Method of identifying an elevator scenario and electronic device

Abstract

The application relates to the terminal field and provides a method for identifying an elevator scene and an electronic device. The method is applied to the electronic device and comprises the following steps: acquiring first data and second data, the first data is data collected by a first sensor, the second data is data collected by a second sensor, and the first sensor is different from the second sensor; obtaining a first identification result based on the first data and the second data, the first identification result is used for indicating that the electronic device is in an elevator scene, or the first identification result is used for indicating that the electronic device is not in the elevator scene; and running an elevator mode in the case of detecting that the electronic device is in the elevator scene, the elevator mode is a mode in which the electronic device performs network switching based on a full-network aggregation acceleration technology. According to the technical scheme, the accuracy of identifying whether the electronic device is in the elevator scene can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the terminal field, in particular to a method for identifying an elevator scenario and an electronic device. BACKGROUND

[0002] At present, the whole network aggregation acceleration technology (Link Turbo) can realize the fusion of mobile data communication and fixed network data communication technology, and through the end-cloud collaborative network aggregation mode, it can bring users an aggregated high network speed and stable low latency mobile Internet experience under variable network conditions. However, for some specific scenarios, such as elevator scenarios, subway scenarios, or tunnel scenarios, etc., the current identification accuracy of electronic devices is low, which cannot accurately identify these scenarios and quickly enable the whole network aggregation acceleration technology in the electronic device, so that the user's Internet experience in some specific scenarios is poor; for example, in the above-mentioned specific scenarios, the user's Internet access will appear to be stuck.

[0003] Therefore, how to accurately identify the scenario (for example, the elevator scenario) in which the electronic device is located has become a problem to be solved. SUMMARY

[0004] The present application provides a method for identifying an elevator scenario and an electronic device, which can accurately identify the scenario in which the electronic device is located and improve the accuracy of identifying whether the electronic device is in an elevator scenario.

[0005] In a first aspect, a method for identifying an elevator scenario is provided, applied to an electronic device, comprising:

[0006] Obtaining first data and second data, the first data being data collected by a first sensor, and the second data being data collected by a second sensor, the first sensor being different from the second sensor;

[0007] Based on the first data and the second data, a first identification result is obtained, the first identification result being used to indicate that the electronic device is in an elevator scenario, or the first identification result being used to indicate that the electronic device is not in an elevator scenario;

[0008] In the case where it is detected that the electronic device is in the elevator scenario, an elevator mode is run, the elevator mode being a mode in which the electronic device performs network switching based on the whole network aggregation acceleration technology.

[0009] It should also be understood that the full-network aggregation acceleration technology (Link Turbo) can refer to a technology for realizing the fusion of mobile data communication and fixed network data communication; through the end-cloud collaborative network aggregation, an aggregated high network speed and stable low latency mobile Internet experience is brought to users under variable network conditions. For example, when playing a game, if the wireless network fluctuates, the mobile cellular network will quickly intervene to reduce the latency caused by the wireless network fluctuation and ensure the smoothness of the game; for another example, when downloading a game or a video, if the wireless network is poor and the download speed is too slow, the mobile cellular network will also be automatically started, and the download speed will be accelerated in parallel with the wireless network.

[0010] In the embodiments of the present application, the first data collected by the air pressure sensor and the second data collected by the acceleration sensor can be obtained; since the elevator scene is directly identified by the data of the acceleration sensor, it is impossible to avoid the collection of error data by the acceleration sensor in the electronic device due to the user's accidental touch, thereby causing the accuracy of identifying the elevator scene to be low; for the air pressure sensor, even if the user has an accidental touch operation on the electronic device, the data of the air pressure sensor is usually unchanged; that is, the accuracy of the data of the air pressure sensor is high; therefore, the accuracy of identifying whether the electronic device is in the elevator scene based on the data of the air pressure sensor and the data of the acceleration sensor is also higher.

[0011] It should be understood that the method provided by the embodiments of the present application is also applicable to identifying other closed scenes or semi-closed scenes (for example, a subway scene or a tunnel scene), and the network signal of the closed scene or semi-closed scene is usually poor and is prone to cause the problem of lagging of the electronic device in online surfing; after identifying these scenes, the electronic device can start the full-network aggregation algorithm to ensure a smooth online surfing experience.

[0012] In combination with the first aspect, in some implementations of the first aspect, the first sensor is an air pressure sensor.

[0013] In a possible implementation, the wearable device includes an air pressure sensor, and the electronic device can obtain the data of the air pressure sensor collected by the wearable device.

[0014] In the embodiments of the present application, the wearable device can include an air pressure sensor; the air pressure sensor can collect air pressure data, and the electronic device can obtain the air pressure sensor collected by the wearable device, so as to obtain an identification result based on the data of the air pressure sensor and the data of the acceleration sensor.

[0015] In a possible implementation, the electronic device includes an air pressure sensor.

[0016] In combination with the first aspect, in some implementations of the first aspect, the obtaining of the identification result based on the first data and the second data comprises:

[0017] obtaining a value of a count parameter based on the second data, the count parameter being used to represent that the electronic device moves in a first direction and has an acceleration;

[0018] obtaining the first identification result based on the first data and the value of the count parameter.

[0019] In the embodiments of the present application, the elevator scenario is identified by the value of the count parameter (for example, Move Count); if the elevator scenario is directly identified by the data of the acceleration sensor, the error data collected by the acceleration sensor due to the user's mis-touch cannot be avoided, thereby resulting in a low accuracy of identifying the elevator scenario; compared with directly identifying the elevator scenario by the data of the acceleration sensor, identifying the elevator scenario by the value of the count parameter can improve the accuracy of the identification result; secondly, when the elevator scenario is directly identified based on the data of the acceleration sensor, in order to reduce the error in the data collected by the acceleration sensor, multiple frames of data of the acceleration sensor need to be obtained, so that the waiting time of the electronic device is relatively long, thereby resulting in that the elevator scenario cannot be quickly identified; based on the method for identifying the elevator scenario of the present application, the elevator scenario can be quickly identified when the elevator scenario is identified by the value of the count parameter; therefore, based on the method for identifying the elevator scenario of the present application, the elevator scenario can be quickly and accurately identified, the waiting time of the user is shortened; and after the electronic device enters the elevator, the full-network aggregation acceleration technology of the electronic device can be quickly triggered, thereby improving the user's online experience.

[0020] In a possible implementation manner, the count parameter can be Move Count, and Move Count is used to represent that the movement is in one direction and there is an acceleration; for example, if the first upward movement has an acceleration, Move Count=A; and if the second upward movement has an acceleration, Move Count=A+1.

[0021] With reference to the first aspect, in some implementation manners of the first aspect, the obtaining the first identification result based on the first data and the value of the count parameter comprises:

[0022] determining that the first data satisfies a first preset condition and the value of the count parameter is greater than a first preset threshold, and the first identification result is used to indicate that the electronic device is in the elevator scenario;

[0023] determining that the first data does not satisfy the first preset condition, or the value of the count parameter is less than or equal to the first preset threshold, and the first identification result is used to indicate that the electronic device is not in the elevator scenario.

[0024] In the embodiments of the present application, in order to avoid the inaccuracy of the recognition result caused by the user's mis-touch, it is determined that the electronic device is in the elevator scene when the data of the count parameter is greater than the first threshold, thereby improving the accuracy of the recognition result.

[0025] With reference to the first aspect, in some implementations of the first aspect, the determining that the first data satisfies the first preset condition comprises:

[0026] obtaining height data based on the first data, the height data being used to indicate the distance between the electronic device and the ground;

[0027] determining that the height data is less than a second preset threshold and / or the change value of the first data is greater than a third preset threshold within a preset time interval.

[0028] In the embodiments of the present application, if the electronic device is in the airplane scene, the data of the air pressure sensor will change after the airplane takes off, and the change value of the data of the air pressure sensor can be greater than the third preset threshold, but at this time the electronic device is not in the elevator scene; in the embodiments of the present application, the determination of whether the height data is less than the second preset threshold is to avoid the electronic device being in the airplane scene, thereby improving the accuracy of the recognition result.

[0029] With reference to the first aspect, in some implementations of the first aspect, the obtaining the numerical value of the count parameter based on the second data comprises:

[0030] performing filter processing on the second data to obtain third data;

[0031] obtaining the numerical value of the count parameter based on the third data.

[0032] In the embodiments of the present application, the filter processing on the data collected by the acceleration sensor can eliminate the error data in the data, thereby improving the accuracy of the data collected by the acceleration sensor.

[0033] In a possible implementation, the third data is obtained by processing the second data through a band-pass filter and a low-pass filter.

[0034] In the embodiments of this application, a bandpass filter is used to filter the data, thereby avoiding the possibility of shaking of the electronic device due to external accidental factors. This filters the acquired accelerometer data and improves its accuracy. Furthermore, a low-pass filter is used to filter the data, thereby preventing minor internal movements of the electronic device from altering the accelerometer data. In other words, to eliminate error data introduced by minor internal movements of the electronic device, the acquired accelerometer data is filtered, further improving its accuracy.

[0035] In conjunction with the first aspect, some implementations of the first aspect also include:

[0036] Acquire a first detection result and a first network identifier. The first detection result is used to indicate the user's motion state. The user is carrying the electronic device. The first network identifier is the network identifier of the network currently accessed by the electronic device.

[0037] Based on the first data and / or the second data, the first detection result and the first network identifier, a second identification result is obtained, which is used to indicate that the electronic device is currently in a waiting elevator scenario.

[0038] In one possible implementation, the user can carry an electronic device and obtain the motion state of the electronic device, which in turn obtains the motion state of the user carrying the electronic device.

[0039] In one possible implementation, other mobile devices (e.g., intelligent robots) can carry electronic devices to obtain the motion state of other mobile devices, i.e., to obtain the motion state of other mobile devices carrying electronic devices.

[0040] In one possible implementation, the first detection result can be obtained through a gradient boosting tree model.

[0041] In one possible implementation, a motion state detection model can be obtained through training. The motion state detection model can be a classification model; for example, the motion detection model can be a pre-trained gradient boosting decision tree (GBDT) model.

[0042] In a possible implementation, data features are extracted by obtaining a variance, a mean value, a first-order difference, a second-order difference, or a third-order difference of values of the acceleration sensor in a preset time length, and the data features are input into a pre-trained GBDT model to obtain a motion state detection result; the motion state detection result can include: static, running (for example, walking or running), and optionally, the motion state detection result can include just exiting a motion (for example, just exiting walking or just exiting running).

[0043] With reference to the first aspect, in some implementations of the first aspect, the motion state includes a static state, a first motion state, and a second motion state, and a speed of the second motion state is greater than a speed of the first motion state.

[0044] With reference to the first aspect, in some implementations of the first aspect, obtaining the second identification result based on the first data and / or the second data, the first detection result, and the first network identifier includes:

[0045] obtaining the second identification result when it is determined that the second data satisfies a second preset condition, the first detection result satisfies a third preset condition, and the first network identifier satisfies a fourth preset condition;

[0046] The second preset condition refers to that a predicted acceleration of the electronic device obtained based on the second data is greater than a fourth preset threshold; the third preset condition refers to that a time length in which the user exits the first motion state or the user exits the second motion state is less than a fifth preset threshold; and the fourth preset condition refers to that the first network identifier matches a network identifier in a network identifier feature library, and the network identifier feature library includes identifiers of local area networks covered by a region where the elevator is located.

[0047] In the embodiments of the present application, the identification result of the elevator scene can be obtained by fusing the first data of the air pressure sensor and / or the second data of the acceleration sensor, the first detection result, and the first network identifier, and other types of data, that is, multi-modal data. Because the method of the embodiments of the present application can obtain the identification result based on the multi-modal data, the accuracy of the identification result can be improved.

[0048] With reference to the first aspect, in some implementations of the first aspect, the method further includes:

[0049] obtaining a second detection result, the second detection result being that the motion state of the user is the first motion state and a time length of the first motion state is greater than a sixth preset threshold;

[0050] exiting the elevator mode based on the second detection result.

[0051] In the embodiments of the present application, since the electronic device can increase the signal search power of the electronic device after running the elevator mode, running the elevator mode causes the electronic device to have large power consumption; after the electronic device runs the elevator mode, a second detection result can be obtained; whether the electronic device exits the elevator mode is determined based on the second detection result, thereby saving the power consumption of the electronic device.

[0052] In combination with the first aspect, in some implementations of the first aspect, the method further includes:

[0053] obtaining a third detection result and a second network identifier, the third detection result being that the motion state of the user is the first motion state and the duration of the first motion state is greater than a seventh preset threshold, and the second network identifier being different from the first network identifier;

[0054] exiting the elevator mode based on the third detection result and the second network identifier.

[0055] In the embodiments of the present application, since the electronic device can increase the signal search power of the electronic device after running the elevator mode, running the elevator mode causes the electronic device to have large power consumption; after the electronic device runs the elevator mode, a third detection result and a second network identifier can be obtained; whether the electronic device exits the elevator mode is determined based on the third detection result and the second network identifier, thereby saving the power consumption of the electronic device.

[0056] In combination with the first aspect, in some implementations of the first aspect, the method further includes:

[0057] In a case where the first data does not satisfy the first preset condition, the elevator mode is exited.

[0058] In the embodiments of the present application, since the electronic device can increase the signal search power of the electronic device after running the elevator mode, running the elevator mode causes the electronic device to have large power consumption; after the electronic device runs the elevator mode, first data can be obtained; whether the electronic device exits the elevator mode is determined based on the first data, thereby saving the power consumption of the electronic device.

[0059] In combination with the first aspect, in some implementations of the first aspect, the method further includes:

[0060] applying for a first resource, the first resource being used for the electronic device to run the elevator mode.

[0061] It should be understood that the first resource can refer to a memory resource pre-applied in the electronic device, and the first resource can be used for the electronic device to run the elevator mode.

[0062] In the embodiments of the present application, the identification result obtained when the elevator scene is identified includes a waiting elevator scene; when the identification result is the waiting elevator scene, the electronic device can pre-apply the first resource; when the identification result is in the elevator scene, the electronic device can directly start the full network aggregation acceleration technology through the pre-applied first resource; since the method of the embodiments of the present application can identify that the electronic device is in the waiting elevator scene; and the electronic device can apply the first resource for executing the full network aggregation acceleration technology when the electronic device is in the waiting elevator scene; therefore, through the method of identifying the elevator scene of the embodiments of the present application, the elevator scene can be accurately identified; and the time length of the user waiting for a signal in the elevator scene is shortened; so that the electronic device can quickly trigger the full network aggregation acceleration technology of the electronic device after entering the elevator, improving the online experience.

[0063] With reference to the first aspect, in some implementations of the first aspect, the air pressure sensor is a sensor in a wearable device.

[0064] With reference to the first aspect, in some implementations of the first aspect, the electronic device includes a transmission module, and the transmission module is located in an application framework layer, and the obtaining of the first data and the second data includes:

[0065] receiving, by the transmission module, the first data sent by the wearable device.

[0066] With reference to the first aspect, in some implementations of the first aspect, further comprising:

[0067] detecting a first operation;

[0068] in response to the first operation, displaying a first interface, and the first interface includes a low power mode, and the low power mode includes turning off the elevator mode.

[0069] With reference to the first aspect, in some implementations of the first aspect, when the electronic device runs the elevator mode, further comprising:

[0070] displaying a first prompt information, and the first prompt information is used to instruct the electronic device to start the elevator mode.

[0071] With reference to the first aspect, in some implementations of the first aspect, when the electronic device runs the elevator mode, further comprising:

[0072] displaying a first icon, and the first icon is used to instruct the electronic device to start the elevator mode.

[0073] In a second aspect, an electronic device is provided, which includes one or more processors and a memory; the memory is coupled to the one or more processors, and is configured to store computer program codes including computer instructions; the one or more processors are configured to invoke the computer instructions to cause the electronic device to perform the following steps:

[0074] obtaining first data and second data, the first data being data collected by a first sensor, and the second data being data collected by a second sensor, the first sensor being different from the second sensor;

[0075] obtaining a first recognition result based on the first data and the second data, the first recognition result being used to indicate that the electronic device is in an elevator scenario, or the first recognition result being used to indicate that the electronic device is not in the elevator scenario;

[0076] in a case where it is detected that the electronic device is in the elevator scenario, running an elevator mode, the elevator mode being a mode in which the electronic device performs network switching based on a full-network aggregation acceleration technology.

[0077] With reference to the second aspect, in some implementations of the second aspect, the first sensor is a barometric pressure sensor.

[0078] With reference to the second aspect, in some implementations of the second aspect, the one or more processors are configured to invoke the computer instructions to cause the electronic device to perform the following steps:

[0079] obtaining a value of a count parameter based on the second data, the count parameter being used to indicate that the electronic device is moving in a first direction and has an acceleration;

[0080] obtaining the first recognition result based on the first data and the value of the count parameter.

[0081] With reference to the second aspect, in some implementations of the second aspect, the one or more processors are configured to invoke the computer instructions to cause the electronic device to perform the following steps:

[0082] determining that the first data satisfies a first preset condition, and the value of the count parameter is greater than a first preset threshold, the first recognition result being used to indicate that the electronic device is in the elevator scenario;

[0083] determining that the first data does not satisfy the first preset condition, or the value of the count parameter is less than or equal to the first preset threshold, the first recognition result being used to indicate that the electronic device is not in the elevator scenario.

[0084] With reference to the second aspect, in some implementations of the second aspect, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0085] obtain height data based on the first data, the height data being used to indicate a distance between the electronic device and a ground;

[0086] determine that the height data is less than a second preset threshold value, and / or a change value of the first data is greater than a third preset threshold value within a preset time interval.

[0087] With reference to the second aspect, in some implementations of the second aspect, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0088] perform filter processing on the second data to obtain third data;

[0089] obtain a numerical value of the counting parameter based on the third data.

[0090] With reference to the second aspect, in some implementations of the second aspect, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0091] obtain a first detection result and a first network identifier, the first detection result being used to indicate a motion state of a user carrying the electronic device, and the first network identifier being a network identifier of a network currently accessed by the electronic device;

[0092] obtain a second identification result based on the first data and / or the second data, the first detection result, and the first network identifier, the second identification result being used to indicate that the electronic device is currently in an elevator waiting scenario.

[0093] With reference to the second aspect, in some implementations of the second aspect, the motion state includes a stationary state, a first motion state, and a second motion state, a speed of the second motion state being greater than a speed of the first motion state.

[0094] With reference to the second aspect, in some implementations of the second aspect, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0095] obtain the second identification result when it is determined that the second data satisfies a second preset condition, the first detection result satisfies a third preset condition, and the first network identifier satisfies a fourth preset condition;

[0096] The second preset condition refers to that the predicted acceleration of the electronic device based on the second data is greater than a fourth preset threshold; the third preset condition refers to that the user exits the first motion state or a time length for the user to exit the second motion state is less than a fifth preset threshold; and the fourth preset condition refers to that the first network identifier matches a network identifier in a network identifier feature library, and the network identifier feature library includes identifiers of local area networks covered by an area where the elevator is located.

[0097] With reference to the second aspect, in some implementations of the second aspect, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0098] obtain a second detection result, the second detection result being that the motion state of the user is the first motion state and a time length for the first motion state to last is greater than a sixth preset threshold;

[0099] exit the elevator mode based on the second detection result.

[0100] With reference to the second aspect, in some implementations of the second aspect, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0101] obtain a third detection result and a second network identifier, the third detection result being that the motion state of the user is the first motion state and a time length for the first motion state to last is greater than a seventh preset threshold, and the second network identifier being different from the first network identifier;

[0102] exit the elevator mode based on the third detection result and the second network identifier.

[0103] With reference to the second aspect, in some implementations of the second aspect, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0104] in a case where the first data does not satisfy the first preset condition, exit the elevator mode.

[0105] With reference to the second aspect, in some implementations of the second aspect, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0106] apply for a first resource, the first resource being used for the electronic device to run an elevator mode.

[0107] With reference to the second aspect, in some implementations of the second aspect, the air pressure sensor is a sensor in a wearable device.

[0108] With reference to the second aspect, in some implementations of the second aspect, the electronic device includes a transmission module, the transmission module is located at an application framework layer, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0109] receive, by the transmission module, the first data sent by the wearable device.

[0110] With reference to the second aspect, in some implementations of the second aspect, it is detected that a first operation;

[0111] In response to the first operation, display a first interface, the first interface includes a low power mode, the low power mode includes turning off the elevator mode.

[0112] With reference to the second aspect, in some implementations of the second aspect, when the electronic device runs the elevator mode, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0113] display a first prompt information, the first prompt information is used to instruct the electronic device to turn on the elevator mode.

[0114] With reference to the second aspect, in some implementations of the second aspect, when the electronic device runs the elevator mode, the one or more processors invoke the computer instructions to cause the electronic device to perform:

[0115] display a first icon, the first icon is used to instruct the electronic device to turn on the elevator mode.

[0116] The third aspect provides an electronic device, including a module / unit for executing the first aspect or the method for identifying the elevator scenario in any one of the first aspect.

[0117] The fourth aspect provides an electronic device, including one or more processors, a memory; the memory is coupled with the one or more processors, the memory is used to store computer program codes, the computer program codes include computer instructions, the one or more processors invoke the computer instructions to cause the electronic device to execute the first aspect or any one of the methods in the first aspect.

[0118] The fifth aspect provides a chip system, applied to an electronic device, the chip system includes one or more processors, the processor is used to invoke computer instructions to cause the electronic device to execute the first aspect or any one of the methods in the first aspect.

[0119] In a sixth aspect, a computer-readable storage medium is provided, which stores computer program codes. When the computer program codes are run by an electronic device, the electronic device is caused to perform the first aspect or any of the methods in the first aspect.

[0120] In a seventh aspect, a computer program product is provided, which includes computer program codes. When the computer program codes are run by an electronic device, the electronic device is caused to perform the first aspect or any of the methods in the first aspect.

[0121] In the embodiments of the present application, the first data collected by the air pressure sensor and the second data collected by the acceleration sensor can be acquired. Since the elevator scenario is directly identified by the data of the acceleration sensor, it is impossible to avoid that the acceleration sensor of the electronic device collects error data due to the user's accidental touch, thereby causing the accuracy of identifying the elevator scenario to be low. For the air pressure sensor, even if the user performs an accidental touch operation on the electronic device, the data of the air pressure sensor is generally unchanged. That is, the accuracy of the data of the air pressure sensor is high. Therefore, the accuracy of identifying whether the electronic device is in the elevator scenario based on the data of the air pressure sensor and the data of the acceleration sensor is also higher.

[0122] In addition, in the embodiments of the present application, the identification result of identifying the elevator scenario includes being in the elevator scenario, not being in the elevator scenario, or being in the waiting elevator scenario. When the electronic device is in the waiting elevator scenario, the electronic device can pre-apply the first resource. When the electronic device identifies that the electronic device is in the elevator scenario, the electronic device can directly execute the Link Turbo by using the pre-applied resource. Since the waiting elevator scenario of the electronic device can be identified in the embodiments of the present application, the Link Turbo resource is applied when the electronic device is in the waiting elevator scenario, so that the user can quickly trigger the Link Turbo of the electronic device after entering the elevator. Therefore, the waiting time of the user is shortened, and the user's online experience is improved. BRIEF DESCRIPTION OF DRAWINGS

[0123] Figure 1 FIG. 1 is a schematic diagram of a hardware system of an electronic device suitable for the present application;

[0124] Figure 2 FIG. 1 is a schematic diagram of a hardware system of an electronic device suitable for the present application;

[0125] Figure 3 FIG. 1 is a schematic diagram of a hardware system of an electronic device suitable for the present application;

[0126] Figure 4 FIG. 1 is a schematic diagram of a hardware system of an electronic device suitable for the present application;

[0127] Figure 5 is a schematic diagram of an application scenario suitable for embodiments of the present application;

[0128] Figure 6 is a schematic diagram of an application scenario suitable for embodiments of the present application;

[0129] Figure 7 is a schematic flow chart of a method for identifying an elevator scenario provided by embodiments of the present application;

[0130] Figure 8 is a schematic flow chart of a method for identifying an elevator scenario provided by embodiments of the present application;

[0131] Figure 9 is a schematic flow chart of a method for identifying an elevator scenario provided by embodiments of the present application;

[0132] Figure 10 is a schematic flow chart of a method for exiting an elevator mode provided by embodiments of the present application;

[0133] Figure 11 is a schematic diagram of a graphical user interface suitable for embodiments of the present application;

[0134] Figure 12 is a schematic diagram of a graphical user interface suitable for embodiments of the present application;

[0135] Figure 13 is a schematic diagram of a graphical user interface suitable for embodiments of the present application;

[0136] Figure 14 is a schematic diagram of a graphical user interface suitable for embodiments of the present application;

[0137] Figure 15 is a schematic diagram of a graphical user interface suitable for embodiments of the present application;

[0138] Figure 16 is a schematic diagram of a graphical user interface suitable for embodiments of the present application;

[0139] Figure 17 is a structural schematic diagram of an electronic device provided by embodiments of the present application;

[0140] Figure 18 is a structural schematic diagram of an electronic device provided by embodiments of the present application. DETAILED DESCRIPTION

[0141] In the embodiments of the present application, the terms "first", "second" and the like are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the embodiments, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0142] In order to facilitate the understanding of the embodiments of the present application, first, the related concepts involved in the embodiments of the present application are briefly described.

[0143] 1. Full network aggregation acceleration technology (Link Turbo)

[0144] Link Turbo refers to a technology for realizing the integration of mobile data communication and fixed network data communication. Through the network aggregation mode of end-cloud cooperation, it brings users an aggregated high network speed and stable low latency mobile Internet experience under variable network conditions.

[0145] Exemplarily, Link Turbo has an "intelligent link splitting mode", which can intelligently judge the wireless network condition. When it is found that the wireless network condition is poor (for example, the signal is weak, or the signal is strong but the network is congested due to multiple terminals and multiple applications sharing the network), and the application program needs to be used, Link Turbo can intelligently switch these application programs to the mobile network (automatically switch back to the wireless network after use), and the background other application programs still maintain the wireless network communication, realizing the parallel of mobile cellular data and wireless network data, and serving different application programs, and using the least traffic to speed up the application program that needs to be used immediately in a short time. Secondly, Link Turbo also supports an "intelligent link aggregation mode". When it is detected that the wireless network condition is poor, and the game download, online video playback and other large data throughput situations need to be performed, Link Turbo will simultaneously start the cellular network, so that the cellular network and the wireless network transmit data at the same time, realizing parallel acceleration, meeting the needs of high-throughput business scenarios, effectively reducing the latency, and improving the communication bandwidth. For example, when playing a game, the wireless network fluctuates, at which time the mobile cellular network quickly intervenes to reduce the latency caused by the fluctuation of the wireless network, and guarantees the smoothness of the game. For another example, when downloading a game or a video, the wireless network is poor, and the download speed is too slow, at which time the mobile cellular network is also automatically started, and the two networks are parallel to speed up the download speed.

[0146] It should be understood that the full network aggregation acceleration technology can also be referred to as a multi-network cooperation technology.

[0147] 2. Elevator fence

[0148] The range of the elevator fence refers to the area where the elevator door is located.

[0149] 3. Band-pass filter

[0150] A band-pass filter is a device that allows a certain band of frequencies to pass through while blocking others; for example, an LC circuit consisting of a resistor, inductor, and capacitor can be an analog band-pass filter.

[0151] 4. Low-pass filter

[0152] A low-pass filter is a type of filtering that allows low-frequency signals to pass through normally, while blocking or attenuating high-frequency signals above a certain threshold.

[0153] 5. Low-pass filter

[0154] A low-pass filter is an electronic filter that allows signals below a certain cutoff frequency to pass through, but blocks signals above the cutoff frequency.

[0155] 6. Exponential moving average

[0156] Exponential moving average, also known as exponentially weighted moving average, is a method used to estimate the local mean of a variable, taking into account the historical values over a certain period of time. It is often used to smooth out random fluctuations in a time series.

[0157] 7. Moving standard deviation

[0158] Moving standard deviation is a measure of the dispersion of a variable from its moving average level.

[0159] The method for identifying an elevator scenario and the electronic device according to the embodiments of the present application will be described below with reference to the accompanying drawings.

[0160] Figure 1 A hardware system suitable for the electronic device of the present application is shown.

[0161] Electronic device 100 can be a mobile phone, smart screen, tablet computer, wearable electronic device, in-vehicle electronic device, augmented reality (AR) device, virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), projector, etc. This application embodiment does not limit the specific type of electronic device 100.

[0162] Electronic device 100 may include processor 110, external memory interface 120, internal memory 121, universal serial bus (USB) interface 130, charging management module 140, power management module 141, battery 142, antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, sensor module 180, button 190, motor 191, indicator 192, camera 193, display screen 194, and subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0163] For example, the audio module 170 is used to convert digital audio information into analog audio signal output, and can also be used to convert analog audio input into digital audio signal. The audio module 170 can also be used to encode and decode audio signals. In some embodiments, the audio module 170 or some functional modules of the audio module 170 may be located in the processor 110.

[0164] For example, in an embodiment of this application, the audio module 170 can send audio data collected by the microphone to the processor 110.

[0165] It should be noted that, Figure 1 The structure shown does not constitute a specific limitation on the electronic device 100. In other embodiments of this application, the electronic device 100 may include... Figure 1 The components shown may include more or fewer components, or the electronic device 100 may include...Figure 1 Some of the components shown can be combined, or implemented in hardware, software, or a combination of both. Figure 1 Some of the components shown can be combined, or implemented in hardware, software, or a combination of both. Figure 1 The components shown can be implemented in hardware, software, or a combination of both.

[0166] The processor 110 can include one or more processing units. For example, the processor 110 can include at least one of an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, a neural-network processing unit (NPU). Different processing units can be independent devices or integrated devices. The controller can generate operation control signals according to instruction opcodes and timing signals, and complete the control of fetching and executing instructions.

[0167] The processor 110 can also be provided with a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory can save instructions or data that the processor 110 has just used or repeatedly uses. If the processor 110 needs to use the instructions or data again, it can directly call from the memory. This avoids repeated access and reduces the waiting time of the processor 110, thereby improving the efficiency of the system.

[0168] Exemplarily, the processor 110 can be configured to execute the method for identifying an elevator scene according to the embodiments of the present application. For example, the processor 110 can be configured to: obtain first data and second data, the first data being data collected by a first sensor, and the second data being data collected by a second sensor, the first sensor and the second sensor being different; obtain a first identification result based on the first data and the second data, the first identification result being used to indicate that the electronic device is in an elevator scene, or the first identification result being used to indicate that the electronic device is not in an elevator scene; and in a case where it is detected that the electronic device is in an elevator scene, run an elevator mode, the elevator mode being a mode in which the electronic device performs network switching based on a full-network aggregation acceleration technology.

[0169] Figure 1 The connection relationship between the modules shown is only illustrative and does not constitute a limitation on the connection relationship between the modules of the electronic device 100. Alternatively, the modules of the electronic device 100 can also adopt a combination of the above-mentioned various connection manners.

[0170] 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, etc.

[0171] The antenna 1 and the antenna 2 are used for transmitting and receiving 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 multiplexed to improve the utilization rate of the antennas. For example: the antenna 1 can be multiplexed as a diversity antenna of a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.

[0172] The electronic device 100 can implement the display function through the GPU, the display screen 194, and the application processor. The GPU is a microprocessor for image processing, connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 can include one or more GPUs that execute program instructions to generate or change display information.

[0173] The display screen 194 can be used to display images or videos.

[0174] The electronic device 100 can implement the shooting function through the ISP, the camera 193, the video codec, the GPU, the display screen 194, and the application processor, etc.

[0175] The ISP is used to process the data fed back by the camera 193. For example, when taking a photo, the shutter is opened, the light is transmitted to the camera photosensitive element through the lens, and the optical signal is converted into an electrical signal. The camera photosensitive element transmits the electrical signal to the ISP for processing, and converts it into an image visible to the naked eye. The ISP can optimize the noise, brightness, and color of the image through algorithms, and the ISP can also optimize the exposure and color temperature of the shooting scene and other parameters. In some embodiments, the ISP can be arranged in the camera 193.

[0176] The camera 193 is used to capture still images or videos. An object projects an optical image through a lens to a photosensitive element. The photosensitive element can be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, which is then passed to an ISP to be converted into a digital image signal. The ISP outputs the digital image signal to a DSP for processing. The DSP converts the digital image signal into a standard red green blue (RGB), YUV, or the like format image signal. In some embodiments, the electronic device 100 can include one or N cameras 193, where N is a positive integer greater than one.

[0177] Exemplarily, in embodiments of the present application, the electronic device can include a plurality of cameras 193, which can include front cameras and rear cameras.

[0178] The digital signal processor is used to process digital signals, in addition to processing digital image signals, it can also process other digital signals. For example, when the electronic device 100 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy, etc.

[0179] The video codec is used to compress or decompress digital videos. The electronic device 100 can support one or more video codecs. In this way, the electronic device 100 can play or record videos in multiple encoding formats, such as moving picture experts group (MPEG) 1, MPEG 2, MPEG 3, and MPEG 4.

[0180] The gyroscope sensor 180B can be used to determine the motion posture of the electronic device 100. In some embodiments, the angular velocity of the electronic device 100 around three axes (i.e., the x-axis, the y-axis, and the z-axis) can be determined by the gyroscope sensor 180B. The gyroscope sensor 180B can be used for anti-shake shooting. For example, when the shutter is pressed, the gyroscope sensor 180B detects the angle of the electronic device 100 shaking, and calculates the distance that the lens module needs to compensate according to the angle, so that the lens offsets the shaking of the electronic device 100 by reverse motion, achieving anti-shake. The gyroscope sensor 180B can also be used for navigation and motion sensing games, etc.

[0181] The acceleration sensor 180E can detect the magnitude of the acceleration of the electronic device 100 in various directions (typically, x-axis, y-axis, and z-axis). The magnitude and direction of gravity can be detected when the electronic device 100 is stationary. The acceleration sensor 180E can also be used to identify the posture of the electronic device 100 as an input parameter for applications such as a screen rotation and a pedometer.

[0182] By way of example, in embodiments of the present application, the acceleration sensor can include an accelerometer.

[0183] The distance sensor 180F is used to measure distance. The electronic device 100 can measure distance by infrared or laser. In some embodiments, for example, in a shooting scene, the electronic device 100 can use the distance sensor 180F to measure distance to achieve fast focusing.

[0184] The ambient light sensor 180L is used to sense ambient light brightness. The electronic device 100 can adaptively adjust the brightness of the display screen 194 according to the sensed ambient light brightness. 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 a pocket to prevent accidental touch.

[0185] The fingerprint sensor 180H is used to collect fingerprints. The electronic device 100 can use the collected fingerprint characteristics to achieve functions such as unlocking, accessing application lock, taking pictures, and answering incoming calls.

[0186] The touch sensor 180K, also known as a touch device. The touch sensor 180K can be disposed on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, also known as a touch screen. The touch sensor 180K is used to detect touch operations acting on or near it. The touch sensor 180K can pass the detected touch operation to the application processor to determine the touch event type. The visual output related to the touch operation can be provided through the display screen 194. In other embodiments, the touch sensor 180K can also be disposed on the surface of the electronic device 100, and disposed in a different position from the display screen 194.

[0187] Currently, the whole network aggregation acceleration technology (Link Turbo) can realize the fusion of mobile data communication and fixed network data communication technology, and through the end-cloud collaborative network aggregation, the user can have the aggregated high network speed and stable low latency mobile Internet experience under the variable network condition. However, for some specific scenarios (for example, a closed scene or a semi-closed scene with poor network signal), for example, an elevator scene, a subway scene or a tunnel scene, etc., the current identification accuracy of the electronic device is low, which cannot accurately identify these scenes and quickly start the whole network aggregation acceleration technology in the electronic device, so that the user has a poor Internet experience in some specific scenarios; for example, in the above specific scenarios, the Internet may appear to be lagging.

[0188] Therefore, the embodiments of the present application provide a method for identifying an elevator scene, by obtaining first data collected by an air pressure sensor and second data collected by an acceleration sensor to obtain a first identification result; since the elevator scene is directly identified by the data of the acceleration sensor, it is impossible to avoid that the acceleration sensor collects error data due to user mis-touch, thereby causing the accuracy of identifying the elevator scene to be low; for the air pressure sensor, even if the user has a mis-touch operation on the electronic device, the data of the air pressure sensor is usually unchanged; that is, the accuracy of the data of the air pressure sensor is high; therefore, identifying whether the electronic device is in the elevator scene based on the data of the air pressure sensor and the data of the acceleration sensor can improve the accuracy of the identification result.

[0189] The following will be described in combination with Figures 2 to 16 The method for identifying an elevator scene provided by the embodiments of the present application will be described in detail.

[0190] Figure 2 is a schematic diagram of a software system of an electronic device provided by the embodiments of the present application.

[0191] In one example, as Figure 2 shown, the system architecture can include an electronic device and a wearable device; wherein the electronic device can include an application layer 210, an application framework layer 220, a hardware abstraction layer 230, a sensor algorithm layer 240 and a hardware layer 250; the wearable device can include an air pressure sensor, an algorithm module and a Bluetooth module.

[0192] Exemplarily, the application layer 210 in the electronic device can include a setting application or other application programs; the other application programs include but are not limited to: camera application programs, galleries, calendars, calls, maps, navigation, WLAN, Bluetooth, music, video, short message, etc. application programs.

[0193] Exemplarily, the application framework layer 220 in the electronic device provides an application program interface (API) and a programming framework for the application program of the application layer; the application framework layer can include some predefined functions.

[0194] Exemplarily, in the embodiment of the present application, the application framework layer 220 can include a LinkTurbo predefined function or interface. For example, the application framework layer 220 can obtain the local area network identifier of the electronic device.

[0195] Exemplarily, the hardware abstraction layer 230 in the electronic device is used to abstract hardware. Exemplarily, the hardware abstraction layer can include a smart sensor fusion hardware abstraction module 231; wherein the smart sensor fusion hardware abstraction module 231 can be used to run an algorithm with large memory occupation and high power consumption; for example, the smart sensor fusion hardware abstraction module 231 can be used to run an elevator scene recognition algorithm, a subway scene recognition algorithm, or a tunnel scene recognition algorithm, etc.

[0196] Exemplarily, the elevator scene recognition algorithm can refer to the related algorithm of the method for recognizing the elevator scene provided by the embodiment of the present application; similarly, the method for recognizing the elevator scene provided by the embodiment of the present application can also recognize other scenes with poor online experience; for example, subway scenes or tunnel scenes, etc.

[0197] Optionally, the smart sensor fusion hardware abstraction module 231 and the bottom algorithm module can realize interactive communication; for example, the output data of the bottom algorithm module can be used as the input data of the smart sensor fusion hardware abstraction module 231, so as to realize the optimization of the high-power-consumption algorithm.

[0198] Optionally, the smart sensor fusion hardware abstraction module 231 and the bottom algorithm module can be located in the same hardware in the electronic device; or the smart sensor fusion hardware abstraction module 231 and the bottom algorithm module can be located in different hardware in the electronic device.

[0199] Exemplarily, the smart sensor fusion hardware abstraction module 231 and the bottom algorithm module can be located in the same chip in the electronic device; or the smart sensor fusion hardware abstraction module 231 and the bottom algorithm module can be located in different chips in the electronic device.

[0200] Exemplarily, the sensor algorithm layer 240 in the electronic device can include a low-power-consumption bottom algorithm module running in the electronic device; for example, the bottom algorithm module can run an algorithm with small memory occupation and low power consumption; for example, the bottom algorithm module can include but not limited to: related algorithms of the walking motion state detection result, such as the subsequent Figure 8The step S415 shown; the walking motion state detection result can include but is not limited to: static, walking or running, etc.

[0201] Exemplarily, the sensor algorithm layer 240 can transmit data to the smart sensor fusion hardware module; or, the sensor algorithm layer 240 can transmit data to the smart sensor fusion hardware abstraction module 231 through the sensor hardware abstraction module.

[0202] The hardware layer 250 is located at the bottom of the operating system; for example, the hardware layer 250 can include an acceleration sensor.

[0203] Optionally, the sensor algorithm layer 240 and the hardware layer 250 can further include a driver layer; the driver layer can be used to provide drivers for different hardware devices.

[0204] Exemplarily, the air pressure sensor in the wearable device can be used to detect air pressure; the algorithm module in the wearable device can be used to run algorithms in the wearable device; for example, the algorithm module can include a height algorithm, based on the data collected by the air pressure sensor, the height of the wearable device can be obtained through the height algorithm; the Bluetooth module can be used to realize data transmission between other devices; for example, the Bluetooth module in the wearable device can transmit data with the Bluetooth hardware abstraction module in the electronic device.

[0205] In the embodiment of the present application, for the electronic device, since the Bluetooth hardware abstraction module in the hardware abstraction layer 230 cannot transmit data with other modules in the hardware abstraction layer; therefore, the transmission module can be included in the application framework layer 220 of the electronic device, the transmission module can receive data of the Bluetooth hardware abstraction module, and send data in the Bluetooth hardware abstraction module to the smart sensor fusion hardware abstraction module 231; in other words, through the Bluetooth hardware abstraction module in the electronic device and the transmission module, data transmission between the electronic device and the wearable device can be realized.

[0206] Figure 3 It is a schematic diagram of the software system of the electronic device provided by the embodiment of the present application.

[0207] In one example, as Figure 3 shown, the system architecture can include an electronic device and a wearable device; wherein the electronic device can include an application layer 210, an application framework layer 220, a hardware abstraction layer 230, a sensor algorithm layer 240 and a hardware layer 250; the wearable device can include an air pressure sensor, an algorithm module and a Bluetooth module.

[0208] Exemplarily, the application layer 210 in the electronic device can include a setting application or other applications, including but not limited to: camera application, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, short message, etc.

[0209] Exemplarily, the application framework layer 220 in the electronic device provides an application programming interface (API) and a programming framework for the application program of the application layer; the application framework layer can include some predefined functions.

[0210] Exemplarily, in the embodiment of the present application, the application framework layer 220 can include a LinkTurbo predefined function or interface. For example, the application framework layer 220 can obtain the local area network identifier of the electronic device.

[0211] Exemplarily, the hardware abstraction layer 230 in the electronic device is used to abstract hardware.

[0212] As shown in Figure 3 , the hardware abstraction layer 230 of the electronic device can include a smart sensor fusion hardware abstraction module 231 and a sensor hardware abstraction module 232; wherein the smart sensor fusion hardware abstraction module 231 can be used to run an algorithm with large memory occupation and high power consumption; for example, the smart sensor fusion hardware abstraction module 231 can be used to run an elevator scene recognition algorithm, a subway scene recognition algorithm or a tunnel scene recognition algorithm, etc. The sensor hardware abstraction module 232 can run an algorithm with small memory occupation and low power consumption; for example, the bottom algorithm module can include but not limited to: related algorithms of walking motion state detection results, such as step S415 shown in the subsequent Figure 8 ; the walking motion state detection result can include but not limited to: static, walking or running, etc.

[0213] Optionally, the smart sensor fusion hardware abstraction module 231 and the sensor hardware abstraction module 232 can realize interactive communication; for example, the output data of the sensor hardware abstraction module 232 can be used as the input data of the smart sensor fusion hardware abstraction module 231, so as to realize the optimization of high-power-consumption algorithms.

[0214] Optionally, the smart sensor fusion hardware abstraction module 231 and the sensor hardware abstraction module 232 can be located in the same hardware in the electronic device; or the smart sensor fusion hardware abstraction module 231 and the sensor hardware abstraction module 232 can be located in different hardware in the electronic device.

[0215] For example, the smart sensor fusion hardware abstraction module 231 and the sensor hardware abstraction module 232 may be located on the same chip in the electronic device; or, the smart sensor fusion hardware abstraction module 231 and the sensor hardware abstraction module 232 may be located on different chips in the electronic device.

[0216] For example, the sensor algorithm layer 240 in the electronic device may include a low-power underlying algorithm module that runs the low-power algorithm in the electronic device; for example, the underlying algorithm module may run an algorithm that consumes less memory and consumes less power.

[0217] For example, the sensor algorithm layer 240 can transmit data to the smart sensor fusion hardware module; or, the sensor algorithm layer 240 can transmit data to the smart sensor fusion hardware abstraction module 231 through the sensor hardware abstraction module 232.

[0218] Hardware layer 250 is located at the lowest level of the operating system; for example, hardware layer 250 may include an accelerometer.

[0219] Optionally, a driver layer may also be included between the sensor algorithm layer 240 and the hardware layer 250; the driver layer can be used to provide drivers for different hardware devices.

[0220] For example, a barometric pressure sensor in a wearable device can be used to detect air pressure; an algorithm module in a wearable device can be used to run algorithms in the wearable device; for example, the algorithm module may include an altitude algorithm, which can obtain the altitude of the wearable device based on the data collected by the barometric pressure sensor; a Bluetooth module can be used to realize data transmission with other devices; for example, the Bluetooth module in a wearable device can transmit data with the Bluetooth hardware abstraction module in an electronic device.

[0221] In the embodiments of this application, for electronic devices, since the Bluetooth hardware abstraction module in the hardware abstraction layer 230 cannot transmit data with other modules in the hardware abstraction layer, a transmission module may be included in the application framework layer 220 of the electronic device. The transmission module can receive data from the Bluetooth hardware abstraction module and send the data in the Bluetooth hardware abstraction module to the smart sensor fusion hardware abstraction module 231. In other words, data transmission between the electronic device and the wearable device can be realized through the Bluetooth hardware abstraction module and the transmission module in the electronic device.

[0222] The following is combined Figures 4 to 6 The application scenarios of the elevator scene identification method provided in the embodiments of this application are illustrated with examples.

[0223] For example, the elevator scene identification result obtained by the method for identifying elevator scenes based on the embodiments of this application may include a waiting elevator scene, an elevator entry scene, or a non-entry elevator scene; wherein, a waiting elevator scene may refer to a user carrying an electronic device not entering the elevator; for example, such as Figure 4 As shown, based on the data collected by wearable device 280 and electronic device 260, electronic device 260 can identify that user 290 is located in front of elevator 270 waiting for the elevator; entering the elevator scenario can refer to the user entering the elevator; for example, based on the data obtained by wearable device 280 and / or electronic device 260, it can be identified that the electronic device is located in the elevator enclosure, that is, user 290 carrying electronic device 260 enters the elevator scenario; entering the elevator scenario can include user entering the elevator and the elevator not starting, or user entering the elevator and the elevator is running; for example, such as Figure 5 As shown, user 290 is currently in elevator 270 and the elevator is not running, meaning elevator 270 does not have upward acceleration or downward acceleration; for example, as Figure 6 As shown, user 290 is currently in an elevator and the elevator is in motion; for example, the elevator may be moving upwards or downwards.

[0224] It should be understood that the elevator scene identification method in this application embodiment can not only identify whether the electronic device has entered or not entered the elevator scene, but also identify the waiting elevator scene. When the waiting elevator scene is identified, the electronic device can request LinkTurbo resources. When the identification result is that the device has entered the elevator scene, the LinkTurbo technology can be executed directly through the pre-requested resources. Since the elevator waiting scene can be identified in this application embodiment, LinkTurbo resources can be requested when the user is waiting for the elevator, so that the user can quickly trigger the LinkTurbo of the electronic device after entering the elevator, thereby shortening the user's waiting time and improving the Internet experience.

[0225] It should also be understood that the above example is based on an elevator scenario; the method provided in this application embodiment is also applicable to identifying other closed or semi-closed scenarios (e.g., subway or tunnel scenarios), where the network signal is usually poor and electronic devices are prone to lag when accessing the internet; by identifying these scenarios, electronic devices can enable the full network aggregation algorithm to ensure a smooth internet experience.

[0226] The following is combined Figures 7 to 16 The method for identifying elevator scenarios provided in the embodiments of this application will be described in detail.

[0227] Figure 7is a schematic flowchart of a method for identifying an elevator scenario provided by an embodiment of the present application. The method 300 can be executed by the electronic device shown in the figure; the method 300 comprises steps S310 to S330, which are described in detail below. Figure 1

[0228] Step S310, obtaining first data and second data.

[0229] The first data is data collected by a first sensor, and the second data is data collected by a second sensor, and the first sensor and the second sensor are different.

[0230] Optionally, the first sensor is an air pressure sensor.

[0231] For example, the wearable device can include an air pressure sensor; the electronic device can obtain the first data collected by the air pressure sensor in the wearable device.

[0232] Optionally, the electronic device can include a transmission module, which is located in the application framework layer, and the electronic device obtains the first data and the second data, comprising:

[0233] The transmission module receives the first data sent by the wearable device.

[0234] For example, as shown in the figure, the wearable device includes an air pressure sensor, which can collect air pressure data; the air pressure sensor can transmit the air pressure data to the Bluetooth hardware abstraction module in the electronic device through the Bluetooth module; the Bluetooth hardware abstraction module transmits the air pressure data to the smart sensor fusion hardware abstraction module 231 through the transmission module located in the application framework layer; the smart sensor fusion hardware abstraction module 231 runs an elevator scenario identification algorithm based on the air pressure data to obtain an identification result. Figure 2 In an embodiment of the present application, since the Bluetooth hardware abstraction module in the hardware abstraction layer 230 of the electronic device cannot transmit data to other modules in the hardware abstraction layer; therefore, the transmission module can be included in the application framework layer 220 of the electronic device, which can receive data of the Bluetooth hardware abstraction module and send data in the Bluetooth hardware abstraction module to the smart sensor fusion hardware abstraction module 231; in other words, data transmission between the electronic device and the wearable device can be realized through the Bluetooth hardware abstraction module and the transmission module in the electronic device.

[0235] Optionally, the second sensor can be an acceleration sensor.

[0236]

[0237] ​​In the embodiments of the present application, the first data collected by the air pressure sensor and the second data collected by the acceleration sensor can be acquired; since the elevator scenario is directly identified by the data of the acceleration sensor, it is impossible to avoid that the acceleration sensor in the electronic device acquires error data due to the user's accidental touch, thereby causing the accuracy of identifying the elevator scenario to be low; for the air pressure sensor, even if the user performs an accidental touch operation on the electronic device, the data of the air pressure sensor is generally unchanged; that is, the accuracy of the data of the air pressure sensor is high; therefore, identifying whether the electronic device is in the elevator scenario based on the data of the air pressure sensor and the data of the acceleration sensor can improve the accuracy of the identification result.

[0238] Exemplarily, the acceleration sensor can be, for example, 180E as shown in the figure, which can detect the magnitude of acceleration of the electronic device in each direction (generally, x-axis, y-axis and z-axis). Figure 1

[0239] Optionally, the electronic device can include an air pressure sensor, and the electronic device can acquire the data collected by the air pressure sensor and the acceleration sensor to identify the elevator scenario.

[0240] Step S320, obtaining a first identification result based on the first data and the second data.

[0241] The first identification result is used to indicate that the electronic device is in the elevator scenario, or the first identification result is used to indicate that the electronic device is not in the elevator scenario.

[0242] Optionally, obtaining an identification result based on the first data and the second data includes:

[0243] Obtaining a value of a count parameter based on the second data, the count parameter being used to represent that the electronic device moves in a first direction and has acceleration;

[0244] Obtaining the first identification result based on the first data and the value of the count parameter.

[0245] Exemplarily, in the embodiments of the present application, the count parameter can be MoveCount, which is used to represent that the movement in a direction exists acceleration; for example, if the first upward movement exists acceleration, MoveCount=A; and the second upward movement exists acceleration, MoveCount=A+1.

[0246] ​In the embodiments of the present application, when judging whether the electronic device is in the elevator scene based on the data of the acceleration sensor, the value of the counting parameter (for example, Move Count) can be used to identify whether the electronic device enters the elevator scene; since the elevator scene is directly identified by the data of the acceleration sensor, it is impossible to avoid that the acceleration sensor of the electronic device collects error data due to user mis-touch, thereby causing the accuracy of identifying the elevator scene to be low; compared with directly identifying the elevator scene by the data of the acceleration sensor, the accuracy of identifying the elevator scene by the value of the counting parameter is obviously improved.

[0247] Exemplarily, in the embodiments of the present application, the second data can be filtered to obtain third data; and the value of the counting parameter is obtained based on the third data. Optionally, the related description of step S402 and step S403 shown in the subsequent Figure 8

[0248] In the embodiments of the present application, the error data in the data collected by the acceleration sensor can be eliminated by filtering the data, thereby improving the accuracy of the data collected by the acceleration sensor.

[0249] Exemplarily, the third data is obtained by processing the second data by the band-pass filter and the low-pass filter.

[0250] In the embodiments of the present application, the data is filtered by the band-pass filter, thereby avoiding the situation that the electronic device shakes due to external accidental factors, and realizing filtering of the collected data of the acceleration sensor and improving the accuracy of the collected data of the acceleration sensor. In addition, the data is filtered by the low-pass filter, thereby avoiding that the data of the acceleration sensor changes due to the internal micro-motion of the electronic device, that is, in order to eliminate the error data of the acceleration sensor introduced by the internal micro-motion of the electronic device, filtering of the collected data of the acceleration sensor is realized, and the accuracy of the collected data of the acceleration sensor is improved.

[0251] Optionally, the moving average and the moving standard deviation can be obtained after the data of the acceleration sensor is processed by the band-pass filter; since the data processed by the band-pass filter may have part of noise data; the part of noise data can be removed by the moving standard and the moving standard deviation, and the precision of the processed data is improved. Optionally, the related description of step S504 shown in the subsequent Figure 9

[0252] ​​Optionally, in embodiments of the present application, whether the electronic device is in the elevator scenario can be identified based on the data of the air pressure sensor; or, the value of the counting parameter can be obtained based on the data of the acceleration sensor, and whether the electronic device is in the elevator scenario can be identified based on the value of the counting parameter; or, whether the electronic device is in the elevator scenario can be identified based on the data of the air pressure sensor and the data of the acceleration sensor.

[0253] For example, when it is determined that the first data satisfies the first preset condition and the value of the counting parameter is greater than the first preset threshold, the first identification result is used to indicate that the electronic device is in the elevator scenario.

[0254] For example, when it is determined that the first data does not satisfy the first preset condition, or the value of the counting parameter is less than or equal to the first preset threshold, the first identification result is used to indicate that the electronic device is not in the elevator scenario.

[0255] For example, determining that the first data satisfies the first preset condition can include: obtaining height data based on the data of the air pressure sensor and a height algorithm; determining that the height data is less than a second preset threshold (e.g., 500 meters); and / or, determining that the change value of the data of the air pressure sensor is greater than a third preset threshold within a preset time interval.

[0256] Optionally, the first preset condition can further include that the electronic device is not currently in the airplane scenario.

[0257] It should be understood that if the electronic device is in the airplane scenario, the data of the air pressure sensor will change after the airplane takes off, and the change value of the data of the air pressure sensor can be greater than the third preset threshold, but at this time the electronic device is not in the elevator scenario; in embodiments of the present application, the height data is determined to be less than the second preset threshold in order to avoid the electronic device being in the airplane scenario.

[0258] In one example, the first preset condition can mean that it is determined whether the change value of the data of the air pressure sensor is greater than 30 Pa within a period of time, and / or the height data is less than 500 meters.

[0259] In embodiments of the present application, the identification result of the elevator scenario can include the first identification result and a second identification result, and the second identification result can be used to indicate that the electronic device is currently in the waiting elevator scenario; the waiting elevator scenario can mean that the electronic device is located near the elevator and has not entered the elevator.

[0260] Optionally, in the embodiments of the present application, the first detection result and the first network identifier can be acquired, the first detection result is used to indicate the motion state of the user carrying the electronic device, and the first network identifier is the network identifier of the network currently accessed by the electronic device; the second identification result is obtained based on the first data and / or the second data, the first detection result and the first network identifier, and the second identification result is used to indicate that the electronic device is currently in an elevator waiting scenario.

[0261] In the embodiments of the present application, the identification result of the elevator scenario can be obtained by fusing the first data of the air pressure sensor and / or the second data of the acceleration sensor, the first detection result and the first network identifier and other types of data, i.e. multi-modal data. Since the method of the embodiments of the present application can obtain the identification result based on the multi-modal data, the accuracy of the identification result can be improved.

[0262] Exemplarily, the motion state includes a static state, a first motion state and a second motion state, and the speed of the second motion state is greater than the speed of the first motion state.

[0263] Optionally, the user can carry the electronic device, and the acquisition of the motion state detection result can refer to the acquisition of the motion state detection result of the user carrying the electronic device.

[0264] Optionally, other mobile devices (for example, intelligent robots) can carry the electronic device, and the acquisition of the motion state detection result can refer to the acquisition of the motion state detection result of the mobile device carrying the electronic device.

[0265] Optionally, the second identification result is obtained based on the first data and / or the second data, the first detection result and the first network identifier, and the second identification result is used to indicate that the electronic device is currently in an elevator waiting scenario.

[0266] When the second data meets the second preset condition, the first detection result meets the third preset condition and the first network identifier meets the fourth preset condition, the second identification result is obtained.

[0267] The second preset condition refers to that the predicted acceleration of the electronic device obtained based on the second data is greater than a fourth preset threshold value; the third preset condition refers to that the user exits the first motion state or the time length for the user to exit the second motion state is less than a fifth preset threshold value; and the fourth preset condition refers to that the first network identifier matches the network identifier in the network identifier feature library, and the network identifier feature library includes the identifier of the local area network covered by the area where the elevator is located.

[0268] Exemplarily, the electronic device accesses a network in the network identification feature library based on the first network identification. The network identification in the network identification feature library can be a network identification (for example, a BSSID) of a local area network near an elevator fence. If the electronic device accesses the local area network near the elevator fence, it can be indicated that the electronic device is near the elevator fence. If the electronic device is near the elevator fence and the user changes from a moving state to a stationary state, for example, the electronic device detects that the user exits from a walking state or a running state to a stationary state, it can be indicated that the user stays at the elevator fence. Therefore, it can be obtained that the identification result is waiting for an elevator. For example, the user is waiting for an elevator.

[0269] Optionally, when the electronic device identifies that the electronic device is currently in the waiting-for-elevator scenario, the electronic device can apply for a first resource. Therefore, when the electronic device enters the elevator scenario, the elevator mode can be run through the first resource. Therefore, the waiting time for running the elevator mode of the electronic device is shortened.

[0270] Optionally, the method further includes that the electronic device applies for a first resource, and the first resource is used for the electronic device to run the elevator mode.

[0271] It should be understood that the first resource can be a memory resource pre-applied in the electronic device, and the first resource can be used for the electronic device to run the elevator mode.

[0272] It should also be understood that the Link Turbo can be a technology for realizing fusion of mobile data communication and fixed network data communication. Through end-cloud collaborative network aggregation, the user can have an aggregated high network speed and stable low latency mobile Internet experience under variable network conditions. For example, when playing a game, if the wireless network fluctuates, the mobile cellular network will quickly intervene to reduce the latency caused by the wireless network fluctuation and ensure the smoothness of the game. For another example, when downloading a game or a video, if the wireless network is poor and the download speed is too slow, the mobile cellular network will also be automatically started to speed up the download speed.

[0273] In the embodiments of the present application, when the electronic device identifies that the electronic device is currently in the waiting-for-elevator scenario, the electronic device can apply for a memory resource for running the elevator mode. When the electronic device identifies that the electronic device is in the elevator scenario, the Link Turbo can be directly executed through the pre-applied resource. In the embodiments of the present application, the waiting-for-elevator scenario of the electronic device can be identified, so that the Link Turbo resource is applied when the electronic device is in the waiting-for-elevator scenario. Therefore, the Link Turbo of the electronic device can be quickly triggered after the user enters the elevator, so that the waiting time of the user is shortened and the Internet experience of the user is improved.

[0274] In step S330, the elevator mode is run when it is detected that the electronic device is in the elevator scenario.

[0275] The elevator mode refers to a mode in which the electronic device performs network switching based on a full-network aggregation acceleration technology.

[0276] For example, as shown in FIG. 3, the electronic device is in the elevator scenario when the electronic device enters the elevator fence. Figure 4 Alternatively, as shown in FIG. 4, the electronic device is in the elevator scenario when the electronic device is in the elevator. Figure 5

[0277] For example, since the electronic device can increase the signal search power of the electronic device after the elevator mode is run, the running of the elevator mode causes the electronic device to have large power consumption. After the electronic device runs the elevator mode, one or more of the first data, the detection result of the motion state, the network identifier, or the second data can be acquired to determine whether the electronic device exits the elevator mode. Alternatively, reference can be made to the related description of the subsequent Figure 10

[0278] Optionally, a second detection result is acquired, the second detection result is that the motion state of the user is the first motion state and the duration of the first motion state is greater than a sixth preset threshold, and the elevator mode is exited based on the second detection result.

[0279] For example, it is detected that the motion state of the user is the walking state, and the duration of the walking state is greater than 6 seconds, and the electronic device can exit the elevator mode.

[0280] Optionally, a third detection result and a second network identifier are acquired, the third detection result is that the motion state of the user is the first motion state and the duration of the first motion state is greater than a seventh preset threshold, and the second network identifier is different from the first network identifier, and the elevator mode is exited based on the third detection result and the second network identifier.

[0281] Optionally, the seventh preset threshold is less than the sixth preset threshold.

[0282] For example, it is detected that the motion state of the user is the walking state, and the duration of the walking state is greater than 4 seconds, and the network identifier of the local area network accessed by the electronic device also changes, and the electronic device can exit the elevator mode.

[0283] It should be understood that the above examples take the sixth preset threshold to be 6 seconds and the seventh preset threshold to be 4 seconds; the present application does not make any limitation in this regard.

[0284] Optionally, the elevator mode is exited when the first data does not satisfy the first preset condition.

[0285] ​​For example, in a case where the height data obtained based on the first data is greater than or equal to a second preset threshold, or in a case where a change in the first data within a preset time interval is less than or equal to a third threshold, the electronic device can exit the elevator mode.

[0286] For example, after the electronic device runs the elevator mode, the electronic device can display a prompt information in the low battery mode of the battery setting interface; for example, see (d) in FIG. 7B. Figure 14 Figure 16 For example, after the electronic device runs the elevator mode, the electronic device can display a prompt information in the low battery mode of the battery setting interface; for example, see (d) in FIG. 7B.

[0287] Optionally, the method further includes: detecting, by the electronic device, a first operation; and in response to the first operation, displaying a first interface, the first interface including a low battery mode, the low battery mode including a function of turning off the elevator mode.

[0288] For example, after the electronic device runs the elevator mode, the electronic device can display a prompt information; for example, display the prompt information "turn on the smart application elevator mode"; see FIG. 7B. Figure 12

[0289] Optionally, in a case where the electronic device runs the elevator mode, the electronic device can display a first prompt information, the first prompt information being used to instruct the electronic device to turn on the elevator mode.

[0290] For example, after the electronic device runs the elevator mode, the electronic device can display a first icon; for example, the first icon can be an icon 670 as shown in FIG. 7B. Figure 13

[0291] Optionally, in a case where the electronic device runs the elevator mode, the electronic device can display a first icon, the first icon being used to instruct the electronic device to turn on the elevator mode.

[0292] In the embodiments of the present application, the first data collected by the air pressure sensor and the second data collected by the acceleration sensor can be obtained; since the elevator scenario is directly identified by the data of the acceleration sensor, it is impossible to avoid the error data collected by the acceleration sensor due to the user's mis-touch, thereby causing the accuracy of identifying the elevator scenario to be relatively low; for the air pressure sensor, even if the user performs a mis-touch operation on the electronic device, the data of the air pressure sensor is generally unchanged; that is, the accuracy of the data of the air pressure sensor is relatively high; therefore, the accuracy of identifying whether the electronic device is in the elevator scenario based on the data of the air pressure sensor and the data of the acceleration sensor is also relatively high.

[0293] ​​​In addition, in the embodiment of the present application, the identification result of identifying the elevator scene includes: being in the elevator scene, not being in the elevator scene, or waiting for the elevator scene; when the electronic device is in the waiting for the elevator scene, the electronic device can pre-apply the first resource; when the electronic device identifies that the electronic device is in the elevator scene, the electronic device can directly execute the Link Turbo through the pre-applied resource; since in the embodiment of the present application, the waiting for the elevator scene of the electronic device can be identified, the Link Turbo resource is applied when the electronic device is in the waiting for the elevator scene, so that the user can quickly trigger the Link Turbo of the electronic device after entering the elevator; thereby shortening the waiting time of the user and improving the online experience of the user.

[0294] In addition, in the embodiment of the present application, the elevator scene is identified by the value of the counting parameter (for example, Move Count); since if the elevator scene is directly identified by the data of the acceleration sensor, the acceleration sensor of the electronic device will collect error data due to the user's mis-touch, thereby reducing the accuracy of identifying the elevator scene; compared with directly identifying the elevator scene by the data of the acceleration sensor, identifying the elevator scene by the value of the counting parameter can improve the accuracy of the identification result; secondly, when the elevator scene is directly identified based on the data of the acceleration sensor, in order to reduce the error in the data collected by the acceleration sensor, multiple frames of data of the acceleration sensor need to be obtained, so that the waiting time of the electronic device is long, which leads to the inability to quickly identify the elevator scene; based on the method for identifying the elevator scene of the present application, the elevator scene can be quickly identified by identifying the elevator scene by the value of the counting parameter; therefore, based on the method for identifying the elevator scene of the present application, the elevator scene can be quickly and accurately identified, the waiting time of the user is shortened; so that the electronic device can quickly trigger the Link Turbo of the electronic device after entering the elevator, and the online experience of the user is improved.

[0295] Exemplarily, in the embodiment of the present application, the electronic device can obtain the data collected by the air pressure sensor from the wearable device; by setting a transmission module in the application framework layer of the electronic device, the transmission of the air pressure sensor data between the electronic device and the wearable device is realized.

[0296] It should be understood that the above is exemplified by the elevator scene; the method in the embodiment of the present application is also applicable to identifying other closed scenes or semi-closed scenes (for example, subway scenes or tunnel scenes), the network signal of the closed scene or semi-closed scene is usually poor, and the electronic device is prone to freezing; after identifying these scenes, the electronic device can start the full network aggregation technology for network switching to ensure smooth online experience.

[0297] Figure 8is a schematic flowchart of a method for identifying an elevator scenario provided by an embodiment of the present application. The method 400 can be executed by the electronic device shown in Figure 1 ; the method 400 includes steps S401 to S416, which are described in detail below.

[0298] Step S401: Obtain data of an acceleration sensor (an example of the second data).

[0299] By way of example, the acceleration sensor can refer to 180E shown in Figure 1 The acceleration sensor can detect the magnitude of acceleration of the electronic device in each direction (generally, the x-axis, the y-axis, and the z-axis).

[0300] Step S402: Process the data of the acceleration sensor by a band-pass filter.

[0301] By way of example, the band-pass filter can be a device that allows waves of a specific frequency band to pass while shielding other frequency bands; for example, an oscillation circuit composed of resistance, inductance, and capacitance can be an analog band-pass filter.

[0302] In an embodiment of the present application, the data is filtered by the band-pass filter, thereby avoiding the situation that the electronic device is shaken due to external accidental factors, achieving filtering of the obtained data of the acceleration sensor, and improving the accuracy of the obtained data of the acceleration sensor.

[0303] Optionally, the data of the acceleration sensor processed by the band-pass filter can obtain a sliding average and a sliding standard deviation; since the data processed by the band-pass filter can have some noise data, the sliding average and the sliding standard deviation can remove the noise data, thereby improving the accuracy of the processed data. Optionally, reference can be made to the related description of step S504 shown in Figure 9

[0304] Step S403: Process the data of the acceleration sensor by a low-pass filter.

[0305] By way of example, the low-pass filter can refer to an electronic filtering device that allows signals below the cutoff frequency to pass, but signals above the cutoff frequency cannot pass.

[0306] In an embodiment of the present application, the data is filtered by the low-pass filter, thereby avoiding the situation that the data of the acceleration sensor changes due to the internal slight movement of the electronic device, i.e., to eliminate the error data of the acceleration sensor introduced by the internal slight movement of the electronic device, achieving filtering of the obtained data of the acceleration sensor, and improving the accuracy of the obtained data of the acceleration sensor. ​

[0307] Step S404, calculating the combined speed based on the data processed by the band-pass filter and the data processed by the low-pass filter.

[0308] Exemplarily, the combined speed of the electronic device can be expressed as x2+y2+z2, where x represents the acceleration in the X-axis direction, y represents the acceleration in the Y-axis direction, and z represents the acceleration in the Z-axis direction.

[0309] For example, the three-axis data processed by the band-pass filter can be used to obtain a combined speed 1; the three-axis data processed by the low-pass filter can be used to obtain a combined speed 2; the combined speed can be obtained based on the combined speed 1 and the combined speed 2; for example, the combined speed 1 and the combined speed 2 are added to obtain the combined speed.

[0310] In the embodiments of the present application, the combined speed is calculated based on the data processed by the band-pass filter and the data processed by the low-pass filter to determine whether there is acceleration or deceleration in a certain direction.

[0311] Step S405, recording the value of the count parameter in a certain direction when the combined speed satisfies the preset condition 1.

[0312] Exemplarily, the combined speed satisfying the preset condition 1 can mean that the combined speed is greater than a threshold 2; alternatively, please refer to the related description of step S509 shown in the subsequent Figure 8

[0313] For example, in the embodiments of the present application, the count parameter can mean Move Count, which is used to represent movement in a direction and the existence of acceleration; for example, if the first upward movement exists and there is acceleration, Move Count=A; then the second upward movement exists and there is acceleration, Move Count=A+1.

[0314] Step S406, obtaining the data of the air pressure sensor (an example of the first data).

[0315] In the embodiments of the present application, the elevator scene can be identified based on the data of the air pressure sensor; since the elevator scene is directly identified by the data of the acceleration sensor, it is impossible to avoid the error data obtained by the acceleration sensor due to the user's mis-touch, thereby resulting in a low accuracy of identifying the elevator scene; if the air pressure sensor is used to identify whether the electronic device enters the elevator scene, even if the user has a mis-touch operation on the electronic device, the data of the air pressure sensor is usually unchanged; therefore, the accuracy of the data of the air pressure sensor is high; the accuracy of identifying whether the electronic device is in the elevator scene based on the data of the air pressure sensor is also high.

[0316] ​Exemplarily, the user can carry the electronic device and the wearable device, the wearable device can include the air pressure sensor, the height data and the air pressure data can be obtained based on the data collected by the air pressure sensor; the electronic device can determine whether the electronic device enters the elevator scene based on the height data and the air pressure data.

[0317] For example, as shown in FIG. 1, the air pressure sensor in the wearable device collects the air pressure data; the air pressure sensor sends the air pressure data to the algorithm module; the algorithm module obtains the algorithm data based on the height algorithm; the algorithm module sends the height data and the air pressure data to the Bluetooth module, the Bluetooth module can transmit the height data and the air pressure data to the Bluetooth hardware abstraction module in the electronic device through the Bluetooth technology, the Bluetooth hardware abstraction module can transmit the height data and the air pressure data to the intelligent sensor fusion hardware abstraction module 231 through the transmission module; the intelligent sensor fusion hardware abstraction module 231 can execute the elevator recognition algorithm based on the height data and the air pressure data. Figure 2 Or Figure 3 For example, as shown in FIG. 1, the air pressure sensor in the wearable device collects the air pressure data; the air pressure sensor sends the air pressure data to the algorithm module; the algorithm module obtains the algorithm data based on the height algorithm; the algorithm module sends the height data and the air pressure data to the Bluetooth module, the Bluetooth module can transmit the height data and the air pressure data to the Bluetooth hardware abstraction module in the electronic device through the Bluetooth technology, the Bluetooth hardware abstraction module can transmit the height data and the air pressure data to the intelligent sensor fusion hardware abstraction module 231 through the transmission module; the intelligent sensor fusion hardware abstraction module 231 can execute the elevator recognition algorithm based on the height data and the air pressure data.

[0318] Exemplarily, the electronic device can include the air pressure sensor, the height data and the air pressure data can be obtained based on the data collected by the air pressure sensor; the electronic device can determine whether the electronic device enters the elevator scene based on the height data and the air pressure data.

[0319] It should be understood that generally, the speed of obtaining the data of the acceleration sensor is higher than that of obtaining the data of the air pressure sensor; however, the accuracy of the data of the air pressure sensor is higher than that of the data of the acceleration sensor; therefore, the data of the air pressure sensor can be obtained after the data of the acceleration sensor is obtained; in the embodiment of the present application, whether the electronic device is in the elevator scene can be determined based on the data of the acceleration sensor and the data of the air pressure sensor.

[0320] Step S407, determining whether the air pressure data and the height data satisfy the first preset condition; if the first preset condition is satisfied, executing step S408; whether the air pressure data is greater than the first threshold value and the height data is less than the second threshold value.

[0321] Exemplarily, the air pressure data and the height data satisfying the first preset condition can mean that the change of the air pressure data is less than the first threshold value and the value of the height data is less than the second threshold value within a preset time interval.

[0322] It should be understood that in the embodiment of the present application, determining whether the height is less than the second threshold value can avoid the user being in the airport scene.

[0323] Exemplarily, based on the data collected by the air pressure sensor and the height algorithm, the height data can be obtained; the height data can be used to indicate the distance information between the user and the horizontal ground.

[0324] For example, if the pressure data changes greatly in a preset time interval, it can be indicated that the electronic device enters the elevator scenario; or if the height data is greater than a first threshold (for example, 5 meters) and less than a second threshold (for example, 500 meters), it can be indicated that the electronic device enters the elevator scenario.

[0325] In one example, it can be judged whether the pressure change of the pressure sensor per second is greater than 30 Pa; and / or whether the height data is less than 500 meters.

[0326] Optionally, the first preset condition can further include that the electronic device is not in the airplane scenario.

[0327] It should be understood that if the electronic device is in the airplane scenario, the data of the pressure sensor will change; at this time, the electronic device is not in the elevator scenario, but the data of the pressure sensor can misjudge that the electronic device is in the elevator scenario, thereby starting the elevator mode.

[0328] Step S408, identifying the pressure as a preset identification.

[0329] Exemplarily, identifying the pressure as the preset identification can mean configuring “pressureFlag = True”.

[0330] Step S409, judging whether the value of the counting parameter is greater than a target threshold, and / or whether the pressure identification is the preset identification; if the value of the counting parameter is greater than the target threshold, and / or the pressure identification is the preset identification, executing step S410; if the value of the counting parameter is less than or equal to the target threshold, and / or the pressure identification is different from the preset identification, executing step S411.

[0331] In one example, if the value of the counting parameter is greater than the target threshold, or the pressure identification is the preset identification, step S410 is executed.

[0332] In one example, if the value of the counting parameter is greater than the target threshold, and the pressure identification is the preset identification, step S410 is executed.

[0333] It should be understood that in the case that the user produces a false touch operation on the electronic device, the data of the pressure sensor is usually unchanged; therefore, the accuracy of the data of the pressure sensor is high; the accuracy of identifying whether the electronic device is in the elevator scenario based on the data of the pressure sensor is also higher. It should also be understood that in the embodiments of the present application, by judging whether the value of the counting parameter is greater than the target threshold, the problem that the value of the counting parameter of a certain direction is recorded incorrectly in the electronic device due to the false touch of the user can be avoided, so that the identification result of the elevator scenario output is not accurate.

[0334] In the embodiments of the present application, the elevator scene is identified by the value of the counting parameter (for example, the Move Count), for example, an entering elevator scene or a non-entering elevator scene is identified; since the elevator scene is directly identified by the data of the acceleration sensor, it is impossible to avoid that the acceleration sensor in the electronic device collects error data due to user mis-touch, thereby causing the accuracy of identifying the elevator scene to be low; compared with directly identifying the elevator scene by the data of the acceleration sensor, identifying the elevator scene by the value of the counting parameter can improve the accuracy of the identification result; secondly, when the elevator scene is directly identified based on the data of the acceleration sensor, in order to reduce the error in the data collected by the acceleration sensor, multiple frames of data of the acceleration sensor need to be acquired, so that the waiting time of the electronic device is long, causing the elevator scene to be unable to be quickly identified; identifying the elevator scene by the value of the counting parameter is efficient, and the elevator scene can be quickly identified; in the embodiments of the present application, the value of the counting parameter can be quickly acquired, and the elevator scene is identified based on the value of the counting parameter, thereby shortening the time of identifying the elevator scene and shortening the waiting time of the user.

[0335] In addition, in the embodiments of the present application, whether the electronic device is in the elevator scene can also be identified based on the data of the air pressure sensor or the data of the air pressure sensor and the acceleration sensor, which can improve the accuracy of the identification result; in addition, in the embodiments of the present application, when whether the electronic device is in the elevator scene is identified based on the data of the acceleration sensor, the value of the counting parameter is obtained based on the data of the acceleration sensor of the electronic device, and the elevator scene is identified based on the value of the counting parameter, thereby the accuracy of the identification result can be improved.

[0336] In step S410, the identification result is output as the electronic device not being in the elevator scene.

[0337] It should be understood that the electronic device not being in the elevator scene can mean that the electronic device does not enter the elevator scene, that is, the electronic device does not enter the elevator fence.

[0338] In step S411, the identification result is output as the electronic device being in the elevator scene.

[0339] It should be understood that the electronic device being in the elevator scene can mean that the electronic device enters the elevator fence; since the user carries the electronic device, the electronic device being in the elevator scene can mean that the user is in the elevator scene, that is, the user enters the elevator fence; through the embodiments of the present application, after the electronic device identifies that the user enters the elevator fence, the electronic device can start the Link Turbo to ensure the smooth online experience of the user in the elevator scene.

[0340] For example, being in the elevator scene can be as shown in Figure 5 , or Figure 6As shown in step S412, the acceleration is calculated based on the resultant velocity.

[0341] Exemplarily, the acceleration = abs(resultant velocity) / sqrt(sliding standard deviation); wherein, abs represents an absolute value function; sqrt represents a square root function; the sliding standard deviation can be calculated based on the data processed by the band-pass filter; optionally, the specific implementation manner is as shown in the following formula: Figure 8 The related description of step S504 is as shown.

[0342] Step S413: Obtain a motion state detection result.

[0343] Exemplarily, the motion state detection model can be obtained by training, and the motion state detection model can be a classification model; for example, the motion detection model can be a pre-trained gradient boosting decision tree (GBDT) model.

[0344] In one example, the data features are extracted by obtaining the variance, mean, first-order difference, second-order difference, or third-order difference of the values of the acceleration sensor in a preset time length, and the data features are sent to the pre-trained GBDT model to obtain the motion state detection result; wherein, the motion state detection result can include: static, running (for example, walking or running); optionally, the motion state detection result can include just exiting the motion (for example, just exiting walking, or just exiting running) and the like.

[0345] It should be understood that the GBDT model is a decision tree model based on the integration idea, and its essence is based on residual learning.

[0346] Optionally, the user can carry the electronic device, and the motion state detection result can refer to the motion state detection result of the user carrying the electronic device.

[0347] Optionally, other mobile devices (for example, intelligent robots) can carry the electronic device, and the motion state detection result can refer to the motion state detection result of the mobile device carrying the electronic device.

[0348] Step S414: Obtain a local area network identifier.

[0349] Exemplarily, each local area network can correspond to a MAC address; the current local area network identifier of the electronic device can be obtained, and the local area network identifier can be used to determine the local area network connected by the electronic device; different local area networks can cover different ranges.

[0350] Exemplarily, if the local area network identifier of the electronic device matches the local area network identifier feature library of the elevator, it can be indicated that the electronic device is located in the coverage range of the local area network near the elevator, i.e., the electronic device is located near the elevator.

[0351] Optionally, the MAC address of the local area network near the elevator can be acquired in advance to obtain the local area network identifier feature library of the elevator.

[0352] In step S415, it is determined whether the acceleration and the motion state detection result satisfy a second preset condition.

[0353] Exemplarily, determining whether the acceleration, the walking state detection result and the local area network identifier satisfy the second preset condition can mean respectively determining whether the acceleration satisfies condition 1, whether the walking state detection result satisfies condition 2 and whether the local area network identifier satisfies condition 3; if the conditions 1, 2 and 3 are satisfied, step S416 is executed.

[0354] Condition 1 can mean that the acceleration is greater than a threshold 5; condition 2 can mean that the motion state detection result is the state of exiting motion; and condition 3 can mean that the local area network identifier of the electronic device matches the local area network identifier feature library of the elevator.

[0355] It should be understood that the acceleration and the motion state detection result are used to determine whether the user carrying the electronic device changes from a running state to a stationary state; for example, if the acceleration is greater than the threshold 5 and the motion state detection result is the state of exiting motion, it can be indicated that the user carrying the electronic device stops from the walking state or the running state.

[0356] It should also be understood that if the local area network identifier of the electronic device matches the local area network identifier feature library of the elevator, it can be indicated that the electronic device is located in the coverage range of the local area network near the elevator, i.e., the electronic device is located near the elevator.

[0357] In step S416, the recognition result is output as the waiting elevator scenario.

[0358] In the embodiments of the present application, the recognition result obtained when the elevator scenario is recognized includes waiting for an elevator; when the recognition result is waiting for an elevator, the electronic device can pre-apply a Link Turbo resource; when the recognition result is in the elevator scenario or, the electronic device can directly start the Link Turbo technology through the pre-applied resource; therefore, by the method for recognizing the elevator scenario in the embodiments of the present application, the time length of the user waiting for a signal in the elevator scenario can be shortened; and the electronic device can quickly trigger the Link Turbo of the electronic device after entering the elevator, thereby improving the user's online experience.

[0359] In addition, in the embodiments of the present application, the elevator scene is identified by the value of the counting parameter (for example, the Move Count), and a recognition result is obtained; for example, the recognition result can include entering an elevator scene or not entering an elevator scene; since the elevator scene is directly identified by the data of the acceleration sensor, it is impossible to avoid that the acceleration sensor collects error data due to user mis-touch, thereby causing the accuracy of identifying the elevator scene to be low; compared with directly identifying the elevator scene by the data of the acceleration sensor, identifying the elevator scene by the value of the counting parameter can improve the accuracy of the recognition result; secondly, when the elevator scene is directly identified based on the data of the acceleration sensor, in order to reduce the error in the data collected by the acceleration sensor, multiple frames of data of the acceleration sensor need to be obtained, so that the waiting time of the electronic device is long, causing the elevator scene to be unable to be quickly identified; identifying the elevator scene by the value of the counting parameter is efficient, that is, the elevator scene can be quickly identified; in the embodiments of the present application, the value of the counting parameter can be quickly obtained, and the elevator scene is identified based on the value of the counting parameter, thereby shortening the time of identifying the elevator scene and shortening the waiting time of the user.

[0360] In addition, in the embodiments of the present application, the electronic device can be identified whether it is in an elevator scene based on the data of the air pressure sensor or the data of the air pressure sensor and the acceleration sensor, which can improve the accuracy of the recognition result; in addition, in the embodiments of the present application, when the electronic device is identified whether it is in an elevator scene based on the data of the acceleration sensor, the value of the counting parameter is obtained based on the data of the acceleration sensor of the electronic device, and the elevator scene is identified based on the value of the counting parameter; thereby the accuracy of the recognition result can be improved. It should be understood that the above is exemplified by the elevator scene; the method in the embodiments of the present application is also applicable to identifying other closed scenes or semi-closed scenes (for example, a subway scene or a tunnel scene), and the network signal of the closed scene or the semi-closed scene is usually poor, and the electronic device is prone to freezing; after identifying these scenes, the electronic device can start the full network aggregation technology to perform network switching, and ensure a smooth online experience.

[0361] Optionally, in the embodiments of the present application, whether the electronic device is in an elevator scene can be identified based on the data of the air pressure sensor; that is, in step S409, it can be judged whether the air pressure identifier is a preset identifier, if the air pressure identifier is the preset identifier, the recognition result is that the electronic device enters an elevator scene; if the air pressure identifier is different from the preset identifier, the recognition result is that the electronic device does not enter an elevator scene.

[0362] Optionally, in the embodiments of the present application, as Figure 8The method shown can not include steps S401 to S405; whether the electronic device is in the elevator scene can be determined based on the data of the air pressure sensor; whether the electronic device is in the waiting elevator scene is determined based on the motion state detection result and the local area network identifier.

[0363] Figure 9 is a schematic flowchart of the method for identifying the elevator scene provided by the embodiment of the present application. The method 500 can be executed by the electronic device shown, and the method 500 includes steps S501 to S523, which are described in detail as follows. Figure 1

[0364] Step S501, data of the acceleration sensor is acquired.

[0365] Exemplarily, the acceleration sensor can refer to 180E shown in the figure, which can detect the magnitude of acceleration of the electronic device in each direction (generally, x-axis, y-axis and z-axis). Figure 1

[0366] Optionally, in the embodiment of the present application, the acquired data of the acceleration sensor can be subjected to parameter verification, which can determine whether the acquired data is abnormal, thereby ensuring the accuracy of the acquired data.

[0367] Step S502, unitization processing is performed on the data.

[0368] In the embodiment of the present application, the unitization processing on the data can convert the data from integer data to floating-point data, thereby facilitating the unitization of the data and being conducive to subsequent operations.

[0369] Optionally, step S503 can be directly executed after step S501, which is not limited in the present application.

[0370] Step S503, the data is processed by a band-pass filter.

[0371] Exemplarily, the band-pass filter can be a device that allows waves of a specific frequency band to pass through while shielding other frequency bands; for example, an oscillation circuit composed of resistance, inductance and capacitance can be an analog band-pass filter.

[0372] In the embodiment of the present application, the data is filtered by the band-pass filter, thereby avoiding the situation that the electronic device is shaken due to external accidental factors, achieving filtering of the acquired data of the acceleration sensor, and improving the accuracy of the acquired data of the acceleration sensor.

[0373] Step S504, the sliding average and the sliding standard deviation are obtained based on the data processed by the band-pass filter. ​​

[0374] The exponential moving average, which can also be referred to as an exponentially weighted moving average, can be used to estimate the local mean of a variable, such that the update of the variable is related to the historical values in a period of time. The moving average is usually used to eliminate the influence of accidental factors; and the moving standard deviation is used to measure the dispersion degree from the moving average level.

[0375] In the embodiments of the present application, the data processed by the band-pass filter can include some noise data; the moving standard deviation and the moving standard deviation can be used to remove the noise data, and improve the accuracy of the processed data.

[0376] In step S505, it is determined whether the moving standard deviation is greater than a threshold 1; if the moving standard deviation is less than or equal to the threshold 1, step S506 is performed.

[0377] In step S506, the value of the count parameter is set to zero.

[0378] In the embodiments of the present application, when the moving standard deviation is less than or equal to the threshold 1, it indicates that the electronic device does not move upward or downward, and the value of the count parameter can be set to zero.

[0379] For example, in the embodiments of the present application, the count parameter can be referred to as a Move Count, which is used to indicate the movement in one direction and the existence of acceleration.

[0380] For example, the moving standard deviation can be output every second, and it is determined whether the moving standard deviation is greater than the threshold 1.

[0381] In step S507, the data is processed by a low-pass filter.

[0382] For example, the low-pass filter can be an electronic filter device that allows signals below the cutoff frequency to pass through, but signals above the cutoff frequency cannot pass through.

[0383] In the embodiments of the present application, the data is filtered by the low-pass filter, so as to avoid the change of the data of the acceleration sensor caused by the slight movement of the internal part of the electronic device, that is, in order to eliminate the data of the accelerometer introduced by the slight movement of the internal part of the electronic device, the acquired data of the acceleration sensor is filtered, and the accuracy of the acquired data of the acceleration sensor is improved.

[0384] In step S508, the resultant velocity of the electronic device is obtained based on the data processed by the low-pass filter, the moving average, and the moving standard deviation.

[0385] Exemplarily, the three-axis data processed by the band-pass filter can obtain the resultant velocity 1; the three-axis data processed by the low-pass filter can obtain the resultant velocity 2; the resultant velocity can be obtained based on the resultant velocity 1 and the resultant velocity 2; for example, the resultant velocity 1 and the resultant velocity 2 are added to obtain the resultant velocity.

[0386] In the embodiment of the present application, the resultant velocity is calculated based on the data processed by the band-pass filter and the data processed by the low-pass filter, so as to determine whether there is acceleration or deceleration in a certain direction.

[0387] In the embodiment of the present application, there can be some noise data in the data processed by the filter processor; the sliding average and the sliding standard deviation can be used to remove the noise data.

[0388] In step S509, it is determined whether the resultant velocity is greater than a threshold 2 and the sliding standard deviation is less than a threshold 3; if the resultant velocity is greater than the threshold 2 and the sliding standard deviation is less than the threshold 3, step S510 is executed; if the resultant velocity is less than or equal to the threshold 2 or the sliding standard deviation is greater than or equal to the threshold 3, the data of the updated acceleration sensor is continuously acquired.

[0389] In step S510, the value of the count parameter in a certain direction is recorded.

[0390] Exemplarily, in the embodiment of the present application, the count parameter can be Move Count, which is used to indicate the movement in a direction and the existence of acceleration; for example, if the first movement in the upward direction and the existence of acceleration, Move Count=A; if the second movement in the upward direction and the existence of acceleration, Move Count=A+1.

[0391] In step S511, the data of the air pressure sensor is acquired.

[0392] In the embodiment of the present application, the elevator scene can be identified based on the data of the air pressure sensor; since the elevator scene is directly identified based on the data of the acceleration sensor, the error data of the acceleration sensor acquired by the electronic device due to the user's mis-touch cannot be avoided, so that the accuracy of identifying the elevator scene is low; if the electronic device is identified to enter the elevator scene based on the data of the air pressure sensor, even if the user has mis-touch operation on the electronic device, the data of the air pressure sensor is usually unchanged; therefore, the accuracy of the data of the air pressure sensor is high; the accuracy of identifying whether the electronic device is in the elevator scene based on the data of the air pressure sensor is also high.

[0393] Exemplarily, the user can carry the electronic device and the wearable device, the wearable device can include the air pressure sensor, the height data and the air pressure data can be obtained based on the data collected by the air pressure sensor; the electronic device can determine whether the electronic device enters the elevator scene based on the height data and the air pressure data.

[0394] For example, as shown in FIG. 13, the air pressure sensor in the wearable device collects the air pressure data; the air pressure sensor sends the air pressure data to the algorithm module; the algorithm module obtains the algorithm data based on the height algorithm; the algorithm module sends the height data and the air pressure data to the Bluetooth module, the Bluetooth module can transmit the height data and the air pressure data to the Bluetooth hardware abstraction module in the electronic device through the Bluetooth technology, the Bluetooth hardware abstraction module can transmit the height data and the air pressure data to the intelligent sensor fusion hardware abstraction module 231 through the transmission module; the intelligent sensor fusion hardware abstraction module 231 can execute the elevator recognition algorithm based on the height data and the air pressure data. Figure 2 Figure 3 For example, as shown in FIG. 13, the air pressure sensor in the wearable device collects the air pressure data; the air pressure sensor sends the air pressure data to the algorithm module; the algorithm module obtains the algorithm data based on the height algorithm; the algorithm module sends the height data and the air pressure data to the Bluetooth module, the Bluetooth module can transmit the height data and the air pressure data to the Bluetooth hardware abstraction module in the electronic device through the Bluetooth technology, the Bluetooth hardware abstraction module can transmit the height data and the air pressure data to the intelligent sensor fusion hardware abstraction module 231 through the transmission module; the intelligent sensor fusion hardware abstraction module 231 can execute the elevator recognition algorithm based on the height data and the air pressure data.

[0395] Exemplarily, the electronic device can include the air pressure sensor, the height data and the air pressure data can be obtained based on the data collected by the air pressure sensor; the electronic device can determine whether the electronic device enters the elevator scene based on the height data and the air pressure data.

[0396] It should be understood that generally, the speed of obtaining the data of the acceleration sensor is higher than that of obtaining the data of the air pressure sensor; however, the accuracy of the data of the air pressure sensor is higher than that of the data of the acceleration sensor; therefore, the data of the air pressure sensor can be obtained after the data of the acceleration sensor is obtained; in the embodiments of the present application, whether the electronic device is in the elevator scene can be determined based on the data of the acceleration sensor and the data of the air pressure sensor.

[0397] In step S512, it is determined whether the change of the air pressure data is greater than a threshold 5 and the height data is less than a threshold 6; if yes, step S513 is executed.

[0398] It should be understood that in the embodiments of the present application, determining that the height data is less than the threshold 6 can avoid that the user is in the airport scene.

[0399] Exemplarily, the height data can be obtained based on the data collected by the air pressure sensor and the height algorithm; the height data can be used to indicate the distance information between the user and the horizontal ground.

[0400] For example, if the change of the air pressure data is large in a preset time interval, it can be indicated that the electronic device enters the elevator scene; or if the height data is greater than a first threshold (for example, 5 meters) and less than a second threshold (for example, 500 meters), it can be indicated that the electronic device enters the elevator scene.

[0401] ​In one example, it can be judged whether the pressure change per second of the pressure sensor is greater than 30 Pa; and / or, whether the height data is less than 500 meters.

[0402] Optionally, the first preset condition can further include that the electronic device is not in a flying field scenario.

[0403] It should be understood that if the electronic device is in a flying field scenario, the data of the pressure sensor will change; at this time, the electronic device is not in an elevator scenario, but based on the data of the pressure sensor, it can be misjudged that the electronic device is in an elevator scenario, so as to start the elevator mode.

[0404] Step S513, configuring the pressure flag as a preset flag.

[0405] Exemplarily, configuring the pressure flag as a preset flag can mean configuring "pressureFlag = True".

[0406] Step S514, judging whether the value of the counting parameter is greater than a target threshold value, and / or whether the pressure flag is the preset flag; if the value of the counting parameter is greater than the target threshold value, and / or the pressure flag is the preset flag, executing step S410; if the value of the counting parameter is less than or equal to the target threshold value, and / or the pressure flag is different from the preset flag, executing step S411.

[0407] In one example, if the value of the counting parameter is greater than the target threshold value, or the pressure flag is the preset flag, executing step S515.

[0408] In one example, if the value of the counting parameter is greater than the target threshold value, and the pressure flag is the preset flag, executing step S515.

[0409] It should be understood that in the case that the user generates a false touch operation on the electronic device, the data of the pressure sensor is usually also unchanged; therefore, the accuracy of the data of the pressure sensor is higher; and the accuracy of identifying whether the electronic device is in an elevator scenario based on the data of the pressure sensor is also higher.

[0410] It should also be understood that in the embodiments of the present application, by judging whether the value of the counting parameter is greater than the target threshold value, the problem that the counting parameter of a certain direction is recorded in error in the electronic device due to the false touch of the user, so that the identification result of the elevator scenario output is inaccurate, can be avoided.

[0411] In the embodiments of the present application, the elevator scenario is identified by the value of the counting parameter (for example, the Move Count), for example, an entering elevator scenario or a non-entering elevator scenario is identified; since the elevator scenario is directly identified by the data of the acceleration sensor, it is impossible to avoid that the acceleration sensor in the electronic device collects error data due to user mis-touch, thereby causing the accuracy of identifying the elevator scenario to be low; compared with directly identifying the elevator scenario by the data of the acceleration sensor, identifying the elevator scenario by the value of the counting parameter can improve the accuracy of the identification result; secondly, when the elevator scenario is directly identified based on the data of the acceleration sensor, in order to reduce the error in the data collected by the acceleration sensor, multiple frames of data of the acceleration sensor need to be acquired, so that the waiting time of the electronic device is long, thereby causing the elevator scenario to be unable to be quickly identified; identifying the elevator scenario by the value of the counting parameter is efficient, that is, the elevator scenario can be quickly identified; in the embodiments of the present application, the value of the counting parameter can be quickly acquired, the elevator scenario is identified based on the value of the counting parameter, thereby shortening the time of identifying the elevator scenario and shortening the waiting time of the user.

[0412] In addition, in the embodiments of the present application, whether the electronic device is in the elevator scenario can also be identified based on the data of the air pressure sensor or the data of the air pressure sensor and the acceleration sensor, which can improve the accuracy of the identification result; in addition, in the embodiments of the present application, when whether the electronic device is in the elevator scenario is identified based on the data of the acceleration sensor, the value of the counting parameter is obtained based on the data of the acceleration sensor of the electronic device, and the elevator scenario is identified based on the value of the counting parameter, thereby the accuracy of the identification result can be improved.

[0413] Step S515: outputting the identification result as the entering elevator scenario.

[0414] It should be understood that the electronic device being in the elevator scenario can mean that the electronic device enters the elevator fence; since the user carries the electronic device, the electronic device being in the elevator scenario can mean that the user is in the elevator scenario, that is, the user enters the elevator fence; through the embodiments of the present application, after the electronic device identifies that the user enters the elevator fence, the electronic device can start the link turbo to ensure the smooth online experience of the user in the elevator scenario.

[0415] For example, being in the elevator scenario can be as shown in Figure 4 , or as shown in Figure 5 .

[0416] Step S516: outputting the identification result as the non-entering elevator scenario.

[0417] It should be understood that the electronic device not being in the elevator scenario can mean that the electronic device does not enter the elevator scenario, that is, the electronic device does not enter the elevator fence.

[0418] Step S517, the predicted acceleration of the electronic device can be obtained based on the resultant velocity.

[0419] Exemplarily, the predicted acceleration = abs(resultant velocity) / sqrt(sliding standard deviation); wherein, abs represents an absolute value function; sqrt represents a square root function; and the sliding standard deviation can be calculated based on the data processed by the band-pass filter.

[0420] Step S518, the motion state detection result is obtained.

[0421] Exemplarily, the motion state detection model can be obtained by training, and the motion state detection model can be a classification model; for example, the motion detection model can be a pre-trained gradient boosting decision tree (GBDT) model.

[0422] In one example, the data features are extracted by obtaining the variance, mean, first-order difference, second-order difference, or third-order difference of the values of the acceleration sensor in a preset time length, and the data features are input into the pre-trained GBDT model to obtain the motion state detection result; wherein, the motion state detection result can include: static, running (for example, walking or running); optionally, the motion state detection result can include just exiting the motion (for example, just exiting the walking or just exiting the running) and the like.

[0423] It should be understood that the GBDT model is a decision tree model based on the integration idea, and its essence is based on residual learning.

[0424] It should also be understood that the motion state result can represent the motion state result of the user carrying the electronic device; or the motion state result of other mobile devices carrying the electronic device.

[0425] Step S519, it is judged whether the motion state detection result is just exiting the motion; if the motion state detection result is just exiting the motion state; for example, just exiting the walking state or just exiting the running state, step S522 is executed.

[0426] Exemplarily, the just exiting the motion state can represent that the time length of exiting the motion state is less than a preset time length.

[0427] Step S520, the local area network identifier is obtained.

[0428] Exemplarily, each local area network can correspond to a MAC address; the current local area network identifier of the electronic device can be obtained, and the local area network identifier can be used to judge the local area network connected by the electronic device; different local area networks can cover different ranges.

[0429] Step S521, determining whether the local area network identifier of the electronic device matches the local area network identifier feature library of the elevator; if the local area network identifier of the electronic device matches the local area network identifier feature library of the elevator, executing step S522.

[0430] Illustratively, if the local area network identifier of the electronic device matches the local area network identifier feature library of the elevator, it can be indicated that the electronic device is located in the coverage range of the local area network near the elevator, i.e., it can be indicated that the electronic device is located near the elevator.

[0431] Optionally, the MAC address of the local area network near the elevator can be acquired in advance to obtain the local area network identifier feature library of the elevator.

[0432] Step S522, determining whether conditions 1, 2 and 3 are met; if conditions 1, 2 and 3 are met, executing step S520.

[0433] Among them, condition 1 can mean that the predicted acceleration is greater than a threshold 5; condition 2 can mean that the walking state recognition result is the state of exiting the motion; and condition 3 can mean that the local area network identifier of the electronic device matches the local area network identifier feature library of the elevator.

[0434] Step S523, outputting the recognition result as the waiting elevator scenario.

[0435] It should be understood that the waiting elevator scenario can mean that the electronic device is located near the elevator and has not entered the elevator; for example, the user carrying the electronic device is located near the elevator and has not entered the elevator.

[0436] In the embodiments of the present application, the recognition result obtained when the elevator scenario is recognized includes waiting for an elevator; when the recognition result is waiting for an elevator, the electronic device can pre-apply Link Turbo resources; when the recognition result is entering an elevator scenario, the electronic device can directly start the Link Turbo technology through the pre-applied resources; therefore, through the method for recognizing the elevator scenario in the embodiments of the present application, the time length of the user waiting for a signal in the elevator scenario can be shortened; so that the electronic device can quickly trigger the Link Turbo of the electronic device after entering the elevator, improving the user's online experience.

[0437] In addition, in the embodiments of the present application, the elevator scene is identified by the value of the counting parameter (for example, the Move Count), and a recognition result is obtained; for example, the recognition result can include an entering elevator scene or a non-entering elevator scene; since the elevator scene is directly identified by the data of the acceleration sensor, it is impossible to avoid that the acceleration sensor collects error data due to user mis-touch, thereby causing the accuracy of identifying the elevator scene to be low; compared with directly identifying the elevator scene by the data of the acceleration sensor, identifying the elevator scene by the value of the counting parameter can improve the accuracy of the recognition result; secondly, when the elevator scene is directly identified based on the data of the acceleration sensor, in order to reduce the error in the data collected by the acceleration sensor, multiple frames of data of the acceleration sensor need to be obtained, so that the waiting time of the electronic device is long, causing the elevator scene to be unable to be quickly identified; identifying the elevator scene by the value of the counting parameter is efficient, that is, the elevator scene can be quickly identified; in the embodiments of the present application, the value of the counting parameter can be quickly obtained, and the elevator scene is identified based on the value of the counting parameter, thereby shortening the time of identifying the elevator scene and shortening the waiting time of the user.

[0438] In addition, in the embodiments of the present application, the electronic device can be identified whether it is in an elevator scene based on the data of the air pressure sensor or the data of the air pressure sensor and the acceleration sensor, which can improve the accuracy of the recognition result; in addition, in the embodiments of the present application, when the electronic device is identified whether it is in an elevator scene based on the data of the acceleration sensor, the value of the counting parameter is obtained based on the data of the acceleration sensor of the electronic device, and the elevator scene is identified based on the value of the counting parameter; thereby the accuracy of the recognition result can be improved. It should be understood that the above is exemplified by the elevator scene; the method in the embodiments of the present application is also applicable to identifying other closed scenes or semi-closed scenes (for example, a subway scene or a tunnel scene), and the network signal of the closed scene or the semi-closed scene is usually poor, and the electronic device is prone to freezing; after identifying these scenes, the electronic device can start the full network aggregation technology to perform network switching, and ensure a smooth online experience.

[0439] Optionally, in the embodiments of the present application, whether the electronic device is in an elevator scene can be identified based on the data of the air pressure sensor; that is, in step S409, it can be judged whether the air pressure identifier is a preset identifier, if the air pressure identifier is the preset identifier, the recognition result is that the electronic device enters the elevator scene; if the air pressure identifier is different from the preset identifier, the recognition result is that the electronic device does not enter the elevator scene.

[0440] Optionally, in the embodiments of the present application, as Figure 8The method shown can not include steps S401 to S405; whether the electronic device is in the elevator scene can be determined based on the data of the air pressure sensor; whether the electronic device is in the waiting elevator scene is obtained based on the motion state detection result and the local area network identifier.

[0441] Figure 10 is a schematic flow chart of the method for exiting the elevator mode provided by the embodiment of the present application. The method 600 can be executed by the electronic device shown; the method 600 includes steps S601 to S608, and the steps S601 to S609 will be described in detail respectively. Figure 1

[0442] Step S601, it is identified that the electronic device enters the elevator scene.

[0443] Optionally, the electronic device entering the elevator scene can be identified based on the method shown in Figure 7 、 Figure 8 or Figure 9 ; that is, it is identified that the electronic device is in the elevator fence; details are not repeated here.

[0444] Step S602, a motion state detection result is obtained.

[0445] Optionally, the user can carry the electronic device, and the motion state detection result obtained can refer to the motion state detection result of the user carrying the electronic device.

[0446] Optionally, other mobile devices can carry the electronic device, and the motion state detection result obtained can refer to the motion state detection result of the other mobile devices carrying the electronic device.

[0447] Step S603, it is judged whether the motion state indicated by the motion state detection result is the first motion state and the duration is greater than a threshold 7; if the motion state is the first motion state and the duration is greater than the threshold 7, step S604 is executed; if the motion state is not the first motion state and / or the duration is not greater than the threshold 7, step S605 is executed.

[0448] Exemplarily, the first motion state can refer to the motion state with a speed greater than a preset threshold; for example, if the user carries the electronic device, the first motion state can refer to the walking state of the user; for example, the first motion state and the duration greater than the threshold 7 can be the walking state, and the walking state duration is greater than 6 seconds.

[0449] It should be understood that if the user carries the electronic device, the current motion state of the user is the walking state and lasts for a period of time, it can be indicated that the user has left the elevator fence, at this time the electronic device can exit the elevator mode.

[0450] ​In step S604, the electronic device exits the elevator mode.

[0451] For example, the exiting of the elevator mode can mean that the electronic device exits Link Turbo; for example, the electronic device can switch to mobile data or other local area networks.

[0452] In step S605, the electronic device runs the elevator mode.

[0453] For example, the running of the elevator mode can mean that the electronic device increases the signal search power of the electronic device, thereby ensuring a smooth online experience.

[0454] In step S606, the air pressure flag is obtained.

[0455] For example, the data of the air pressure sensor can be obtained; if the data of the air pressure sensor meets the first preset condition, the air pressure flag is a preset flag; if the data of the air pressure sensor does not meet the first preset condition, the flag of the air pressure sensor is different from the preset flag.

[0456] For example, the preset flag can be "pressureFlag=True".

[0457] In step S607, it is determined whether the air pressure flag is the preset flag; if the air pressure flag is the preset flag, step S604 is performed; if the air pressure flag is different from the preset flag, step S605 is performed.

[0458] In step S608, the local area network flag of the electronic device is obtained.

[0459] For example, the network flag of the local area network currently connected by the electronic device can be obtained.

[0460] Optionally, in the embodiments of the present application, it can be determined whether the electronic device leaves the elevator fence based on the motion state and the network flag; if the electronic device leaves the elevator fence, the electronic device can exit the elevator mode.

[0461] For example, the network flag of the electronic device is different from the network flag of the electronic device entering the elevator fence; if the local area network flag accessed by the electronic device before entering the elevator scene is local area network 1, and the current local area network flag of the electronic device is local area network 2, it can be indicated that the electronic device currently leaves the elevator scene.

[0462] In step S609, it is determined whether the duration of the first motion state is greater than a threshold value 8 and the network flag changes; if the duration of the first motion state is greater than the threshold value 8 and the network flag changes, step S605 is performed; if the duration of the first motion state is less than or equal to the threshold value 8 and / or the network flag does not change, step S604 is performed.

[0463] Optionally, threshold 8 can be less than threshold 7.

[0464] For example, step S603 may be determining whether the duration of the electronic device in the first motion state is greater than 6 seconds; step S609 may be determining whether the duration of the electronic device in the first motion state is greater than 4 seconds, and whether the network identifier of the local area network accessed by the electronic device changes.

[0465] For example, if the movement state of the electronic device is not the first movement state; or, the movement state of the electronic device is the first state but the duration is less than or equal to the threshold 8; or, the network identifier of the electronic device has not changed, it can be indicated that the electronic device is still in the elevator fence; at this time, the electronic device can continue to operate in elevator mode.

[0466] It should also be understood that the above examples are based on a threshold of 6 seconds for threshold 7 and 4 seconds for threshold 8; this application does not impose any limitations on this.

[0467] Optionally, Figure 10 The method shown can also be performed by executing step S604 if at least two of steps S603, S607 or S609 are satisfied; this application does not limit this in any way.

[0468] The following is combined Figures 11 to 16 An example diagram is provided to illustrate the interface diagram of the method for recognizing elevator scenes according to the embodiments of this application when Link Turbo is enabled in an electronic device.

[0469] In one example, such as Figure 11 The graphical user interface (GUI) shown in (a) is the desktop 610 of the electronic device; when the electronic device detects that the user clicks the icon 620 of the settings application on the desktop 610, it can display as follows: Figure 11 Another GUI is shown in (b) above; Figure 11 The GUI shown in (b) can be the display interface of a settings application, which may include controls for wireless network, Bluetooth, battery, or mobile network; for example, a mobile network control 630, such as... Figure 11 As shown in (b); the electronic device detects an operation on control 630 of the mobile network, such as Figure 11 As shown in (c); after the electronic device detects an operation on the control 630 of the mobile network, it displays the mobile network settings display interface; the mobile network settings display interface may include controls 640 for mobile data and network acceleration, such as... Figure 11 As shown in (d) in the diagram; the electronic device detects an operation on the network acceleration control 640, such as...Figure 11 (e) in FIG. 6B; after the electronic device detects the operation on the control 640 of network acceleration, a setting display interface of network acceleration is displayed; in the setting display interface of network acceleration, a control 650 of starting network acceleration and applications supporting network acceleration can be included; the electronic device detects the operation on the control 650 of starting network acceleration, and the electronic device starts the Link Turbo function. Figure 11 (f) in FIG. 6B; after the electronic device detects the operation on the control 650 of starting network acceleration, the electronic device can start the Link Turbo function of the electronic device; that is, the electronic device can identify whether the user is in the elevator scenario by the method for identifying the elevator scenario in the embodiments of the present application, and start the Link Turbo function of the electronic device based on the identification result.

[0470] Exemplarily, after the electronic device starts the Link Turbo function, if the identification result obtained by the method for identifying the elevator scenario in the embodiments of the present application includes entering the elevator scenario, not entering the elevator scenario or waiting for the elevator scenario; when the identification result is entering the elevator scenario, the electronic device can start the elevator mode; that is, in order to ensure the smooth online experience of the user, the signal search power of the electronic device can be increased to realize the Link Turbo function; after the elevator mode is started, the electronic device can display a prompt information "starting the intelligent application elevator mode", such as the prompt box 660 shown in Figure 12

[0471] Optionally, the prompt box 660 can be automatically closed after being displayed in the display interface of the electronic device for a preset time length.

[0472] Exemplarily, after the electronic device starts the Link Turbo function, if the identification result obtained by the method for identifying the elevator scenario in the embodiments of the present application includes entering the elevator scenario, not entering the elevator scenario or waiting for the elevator scenario; when the identification result is entering the elevator scenario, the electronic device can start the elevator mode; that is, in order to ensure the smooth online experience of the user, the signal search power of the electronic device can be increased to realize the Link Turbo function; after the elevator mode is started, the electronic device can display a control of starting the intelligent application elevator mode, such as the icon 670 shown in Figure 13

[0473] Exemplarily, after the electronic device starts the intelligent application elevator mode, the specific information of the intelligent application elevator mode can be viewed through the battery usage of the electronic device; for example, the specific information can include but is not limited to: the number of starts, the background occupation time length / power consumption, the activity time distribution, etc.

[0474] Exemplarily, as shown in Figure 14 ​​The graphical user interface shown in (a) is the desktop 710 of the electronic device. When the electronic device detects that the user clicks the icon 720 of the settings application on the desktop 710, it can display the settings display interface. The settings display interface of the electronic device can include controls such as wireless network, Bluetooth, or battery; for example, it includes a battery control 730, such as... Figure 14 As shown in (b); the electronic device detects an operation on the battery control 730, such as Figure 14 As shown in (c); after the electronic device detects an operation on the battery control 730, it displays the battery settings interface, as shown in [image / image]. Figure 14 As shown in (d); because the smart elevator application mode requires increased signal search power from electronic devices, power consumption is relatively high; therefore, in low power mode, the smart elevator application mode will be turned off, as shown in (d). Figure 14 As shown in (d); after enabling the smart application elevator mode, the specific information of the electronic device can include battery usage and power consumption. Battery usage can include today's screen-on time and a battery level distribution chart; power consumption can include a power consumption distribution chart and a ranking of smart application power consumption. For example, the power consumption of the smart application elevator mode can be 25%, such as... Figure 14 As shown in (e) in the diagram.

[0475] Optionally, such as Figure 15 As shown in (a), the electronic device detects an operation on the control 740 of the smart application elevator mode; after the electronic device detects the operation on the control 740 of the smart application elevator mode, it displays the smart application power consumption display interface of the smart application elevator mode; the smart application power consumption display interface includes a startup management control 750, such as... Figure 15 As shown in (b); the power consumption display interface of the smart application elevator mode includes the background usage time / power consumption, number of launches, activity time distribution chart, and launch management of the smart application elevator mode in the most recent day; among them, in the most recent day "March 31, 11:00 - April 1, 11:00", the background usage time of the smart application elevator mode was "10 minutes and 30 seconds", and the power consumption was "105mAh"; the number of launches of the smart application elevator mode was "5 times", that is, the electronic device detected the user being in the elevator scene 5 times. The electronic device detected the operation of the launch management control 750, such as Figure 15 As shown in (c); after the electronic device detects an operation on the startup management control 750, the startup management display interface is displayed, as shown in [image / image]. Figure 15As shown in (d) in the figure; startup management can include automatic management, enabling / disabling manual management, and specific options for manual management; when the user selects automatic management, the electronic device can automatically adopt targeted power-saving measures; when the user selects to enable manual management, they can further select whether to allow automatic startup or associated startup, and whether to allow running in the background; users can select the startup management options for the smart application elevator mode according to their own needs.

[0476] For example, such as Figure 16 The electronic device shown in (a) detects an operation to learn more about the low power mode; after the electronic device detects the operation to learn more about the low power mode, a display interface for low power mode details can be displayed; as shown Figure 16 As shown in (b), the display interface for low power mode details may include the following power-saving measures that the system will implement in this mode: turn off 5G, turn off always-on display, turn off automatic synchronization, turn off haptic feedback, turn off system notification sounds, reduce display visual effects, display application background activities, reduce system performance, and turn off smart application elevator mode, etc.

[0477] It should be understood that the smart application elevator mode can refer to the electronic device recognizing that the user is in an elevator scene after using the elevator scene recognition method in the embodiments of this application; for example, recognizing that the user is waiting for the elevator, or recognizing that the user has entered the elevator scene, the electronic device can enhance the signal search power so that the user can have a smooth Internet experience in the elevator scene.

[0478] It should also be understood that the above examples are provided to help those skilled in the art understand the embodiments of this application, and are not intended to limit the embodiments of this application to the specific values ​​or scenarios illustrated. Those skilled in the art can obviously make various equivalent modifications or changes based on the above examples, and such modifications or changes also fall within the scope of the embodiments of this application.

[0479] The above text combined Figures 1 to 16 The method for recognizing elevator scenes provided in the embodiments of this application has been described in detail; the following will be combined with Figure 17 and Figure 18 The apparatus embodiments of this application are described in detail below. It should be understood that the apparatus in the embodiments of this application can perform the various methods described in the foregoing embodiments of this application, that is, the specific working processes of the various products described below can be referred to the corresponding processes in the foregoing method embodiments.

[0480] Figure 17 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 800 includes an acquisition module 810 and a processing module 820.

[0481] The acquisition module 810 is configured to acquire first data and second data, the first data is data collected by a first sensor, the second data is data collected by a second sensor, and the first sensor is different from the second sensor; the processing module 820 is configured to obtain a first identification result based on the first data and the second data, the first identification result is used to indicate that the electronic device is in an elevator scenario, or the first identification result is used to indicate that the electronic device is not in the elevator scenario; and in a case where it is detected that the electronic device is in the elevator scenario, an elevator mode is run, the elevator mode being a mode in which the electronic device performs network switching based on a full-network aggregation acceleration technology.

[0482] Optionally, as an embodiment, the first sensor is an air pressure sensor.

[0483] Optionally, as an embodiment, the processing module 820 is specifically configured to:

[0484] obtain a value of a counting parameter based on the second data, the counting parameter being used to indicate that the electronic device moves in a first direction and has an acceleration;

[0485] obtain the first identification result based on the first data and the value of the counting parameter.

[0486] Optionally, as an embodiment, the processing module 820 is specifically configured to:

[0487] determine that the first data satisfies a first preset condition and the value of the counting parameter is greater than a first preset threshold, and the first identification result is used to indicate that the electronic device is in the elevator scenario;

[0488] determine that the first data does not satisfy the first preset condition or the value of the counting parameter is less than or equal to the first preset threshold, and the first identification result is used to indicate that the electronic device is not in the elevator scenario.

[0489] Optionally, as an embodiment, the processing module 820 is specifically configured to:

[0490] obtain height data based on the first data, the height data being used to indicate a distance between the electronic device and the ground;

[0491] determine that the height data is less than a second preset threshold and / or a change value of the first data in a preset time interval is greater than a third preset threshold.

[0492] Optionally, as an embodiment, the processing module 820 is specifically configured to:

[0493] perform filter processing on the second data to obtain third data;

[0494] obtaining a value of the counting parameter based on the third data.

[0495] Optionally, as an embodiment, the obtaining module 810 is further configured to:

[0496] obtain a first detection result and a first network identifier, the first detection result being used to indicate a motion state of a user, the user carrying the electronic device, and the first network identifier being a network identifier of a network currently accessed by the electronic device;

[0497] The processing module 820 is further configured to:

[0498] obtain a second identification result based on the first data and / or the second data, the first detection result and the first network identifier, the second identification result being used to indicate that the electronic device is currently in an elevator waiting scenario.

[0499] Optionally, as an embodiment, the motion state includes a static state, a first motion state and a second motion state, and a speed of the second motion state is greater than a speed of the first motion state.

[0500] Optionally, as an embodiment, the processing module 820 is specifically configured to:

[0501] obtain the second identification result when it is determined that the second data satisfies a second preset condition, the first detection result satisfies a third preset condition, and the first network identifier satisfies a fourth preset condition;

[0502] The second preset condition is that a predicted acceleration of the electronic device obtained based on the second data is greater than a fourth preset threshold value; the third preset condition is that the user exits the first motion state or a time length for the user to exit the second motion state is less than a fifth preset threshold value; and the fourth preset condition is that the first network identifier matches a network identifier in a network identifier feature library, the network identifier feature library including identifiers of local area networks covered by an area where the elevator is located.

[0503] Optionally, as an embodiment, the obtaining module 810 is further configured to:

[0504] obtain a second detection result, the second detection result being that the motion state of the user is the first motion state and a duration of the first motion state is greater than a sixth preset threshold value;

[0505] The processing module 820 is further configured to:

[0506] exit the elevator mode based on the second detection result.

[0507] Optionally, as an embodiment, the obtaining module 810 is further configured to:

[0508] obtain a third detection result and a second network identifier, the third detection result is that the motion state of the user is the first motion state and the duration of the first motion state is greater than a seventh preset threshold, and the second network identifier is different from the first network identifier;

[0509] The processing module 820 is further configured to:

[0510] exit the elevator mode based on the third detection result and the second network identifier.

[0511] Optionally, as an embodiment, the processing module 820 is further configured to:

[0512] exit the elevator mode in a case where the first data does not satisfy the first preset condition.

[0513] Optionally, as an embodiment, the processing module 820 is further configured to:

[0514] apply for a first resource, the first resource is used for the electronic device to run an elevator mode.

[0515] Optionally, as an embodiment, the air pressure sensor is a sensor in a wearable device.

[0516] Optionally, as an embodiment, the electronic device comprises a transmission module, the transmission module is located in an application framework layer, and the obtaining module 810 is specifically configured to:

[0517] receive the first data sent by the wearable device through the transmission module.

[0518] Optionally, as an embodiment, the processing module 820 is further configured to:

[0519] detect a first operation;

[0520] in response to the first operation, display a first interface, the first interface comprises a low power mode, and the low power mode comprises turning off the elevator mode.

[0521] Optionally, as an embodiment, in a case where the electronic device runs the elevator mode, the processing module 820 is further configured to:

[0522] display a first prompt information, the first prompt information is used to instruct the electronic device to turn on the elevator mode.

[0523] Optionally, as an embodiment, in a case where the electronic device runs the elevator mode, the processing module 820 is further configured to:

[0524] displaying a first icon, the first icon being used to indicate that the electronic device starts the elevator mode.

[0525] It should be noted that the electronic device 800 is embodied in the form of functional modules. The term "module" herein can be implemented in the form of software and / or hardware, and is not limited in this regard.

[0526] For example, the "module" can be a software program, hardware circuit, or a combination of both, which implements the above functions. The hardware circuit can include an application specific integrated circuit (ASIC), an electronic circuit, a processor (for example, a shared processor, a dedicated processor, or a group processor, etc.) and a memory for executing one or more software or firmware programs, a combination logic circuit, and / or other suitable components that support the described functions.

[0527] Therefore, the units of the examples described in the embodiments of the present application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0528] Figure 18 A structural schematic diagram of an electronic device provided by the present application is shown. Figure 18 The dashed line in the figure indicates that the unit or the module is optional; the electronic device 900 can be used to implement the method described in the above method embodiments.

[0529] The electronic device 900 includes one or more processors 901, which can support the electronic device 900 to implement the method of identifying an elevator scenario in the method embodiments. The processor 901 can be a general-purpose processor or a special-purpose processor. For example, the processor 901 can be a central processing unit (CPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, such as discrete gates or transistor logic devices, or discrete hardware components.

[0530] The processor 901 can be configured to control the electronic device 900, execute a software program, and process data of the software program. The electronic device 900 can further include a communication unit 905 configured to implement input (reception) and output (transmission) of signals.

[0531] For example, the electronic device 900 can be a chip, the communication unit 905 can be an input and / or output circuit of the chip, or the communication unit 905 can be a communication interface of the chip, and the chip can be a component of a terminal device or other electronic device.

[0532] For another example, the electronic device 900 can be a terminal device, the communication unit 905 can be a transceiver of the terminal device, or the communication unit 905 can be a transceiving circuit of the terminal device.

[0533] The electronic device 900 can include one or more memories 902 having a program 904 stored thereon, and the program 904 can be executed by the processor 901 to generate an instruction 903, so that the processor 901 performs the method of identifying an elevator scenario described in the above method embodiments according to the instruction 903.

[0534] Optionally, the memory 902 can further store data.

[0535] Optionally, the processor 901 can further read data stored in the memory 902, and the data can be stored in the same storage address as the program 904, or the data can be stored in a different storage address from the program 904.

[0536] The processor 901 and the memory 902 can be separately arranged or integrated together, for example, integrated on a system on chip (SOC) of a terminal device.

[0537] For example, the memory 902 can be configured to store the program 904 related to the method of identifying an elevator scenario provided in the embodiments of the present application, and the processor 901 can be configured to call the program 904 related to the method stored in the memory 902 when executing the method of identifying an elevator scenario, and execute the method of the embodiments of the present application; for example, obtaining first data and second data, the first data being data collected by a first sensor, and the second data being data collected by a second sensor, the first sensor being different from the second sensor; obtaining a first identification result based on the first data and the second data, the first identification result being used to indicate that the electronic device is in an elevator scenario, or the first identification result being used to indicate that the electronic device is not in an elevator scenario; running an elevator mode in a case where it is detected that the electronic device is in an elevator scenario, the elevator mode being a mode in which the electronic device performs network switching based on a full-network aggregation acceleration technology.

[0538] The application further provides a computer program product, which, when executed by the processor 901, implements the method for identifying an elevator scenario according to any of the method embodiments.

[0539] The computer program product can be stored in the memory 902, for example, a program 904, which is finally converted into an executable object file capable of being executed by the processor 901 through preprocessing, compiling, assembling, linking and other processing procedures.

[0540] The application further provides a computer readable storage medium, which stores a computer program, and the computer program, when executed by a computer, implements the method for identifying an elevator scenario according to any of the method embodiments. The computer program can be a high-level language program or an executable target program.

[0541] The computer readable storage medium is, for example, the memory 902. The memory 902 can be a volatile memory or a non-volatile memory, or the memory 902 can include both volatile memory and non-volatile memory. The non-volatile memory can be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically EPROM (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM) used as an external cache. By way of example, but not limitation, many forms of RAM can be used, such as a static RAM (SRAM), a dynamic RAM (DRAM), a synchronous DRAM (SDRAM), a double data rate SDRAM (DDR SDRAM), an enhanced SDRAM (ESDRAM), a synchlink DRAM (SLDRAM) and a direct rambus RAM (DR RAM).

[0542] Those skilled in the art can clearly understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0543] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0544] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the above-described embodiments of the electronic device are only schematic, for example, the division of the modules is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0545] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e. can be located in one place or distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0546] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0547] It should be understood that in various embodiments of the present application, the size of the sequence number of each process does not mean the execution order, and the execution order of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0548] In addition, the term "and / or" in this paper is only a description of the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist together, and B exists alone. In addition, the character " / " in this paper generally represents an "or" relationship between the front and rear associated objects.

[0549] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0550] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims. In summary, the above is only a preferred embodiment of the technical solutions of the present application and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method of identifying an elevator scenario, characterized by The application is applied to an electronic device, comprising: obtaining first data and second data, the first data being data collected by an air pressure sensor, and the second data being data collected by an acceleration sensor; obtaining a value of a counting parameter based on the second data, the counting parameter being used to indicate that the electronic device moves in a first direction and has acceleration; obtaining height data based on the first data and an altitude algorithm, the height data being used to indicate the distance between the electronic device and the ground; in the case that the first data meets a first preset condition and the value of the counting parameter increases, determining that the electronic device is in the elevator scenario and running an elevator mode, the elevator mode being a mode in which the electronic device performs network switching based on a full-network aggregation acceleration technology, and the first preset condition including that the change value of the first data is greater than a third preset threshold value within a preset time interval, and the height data is less than a second preset threshold value.

2. The method of claim 1, wherein, The method further comprises: determining that the first data does not meet the first preset condition, or the value of the counting parameter is less than or equal to a first preset threshold value, and determining that the electronic device is not in the elevator scenario.

3. The method of claim 1 or 2, wherein, The obtaining of the value of the counting parameter based on the second data comprises: performing filter processing on the second data to obtain third data; obtaining the value of the counting parameter based on the third data.

4. The method of claim 1 or 2, wherein, Further comprising: obtaining a first detection result and a first network identifier, the first detection result being used to indicate the motion state of a user, the user carrying the electronic device, and the first network identifier being the network identifier of the network currently accessed by the electronic device; obtaining a second identification result based on the first data and / or the second data, the first detection result and the first network identifier, the second identification result being used to indicate that the electronic device is currently in a waiting elevator scenario.

5. The method of claim 4, wherein, The motion state includes a static state, a first motion state and a second motion state, and the speed of the second motion state is greater than that of the first motion state.

6. The method of claim 5, wherein, The obtaining of the second identification result based on the first data and / or the second data, the first detection result and the first network identifier comprises: obtaining the second identification result when the second data meets a second preset condition, the first detection result meets a third preset condition and the first network identifier meets a fourth preset condition; wherein the second preset condition is that the predicted acceleration of the electronic device obtained based on the second data is greater than a fourth preset threshold value; the third preset condition is that the user exits the first motion state or the time length for which the user exits the second motion state is less than a fifth preset threshold value; and the fourth preset condition is that the first network identifier matches a network identifier in a network identifier feature library, the network identifier feature library including the identifiers of local area networks covered by the area where the elevator is located.

7. The method of claim 5, wherein, Further comprising: obtaining a second detection result, the second detection result being that the motion state of the user is the first motion state and the duration of the first motion state is greater than a sixth preset threshold value; exiting the elevator mode based on the second detection result.

8. The method of claim 5, wherein, Further comprising: obtaining a third detection result and a second network identifier, the third detection result being that the motion state of the user is the first motion state and the duration of the first motion state is greater than a seventh preset threshold, and the second network identifier being different from the first network identifier; based on the third detection result and the second network identifier, exiting the elevator mode.

9. The method of claim 1, wherein, Further comprising: in the case that the first data does not satisfy the first preset condition, exiting the elevator mode.

10. The method of claim 4, wherein, Further comprising: applying for a first resource, the first resource being used for the electronic device to run the elevator mode.

11. The method of claim 1, wherein, The air pressure sensor is a sensor in a wearable device.

12. The method of claim 11, wherein, The electronic device comprises a transmission module, the transmission module being located in an application framework layer, and the obtaining of the first data and the second data comprises: receiving, by the transmission module, the first data sent by the wearable device.

13. The method of claim 1 or 2, wherein, Further comprising: detecting a first operation; in response to the first operation, displaying a first interface, the first interface comprising a low power mode, and the low power mode comprising turning off the elevator mode.

14. The method of claim 1 or 2, wherein, In the case that the electronic device runs the elevator mode, further comprising: displaying first prompt information, the first prompt information being used for indicating the electronic device to start the elevator mode.

15. The method of claim 1 or 2, wherein, In the case that the electronic device runs the elevator mode, further comprising: displaying a first icon, the first icon being used for indicating the electronic device to start the elevator mode.

16. An electronic device, comprising: comprising: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program codes, the computer program codes comprising computer instructions, and the one or more processors invoke the computer instructions to enable the electronic device to perform the method according to any one of claims 1 to 15.

17. A chip system, characterized by The chip system is applied to an electronic device, and the chip system comprises one or more processors, and the processor is used to invoke computer instructions to enable the electronic device to perform the method according to any one of claims 1 to 15.

18. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the method according to any one of claims 1 to 15.

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