wireless networks, and optimize the function of the terminal device. Or, by determining the network signals provided by different base stations on a specific route for the terminal device, the terminal device can quickly obtain network services and improve user experience.
  • an electronic device in order to implement the above-mentioned functions, includes hardware and/or software modules corresponding to each function.
  • this application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed by hardware or computer software-driven hardware depends on the specific application and design constraint conditions of the technical solution. Those skilled in the art can use different methods for each specific application in combination with the embodiments to implement the described functions, but such implementation should not be considered as going beyond the scope of the present application.
  • the electronic device can be divided into functional modules according to the foregoing method examples.
  • each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module.
  • the above integrated modules can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is illustrative, and is only a logical function division, and there may be other division methods in actual implementation.
  • FIG. 17 shows a schematic diagram of a possible composition of the electronic device 1700 involved in the foregoing embodiment.
  • the electronic device 1700 may include: an acquiring unit 1701, a detection unit 1702, and a processing unit 1703.
  • the obtaining unit 1701 may be used to support the electronic device 1700 to perform the above-mentioned steps 1601 and so on, and/or be used in other processes of the technology described herein.
  • the detection unit 1702 may be used to support the electronic device 1700 to perform the above-mentioned steps 1602, etc., and/or other processes used in the technology described herein.
  • the processing unit 1703 may be used to support the electronic device 1700 to perform the above-mentioned steps 1603, etc., and/or other processes used in the technology described herein.
  • the electronic device provided in this embodiment is used to execute the above-mentioned method for identifying a specific location on a specific route, and therefore can achieve the same effect as the above-mentioned implementation method.
  • the electronic device may include a processing module, a storage module, and a communication module.
  • the processing module can be used to control and manage the actions of the electronic device, for example, can be used to support the electronic device to execute the steps performed by the acquisition unit 1701, the detection unit 1702, and the processing unit 1703.
  • the storage module can be used to support the electronic device to execute the storage program code and data.
  • the communication module can be used to support communication between electronic devices and other devices.
  • the processing module may be a processor or a controller. It can implement or execute various exemplary logical blocks, modules and circuits described in conjunction with the disclosure of this application.
  • the processor may also be a combination of computing functions, for example, a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, and so on.
  • the storage module may be a memory.
  • the communication module may specifically be a radio frequency circuit, a Bluetooth chip, a Wi-Fi chip, and other devices that interact with other electronic devices.
  • the electronic device involved in this embodiment may be a device having the structure shown in FIG. 1.
  • This embodiment also provides a computer storage medium.
  • the computer storage medium stores computer instructions.
  • the computer instructions run on an electronic device, the electronic device executes the steps of the above-mentioned related method to realize the specific route in the above-mentioned embodiment. Method for identifying specific locations.
  • This embodiment also provides a computer program product.
  • the computer program product runs on a computer
  • the computer executes the above-mentioned related steps to realize the method for identifying a specific location on a specific route in the above-mentioned embodiment.
  • the embodiments of the present application also provide a device.
  • the device may specifically be a chip, component or module.
  • the device may include a connected processor and a memory; wherein the memory is used to store computer execution instructions.
  • the processor can execute the computer-executable instructions stored in the memory, so that the chip executes the method of identifying a specific location on a specific route in the foregoing method embodiments.
  • the electronic equipment, computer storage medium, computer program product, or chip provided in this embodiment are all used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the corresponding method provided above. The beneficial effects of the method will not be repeated here.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are only illustrative, for example, the division of modules or units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or It can be integrated into another device, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separate, and the components displayed as units may be one physical unit or multiple physical units, that is, they may be located in one place, or they may be distributed to multiple different places. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium.
  • the technical solutions of the embodiments of the present application are essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of software products, which are stored in a storage medium It includes several instructions to make a device (may be a single-chip microcomputer, a chip, etc.) or a processor (processor) execute all or part of the steps of the methods in the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read only memory (read only memory, ROM), random access memory (random access memory, RAM), magnetic disk or optical disk and other media that can store program codes.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Security & Cryptography (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Telephone Function (AREA)

Abstract

本申请提供了一种对特定路线上的特定位置进行识别以优化终端性能的方法及电子设备，该方法可以根据用户日常的行为习惯，预测用户日常特定路线，执行与该预测的特定路线相关的特定动作，例如，改变搜网间隔，或根据网络制式的变化，搜寻不同的网络信号；或当终端设备运行游戏应用时，向用户指示终端设备接入异常基站的时刻，提醒用户应对网络异常情况；或当终端设备运行音频视频应用时，向对应的服务器发送缓存请求，该方法可以降低网络服务质量差对用户的影响，同时优化终端性能，提高用户体验。

Description

对特定路线上的特定位置进行识别的方法及电子设备
本申请要求在2019年2月21日提交中国国家知识产权局、申请号为201910129795.9、发明名称为“对特定路线上的特定位置进行识别的方法及电子设备”的中国专利申请的优先权其全部内容通过引用结合在本申请中。
技术领域
本申请涉及电子技术领域，尤其涉及一种对特定路线上的特定位置进行识别的方法、以及优化终端性能的方法及电子设备。
背景技术
在各类应用程序(application，APP)的使用过程中，往往需要良好的网络环境。但是，并不是所有的基站都可以为电子设备提供较好的网络环境。例如，在用户日常的某一固定的路线上，可能会有多个基站为用户提供网络服务，该多个基站中可以包括信号质量好的基站和信号质量差的基站。用户途经信号质量差的基站时，可能无法正常使用网络服务。
发明内容
本申请提供一种对特定路线上的特定位置进行识别的方法及电子设备，该方法可以提醒用户应对网络异常情况，使得网络异常不会影响用户的操作，提高用户体验。
第一方面，提供了一种优化性能的方法，应用于终端设备，该终端设备保存特定路线判定模型，该特定路线判定模型包括多条特定路线的信息，该方法包括：获取当前路线的信息，当前路线的信息包括第一无线网络集合的信息，该第一无线网络集合包括第一无线网络和第二无线网络，该第一无线网络的通信质量大于第一阈值，该第二无线网络通信质量小于或等于该第一阈值；根据该特定路线判定模型和该当前路线的信息，确定该当前路线为第一特定路线；执行与该第一特定路线相关的第一特定动作，该第一特定动作包括以下至少一项：改变搜网间隔；或根据网络制式的变化，搜寻不同的网络信号；或当确定该终端设备当前运行的应用为第一应用时，生成第一消息，该第一消息用于指示该终端设备向该第一应用对应的服务器发送缓存请求，和/或该第一消息用于指示该终端设备接入该第二无线网络的时刻。
应理解，在本申请中，路线的信息指的是该路线上无线网络的信息，例如基站的信息。本申请将以基站为例，具体介绍优化终端性能的方法。在本申请中，第一无线网络对应于正常基站，正常基站是能为终端设备提供正常网络服务的基站；第二无线网络对应于异常基站，异常基站可以是不能为终端设备提供网络服务的基站，终端设备在该异常基站的覆盖范围内会断网，或者下载速率低于一定门限和/或业务发生卡顿。
还应理解，电子设备获取当前路线的信息就是获取当前路线上的所有基站的信息或者 记录多个基站的位置信息。可选地，基站的信息包括基站的标识信息或小区标识信息，本申请对此不做限定。
还应理解，上述第一无线网络集合中可以包括至少一个基站，该至少一个基站可以对应于实施例描述中的正常基站和异常基站，本申请对第一无线网络集合中包括的正常基站和异常基站的数量不做限定。
本申请提供的特定路线识别方法可以用于优化终端性能，在不同的应用场景，执行不同用户业务过程中，可以通过不同的方式提醒用户网络情况，或者提前缓存音视频等，提高用户体验。其中，提醒方式可以包括弹窗等动态方式，也可以包括配置开关等静态方式。
示例性的，当终端设备运行的第一应用为游戏应用时，该方法还包括：在第一界面上显示第一消息，该第一界面是该游戏应用的运行界面，该第一消息用于指示该终端设备执行与该特定路线相关的特定动作的时刻。
或者，当终端设备运行的第一应用为音频或视频应用时，该方法还包括：确定该终端设备执行与该特定路线相关的特定动作的时刻；根据该终端设备执行与该特定路线相关的特定动作的时刻，该终端设备向该音频或视频应用对应的服务器发送缓存请求，该缓存请求用于从该服务器缓存音频数据或视频数据。
此外，在其他应用场景中，还可以通过其他方式优化终端性能。
示例性的，优化终端性能可以指优化终端设备的功耗。在实际使用中，当终端设备从正常基站的覆盖范围进入异常基站的覆盖范围，会出现掉网情况。当掉网以后，终端设备会不断搜网，例如搜寻可接入的无线网络(2G/3G/4G)信号。通过本申请实施例提供的方法，终端设备可以根据特定路线识别的结果，预测到终端设备在该特定路线上进入异常基站覆盖范围的时刻和离开异常基站覆盖范围的时刻，从而可以执行以下任一种可能的动作：
(1)改变终端设备搜网的时间间隔。
例如，增加终端设备搜网的时间间隔。或者，缩短终端设备搜网的时间间隔。
示例性的，在正常基站的覆盖范围内，终端设备的搜网频率为每2分钟搜索一次，在异常基站的覆盖范围内，终端设备的搜网频率改变为每4分钟搜索一次。通过增加终端设备的搜网的时间间隔，降低终端设备的功耗。
示例性的，在终端设备即将进入正常基站覆盖范围时，可以缩短终端设备搜网的时间间隔，使终端设备可以提前启动搜网，从而进入正常基站覆盖范围时快速接入网络，为用户提供网络服务。
(2)在第一时段内，关闭终端设备的搜网功能，使得终端设备在该第一时段内不会一直搜索和检测可用的无线网络，从而降低终端设备的功耗。
可选地，第一时段可以是指终端设备进入异常基站覆盖范围的时刻和离开异常基站覆盖范围的时刻之间的时段。应理解，该第一时段可以不包括终端设备离开异常基站的时刻，或者该第一时段可以包括终端设备离开异常基站的时刻。本申请对此不做限定。
例如，第一时段是8:30:60-8:35:60之间的时段。那么，第一时段不包括终端设备离开异常基站的时刻08:35:60，终端设备预测到8:35:60时进入正常基站内，则在8:35:60终端设备可以启动搜网功能，或者在8:35:60的前n秒(例如8:35:50)就提前启动搜网功能，可以在终端设备离开异常基站时，就接入其他无线网络，缩短断网时间，提高用户体验。
可选地，终端设备在从基站A的覆盖范围进入基站B的覆盖范围的过程中，可能会有一个没有无线网络覆盖的区域，因此，该第一时段还可以指终端设备在该没有无线网络覆盖的区域的时长。
例如，终端设备8:30:60-8:35:60在基站A的覆盖范围内，在8:35:60-8:38:60在没有任何无线网络的覆盖范围内，8:38:60-8:40:60在基站B的覆盖范围内。那么第一时段就指8:35:60-8:38:60。在该时段内，可以关闭终端设备的搜网功能，从而降低终端设备的功耗。终端设备在8:38:60离开没有任何无线网络的覆盖范围进入基站B时，可以提前开启终端设备的搜网功能，例如提前8:38:50重新搜网，当进入基站B时就可以快速接入，提高用户体验。本申请对此不作限定。
示例性的，优化终端性能还可以指快速使终端设备获取网络服务。在实际使用中，当终端设备进入异常基站的覆盖范围出现掉网情况后，终端设备会不断搜网，例如搜寻可接入的无线网络(2G/3G/4G)信号。通过本申请实施例提供的方法，终端设备可以根据特定路线识别的结果，获取该特定路线上基站的信息。
例如，终端设备从基站A切换到基站B时，终端设备可以知道，会发生何种网络制式的变化。如高低网络制式的切换，从2G到3G，还是3G到4G，或者未来的5G等。
示例性的，终端设备可以知道该特定路线上基站A为终端设备提供4G网络，基站B只能为终端设备提供3G网络，在终端设备确定基站A切换到基站B的时刻，直接搜索3G网络信号，而不需要同时搜寻其他不同网络制式提供的网络信号，如2G/4G/5G等网络信号。
或者，示例性的，终端设备还可以预测在该特定路线上从正常基站覆盖范围进入异常基站覆盖范围的时刻和离开异常基站覆盖范围的时刻，而且终端设备可以知道该正常基站可以为终端设备提供5G网络，异常基站只能为终端设备提供2G网络。从而，当终端设备从正常基站覆盖范围进入到异常基站覆盖范围时，直接搜寻该异常基站可以提供的2G网络信号，不需要同时搜寻其他不同网络制式提供的网络信号，如禁止终端设备搜寻4G/3G/5G网络等网络制式下的网络信号，从而使得终端设备可以快速获取网络服务。
结合第一方面，在第一方面的某些实现方式中，该方法还包括：确定该特定路线判定模型，该多条特定路线中的每条特定路线上包括第二无线网络集合的信息，该第二无线网络集合包括至少一个无线网络。
结合第一方面和上述实现方式，在第一方面的某些实现方式中，确定该特定路线判定模型，包括：获取该多条特定路线上第二无线网络集合中包括的无线网络的信息；根据获取的该多条特定路线上第二无线网络集合中包括的无线网络的信息，构建该多条特定路线的第一特征矩阵；根据该第一特征矩阵，对该多条特定路线进行分类处理得到第二特征矩阵；根据该第二特征矩阵，确定该特定路线判定模型。
结合第一方面和上述实现方式，在第一方面的某些实现方式中，构建该多条特定路线的第一特征矩阵，包括：通过滑动相关系数计算该多条特定路线中的任意两条特定路线的匹配特征曲线；根据该匹配特征曲线构建该第一特征矩阵；其中，该滑动相关系数计算包括硬判决计算或软判决计算。
结合第一方面和上述实现方式，在第一方面的某些实现方式中，该方法还包括：根据K最近邻算法和该第一特征矩阵，归类该多条特定路线中的任意一条路线。
应理解，在对原始特征矩阵的自主聚类过程中，可能有两个特定路线之间相似度都接近。换言之，按照上述的自主聚类过程，该两个特定路线既可以被归类到两个特定路线中的任一个。为了精确地对该类路线进行归类处理，对原始特征矩阵中进行KNN算法聚类处理。
结合第一方面和上述实现方式，在第一方面的某些实现方式中，根据该特定路线判定模型和该当前路线的信息，确定该当前路线为第一特定路线，包括：获取该特定路线判定模型中每条特定路线上包括的第二无线网络集合中包括的无线网络的信息；判断该第二无线网络集合中包括的无线网络的信息和该第一无线网络集合中包括的无线网络的信息的匹配程度大于或等于第二阈值时，确定该当前路线为第一特定路线。
结合第一方面和上述实现方式，在第一方面的某些实现方式中，获取该特定路线判定模型中包括的第二无线网络集合中包括的无线网络的信息，包括：周期性获取该第二无线网络集合中包括的无线网络的信息。
可选地，下采样是周期性获取已经学习的特定路线的信息的一种方式，同时，下采样可以降低电子设备运算量。例如，一般采样可以是1秒采样一次，下采样就可以是2秒采样一次。在不影响识别准确率的前提下，减小采样频率可以减少电子设备的计算量，从而降低功耗。
结合第一方面和上述实现方式，在第一方面的某些实现方式中，该无线网络的信息包括基站的标识信息和/或小区标识信息。
第二方面，提供了一种电子设备，包括：一个或多个处理器；存储器；多个应用程序；以及一个或多个程序，其中该一个或多个程序被存储在该存储器中，当该一个或者多个程序被该处理器执行时，使得该电子设备执行以下步骤：获取当前路线的信息，当前路线的信息包括第一无线网络集合的信息，该第一无线网络集合包括第一无线网络和第二无线网络，该第一无线网络的通信质量大于第一阈值，该第二无线网络通信质量小于或等于该第一阈值；根据该特定路线判定模型和该当前路线的信息，确定该当前路线为第一特定路线；执行与该第一特定路线相关的第一特定动作，该第一特定动作包括以下至少一项：改变搜网间隔；或根据网络制式的变化，搜寻不同的网络信号；或当确定该终端设备当前运行的应用为第一应用时，生成第一消息，该第一消息用于指示该终端设备向该第一应用对应的服务器发送缓存请求，和/或该第一消息用于指示该终端设备接入该第二无线网络的时刻。
结合第二方面，在第二方面的某些实现方式中，当该一个或者多个程序被该处理器执行时，使得该电子设备执行以下步骤：确定该特定路线判定模型，该多条特定路线中的每条特定路线上包括第二无线网络集合的信息，该第二无线网络集合包括至少一个无线网络。
结合第二方面和上述实现方式，在第二方面的某些实现方式中，当该一个或者多个程序被该处理器执行时，使得该电子设备执行以下步骤：获取该多条特定路线上第二无线网络集合中包括的无线网络的信息；根据获取的该多条特定路线上第二无线网络集合中包括的无线网络的信息，构建该多条特定路线的第一特征矩阵；根据该第一特征矩阵，对该多条特定路线进行分类处理得到第二特征矩阵；根据该第二特征矩阵，确定该特定路线判定模型。
结合第二方面和上述实现方式，在第二方面的某些实现方式中，当该一个或者多个程 序被该处理器执行时，使得该电子设备执行以下步骤：通过滑动相关系数计算该多条特定路线中的任意两条特定路线的匹配特征曲线；根据该匹配特征曲线构建该第一特征矩阵；其中，该滑动相关系数计算包括硬判决计算或软判决计算。
结合第二方面和上述实现方式，在第二方面的某些实现方式中，当该一个或者多个程序被该处理器执行时，使得该电子设备执行以下步骤：根据K最近邻算法和该第一特征矩阵，归类该多条特定路线中的任意一条路线。
结合第二方面和上述实现方式，在第二方面的某些实现方式中，当该一个或者多个程序被该处理器执行时，使得该电子设备执行以下步骤：获取该特定路线判定模型中每条特定路线上包括的第二无线网络集合中包括的无线网络的信息；判断该第二无线网络集合中包括的无线网络的信息和该第一无线网络集合中包括的无线网络的信息的匹配程度大于或等于第二阈值时，确定该当前路线为第一特定路线。
结合第二方面和上述实现方式，在第二方面的某些实现方式中，当该一个或者多个程序被该处理器执行时，使得该电子设备执行以下步骤：周期性获取该第二无线网络集合中包括的无线网络的信息。
结合第二方面和上述实现方式，在第二方面的某些实现方式中，该无线网络的信息包括基站的标识信息和/或小区标识信息。
第三方面，本申请提供了一种装置，该装置包含在电子设备中，该装置具有实现上述方面及上述方面的可能实现方式中电子设备行为的功能。功能可以通过硬件实现，也可以通过硬件执行相应的软件实现。硬件或软件包括一个或多个与上述功能相对应的模块或单元。例如，显示模块或单元、检测模块或单元、处理模块或单元等。
第四方面，本申请提供了一种电子设备，包括：触摸显示屏，其中，触摸显示屏包括触敏表面和显示器；摄像头；一个或多个处理器；一个或多个存储器；多个应用程序；以及一个或多个计算机程序。其中，一个或多个计算机程序被存储在存储器中，一个或多个计算机程序包括指令。当指令被一个或多个处理器执行时，使得电子设备执行上述任一方面任一项可能的实现中的方法。
第五方面，本申请提供了一种电子设备，包括一个或多个处理器和一个或多个存储器。该一个或多个存储器与一个或多个处理器耦合，一个或多个存储器用于存储计算机程序代码，计算机程序代码包括计算机指令，当一个或多个处理器执行计算机指令时，使得电子设备执行上述任一方面任一项可能的实现中的方法。
第六方面，本申请提供了一种计算机存储介质，包括计算机指令，当计算机指令在电子设备上运行时，使得电子设备执行上述任一方面任一项可能的方法。
第七方面，本申请提供了一种计算机程序产品，当计算机程序产品在电子设备上运行时，使得电子设备执行上述任一方面任一项可能的方法。
附图说明
图1为本申请实施例提供的一种电子设备的硬件结构示意图。
图2为本申请实施例提供的一种电子设备的软件结构示意图。
图3是本申请提供的一例路线识别的示意图。
图4是本申请提供的多种可能的应用场景示意图。
图5是一例电子设备识别路线的流程图。
图6是本申请实施例提供的一例路线示意图。
图7是本申请实施例提供的一例启动特定路线的识别方法的示意图。
图8是本申请实施例提供的一例算法流程示意图。
图9是本申请实施例提供的一例滑动相关系数的计算过程示意图。
图10是本申请实施例提供的一例滑动计算过程的流程图。
图11是本申请实施例提供的一例特征曲线示意图。
图12是本申请实施例提供的又一例滑动计算过程的流程图。
图13是本申请实施例提供的一例自主聚类过程的流程图。
图14是本申请实施例提供的一例KNN聚类过程的流程图。
图15是本申请实施例提供的一例特定路线识别方法的示意性流程图。
图16是本申请实施例提供的特定路线的识别方法的示意性流程图。
图17是本申请实施例提供的一种可能的电子设备组成示意图。
具体实施方式
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描述。其中，在本申请实施例的描述中，除非另有说明，“/”表示或的意思，例如，A/B可以表示A或B；本文中的“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，在本申请实施例的描述中，“多个”是指两个或多于两个。
以下，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。例如，本申请中的第一特征矩阵、第二特征矩阵，只是用于表征特征矩阵处理的不同阶段得到的不同处理结果。在本实施例的描述中，除非另有说明，“多个”的含义是两个或两个以上。
本申请实施例提供了一种对特定路线上的特定位置进行识别的方法，可以应用于电子设备，也可是单独的应用程序，该应用程序可实现本申请中对特定路线上的特定位置进行识别的方法。具体地，电子设备可以根据用户日常的行为习惯，预测用户日常特定路线，确定用户日常特定路线以及特定路线中电子设备接入的多个基站的信息。当日常特定路线中存在信号较差的基站时，电子设备可以首先预测出到达此类基站的时间，再结合电子设备运行的APP的特性，提前向服务器发送缓存请求，防止电子设备接入信号较差的基站时影响用户的使用，或者以消息的形式告知用户到达此类基站的时间，提醒用户应对网络异常情况。
本申请实施例提供的对特定路线上的特定位置进行识别的方法可以应用于手机、平板电脑、可穿戴设备、车载设备、增强现实(augmented reality，AR)/虚拟现实(virtual reality，VR)设备、笔记本电脑、超级移动个人计算机(ultra-mobile personal computer，UMPC)、上网本、个人数字助理(personal digital assistant，PDA)等电子设备上，本申请实施例对电子设备的具体类型不作任何限制。
示例性的，图1示出了电子设备100的结构示意图。电子设备100可以包括处理器 110，外部存储器接口120，内部存储器121，通用串行总线(universal serial bus，USB)接口130，充电管理模块140，电源管理模块141，电池142，天线1，天线2，移动通信模块150，无线通信模块160，音频模块170，扬声器170A，受话器170B，麦克风170C，耳机接口170D，传感器模块180，按键190，马达191，指示器192，摄像头193，显示屏194，以及用户标识模块(subscriber identification module，SIM)卡接口195等。其中传感器模块180可以包括压力传感器180A，陀螺仪传感器180B，气压传感器180C，磁传感器180D，加速度传感器180E，距离传感器180F，接近光传感器180G，指纹传感器180H，温度传感器180J，触摸传感器180K，环境光传感器180L，骨传导传感器180M等。
可以理解的是，本申请实施例示意的结构并不构成对电子设备100的具体限定。在本申请另一些实施例中，电子设备100可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。
处理器110可以包括一个或多个处理单元，例如：处理器110可以包括应用处理器(application processor，AP)，调制解调处理器，图形处理器(graphics processing unit，GPU)，图像信号处理器(image signal processor，ISP)，控制器，存储器，视频编解码器，数字信号处理器(digital signal processor，DSP)，基带处理器，和/或神经网络处理器(neural-network processing unit，NPU)等。其中，不同的处理单元可以是独立的器件，也可以集成在一个或多个处理器中。
其中，控制器可以是电子设备100的神经中枢和指挥中心。控制器可以根据指令操作码和时序信号，产生操作控制信号，完成取指令和执行指令的控制。
处理器110中还可以设置存储器，用于存储指令和数据。在一些实施例中，处理器110中的存储器为高速缓冲存储器。该存储器可以保存处理器110刚用过或循环使用的指令或数据。如果处理器110需要再次使用该指令或数据，可从所述存储器中直接调用。避免了重复存取，减少了处理器110的等待时间，因而提高了系统的效率。
在一些实施例中，处理器110可以包括一个或多个接口。接口可以包括集成电路(inter-integrated circuit，I2C)接口，集成电路内置音频(inter-integrated circuit sound，I2S)接口，脉冲编码调制(pulse code modulation，PCM)接口，通用异步收发传输器(universal asynchronous receiver/transmitter，UART)接口，移动产业处理器接口(mobile industry processor interface，MIPI)，通用输入输出(general-purpose input/output，GPIO)接口，用户标识模块(subscriber identity module，SIM)接口，和/或通用串行总线(universal serial bus，USB)接口等。
在本申请实施例中，处理器110可以用于确定特定路线判定模型，并根据该特定路线判定模型判断当前的路线为哪一条特定路线，从而预测该特定路线上基站的位置，以及电子设备接入该特定路线上包括的多个基站的时间。此外，处理器110还可以用于确定电子设备当前运行的应用类型，以及确定是否需要向服务器请求缓存音视频数据等。
I2C接口是一种双向同步串行总线，包括一根串行数据线(serial data line，SDA)和一根串行时钟线(derail clock line，SCL)。在一些实施例中，处理器110可以包含多组I2C总线。处理器110可以通过不同的I2C总线接口分别耦合触摸传感器180K，充电器，闪光灯，摄像头193等。例如：处理器110可以通过I2C接口耦合触摸传感器180K，使处理 器110与触摸传感器180K通过I2C总线接口通信，实现电子设备100的触摸功能。
I2S接口可以用于音频通信。在一些实施例中，处理器110可以包含多组I2S总线。处理器110可以通过I2S总线与音频模块170耦合，实现处理器110与音频模块170之间的通信。在一些实施例中，音频模块170可以通过I2S接口向无线通信模块160传递音频信号，实现通过蓝牙耳机接听电话的功能。
PCM接口也可以用于音频通信，将模拟信号抽样，量化和编码。在一些实施例中，音频模块170与无线通信模块160可以通过PCM总线接口耦合。在一些实施例中，音频模块170也可以通过PCM接口向无线通信模块160传递音频信号，实现通过蓝牙耳机接听电话的功能。所述I2S接口和所述PCM接口都可以用于音频通信。
UART接口是一种通用串行数据总线，用于异步通信。该总线可以为双向通信总线。它将要传输的数据在串行通信与并行通信之间转换。在一些实施例中，UART接口通常被用于连接处理器110与无线通信模块160。例如：处理器110通过UART接口与无线通信模块160中的蓝牙模块通信，实现蓝牙功能。在一些实施例中，音频模块170可以通过UART接口向无线通信模块160传递音频信号，实现通过蓝牙耳机播放音乐的功能。
MIPI接口可以被用于连接处理器110与显示屏194，摄像头193等外围器件。MIPI接口包括摄像头串行接口(camera serial interface，CSI)，显示屏串行接口(display serial interface，DSI)等。在一些实施例中，处理器110和摄像头193通过CSI接口通信，实现电子设备100的拍摄功能。处理器110和显示屏194通过DSI接口通信，实现电子设备100的显示功能。
GPIO接口可以通过软件配置。GPIO接口可以被配置为控制信号，也可被配置为数据信号。在一些实施例中，GPIO接口可以用于连接处理器110与摄像头193，显示屏194，无线通信模块160，音频模块170，传感器模块180等。GPIO接口还可以被配置为I2C接口，I2S接口，UART接口，MIPI接口等。
USB接口130是符合USB标准规范的接口，具体可以是Mini USB接口，Micro USB接口，USB Type C接口等。USB接口130可以用于连接充电器为电子设备100充电，也可以用于电子设备100与外围设备之间传输数据。也可以用于连接耳机，通过耳机播放音频。该接口还可以用于连接其他电子设备，例如AR设备等。
可以理解的是，本申请实施例示意的各模块间的接口连接关系，只是示意性说明，并不构成对电子设备100的结构限定。在本申请另一些实施例中，电子设备100也可以采用上述实施例中不同的接口连接方式，或多种接口连接方式的组合。
充电管理模块140用于从充电器接收充电输入。其中，充电器可以是无线充电器，也可以是有线充电器。在一些有线充电的实施例中，充电管理模块140可以通过USB接口130接收有线充电器的充电输入。在一些无线充电的实施例中，充电管理模块140可以通过电子设备100的无线充电线圈接收无线充电输入。充电管理模块140为电池142充电的同时，还可以通过电源管理模块141为电子设备供电。
电源管理模块141用于连接电池142，充电管理模块140与处理器110。电源管理模块141接收电池142和/或充电管理模块140的输入，为处理器110，内部存储器121，外部存储器，显示屏194，摄像头193，和无线通信模块160等供电。电源管理模块141还可以用于监测电池容量，电池循环次数，电池健康状态(漏电，阻抗)等参数。在其他一些 实施例中，电源管理模块141也可以设置于处理器110中。在另一些实施例中，电源管理模块141和充电管理模块140也可以设置于同一个器件中。
电子设备100的无线通信功能可以通过天线1，天线2，移动通信模块150，无线通信模块160，调制解调处理器以及基带处理器等实现。
天线1和天线2用于发射和接收电磁波信号。电子设备100中的每个天线可用于覆盖单个或多个通信频带。不同的天线还可以复用，以提高天线的利用率。例如：可以将天线1复用为无线局域网的分集天线。在另外一些实施例中，天线可以和调谐开关结合使用。
移动通信模块150可以提供应用在电子设备100上的包括2G/3G/4G/5G等无线通信的解决方案。移动通信模块150可以包括至少一个滤波器，开关，功率放大器，低噪声放大器(low noise amplifier，LNA)等。移动通信模块150可以由天线1接收电磁波，并对接收的电磁波进行滤波，放大等处理，传送至调制解调处理器进行解调。移动通信模块150还可以对经调制解调处理器调制后的信号放大，经天线1转为电磁波辐射出去。在一些实施例中，移动通信模块150的至少部分功能模块可以被设置于处理器110中。在一些实施例中，移动通信模块150的至少部分功能模块可以与处理器110的至少部分模块被设置在同一个器件中。
在本申请实施例中，当处理器110确定需要向服务器请求缓存数据时，移动通信模块150可以向服务器发送请求消息，用于请求缓存。此外，移动通信模块110还可以用于检测基站信号等。
调制解调处理器可以包括调制器和解调器。其中，调制器用于将待发送的低频基带信号调制成中高频信号。解调器用于将接收的电磁波信号解调为低频基带信号。随后解调器将解调得到的低频基带信号传送至基带处理器处理。低频基带信号经基带处理器处理后，被传递给应用处理器。应用处理器通过音频设备(不限于扬声器170A，受话器170B等)输出声音信号，或通过显示屏194显示图像或视频。在一些实施例中，调制解调处理器可以是独立的器件。在另一些实施例中，调制解调处理器可以独立于处理器110，与移动通信模块150或其他功能模块设置在同一个器件中。
无线通信模块160可以提供应用在电子设备100上的包括无线局域网(wireless local area networks，WLAN)(如无线保真(wireless fidelity，Wi-Fi)网络)，蓝牙(bluetooth，BT)，全球导航卫星系统(global navigation satellite system，GNSS)，调频(frequency modulation，FM)，近距离无线通信技术(near field communication，NFC)，红外技术(infrared，IR)等无线通信的解决方案。无线通信模块160可以是集成至少一个通信处理模块的一个或多个器件。无线通信模块160经由天线2接收电磁波，将电磁波信号调频以及滤波处理，将处理后的信号发送到处理器110。无线通信模块160还可以从处理器110接收待发送的信号，对其进行调频，放大，经天线2转为电磁波辐射出去。
在一些实施例中，电子设备100的天线1和移动通信模块150耦合，天线2和无线通信模块160耦合，使得电子设备100可以通过无线通信技术与网络以及其他设备通信。所述无线通信技术可以包括全球移动通讯系统(global system for mobile communications，GSM)，通用分组无线服务(general packet radio service，GPRS)，码分多址接入(code division multiple access，CDMA)，宽带码分多址(wideband code division multiple access，WCDMA)，时分码分多址(time-division code division multiple access，TD-SCDMA)，长期演进(long term  evolution，LTE)，BT，GNSS，WLAN，NFC，FM，和/或IR技术等。所述GNSS可以包括全球卫星定位系统(global positioning system，GPS)，全球导航卫星系统(global navigation satellite system，GLONASS)，北斗卫星导航系统(beidou navigation satellite system，BDS)，准天顶卫星系统(quasi-zenith satellite system，QZSS)和/或星基增强系统(satellite based augmentation systems，SBAS)。
电子设备100通过GPU，显示屏194，以及应用处理器等实现显示功能。GPU为图像处理的微处理器，连接显示屏194和应用处理器。GPU用于执行数学和几何计算，用于图形渲染。处理器110可包括一个或多个GPU，其执行程序指令以生成或改变显示信息。
显示屏194用于显示图像，视频等。显示屏194包括显示面板。显示面板可以采用液晶显示屏(liquid crystal display，LCD)，有机发光二极管(organic light-emitting diode，OLED)，有源矩阵有机发光二极体或主动矩阵有机发光二极体(active-matrix organic light emitting diode的，AMOLED)，柔性发光二极管(flex light-emitting diode，FLED)，Miniled，MicroLed，Micro-oLed，量子点发光二极管(quantum dot light emitting diodes，QLED)等。在一些实施例中，电子设备100可以包括1个或N个显示屏194，N为大于1的正整数。
电子设备100可以通过ISP，摄像头193，视频编解码器，GPU，显示屏194以及应用处理器等实现拍摄功能。
ISP用于处理摄像头193反馈的数据。例如，拍照时，打开快门，光线通过镜头被传递到摄像头感光元件上，光信号转换为电信号，摄像头感光元件将所述电信号传递给ISP处理，转化为肉眼可见的图像。ISP还可以对图像的噪点，亮度，肤色进行算法优化。ISP还可以对拍摄场景的曝光，色温等参数优化。在一些实施例中，ISP可以设置在摄像头193中。
摄像头193用于捕获静态图像或视频。物体通过镜头生成光学图像投射到感光元件。感光元件可以是电荷耦合器件(charge coupled device，CCD)或互补金属氧化物半导体(complementary metal-oxide-semiconductor，CMOS)光电晶体管。感光元件把光信号转换成电信号，之后将电信号传递给ISP转换成数字图像信号。ISP将数字图像信号输出到DSP加工处理。DSP将数字图像信号转换成标准的RGB，YUV等格式的图像信号。在一些实施例中，电子设备100可以包括1个或N个摄像头193，N为大于1的正整数。
数字信号处理器用于处理数字信号，除了可以处理数字图像信号，还可以处理其他数字信号。例如，当电子设备100在频点选择时，数字信号处理器用于对频点能量进行傅里叶变换等。
视频编解码器用于对数字视频压缩或解压缩。电子设备100可以支持一种或多种视频编解码器。这样，电子设备100可以播放或录制多种编码格式的视频，例如：动态图像专家组(moving picture experts group，MPEG)1，MPEG2，MPEG3，MPEG4等。
NPU为神经网络(neural-network，NN)计算处理器，通过借鉴生物神经网络结构，例如借鉴人脑神经元之间传递模式，对输入信息快速处理，还可以不断的自学习。通过NPU可以实现电子设备100的智能认知等应用，例如：图像识别，人脸识别，语音识别，文本理解等。
外部存储器接口120可以用于连接外部存储卡，例如Micro SD卡，实现扩展电子设 备100的存储能力。外部存储卡通过外部存储器接口120与处理器110通信，实现数据存储功能。例如将音乐，视频等文件保存在外部存储卡中。
内部存储器121可以用于存储计算机可执行程序代码，所述可执行程序代码包括指令。处理器110通过运行存储在内部存储器121的指令，从而执行电子设备100的各种功能应用以及数据处理。内部存储器121可以包括存储程序区和存储数据区。其中，存储程序区可存储操作系统，至少一个功能所需的应用程序(比如声音播放功能，图像播放功能等)等。存储数据区可存储电子设备100使用过程中所创建的数据(比如音频数据，电话本等)等。此外，内部存储器121可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件，闪存器件，通用闪存存储器(universal flash storage，UFS)等。
电子设备100可以通过音频模块170，扬声器170A，受话器170B，麦克风170C，耳机接口170D，以及应用处理器等实现音频功能。例如音乐播放，录音等。
音频模块170用于将数字音频信息转换成模拟音频信号输出，也用于将模拟音频输入转换为数字音频信号。音频模块170还可以用于对音频信号编码和解码。在一些实施例中，音频模块170可以设置于处理器110中，或将音频模块170的部分功能模块设置于处理器110中。
扬声器170A，也称“喇叭”，用于将音频电信号转换为声音信号。电子设备100可以通过扬声器170A收听音乐，或收听免提通话。
受话器170B，也称“听筒”，用于将音频电信号转换成声音信号。当电子设备100接听电话或语音信息时，可以通过将受话器170B靠近人耳接听语音。
麦克风170C，也称“话筒”，“传声器”，用于将声音信号转换为电信号。当拨打电话或发送语音信息时，用户可以通过人嘴靠近麦克风170C发声，将声音信号输入到麦克风170C。电子设备100可以设置至少一个麦克风170C。在另一些实施例中，电子设备100可以设置两个麦克风170C，除了采集声音信号，还可以实现降噪功能。在另一些实施例中，电子设备100还可以设置三个，四个或更多麦克风170C，实现采集声音信号，降噪，还可以识别声音来源，实现定向录音功能等。
耳机接口170D用于连接有线耳机。耳机接口170D可以是USB接口130，也可以是3.5mm的开放移动电子设备平台(open mobile terminal platform，OMTP)标准接口，美国蜂窝电信工业协会(cellular telecommunications industry association of the USA，CTIA)标准接口。
压力传感器180A用于感受压力信号，可以将压力信号转换成电信号。在一些实施例中，压力传感器180A可以设置于显示屏194。压力传感器180A的种类很多，如电阻式压力传感器，电感式压力传感器，电容式压力传感器等。电容式压力传感器可以是包括至少两个具有导电材料的平行板。当有力作用于压力传感器180A，电极之间的电容改变。电子设备100根据电容的变化确定压力的强度。当有触摸操作作用于显示屏194，电子设备100根据压力传感器180A检测所述触摸操作强度。电子设备100也可以根据压力传感器180A的检测信号计算触摸的位置。在一些实施例中，作用于相同触摸位置，但不同触摸操作强度的触摸操作，可以对应不同的操作指令。例如：当有触摸操作强度小于第一压力阈值的触摸操作作用于短消息应用图标时，执行查看短消息的指令。当有触摸操作强度大 于或等于第一压力阈值的触摸操作作用于短消息应用图标时，执行新建短消息的指令。
陀螺仪传感器180B可以用于确定电子设备100的运动姿态。在一些实施例中，可以通过陀螺仪传感器180B确定电子设备100围绕三个轴(即，x，y和z轴)的角速度。陀螺仪传感器180B可以用于拍摄防抖。示例性的，当按下快门，陀螺仪传感器180B检测电子设备100抖动的角度，根据角度计算出镜头模组需要补偿的距离，让镜头通过反向运动抵消电子设备100的抖动，实现防抖。陀螺仪传感器180B还可以用于导航，体感游戏场景。
气压传感器180C用于测量气压。在一些实施例中，电子设备100通过气压传感器180C测得的气压值计算海拔高度，辅助定位和导航。
磁传感器180D包括霍尔传感器。电子设备100可以利用磁传感器180D检测翻盖皮套的开合。在一些实施例中，当电子设备100是翻盖机时，电子设备100可以根据磁传感器180D检测翻盖的开合。进而根据检测到的皮套的开合状态或翻盖的开合状态，设置翻盖自动解锁等特性。
加速度传感器180E可检测电子设备100在各个方向上(一般为三轴)加速度的大小。当电子设备100静止时可检测出重力的大小及方向。还可以用于识别电子设备姿态，应用于横竖屏切换，计步器等应用。
距离传感器180F，用于测量距离。电子设备100可以通过红外或激光测量距离。在一些实施例中，拍摄场景，电子设备100可以利用距离传感器180F测距以实现快速对焦。
接近光传感器180G可以包括例如发光二极管(LED)和光检测器，例如光电二极管。发光二极管可以是红外发光二极管。电子设备100通过发光二极管向外发射红外光。电子设备100使用光电二极管检测来自附近物体的红外反射光。当检测到充分的反射光时，可以确定电子设备100附近有物体。当检测到不充分的反射光时，电子设备100可以确定电子设备100附近没有物体。电子设备100可以利用接近光传感器180G检测用户手持电子设备100贴近耳朵通话，以便自动熄灭屏幕达到省电的目的。接近光传感器180G也可用于皮套模式，口袋模式自动解锁与锁屏。
环境光传感器180L用于感知环境光亮度。电子设备100可以根据感知的环境光亮度自适应调节显示屏194亮度。环境光传感器180L也可用于拍照时自动调节白平衡。环境光传感器180L还可以与接近光传感器180G配合，检测电子设备100是否在口袋里，以防误触。
指纹传感器180H用于采集指纹。电子设备100可以利用采集的指纹特性实现指纹解锁，访问应用锁，指纹拍照，指纹接听来电等。
温度传感器180J用于检测温度。在一些实施例中，电子设备100利用温度传感器180J检测的温度，执行温度处理策略。例如，当温度传感器180J上报的温度超过阈值，电子设备100执行降低位于温度传感器180J附近的处理器的性能，以便降低功耗实施热保护。在另一些实施例中，当温度低于另一阈值时，电子设备100对电池142加热，以避免低温导致电子设备100异常关机。在其他一些实施例中，当温度低于又一阈值时，电子设备100对电池142的输出电压执行升压，以避免低温导致的异常关机。
触摸传感器180K，也称“触控面板”。触摸传感器180K可以设置于显示屏194，由触摸传感器180K与显示屏194组成触摸屏，也称“触控屏”。触摸传感器180K用于检测作 用于其上或附近的触摸操作。触摸传感器可以将检测到的触摸操作传递给应用处理器，以确定触摸事件类型。可以通过显示屏194提供与触摸操作相关的视觉输出。在另一些实施例中，触摸传感器180K也可以设置于电子设备100的表面，与显示屏194所处的位置不同。
骨传导传感器180M可以获取振动信号。在一些实施例中，骨传导传感器180M可以获取人体声部振动骨块的振动信号。骨传导传感器180M也可以接触人体脉搏，接收血压跳动信号。在一些实施例中，骨传导传感器180M也可以设置于耳机中，结合成骨传导耳机。音频模块170可以基于所述骨传导传感器180M获取的声部振动骨块的振动信号，解析出语音信号，实现语音功能。应用处理器可以基于所述骨传导传感器180M获取的血压跳动信号解析心率信息，实现心率检测功能。
按键190包括开机键，音量键等。按键190可以是机械按键。也可以是触摸式按键。电子设备100可以接收按键输入，产生与电子设备100的用户设置以及功能控制有关的键信号输入。
马达191可以产生振动提示。马达191可以用于来电振动提示，也可以用于触摸振动反馈。例如，作用于不同应用(例如拍照，音频播放等)的触摸操作，可以对应不同的振动反馈效果。作用于显示屏194不同区域的触摸操作，马达191也可对应不同的振动反馈效果。不同的应用场景(例如：时间提醒，接收信息，闹钟，游戏等)也可以对应不同的振动反馈效果。触摸振动反馈效果还可以支持自定义。
指示器192可以是指示灯，可以用于指示充电状态，电量变化，也可以用于指示消息，未接来电，通知等。
SIM卡接口195用于连接SIM卡。SIM卡可以通过插入SIM卡接口195，或从SIM卡接口195拔出，实现和电子设备100的接触和分离。电子设备100可以支持1个或N个SIM卡接口，N为大于1的正整数。SIM卡接口195可以支持Nano SIM卡，Micro SIM卡，SIM卡等。同一个SIM卡接口195可以同时插入多张卡。所述多张卡的类型可以相同，也可以不同。SIM卡接口195也可以兼容不同类型的SIM卡。SIM卡接口195也可以兼容外部存储卡。电子设备100通过SIM卡和网络交互，实现通话以及数据通信等功能。在一些实施例中，电子设备100采用eSIM，即：嵌入式SIM卡。eSIM卡可以嵌在电子设备100中，不能和电子设备100分离。
电子设备100的软件系统可以采用分层架构，事件驱动架构，微核架构，微服务架构，或云架构。本申请实施例以分层架构的Android系统为例，示例性说明电子设备100的软件结构。
图2是本申请实施例的电子设备100的软件结构框图。分层架构将软件分成若干个层，每一层都有清晰的角色和分工。层与层之间通过软件接口通信。在一些实施例中，将Android系统分为四层，从上至下分别为应用程序层，应用程序框架层，安卓运行时(Android runtime)和系统库，以及内核层。应用程序层可以包括一系列应用程序包。
如图2所示，应用程序包可以包括相机，图库，日历，通话，地图，导航，WLAN，蓝牙，音乐，视频，短信息等应用程序。
应用程序框架层为应用程序层的应用程序提供应用编程接口(application programming interface，API)和编程框架。应用程序框架层包括一些预先定义的函数。
如图2所示，应用程序框架层可以包括窗口管理器，内容提供器，视图系统，电话管理器，资源管理器，通知管理器等。
窗口管理器用于管理窗口程序。窗口管理器可以获取显示屏大小，判断是否有状态栏，锁定屏幕，截取屏幕等。
内容提供器用来存放和获取数据，并使这些数据可以被应用程序访问。所述数据可以包括视频，图像，音频，拨打和接听的电话，浏览历史和书签，电话簿等。
视图系统包括可视控件，例如显示文字的控件，显示图片的控件等。视图系统可用于构建应用程序。显示界面可以由一个或多个视图组成的。例如，包括短信通知图标的显示界面，可以包括显示文字的视图以及显示图片的视图。
电话管理器用于提供电子设备100的通信功能。例如通话状态的管理(包括接通，挂断等)。
资源管理器为应用程序提供各种资源，比如本地化字符串，图标，图片，布局文件，视频文件等等。
通知管理器使应用程序可以在状态栏中显示通知信息，可以用于传达告知类型的消息，可以短暂停留后自动消失，无需用户交互。比如通知管理器被用于告知下载完成，消息提醒等。通知管理器还可以是以图表或者滚动条文本形式出现在系统顶部状态栏的通知，例如后台运行的应用程序的通知，还可以是以对话窗口形式出现在屏幕上的通知。例如在状态栏提示文本信息，发出提示音，电子设备振动，指示灯闪烁等。
在本申请中，电子设备首先确定将要接入异常基站的时刻，然后可以将接入异常基站的时刻以状态栏的通知信息的形式进行显示，以提醒用户应对网络异常等情况。
Android runtime包括核心库和虚拟机。Android runtime负责安卓系统的调度和管理。
核心库包含两部分：一部分是java语言需要调用的功能函数，另一部分是安卓的核心库。
应用程序层和应用程序框架层运行在虚拟机中。虚拟机将应用程序层和应用程序框架层的java文件执行为二进制文件。虚拟机用于执行对象生命周期的管理，堆栈管理，线程管理，安全和异常的管理，以及垃圾回收等功能。
系统库可以包括多个功能模块。例如：表面管理器(surface manager)，媒体库(media libraries)，三维图形处理库(例如：OpenGL ES)，2D图形引擎(例如：SGL)等。
表面管理器用于对显示子系统进行管理，并且为多个应用程序提供了2D和3D图层的融合。
媒体库支持多种常用的音频，视频格式回放和录制，以及静态图像文件等。媒体库可以支持多种音视频编码格式，例如:MPEG4，H.264，MP3，AAC，AMR，JPG，PNG等。
三维图形处理库用于实现三维图形绘图，图像渲染，合成，和图层处理等。
2D图形引擎是2D绘图的绘图引擎。
内核层是硬件和软件之间的层。内核层至少包含显示驱动，摄像头驱动，音频驱动，传感器驱动。
为了便于理解，本申请以下实施例将以具有图1和图2所示结构的电子设备为例，结合附图和应用场景，对本申请实施例提供的视频中实现单词复读的方法进行具体阐述。
图3是本申请提供的一例特定路线识别的示意图。如图3所示，从家到公司的路线中， 包括6个不同的基站，如图中小三角形所示出的基站。其中白色小三角形示出的基站1、3、4和6是正常基站，用户途经正常基站覆盖的区域时，电子设备可以正常接入基站，基站可以为用户提供网络服务；黑色小三角形示出的基站2和5是异常基站，用户途经异常基站覆盖的区域时，电子设备无法正常接入基站，处于掉网或者网络信号弱的状态，网络服务异常。此时，用户无法正常使用某应用的在线服务，例如使用在线音频、在线视频类等在线应用。为了不影响用户正常使用在线音频、在线视频类等在线应用，提高用户体验，电子设备可以根据用户日常的行为习惯，预测用户日常特定路线，确定用户日常特定路线以及特定路线中电子设备接入的多个基站的信息。当日常特定路线中存在信号较差的基站时，电子设备可以首先预测出到达此类基站的时间，再结合电子设备运行的APP的特性，提前向服务器发送缓存请求，防止电子设备接入信号较差的基站时影响用户的使用，或者以消息的形式告知用户到达此类基站的时间，提醒用户应对网络异常情况。
具体地，上述过程可以包括以下步骤：S301，电子设备预测接入异常基站的时间；S302，电子设备在接入异常基站的时间到来之前，向服务器发送请求，用于提前缓存数据。
应理解，本申请中以音频、视频类应用为例，介绍了电子设备预测用户的路线且提前缓存数据的机制。例如图3中电子设备的显示界面为音频播放过程中一种可能的显示界面示意图，本申请中电子设备还可以运行其他的应用，例如视频等需要缓存数据的应用类型，或者其他在线类的应用类型。
当运行音频、视频类应用时，电子设备可以预测用户的路线，并预测在该路线中接入异常基站的时间，在该时间到来之前提前向服务器发送请求，缓存音频数据或视频数据。当电子设备接入异常基站时，提前缓存的音频或视频数据可供用户使用，从而，网络异常不会影响用户的操作，该方法可以提高用户体验。
示例性的，图3中示出的电子设备的界面为音频播放界面，用于表示当前电子设备正在播放音频文件。用户从家出发，在基站1的覆盖区域内，电子设备预测到用户选取的特定路线为家到公司的路线，期间会接入异常基站2和基站5，并确定接入异常基站2和基站5的时间。在到达基站2的覆盖区域之前，电子设备向服务器发送请求，请求缓存更多的音频数据。
在一种可能的实施方式中，上述提前预测路线和网络状况的机制还可以应用于其他应用场景。
图4是本申请提供的多种可能的应用场景示意图。具体地，图4中的(a)图示出的是电子设备运行游戏应用的场景示意图。当用户运行在线游戏应用时，电子设备根据用户当前的行进速度，预测在该特定路线中接入通信质量较差的基站的时间，并提前生成消息，该消息用于通知用户网络将在一定时长后变差，以便用户采取相应的应对措施。该消息可以以(a)图所示的消息弹窗401的形式提醒用户，消息弹窗401的内容可以是：“10分钟后网络质量差”等，或者更多用于提醒用户网络质量变差的消息内容，本申请对消息弹窗的内容不作限定。
当用户的行进速度发生变化，导致接入通信质量较差的基站的时间发生变化时，通知消息可以做相应变更。例如，用户开始处于驾驶模式，电子设备在08:30时提醒用户“10分钟后网络质量差”，在08:35时，电子设备确定用户处于步行模式，接入通信质量较差的基站的时间由原来预测的08:40变化为8:55，此时通知消息可以变更为“20分钟后网络质 量差”，并再次以消息弹窗形式进行显示。
可选地，当电子设备运行图4中的(b)图示出的视频播放应用时，电子设备预测在该特定路线中接入通信质量较差的基站的时间，电子设备可以向服务器发送请求，请求缓存视频数据，在视频显示界面中的播放进度条上可以显示更多的缓存进度。例如，(b)图中的播放进度条上，黑实线是用户已经观看的影片内容，黑色实心点用于表示当前播放的位置。当电子设备向服务器发送缓存请求后，影片的缓存进度可以到空心圆点示出的位置。
在一种可能的情况中，黑色实心点标识的播放位置到空心圆点标识的播放位置之间的时长，大于或等于从当前时刻起，到用户离开异常基站的覆盖范围时的时刻之间的时长。从而保证在用户接入异常基站时，不会影响用户在线观看视频。
或者，电子设备也可以提前生成消息，如消息弹窗402，该消息弹窗402的内容用于通知用户网络将在一定时长后变差，以便用户采取相应的应对措施。本申请对此不作限定。
本申请提供的特定路线识别方法可以用于优化终端性能，结合图4中列举的两种应用场景，在执行不同用户业务过程中，通过不同的方式提醒用户网络情况，或者提前缓存音视频等，提高用户体验。其中，提醒方式可以包括弹窗等动态方式，也可以包括配置开关等静态方式。此外，在其他应用场景中，还可以通过其他方式优化终端性能。
示例性的，优化终端性能可以指优化终端设备的功耗。在实际使用中，当终端设备从正常基站的覆盖范围进入异常基站的覆盖范围，会出现掉网情况。当掉网以后，终端设备会不断搜网，例如搜寻可接入的无线网络(2G/3G/4G)信号。通过本申请实施例提供的方法，终端设备可以根据特定路线识别的结果，预测到终端设备在该特定路线上进入异常基站覆盖范围的时刻和离开异常基站覆盖范围的时刻，从而可以执行以下任一种可能的动作：
(1)改变终端设备搜网的时间间隔。
例如，增加终端设备搜网的时间间隔。或者，缩短终端设备搜网的时间间隔。
示例性的，在正常基站的覆盖范围内，终端设备的搜网频率为每2分钟搜索一次，在异常基站的覆盖范围内，终端设备的搜网频率改变为每4分钟搜索一次。通过增加终端设备的搜网的时间间隔，降低终端设备的功耗。
示例性的，在终端设备即将进入正常基站覆盖范围时，可以缩短终端设备搜网的时间间隔，使终端设备可以提前启动搜网，从而进入正常基站覆盖范围时快速接入网络，为用户提供网络服务。
(2)在第一时段内，关闭终端设备的搜网功能，使得终端设备在该第一时段内不会一直搜索和检测可用的无线网络，从而降低终端设备的功耗。
可选地，第一时段可以是指终端设备进入异常基站覆盖范围的时刻和离开异常基站覆盖范围的时刻之间的时段。应理解，该第一时段可以不包括终端设备离开异常基站的时刻，或者该第一时段可以包括终端设备离开异常基站的时刻。本申请对此不做限定。
例如，第一时段是8:30:60-8:35:60之间的时段。那么，第一时段不包括终端设备离开异常基站的时刻08:35:60，终端设备预测到8:35:60时进入正常基站内，则在8:35:60终端设备可以启动搜网功能，或者在8:35:60的前n秒(例如8:35:50)就提前启动搜网功能，可以在终端设备离开异常基站时，就接入其他无线网络，缩短断网时间，提高用户体验。
可选地，终端设备在从基站A的覆盖范围进入基站B的覆盖范围的过程中，可能会有一个没有无线网络覆盖的区域，因此，该第一时段还可以指终端设备在该没有无线网络覆盖的区域的时长。
例如，终端设备8:30:60-8:35:60在基站A的覆盖范围内，在8:35:60-8:38:60在没有任何无线网络的覆盖范围内，8:38:60-8:40:60在基站B的覆盖范围内。那么第一时段就指8:35:60-8:38:60。在该时段内，可以关闭终端设备的搜网功能，从而降低终端设备的功耗。终端设备在8:38:60离开没有任何无线网络的覆盖范围进入基站B时，可以提前开启终端设备的搜网功能，例如提前8:38:50重新搜网，当进入基站B时就可以快速接入，提高用户体验。本申请对此不作限定。
示例性的，优化终端性能还可以指快速使终端设备获取网络服务。在实际使用中，当终端设备进入异常基站的覆盖范围出现掉网情况后，终端设备会不断搜网，例如搜寻可接入的无线网络(2G/3G/4G)信号。通过本申请实施例提供的方法，终端设备可以根据特定路线识别的结果，获取该特定路线上基站的信息。
例如，终端设备从基站A切换到基站B时，终端设备可以知道，会发生何种网络制式的变化。如高低网络制式的切换，从2G到3G，还是3G到4G，或者未来的5G等。
示例性的，终端设备可以知道该特定路线上基站A为终端设备提供4G网络，基站B只能为终端设备提供3G网络，在终端设备确定基站A切换到基站B的时刻，直接搜索3G网络信号，而不需要同时搜寻其他不同网络制式提供的网络信号，如2G/4G/5G等网络信号。
或者，示例性的，终端设备还可以预测在该特定路线上从正常基站覆盖范围进入异常基站覆盖范围的时刻和离开异常基站覆盖范围的时刻，而且终端设备可以知道该正常基站可以为终端设备提供5G网络，异常基站只能为终端设备提供2G网络。从而，当终端设备从正常基站覆盖范围进入到异常基站覆盖范围时，直接搜寻该异常基站可以提供的2G网络信号，不需要同时搜寻其他不同网络制式提供的网络信号，如禁止终端设备搜寻4G/3G/5G等网络制式下的网络信号，从而使得终端设备可以快速获取网络服务。
为了实现上述功能，首先电子设备需要准确预测用户途经的特定路线。在确定用户路线过程中，电子设备需要对该途经的特定路线信息进行学习，并识别出当前用户所处的路线，从而针对该路线选取对应的预测模型。
目前电子设备识别特定路线方法，主要依靠时间戳信息进行路线的识别。具体地，图5是一例电子设备识别路线的流程图。如图5所示，首先依据电子设备接入基站时间信息进行场景判别，主要分为家附近的基站和公司附近的基站的判别。图5中的(a)图为电子设备判断家附近的基站的流程，(b)图为电子设备判断公司附近的基站的流程。该识别方法中，电子设备将晚上长时间接入的基站标识为家附近的基站，记录晚上接入家附近的基站的时间戳信息；白天长时间接入的基站标识为公司附近的基站，电子设备记录白天接入公司附近的基站的时间戳信息。从而电子设备可以基于时间戳信息，并结合基站的信息判断上下班的路线，将白天脱离家附近的基站的路线标识为上班路线，晚上脱离公司附近的基站的路线标识为下班路线。
图6是本申请实施例提供的一例路线示意图。如图6所示，以用户从家、公司和最常去的商场之间的路线为例，可能会有多种路线或者不同的往返路线。对于不同的多种路线， 每条路线上经过的基站不同，异常基站和正常基站的分布也不同。上述依据时间戳信息识别路线的方法，电子设备只能识别出家附近的基站和公司附近的基站，对家到公司的上班路线或者公司到家的下班路线并不能准确的识别出来。该方法只能粗略的根据时间信息估计用户在上班途中或者下班途中，并不能准确确定用户的路线以及预估路线中是否存在通信质量较差的基站。该方法存在鲁棒性和灵敏度较差的问题，如识别出路线的种类受限，以及无法识别折返的路线等问题。
此外，另外一种识别特定路线的方法，主要依靠全球定位系统(global positioning system，GPS)或无线网络(wireless fidelity，Wi-Fi)定位。具体地，GPS的定位方式可以利用已知位置的卫星，通过电子设备的GPS接收器计算出当前的位置。WI-FI网络定位的方式主要利用WI-FI的物理地址信息，通过三角定位法或指纹定位法，计算出电子设备的位置信息。在实际应用过程中，由于GPS搜星、WI-FI网络信号质量不佳，会造成的定位不准确、更新不及时等问题。此外，采用GPS或者WI-FI定位会导致电子设备的高功耗问题。
因此，本申请提供一种对特定路线上的特定位置进行识别的方法，可以实现对特定路线的分类和识别，能够实时和高准确度的实现路线识别，同时满足低功耗的要求。应理解，本申请所说的特定路线上的特定位置，可以指该特定路线上包括的多个基站的位置。
在一种可能的实施方式中，本申请提供的特定路线的识别方法可以通过设置应用进行启动。
图7是本申请实施例提供的一例启动特定路线的识别方法的示意图。作为一种示例而非限定，如图7中的(a)图所示，手机的屏幕显示系统显示了当前一种可能的界面内容，该界面内容为手机的主界面701。该主界面701可以显示多款第三方应用程序(application，App)，例如支付宝、任务卡商店、微博、设置、微信、卡包、相册、相机等。应理解，界面内容701还可以包括其他更多的应用程序，本申请对此不作限定。
用户执行(a)图所示的对设置应用的点击操作，响应于该点击操作，手机进入设置应用的主界面702，设置应用的主界面702可以显示如图7中(b)图所示的内容。该界面702具体可以包括飞行模式设置控件、Wi-Fi设置控件、蓝牙控件、个人热点控件、移动网络控件、电池控件、显示与亮度设置控件、华为账号控件、声音设置控件和隐私控件等。应理解，设置应用的主界面702还可以包括其他更多或更少的显示内容，本申请对此不作限定。
用户执行(b)图所示的对桌面与壁纸控件的点击操作，响应于该点击操作，手机进入桌面与壁纸设置界面703。在该桌面与壁纸设置界面703中，包括本地主题设置控件、本地壁纸设置控件、本地锁屏设置控件、本地字体设置控件以及智能助手控件。
用户执行(c)图所示的对智能助手控件的开启操作，响应于该开启操作，手机启动智能助手，如图(d)所示智能助手已经开启。可选地，手机就启动了本申请实施例提供的特定路线识别功能。
应理解，该智能助手启动后还可以包括其他更多的其他功能，或者启动该特定路线识别功能还可以有其他可能的快捷方式，例如通过电子设备运行的应用的设置选项进行启动。具体地，当电子设备运行视频播放应用时，可以通过视频播放应用的设置选项进行启动，本申请对此不做限定。
在一种可能的实施方式中，本申请提供的特定路线的识别方法可以默认为启动状态，即当监测到用户目前的路线可能为电子设备已经记录的多条特定路线中的某条路线且该特定路线存在异常基站时，检测电子设备当前运行的应用，当确定在运行音频类的应用时向服务器提前请求缓存，或者在用户运行游戏等应用时以消息通知的方式提醒用户接入异常基站的时刻，以便用户做好其他准备，防止异常基站断网造成不良影响。当监测到用户目前的路线不是电子设备记录的多条特定路线中的任意路线，电子设备不采取后续的请求缓存或者生成接入异常基站的时刻提醒消息等操作。
下面结合附图介绍本申请提供的路线的识别方法，该方法可以包含两个阶段：学习阶段和预测阶段。学习阶段主要依据电子设备采集的路线信息，进行相关的匹配特征的计算，构建学习数据库的匹配特征矩阵，搜索初始自主聚类点，并采用K最近邻(k-nearest neighbor，KNN)算法，归类出多个特定路线信息。预测阶段主要根据聚类完成的数据记录，进行下采样操作，并与实时读取的基站序列进行匹配，将分类集合中匹配程度最高的路线作为预测输出，实现路线识别。当输出了预测的特定路线后，电子设备可以获取该特定路线上的基站的通信情况，预测用户到达网络质量较差的基站的时间。电子设备再根据当前运行的应用，确定是否需要提前向服务器发送请求，请求更多的数据缓存。为了更好地理解本申请提供的特定路线的识别方法，下面将介绍具体的实现过程和算法原理。
阶段一：学习阶段
在学习阶段，电子设备可以采集多条特定路线信息，例如记录多条路线上的所有基站的信息或者记录多个点的位置等。电子设备对每一条特定路线，通过滑动相关系数的计算，得到特征矩阵，并根据特征矩阵，对每条特定路线进行分类，归类出多个特定路线。
应理解，学习阶段的方法流程可以离线进行，也可以在线进行。而且，电子设备可以周期性进行路线学习。例如，对于从用户家到公司之间的路线，电子设备10天进行一次学习，更新路线数据库的信息，提高路线识别的准确度。本申请对此不作限定。
下面，将学习阶段具体分为三个步骤进行介绍。
1、特征识别及特征矩阵构建
特征提取是从原始特征中找出最有效的特征，通过特征转换的方式得到一组具有明显物理意义或者统计意义的特征。特征提取的过程需要先获取原始数据，将原始数据转变为模型的训练数据。例如，在本申请实施例中，对特定路线的特征提取过程就是获取该特定路线包括的多个基站的信息，将获取的基站的信息转变为特征矩阵的过程。特征矩阵构建就是先用原始数据协方差矩阵的前N个最大特征值对应的特征向量构成映射矩阵的过程，再对特征矩阵进行相关处理等。在特征识别及特征矩阵构建的过程中，具体可以包括计算路线小区匹配特征和构建线路匹配特征矩阵两个部分。
图8是本申请实施例提供的一例算法流程示意图。如图8所示，具体的处理流程包括：S801，滑动相关系数计算任意两条基站记录的匹配特征曲线；S802，检测相关峰作为这两条记录的匹配特征；S803，构建学习数据库的匹配特征矩阵；S804，返回特征矩阵。其中S801和S802为计算路线小区匹配特征的过程，S803为构建线路匹配特征矩阵过程。
具体地，图9是本申请实施例提供的一例滑动相关系数的计算过程示意图。在S801中，首先滑动任意两条基站记录的匹配特征曲线，如图9所示的示意图，对于两条路线，分别记做路线1和路线2。路线1上包括A1至E1五个基站，路线2上包括A2至E2五 个基站。在滑动过程中，以路线1的每一个基站信息去匹配路线2的每一个基站信息。如图所示，滑动1表示路线2和路线1滑动一次，计算路线1的A1基站和路线2的E2基站的匹配程度；同理，滑动2表示路线2和路线1滑动两次，计算路线1的A1基站和路线2的D2基站、路线1的B1基站和路线2的E2基站的匹配程度；滑动5表示路线2和路线1滑动五次，计算路线1的A1基站和路线2的A2基站、路线1的B1基站和路线2的B2基站、路线1的C1基站和路线2的C2基站、路线1的D1基站和路线2的D2基站、路线1的E1基站和路线2的E2基站的匹配程度；滑动8表示路线2和路线1滑动八次，计算路线1的D1基站和路线2的A2基站、路线1的E1基站和路线2的B2基站的匹配程度。应理解，滑动次数的可以是两条特定路线上的基站数量之和减去1的到的，例如，图9中路线1和路线2的滑动次数为5+5-1＝9次。
在滑动相关系数计算过程中，以路线1中的基站的特征去匹配路线2的基站的特征，如果路线1中的基站的特征和路线2的基站的特征匹配程度大于或等于第一阈值TH，则判断路线1中的基站和路线2的基站是同一个基站，记做1；如果A1的特征和A2的特征匹配低于第一阈值TH，则判断A1和A2不是同一个基站，记做0，以此类推滑动计算两条路线中的每一个基站之间的匹配程度。
图10是本申请实施例提供的一例滑动计算过程的流程图。如图10所示的过程，滑动相关系数的计算可以采取基于硬判决的相关计算方式，其中硬判决的规则为两个基站的标识ID(identification)或者基站下的小区标识(cell identification，CID)相同，则统计信息累加1，否则不累加。该过程可以包括：S1001，判断B序列是否到达最大移位；S1002，当B序列到达最大移位时，结束计算；S1003，当B序列没有到达最大移位时，判断累项求和是否结束；S1004，累项求和结束时，求和(sum)归一化；S1005，累项求和没有结束时，判断是否A[i]＝＝B[i]；S1006，当A[i]＝＝B[i]时，统计信息累加1，表示为sum＝sum+1；否则循环继续判断累项求和是否结束。
具体地，通过滑动相关系数计算任意两条小区记录的匹配特征曲线过程中，首先取出任意两条采集记录的路线序列，分别是路线1对应的A序列和路线2对应的B序列，当A序列的中的CID和B序列中的CID相同时，将sum加1，否则sum不变，然后通过sum除以比较次数进行归一化，可以求出相关系数。接着移位B序列，再次进行相关系数的计算。该计算过程直到B序列移位达到最大值为止。当滑动次数达到最大次数时，即序列达到最大移位，如图8中所示的路线1和路线2的滑动相关系数计算过程中，当滑动到用路线1的E1基站匹配路线2的A2基站时，即滑动到最大次数9次，即B序列的移位达到最大值。这样便可以随着B序列的移位值的变化，求得对应的相关系数的曲线，也就是特征曲线，并将特征曲线的最大值作为这两条记录的相关特征。
应理解，每一次移位对应一个sum值，当A[i]＝＝B[i]时，统计信息累加1，当A[i]和B[i]不匹配时，不累加，直到最大移位。当路线2的每一个基站和路线1的任意一个基站完成匹配程度的确定后，得到一个求和序列，如下表1所示的求和序列。该序列进行归一化处理得到相应的相关系数，即求出了路线1的每一个基站和路线2的每一个基站相互之间的相关系数。
表1
0 1 1 1 1 1 1 1 1 1 1 1 1
1 0 1 1 1 1 1 1 1 1 1 1 1
1 1 0 1 1 1 1 1 1 1 1 1 1
1 1 1 0 1 1 1 1 1 1 1 1 1
1 1 1 1 0 1 1 1 1 1 1 1 1
1 1 1 1 1 0 1 1 1 1 1 1 1
1 1 1 1 1 1 0 1 1 1 1 1 1
1 1 1 1 1 1 1 0 1 1 1 1 1
1 1 1 1 1 1 1 1 0 1 1 1 1
1 1 1 1 1 1 1 1 1 0 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1
1 1 1 1 1 1 1 1 1 1 1 0 1
1 1 1 1 1 1 1 1 1 1 1 1 0
将相关系数随着采样点的变化而变化过程绘制成曲线，如图11所示。图11是本申请实施例提供的一例特征曲线示意图。其中，图11中的特征曲线横轴为采样点偏移值，纵轴为求得的相关系数。当计算完相关匹配特征曲线后，检测相关峰作为这两条记录的匹配特征，构建学习数据库的匹配特征矩阵，该矩阵为上三角矩阵，如下表2所示的上三角矩阵。
表2
Figure PCTCN2020074592-appb-000001
Figure PCTCN2020074592-appb-000002
应理解，该上三角矩阵的每一项都是两条路线之间的相关系数，用于表征两条路线之间的匹配程度。
还应理解，构建的匹配特征矩阵为上三角矩阵，因为路线1的A1基站和路线2的A2基站之间的相关系数只对应一个数值，故而将表征路线2的A2基站和路线1的A1基站之间的相关系数的矩阵下三角部分各项记做0，这样的上三角矩阵可以简化计算量，提高检测效率。
经过上述步骤，完成了特征矩阵的构建过程。
在一种可能的实施方式中，进行滑动匹配时，可以采用基于软判决的相关计算方式。图12是本申请实施例提供的又一例滑动计算过程的流程图。如图12所示的过程，滑动相关系数的计算采取基于软判决的相关计算方式，其中软判决考虑了运营商组网时，对于位置相邻的基站会分配相邻的CID，所以在相关计算的时候，若CID相同则统计信息累加1，若CID的差别为M以内情况下，认为位置相邻，统计信息累加0.5，除此之外统计信息不累加。其中M为1-20。该过程可以包括：S1201，判断B序列是否到达最大移位；S1202，当B序列到达最大移位时，结束计算；S1203，当B序列没有到达最大移位时，判断累项求和是否结束；S1204，累项求和结束时，求和(sum)归一化；S1205，累项求和没有结束时，判断是否A[i]＝＝B[i]；S1206，当A[i]＝＝B[i]时，统计信息累加1，表示为sum＝sum+1；S1207，当A[i]不等于B[i]时，继续判断Abs(A[i]-B[i])是否小于M；S1208，当Abs(A[i]-B[i])<M时，统计信息累加0.5，表示为sum＝sum+0.5；否则循环继续判断累项求和是否结束。
上述介绍的软判决方法在前述硬判滑动计算的基础上，考虑了运营商组网的因素，对于位置相邻的小区且CID也相邻时，能够保证相邻的小区因为CID的差异导致特定路线识别的误差，从而进一步提高线路识别的鲁棒性。
2、自主聚类
在学习阶段，经过上述步骤1中的方法，可以构建线路匹配的特征矩阵。例如，上表2列举的初始特征矩阵，然后对该初始特征矩阵进行处理，筛选初始自主聚类点。
图13是本申请实施例提供的一例自主聚类过程的流程图。如图13所示的过程，该过程包括：S1301，判断特征矩阵是否为全零阵；S1302，当特征矩阵是全零阵时，结束筛选过程；S1303，寻找上三角特征矩阵满足匹配特征>TH的最大值，取出对应的行坐标作为 初始自主聚类点；S1304，寻找在与该行记录满足匹配特征>TH1的记录，其中TH取值可以为0-0.55；S1305，更新特征矩阵，将满足要求的记录的行和列置0；S1306，继续寻找和检查，直到特征矩阵为全零阵。
具体地，可以取TH1＝0.5，在表2所示的上三角矩阵中，先查找相关系数最大值为0.958711，将最大值0.958711对应的行中满足匹配特征>0.5的项全部归零，例如将表2中的最大值0.958711所在的行中大于0.5的相关系数全部归零；再寻找与该行记录满足匹配特征大于TH的记录，将对应的行和列全部置零。经过初始聚类搜索第一轮处理得到如下表3所示的矩阵，在算法中输出体现为InitialSet＝[7]。以此类推，继续寻找和检查，经过初始聚类搜索第二轮处理，直到特征矩阵为表4所示的全零阵，在算法中输出体现为InitialSet＝[7,4]。
表3
0 0 0.66492147 0 0.832972 0 0.843063 0 0.80316 0 0 0 0.878719
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0.806218 0 0.830933 0 0.865043 0 0 0 0.807018
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0.954511 0 0.797542 0 0 0 0.812357
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0.806672 0 0 0 0.79405
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0.816171
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
表4
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
经过上述处理后，完成对所有的特定路线的分类，得到两类不同的路线。例如，本申请实施例中归类出路线4和路线7两类，且路线4和7为完全不同的两类路线，换言之，路线4和7为所有获取的特定路线中区别最大的两类路线。
3、KNN算法聚类
应理解，在对原始特征矩阵的自主聚类过程中，判断路线4和7为完全不同的两类路线。对于获取的多个特定路线中，可能有一种特定路线和特定路线4和特定路线7的相似度都接近。换言之，按照上述的自主聚类过程，该路线既可以被归类到特定路线4的一类，也可以被归类到特定路线7的一类，为了精确地对该类路线进行归类处理，在上述步骤2的自主聚类之后，对原始特征矩阵中进行KNN算法聚类处理。
接下来基于K最近邻算法(KNN算法)归类剩余路线。首先从剩余记录中选取一条路线，基于KNN法，可以选出与这个路线K个最大的匹配特征，并且匹配特征大于TH2，然后这K个特征中多数属于哪个类，就把该类作为这个路线的类，其中TH2取值0-0.55。应理解，这里TH2和上述TH1的取值可以相同也可以不同，本申请对此不做限定。
图14是本申请实施例提供的一例KNN聚类过程的流程图。如图14所示的过程，该过程包括：S1401，随机取出剩余路线中某次记录点；S1402，在满足匹配特征大于TH条件下，基于KNN算法，找到该点的匹配类；S1403，把该点纳入匹配的类集合中；S1404，判断剩余路线中记录数是否为0；S1406，当剩余路线中记录数为0时，结束聚类，否则循环继续读取剩余路线中的记录点进行判断和匹配类。
具体地，基于第二轮初始聚类搜索出来的初始自主聚类点InitialSet＝[7,4]，基于KNN法(选取K＝1)，选取与这一点最近邻的类作为该点的类，即满足匹配特征最大匹配特征>0.5。
应理解，上述经过分类之后，还有部分剩余路线未完成聚类，通过上述流程，可以将剩余路线进行归类。从每条剩余路线中提取该路线的K个最大的相关系数，且保证该K个相关系数都是大于TH2，确定该K个特征中多数属于哪个类，就把该类作为这个路线的类。
综上，电子设备完成了用户的特定路线的学习过程，经过学习阶段的处理，电子设备获取了多条家到公司之间的特定路线，以及每一条特定路线上的基站信息等，是电子设备进行路线识别与匹配的基础。应理解，该特定路线的学习可以周期性进行，可以及时对用户的特定路线进行更新，提高路线识别的准确性。
阶段二：预测阶段
经过学习阶段中的相关处理，已经完成了对特定路线的分类，预测阶段可以基于已分类的特定路线，实现对用户路线的在线识别。
图15是本申请实施例提供的一例路线识别过程的流程图。如图15所示的过程，该过程包括：S1501，将已标注的数据库记录进行下采样；S1502，滑动存储当前时刻开始T秒内的小区序列；S1503，获取与下采样数据库的匹配特征；S1504，判断最大匹配特征值Max是否大于TH；S1505，当最大匹配特征值Max大于或等于TH3时，判断为对应路线；S1506，当最大匹配特征值Max小于TH3时，放弃本次预测，继续循环对数据库进行下采样。
具体地，在预测阶段首先从剩余记录中选取一条路线，为了实现快速识别，电子设备 对已归类的路线的数据集合进行采样，获取已经学习的特定路线的信息。可选地，在采样过程中，可以适当降低采样频率，例如通过下采样周期性获取学习的特定路线的信息。然后电子设备存储当前时刻开始T秒内的小区序列，将实时读取的路线信息和采样的特定路线的信息进行匹配，获取与下采样数据库的匹配特征，选取匹配特征最大且大于TH3的类作为该在线预测的结果，其中下采样周期T小于或等于120s，TH3取值0-0.55。类似的，这里TH3和上述TH2或者TH1的取值可以相同也可以不同，本申请对此不做限定。
应理解，下采样是周期性获取已经学习的特定路线的信息的一种方式，同时，下采样可以降低电子设备运算量。例如，一般采样可以是1秒采样一次，下采样就可以是2秒采样一次。在不影响识别准确率的前提下，减小采样频率可以减少电子设备的计算量，从而降低功耗。
通过上述方案，电子设备可以完成对特定路线的学习识别。滑动匹配基站的CID，构建特征信息，为线路优化提供保证。此外，该过程无需任何路径的先验信息，基于匹配特征矩阵的搜索方法，划分初始自主聚类点，通过自主聚类可以达到路线归类效果。再利用KNN算法计算剩余线路的归属类别，通过下采样达到快速线路预测效果。在滑动过程中，本申请还提供一种软判滑动算法，考虑现网组网的特征，实现基于软判的线路小区序列特征相关匹配，进一步提高线路识别的鲁棒性，在线路预测阶段提高检测实时性和灵敏度。
综上所述，本申请提供的特定路线的识别方法，相比于现有的GPS和WI-FI等识别路线的方法，大幅降低了电子设备的功耗；相比于通过时间维度去识别路线的方法，鲁棒性更强，而且提高了路线检测的实时性和灵敏度。
此外，在该特定路线的识别过程中，要将该方法应用于电子设备中，可以包括不同的实现方式。
在一种可能的实现方式中，与源应用开发端达成共识，在源应用内部提供一个接口，该接口可以用于用户设置是否启动特定路线识别功能。当用户在该接口设置启动了特定路线的识别功能，后续在特定路线识别过程中，当电子设备监测到判断输出的特定路线上有异常基站时，可以根据该应用的类型确定在接入异常基站之前进行缓存，或者以消息提醒的方式通知用户接入异常基站的时刻。在某应用内不开启特定路线的识别功能时，则电子设备不进行后续的上述操作。
示例性的，以视频播放应用为例，在视频播放应用内设置菜单提供一个开关控件，该开关控件的功能类似于图7中(d)图示出的智能助手控件。当该开关控件处于开启状态时，启动特定路线的识别功能。后续在特定路线识别过程中，当监测到特定路线上有异常基站时，电子设备可以向视频播放应用的服务器发送缓存请求，请求缓存更多的视频数据。
在另一种可能的实现方式中，不需要与源应用开发端的协商，本申请提供一套软件开发工具包(software development kit，SDK)，使得电子设备在出厂之前就已经具备该特定路线识别的功能。该软件运行于图2中电子设备软件架构的系统库，为电子设备提供一种对特定路线上的特定位置进行识别的功能。
具体地，以视频播放为例，电子设备可以不依赖视频开发端，直接在电子设备内部形成功能代理，在用户无感情况下，可以实现视频数据包的收发控制。例如和服务器之间进行通信，提前请求视频数据包的缓存。当判断电子设备在当前识别出的特定路线上将接入异常基站时，将已经获取的视频数据包提前发送到该视频应用，当判断电子设备在当前识 别出的特定路线上将没有异常基站时，按照电子设备正常获取视频数据包的速率发送请求并接受视频数据包。
结合上述实施例及相关附图，本申请实施例提供了一种特定路线的识别方法，该方法可以在如图1、图2所示的电子设备(例如手机、平板电脑等)中实现。图16是本申请实施例提供的特定路线的识别方法的示意性流程图，如图16所示，该方法可以包括以下步骤：
1601，电子设备获取当前路线的信息。
其中，所述当前路线的信息包括第一无线网络集合的信息，所述第一无线网络集合包括第一无线网络和第二无线网络，所述第一无线网络的通信质量大于第一阈值，所述第二无线网络通信质量小于或等于所述第一阈值，所述当前路线的信息包括所述第一无线网络的信息和所述第二无线网络的信息。
应理解，在本申请中，路线的信息指的是该路线上无线网络的信息，例如基站的信息。本申请将以基站为例，具体介绍优化终端性能的方法。在本申请中，第一无线网络对应于正常基站，正常基站可以是终端设备提供正常网络服务的基站；第二无线网络对应于异常基站，异常基站可以是不能为终端设备提供网络服务的基站，终端设备在该异常基站的覆盖范围内会断网，或者下载速率低于一定门限和/或业务发生卡顿。
还应理解，电子设备获取当前路线的信息就是获取当前路线上的所有基站的信息或者记录多个基站的位置信息。可选地，基站的信息包括基站的标识信息或小区标识信息，本申请对此不做限定。
还应理解，上述第一无线网络集合中可以包括至少一个基站，该至少一个基站可以对应于实施例描述中的正常基站和异常基站，本申请对第一无线网络集合中包括的正常基站和异常基站的数量不做限定。
在用户运动路线变化过程中，电子设备实时采集当前路线途经的基站的信息。
1602，电子设备根据该特定路线判定模型和该当前路线的信息，确定该当前路线为第一特定路线。
可选地，在步骤1602之前，电子设备可以先确定所述特定路线判定模型。其中，所述特定路线判定模型包括多条特定路线的信息，所述多条特定路线中的每条特定路线上包括第二无线网络集合。
在一种可能的实施方式中，电子设备可以获取多条特定路线上的信息，根据获取的所述多条特定路线上的信息，构建所述多条特定路线的第一特征矩阵，再根据所述第一特征矩阵，对所述多条特定路线进行分类处理得到第二特征矩阵，根据所述第二特征矩阵，确定所述特定路线判定模型。
在一种可能的实施方式中，电子设备通过滑动相关系数计算所述多条特定路线中的任意两条路线的匹配特征曲线，根据所述匹配特征曲线构建所述第一特征矩阵。其中，所述滑动相关系数计算包括硬判决计算或软判决计算。
应理解，在对原始特征矩阵的自主聚类过程中，可能有两个特定路线之间相似度都接近。换言之，按照上述的自主聚类过程，该两个特定路线既可以被归类到两个特定路线中的任一个。为了精确地对该类路线进行归类处理，对原始特征矩阵中进行KNN算法聚类处理。
具体地，可以根据K最近邻算法和所述第一特征矩阵，归类所述多条特定路线中的任意一条路线，过程请参照图14以及相关描述，此处不再赘述。
示例性的，以上过程对应于特定路线的识别过程的学习阶段，关于学习阶段的详细过程，请参照图8至图14的相关介绍，此处不再赘述。
在一种可能的实施方式中，电子设备可以获取所述特定路线判定模型中每条特定路线上包括的第二无线网络集合中基站的信息，判断所述第二无线网络集合中基站的信息和所述第一无线网络集合中基站的信息的匹配程度大于或等于第二阈值时，确定所述当前路线为所述第一特定路线。
应理解，上述第一阈值和第二阈值可以提前配置，本申请对第一阈值和第二阈值的大小和配置方式不做限定。
在一种可能的实施方式中，电子设备可以周期性获取所述特定路线判定模型中包括的第二无线网络集合中基站的信息。
示例性的，下采样是周期性获取已经学习的特定路线的信息的一种方式，同时，下采样可以降低电子设备运算量。例如，一般采样可以是1秒采样一次，下采样就可以是2秒采样一次。在不影响识别准确率的前提下，减小采样频率可以减少电子设备的计算量，从而降低功耗。
1603，执行与该第一特定路线相关的第一特定动作，该第一特定动作包括以下至少一项：改变搜网间隔；或根据网络制式的变化，搜寻不同的网络信号；或当确定所述终端设备当前运行的应用为第一应用时，生成第一消息，所述第一消息用于指示所述终端设备向所述第一应用对应的服务器发送缓存请求，和/或所述第一消息用于指示所述终端设备接入所述第二无线网络的时刻。
在一种可能的实施方式中，当所述第一应用为游戏应用时，电子设备在第一界面上显示所述第一消息，所述第一界面是所述游戏应用的运行界面，所述第一消息用于指示所述电子设备接入异常基站的时刻。
示例性的，如图4中的(a)图或(b)所示的弹窗提醒。
在一种可能的实施方式中，当所述第一应用为音频或视频应用时，电子设备根据所述第一消息，所述电子设备向所述音频或视频应用对应的服务器发送缓存请求，所述缓存请求用于从所述服务器缓存音频数据或视频数据。
示例性的，如图4中的(b)图所示的视频播放应用，电子设备可以向服务器发送请求，请求缓存视频数据，在视频显示界面中的播放进度条上可以显示更多的缓存进度。
此外，在其他应用场景中，还可以通过其他方式优化终端性能。参加前述实施例中的相关描述，此处不再赘述。
通过上述对特定路线上的特定位置进行识别的方法，电子设备可以根据用户日常的行为习惯，预测用户日常特定路线，确定用户日常特定路线以及特定路线中电子设备接入的多个基站的信息。当日常特定路线中存在信号较差的基站时，电子设备可以首先预测出到达此类基站的时间，再结合电子设备运行的APP的特性，提前向服务器发送缓存请求，防止电子设备接入信号较差的基站时影响用户的使用，或者以消息的形式告知用户到达此类基站的时间，提醒用户应对网络异常情况。从而，网络异常不会影响用户的操作，该方法可以提高用户体验。
此外，通过上述对特定路线上的特定位置进行识别的方法，优化终端的性能。例如，通过改变终端设备的搜网的时间间隔，或者在没有无线网络服务的区域内，关闭终端设备的搜网功能，使得终端设备不会一直搜索和检测可用的无线网络，优化终端设备的功耗；又或者，通过确定特定路线上不同的基站为终端设备提供的网络信号，使终端设备可以快速获取网络服务，提高用户体验。
可以理解的是，电子设备为了实现上述功能，其包含了执行各个功能相应的硬件和/或软件模块。结合本文中所公开的实施例描述的各示例的算法步骤，本申请能够以硬件或硬件和计算机软件的结合形式来实现。某个功能究竟以硬件还是计算机软件驱动硬件的方式来执行，取决于技术方案的特定应用和设计约束条件。本领域技术人员可以结合实施例对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
本实施例可以根据上述方法示例对电子设备进行功能模块的划分，例如，可以对应各个功能划分各个功能模块，也可以将两个或两个以上的功能集成在一个处理模块中。上述集成的模块可以采用硬件的形式实现。需要说明的是，本实施例中对模块的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。
在采用对应各个功能划分各个功能模块的情况下，图17示出了上述实施例中涉及的电子设备1700的一种可能的组成示意图，如图17所示，该电子设备1700可以包括：获取单元1701、检测单元1702和处理单元1703。
其中，获取单元1701可以用于支持电子设备1700执行上述步骤1601等，和/或用于本文所描述的技术的其他过程。
检测单元1702可以用于支持电子设备1700执行上述步骤1602等，和/或用于本文所描述的技术的其他过程。
处理单元1703可以用于支持电子设备1700执行上述步骤1603等，和/或用于本文所描述的技术的其他过程。
需要说明的是，上述方法实施例涉及的各步骤的所有相关内容均可以援引到对应功能模块的功能描述，在此不再赘述。
本实施例提供的电子设备，用于执行上述对特定路线上的特定位置进行识别的方法，因此可以达到与上述实现方法相同的效果。
在采用集成的单元的情况下，电子设备可以包括处理模块、存储模块和通信模块。其中，处理模块可以用于对电子设备的动作进行控制管理，例如，可以用于支持电子设备执行上述获取单元1701、检测单元1702和处理单元1703执行的步骤。存储模块可以用于支持电子设备执行存储程序代码和数据等。通信模块，可以用于支持电子设备与其他设备的通信。
其中，处理模块可以是处理器或控制器。其可以实现或执行结合本申请公开内容所描述的各种示例性的逻辑方框，模块和电路。处理器也可以是实现计算功能的组合，例如包含一个或多个微处理器组合，数字信号处理(digital signal processing，DSP)和微处理器的组合等等。存储模块可以是存储器。通信模块具体可以为射频电路、蓝牙芯片、Wi-Fi芯片等与其他电子设备交互的设备。
在一个实施例中，当处理模块为处理器，存储模块为存储器时，本实施例所涉及的电 子设备可以为具有图1所示结构的设备。
本实施例还提供一种计算机存储介质，该计算机存储介质中存储有计算机指令，当该计算机指令在电子设备上运行时，使得电子设备执行上述相关方法步骤实现上述实施例中的对特定路线上的特定位置进行识别的方法。
本实施例还提供了一种计算机程序产品，当该计算机程序产品在计算机上运行时，使得计算机执行上述相关步骤，以实现上述实施例中的对特定路线上的特定位置进行识别的方法。
另外，本申请的实施例还提供一种装置，这个装置具体可以是芯片，组件或模块，该装置可包括相连的处理器和存储器；其中，存储器用于存储计算机执行指令，当装置运行时，处理器可执行存储器存储的计算机执行指令，以使芯片执行上述各方法实施例中的对特定路线上的特定位置进行识别的方法。
其中，本实施例提供的电子设备、计算机存储介质、计算机程序产品或芯片均用于执行上文所提供的对应的方法，因此，其所能达到的有益效果可参考上文所提供的对应的方法中的有益效果，此处不再赘述。
通过以上实施方式的描述，所属领域的技术人员可以了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个装置，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是一个物理单元或多个物理单元，即可以位于一个地方，或者也可以分布到多个不同地方。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个可读取存储介质中。基于这样的理解，本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该软件产品存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(processor)执行本申请各个实施例方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上内容，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (20)

  1. 一种优化性能的方法，应用于终端设备，其特征在于，所述终端设备保存特定路线判定模型，所述特定路线判定模型包括多条特定路线的信息，所述方法包括：
    获取当前路线的信息，所述当前路线的信息包括第一无线网络集合的信息，所述第一无线网络集合包括第一无线网络和第二无线网络，所述第一无线网络的通信质量大于第一阈值，所述第二无线网络通信质量小于或等于所述第一阈值；
    根据所述特定路线判定模型和所述当前路线的信息，确定所述当前路线为第一特定路线；
    执行与所述第一特定路线相关的第一特定动作，所述第一特定动作包括以下至少一项：
    改变搜网间隔；或
    根据网络制式的变化，搜寻不同的网络信号；或
    当确定所述终端设备当前运行的应用为第一应用时，生成第一消息，所述第一消息用于指示所述终端设备向所述第一应用对应的服务器发送缓存请求，和/或所述第一消息用于指示所述终端设备接入所述第二无线网络的时刻。
  2. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    确定所述特定路线判定模型，所述多条特定路线中的每条特定路线上包括第二无线网络集合的信息，所述第二无线网络集合包括至少一个无线网络。
  3. 根据权利要求2所述的方法，其特征在于，所述确定所述特定路线判定模型，包括：
    获取所述多条特定路线上第二无线网络集合中包括的无线网络的信息；
    根据获取的所述多条特定路线上第二无线网络集合中包括的无线网络的信息，构建所述多条特定路线的第一特征矩阵；
    根据所述第一特征矩阵，对所述多条特定路线进行分类处理得到第二特征矩阵；
    根据所述第二特征矩阵，确定所述特定路线判定模型。
  4. 根据权利要求3所述的方法，其特征在于，所述构建所述多条特定路线的第一特征矩阵，包括：
    通过滑动相关系数计算所述多条特定路线中的任意两条特定路线的匹配特征曲线；
    根据所述匹配特征曲线构建所述第一特征矩阵；
    其中，所述滑动相关系数计算包括硬判决计算或软判决计算。
  5. 根据权利要求3或4所述的方法，其特征在于，所述方法还包括：
    根据K最近邻算法和所述第一特征矩阵，归类所述多条特定路线中的任意一条路线。
  6. 根据权利要求1至5中任一项所述的方法，其特征在于，所述根据所述特定路线判定模型和所述当前路线的信息，确定所述当前路线为第一特定路线，包括：
    获取所述特定路线判定模型中每条特定路线上包括的第二无线网络集合中包括的无线网络的信息；
    判断所述第二无线网络集合中包括的无线网络的信息和所述第一无线网络集合中包 括的无线网络的信息的匹配程度大于或等于第二阈值时，确定所述当前路线为第一特定路线。
  7. 根据权利要求6所述的方法，其特征在于，所述获取所述特定路线判定模型中包括的第二无线网络集合中包括的无线网络的信息，包括：
    周期性获取所述第二无线网络集合中包括的无线网络的信息。
  8. 根据权利要求1至7中任一项所述的方法，其特征在于，所述无线网络的信息包括基站的标识信息和/或小区标识信息。
  9. 根据权利要求1至8中任一项所述的方法，其特征在于，所述第一应用为游戏应用，或者所述第一应用是音频或视频应用。
  10. 一种电子设备，其特征在于，包括：
    一个或多个处理器；
    一个或多个存储器；
    多个应用程序；
    以及一个或多个程序，其中所述一个或多个程序被存储在所述存储器中，当所述一个或者多个程序被所述处理器执行时，使得所述电子设备执行以下步骤：
    获取当前路线的信息，所述当前路线的信息包括第一无线网络集合的信息，所述第一无线网络集合包括第一无线网络和第二无线网络，所述第一无线网络的通信质量大于第一阈值，所述第二无线网络通信质量小于或等于所述第一阈值；
    根据所述特定路线判定模型和所述当前路线的信息，确定所述当前路线为第一特定路线；
    执行与所述第一特定路线相关的第一特定动作，所述第一特定动作包括以下至少一项：
    改变搜网间隔；或
    根据网络制式的变化，搜寻不同的网络信号；或
    当确定所述电子设备当前运行的应用为第一应用时，生成第一消息，所述第一消息用于指示所述电子设备向所述第一应用对应的服务器发送缓存请求，和/或所述第一消息用于指示所述电子设备接入所述第二无线网络的时刻。
  11. 根据权利要求10所述的电子设备，其特征在于，当所述一个或者多个程序被所述处理器执行时，使得所述电子设备执行以下步骤：
    确定所述特定路线判定模型，所述多条特定路线中的每条特定路线上包括第二无线网络集合的信息，所述第二无线网络集合包括至少一个无线网络。
  12. 根据权利要求10所述的电子设备，其特征在于，当所述一个或者多个程序被所述处理器执行时，使得所述电子设备执行以下步骤：
    获取所述多条特定路线上第二无线网络集合中包括的无线网络的信息；
    根据获取的所述多条特定路线上第二无线网络集合中包括的无线网络的信息，构建所述多条特定路线的第一特征矩阵；
    根据所述第一特征矩阵，对所述多条特定路线进行分类处理得到第二特征矩阵；
    根据所述第二特征矩阵，确定所述特定路线判定模型。
  13. 根据权利要求12所述的电子设备，其特征在于，当所述一个或者多个程序被所 述处理器执行时，使得所述电子设备执行以下步骤：
    通过滑动相关系数计算所述多条特定路线中的任意两条特定路线的匹配特征曲线；
    根据所述匹配特征曲线构建所述第一特征矩阵；
    其中，所述滑动相关系数计算包括硬判决计算或软判决计算。
  14. 根据权利要求13所述的电子设备，其特征在于，当所述一个或者多个程序被所述处理器执行时，使得所述电子设备执行以下步骤：
    根据K最近邻算法和所述第一特征矩阵，归类所述多条特定路线中的任意一条路线。
  15. 根据权利要求11至14中任一项所述的电子设备，其特征在于，当所述一个或者多个程序被所述处理器执行时，使得所述电子设备执行以下步骤：
    获取所述特定路线判定模型中每条特定路线上包括的第二无线网络集合中包括的无线网络的信息；
    判断所述第二无线网络集合中包括的无线网络的信息和所述第一无线网络集合中包括的无线网络的信息的匹配程度大于或等于第二阈值时，确定所述当前路线为第一特定路线。
  16. 根据权利要求15所述的电子设备，其特征在于，当所述一个或者多个程序被所述处理器执行时，使得所述电子设备执行以下步骤：
    周期性获取所述第二无线网络集合中包括的无线网络的信息。
  17. 根据权利要求10至16中任一项所述的电子设备，其特征在于，所述无线网络的信息包括基站的标识信息和/或小区标识信息。
  18. 根据权利要求10至17中任一项所述的电子设备，其特征在于，所述第一应用为游戏应用，或者所述第一应用是音频或视频应用。
  19. 一种计算机存储介质，其特征在于，包括计算机指令，当所述计算机指令在电子设备上运行时，使得所述电子设备执行如权利要求1至9中任一项所述的方法。
  20. 一种计算机程序产品，其特征在于，当所述计算机程序产品在计算机上运行时，使得所述计算机执行如权利要求1至9中任一项所述的方法。
PCT/CN2020/074592 2019-02-21 2020-02-10 对特定路线上的特定位置进行识别的方法及电子设备 WO2020168929A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP20758903.7A EP3923634B1 (en) 2019-02-21 2020-02-10 Method for identifying specific position on specific route and electronic device
US17/432,807 US11871328B2 (en) 2019-02-21 2020-02-10 Method for identifying specific position on specific route and electronic device

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201910129795.9A CN109890067B (zh) 2019-02-21 2019-02-21 对特定路线上的特定位置进行识别的方法及电子设备
CN201910129795.9 2019-02-21

Publications (1)

Publication Number Publication Date
WO2020168929A1 true WO2020168929A1 (zh) 2020-08-27

Family

ID=66928704

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2020/074592 WO2020168929A1 (zh) 2019-02-21 2020-02-10 对特定路线上的特定位置进行识别的方法及电子设备

Country Status (4)

Country Link
US (1) US11871328B2 (zh)
EP (1) EP3923634B1 (zh)
CN (2) CN113163470B (zh)
WO (1) WO2020168929A1 (zh)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113079252A (zh) * 2021-03-29 2021-07-06 支付宝(杭州)信息技术有限公司 地铁乘坐提醒方法及装置
CN113407569A (zh) * 2021-06-29 2021-09-17 北京小米移动软件有限公司 信息处理方法、装置以及存储介质
CN114268919A (zh) * 2021-11-12 2022-04-01 北京航空航天大学 一种基于加权k近邻的信道状态信息指纹定位方法
CN114979938A (zh) * 2021-02-20 2022-08-30 深圳市万普拉斯科技有限公司 一种网络重连方法、装置及移动终端
US11876849B2 (en) 2019-10-29 2024-01-16 Huawei Technologies Co., Ltd. Media service processing method and electronic device

Families Citing this family (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113163470B (zh) * 2019-02-21 2023-06-09 荣耀终端有限公司 对特定路线上的特定位置进行识别的方法及电子设备
CN115396964A (zh) * 2019-12-11 2022-11-25 华为技术有限公司 一种网络切换方法及电子设备
CN113316199B (zh) * 2020-02-26 2023-06-20 华为技术有限公司 一种连接管理方法及相关设备
US11438886B2 (en) * 2020-02-27 2022-09-06 Psj International Ltd. System for establishing positioning map data and method for the same
CN111654824B (zh) * 2020-05-29 2023-07-25 Oppo广东移动通信有限公司 网络状况提示方法、装置、电子设备及存储介质
CN117221958A (zh) * 2020-09-16 2023-12-12 华为技术有限公司 数据缓存方法及相关装置
CN114268998B (zh) * 2020-09-16 2023-11-10 华为技术有限公司 数据缓存方法及相关装置
CN112783731B (zh) * 2021-01-29 2023-09-05 北京百度网讯科技有限公司 异常设备检测方法、装置、设备和存储介质
CN112926862B (zh) * 2021-03-04 2024-10-01 上海第二工业大学 一种新能源汽车动力电池召回选址的决策方法
CN113063433B (zh) * 2021-03-24 2024-10-15 维沃移动通信有限公司 导航路线显示方法及装置
CN113596987A (zh) * 2021-07-26 2021-11-02 未鲲(上海)科技服务有限公司 业务办理方法、装置、计算机设备及介质
CN114585037B (zh) * 2022-04-12 2024-02-27 深圳市锐尔觅移动通信有限公司 网络制式切换方法及装置、终端设备、计算机可读介质
CN116962794A (zh) * 2022-04-19 2023-10-27 华为技术有限公司 应用优化方法及电子设备
US20240062774A1 (en) * 2022-08-17 2024-02-22 Caterpillar Inc. Detection of audio communication signals present in a high noise environment
CN116744328B (zh) * 2022-10-17 2024-04-23 荣耀终端有限公司 一种网络加速方法和装置

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102595560A (zh) * 2012-02-17 2012-07-18 华为技术有限公司 一种搜网和选网的方法、装置及系统
CN104640224A (zh) * 2013-11-12 2015-05-20 华为技术有限公司 一种网络数据传输方法、装置及系统
US20150379993A1 (en) * 2014-06-30 2015-12-31 Samsung Electronics Co., Ltd. Method of providing voice command and electronic device supporting the same
CN109890067A (zh) * 2019-02-21 2019-06-14 华为技术有限公司 对特定路线上的特定位置进行识别的方法及电子设备

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9596670B2 (en) * 2013-01-16 2017-03-14 Apple Inc. Location assisted service capability monitoring
KR102091265B1 (ko) * 2013-07-10 2020-03-19 삼성전자주식회사 무선 통신 시스템에서 빔포밍을 이용한 다중 셀 통신 장치 및 방법
CN104350784A (zh) * 2014-03-18 2015-02-11 华为终端有限公司 一种终端搜网方法及终端
EP3251295A1 (en) * 2015-01-27 2017-12-06 Nokia Solutions and Networks Oy Traffic flow monitoring
CN105307240B (zh) * 2015-09-29 2018-10-02 北京元心科技有限公司 基于位置搜索移动通信网络的方法及装置
US10326521B2 (en) * 2016-08-25 2019-06-18 Global Eagle Entertainment Inc.. Switching communication networks aboard a moving vessel based on control of priority
CN109104755A (zh) * 2017-06-20 2018-12-28 中兴通讯股份有限公司 一种网络搜索方法、移动终端和网络搜索装置
US11576022B2 (en) * 2017-06-22 2023-02-07 Telefonaktiebolaget Lm Ericsson (Publ) Handling communication of data in a bluetooth low energy (BLE), mesh network
CN108510011B (zh) * 2018-05-03 2020-05-29 浙江大学 一种基于手机多传感器的用户出行方式分析方法
CN109041148B (zh) * 2018-08-27 2021-01-08 维沃移动通信有限公司 一种移动终端操作方法及移动终端
CN112369062A (zh) * 2018-08-27 2021-02-12 Oppo广东移动通信有限公司 一种ui显示方法、装置、终端设备及存储介质

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102595560A (zh) * 2012-02-17 2012-07-18 华为技术有限公司 一种搜网和选网的方法、装置及系统
CN104640224A (zh) * 2013-11-12 2015-05-20 华为技术有限公司 一种网络数据传输方法、装置及系统
US20150379993A1 (en) * 2014-06-30 2015-12-31 Samsung Electronics Co., Ltd. Method of providing voice command and electronic device supporting the same
CN109890067A (zh) * 2019-02-21 2019-06-14 华为技术有限公司 对特定路线上的特定位置进行识别的方法及电子设备

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3923634A4

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11876849B2 (en) 2019-10-29 2024-01-16 Huawei Technologies Co., Ltd. Media service processing method and electronic device
CN114979938A (zh) * 2021-02-20 2022-08-30 深圳市万普拉斯科技有限公司 一种网络重连方法、装置及移动终端
CN113079252A (zh) * 2021-03-29 2021-07-06 支付宝(杭州)信息技术有限公司 地铁乘坐提醒方法及装置
CN113079252B (zh) * 2021-03-29 2023-10-27 支付宝(杭州)信息技术有限公司 地铁乘坐提醒方法及装置
CN113407569A (zh) * 2021-06-29 2021-09-17 北京小米移动软件有限公司 信息处理方法、装置以及存储介质
CN114268919A (zh) * 2021-11-12 2022-04-01 北京航空航天大学 一种基于加权k近邻的信道状态信息指纹定位方法
CN114268919B (zh) * 2021-11-12 2022-10-18 北京航空航天大学 一种基于加权k近邻的信道状态信息指纹定位方法

Also Published As

Publication number Publication date
CN113163470A (zh) 2021-07-23
US20220124597A1 (en) 2022-04-21
CN109890067A (zh) 2019-06-14
CN109890067B (zh) 2021-03-30
EP3923634A1 (en) 2021-12-15
CN113163470B (zh) 2023-06-09
EP3923634A4 (en) 2022-04-06
US11871328B2 (en) 2024-01-09
EP3923634B1 (en) 2023-06-21

Similar Documents

Publication Publication Date Title
WO2020168929A1 (zh) 对特定路线上的特定位置进行识别的方法及电子设备
EP3872807B1 (en) Voice control method and electronic device
CN110910872B (zh) 语音交互方法及装置
WO2020177622A1 (zh) Ui组件显示的方法及电子设备
WO2021000807A1 (zh) 一种应用程序中等待场景的处理方法和装置
WO2021213164A1 (zh) 应用界面交互方法、电子设备和计算机可读存储介质
EP4064284A1 (en) Voice detection method, prediction model training method, apparatus, device, and medium
WO2021017901A1 (zh) 一种屏幕显示方法及电子设备
WO2020259554A1 (zh) 可进行学习的关键词搜索方法和电子设备
CN111222836B (zh) 一种到站提醒方法及相关装置
WO2021218429A1 (zh) 应用窗口的管理方法、终端设备及计算机可读存储介质
WO2021082815A1 (zh) 一种显示要素的显示方法和电子设备
CN111881315A (zh) 图像信息输入方法、电子设备及计算机可读存储介质
CN111835904A (zh) 一种基于情景感知和用户画像开启应用的方法及电子设备
CN115333941B (zh) 获取应用运行情况的方法及相关设备
WO2023273543A1 (zh) 一种文件夹管理方法及装置
WO2022166435A1 (zh) 分享图片的方法和电子设备
CN116521033B (zh) 图片分享或分类方法、电子设备及存储介质
WO2022166550A1 (zh) 数据传输方法及电子设备
WO2024012346A1 (zh) 任务迁移的方法、电子设备和系统
WO2022166421A1 (zh) 搜索方法和电子设备
WO2022206762A1 (zh) 一种显示方法、电子设备和系统
CN116204145A (zh) 一种电子设备投屏的方法、通信装置以及电子设备
CN118646821A (zh) 一种卡片显示方法及电子设备
CN116700568A (zh) 删除对象的方法及电子设备

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20758903

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2020758903

Country of ref document: EP

Effective date: 20210907