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, a first detection result and a first network identifier; obtaining an identification result based on the first data, the first detection result and / or the first network identifier, wherein the identification result comprises a first identification result, and the first identification result is used for indicating that the electronic device is currently in an elevator waiting scene; applying for a first resource based on the first identification result, wherein the first resource is used for running an elevator mode of the electronic device, and the elevator mode refers to a mode in which the electronic device performs network switching based on a full-network aggregation acceleration technology; and running the elevator mode based on the first resource in the case of detecting that the electronic device is in the elevator scene. According to the technical scheme of the application, the scene in which the electronic device is located can be accurately identified, the time length for the electronic device to wait for a network signal is shortened, the electronic device can be prevented from appearing a long-time freezing phenomenon, and a smooth online experience is ensured.

Description

Technical Field

[0001] This application relates to the field of terminals, and more specifically, to a method and electronic device for identifying elevator scenes. Background Technology

[0002] Currently, Link Turbo, a full-network aggregation acceleration technology, integrates mobile and fixed-line data communication technologies. Through edge-cloud collaborative network aggregation, it delivers a high-speed, stable, and low-latency mobile internet experience to users under varying network conditions. However, in certain closed or semi-closed scenarios, such as elevators, subways, or tunnels, the current recognition accuracy of electronic devices is low, failing to accurately identify these scenarios. Furthermore, even after recognizing these scenarios, the full-network aggregation acceleration technology on the electronic device cannot be quickly activated, resulting in a poor internet experience for users in certain scenarios; for example, in these specific scenarios, users may experience buffering or stuttering.

[0003] Therefore, accurately identifying the scene in which electronic devices are located (e.g., an elevator scene) and avoiding prolonged lag in electronic devices has become an urgent problem to be solved. Summary of the Invention

[0004] This application provides a method and electronic device for identifying elevator scenes, which can accurately identify the scene in which the electronic device is located, shorten the time the electronic device waits for network signals, avoid prolonged lag in the electronic device, and ensure a smooth Internet experience.

[0005] Firstly, a method for recognizing elevator scenes is provided, which can be applied to electronic devices, including:

[0006] Acquire first data, first detection result and first network identifier, wherein the first data is data collected by the accelerometer in the electronic device, the first detection result is used to indicate the user's motion state, the user is carrying the electronic device, and the first network identifier is the network identifier of the network currently accessed by the electronic device;

[0007] An identification result is obtained based on the first data, the first detection result, and / or the first network identifier. The identification result includes a first identification result, which is used to indicate that the electronic device is currently in a waiting elevator scenario.

[0008] Based on the first identification result, a first resource is applied for. The first resource is used for the electronic device to operate in elevator mode. The elevator mode refers to the mode in which the electronic device switches networks based on full network aggregation acceleration technology.

[0009] If the electronic device is detected to be in an elevator scenario, the elevator mode is run based on the first resource.

[0010] 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.

[0011] 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.

[0012] It should be understood that the primary resource can refer to the memory resources of an electronic device, and the primary resource can be used for the electronic device to run elevator mode.

[0013] It should also be understood that, in the embodiments of this application, the identification result can be obtained based on multimodal data of the first data, the first detection result and / or the first network identifier. The identification result includes the first identification result, which is that the electronic device is in a waiting elevator scenario. Since this application obtains the identification result based on multimodal data, the accuracy of the identification result is high. In addition, through the solution of this application, not only can the electronic device be identified as being in an elevator scenario, but also the electronic device can be identified as being in a waiting elevator scenario; that is, the scenario where the electronic device is at the elevator entrance but has not entered the elevator.

[0014] In the embodiments of this application, an identification result can be obtained through first data, a first detection result, and / or a first network identifier. The identification result includes a first identification result, that is, the electronic device can identify a waiting elevator scenario. When the identification result is a waiting elevator scenario, the electronic device can pre-apply for a first resource. When the identification result is an elevator scenario, the electronic device can directly activate the full network aggregation acceleration technology through the pre-applied first resource. Since the method of this application embodiment can identify that the electronic device is in a waiting elevator scenario, and the electronic device can apply for a first resource to execute the full network aggregation acceleration technology when it is in an elevator scenario, the electronic device can quickly run elevator mode through the first resource after entering the elevator scenario. Therefore, the method of identifying elevator scenarios in this application embodiment can accurately identify elevator scenarios and shorten the time users wait for signals in elevator scenarios. This enables the electronic device to quickly trigger the full network aggregation acceleration technology after entering the elevator, improving the internet experience.

[0015] In one possible implementation, the identification result can be obtained based on the first data; for example, based on the first data, it can be determined whether the electronic device is in an elevator scene or not.

[0016] In one possible implementation, the identification result can be obtained based on the first data and the first detection result; for example, based on the first data and the first detection result, it can be determined whether the electronic device is in an elevator scene or not.

[0017] In one possible implementation, the identification result can be obtained based on the first data and the first network identifier; for example, based on the first data and the first network identifier, it can be determined whether the electronic device is in an elevator scene or not.

[0018] In one possible implementation, the identification result can be obtained based on the first data, the first detection result, and the first network identifier; for example, obtaining the identification result based on the first data, the first detection result, and the first network identifier can reveal that the electronic device is in a scenario of waiting for an elevator.

[0019] In conjunction with the first aspect, in certain implementations of the first aspect, obtaining the identification result based on the first data, the first detection result, and / or the first network identifier includes:

[0020] The first identification result is obtained based on the first data, the first detection result, and the first network identifier.

[0021] In the embodiments of this application, the recognition result of the elevator scene can be obtained by fusing multimodal data such as the first data from the accelerometer, the first detection result, and the first network identifier. Since the method of the embodiments of this application can obtain the recognition result based on multimodal data, the accuracy of the recognition result can be improved.

[0022] In conjunction with the first aspect, in some implementations of the first aspect, the identification result includes a second identification result, and obtaining the identification result based on the first data, the first detection result, and / or the first network identifier includes:

[0023] The value of the counting parameter is obtained based on the first data, and the counting parameter is used to indicate that the electronic device is moving in a first direction and has acceleration;

[0024] The second identification result is obtained based on the value of the counting parameter, and the second identification result is used to indicate whether the electronic device is in the elevator scene.

[0025] In the embodiments of this application, elevator scenes are identified by the value of a counting parameter (e.g., Move Count). Since identifying elevator scenes directly using data from an accelerometer cannot avoid errors caused by user accidental touches leading to lower accuracy, identifying elevator scenes by using the value of the counting parameter improves accuracy. Furthermore, directly identifying elevator scenes based on accelerometer data requires acquiring multiple frames of accelerometer data to reduce errors, resulting in longer waiting times for the electronic device and hindering rapid scene identification. The elevator scene identification method of this application, using the value of the counting parameter, is more efficient, enabling rapid scene identification. Therefore, the elevator scene identification method of this application can quickly and accurately identify elevator scenes.

[0026] In conjunction with the first aspect, in certain implementations of the first aspect, obtaining the second identification result based on the value of the counting parameter includes:

[0027] If the value of the counting parameter is greater than a first preset threshold, the second identification result is used to indicate that the electronic device is in the elevator scene;

[0028] If the value of the counting parameter is less than or equal to the first preset threshold, the second identification result is used to indicate that the electronic device is not in the elevator scenario.

[0029] In the embodiments of this application, in order to avoid the user accidentally touching the screen and causing low accuracy of the recognition result, when the data of the counting parameter is greater than the first threshold, the second recognition result is determined to be that the electronic device is in an elevator scene, thereby improving the accuracy of the recognition result.

[0030] In conjunction with the first aspect, in some implementations of the first aspect, obtaining the value of the counting parameter based on the first data includes:

[0031] The first data is filtered to obtain the second data;

[0032] Based on the second data, the value of the counting parameter is obtained.

[0033] In the embodiments of this application, by performing filter processing on the first data, error data in the first data can be eliminated, thereby improving the accuracy of the counting parameter values.

[0034] In conjunction with the first aspect, in some implementations of the first aspect, the step of performing filter processing on the first data to obtain the second data includes:

[0035] The second data is obtained by processing the first data with a bandpass filter and a lowpass filter.

[0036] 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.

[0037] In conjunction with the first aspect, some implementations of the first aspect also include:

[0038] The first detection result is obtained by using a gradient boosting tree model.

[0039] In conjunction with the first aspect, in some implementations of the first aspect, the motion state includes a stationary state, a first motion state, and a second motion state, wherein the speed of the second motion state is greater than the speed of the first motion state.

[0040] In conjunction with the first aspect, in certain implementations of the first aspect, obtaining the first identification result based on the first data, the first detection result, and the first network identifier includes:

[0041] When the first data meets the first preset condition, the first detection result meets the second preset condition, and the first network identifier meets the third preset condition, the first identification result is obtained;

[0042] Wherein, the first preset condition refers to the predicted acceleration of the electronic device obtained based on the first data being greater than the second preset threshold; the second preset condition refers to the duration of the user exiting the first motion state or the duration of the user exiting the second motion state being less than the third threshold; the third preset condition is that the first network identifier matches the network identifier in the network identifier feature library, which includes the identifiers of the local area networks covered by the area where the elevator is located.

[0043] In conjunction with the first aspect, some implementations of the first aspect also include:

[0044] Obtain a second detection result, wherein the user's motion state is the first motion state and the duration of the first motion state is greater than a fourth preset threshold.

[0045] Exit the elevator mode based on the second detection result.

[0046] In the embodiments of this application, after the electronic device activates elevator mode, the scene of the electronic device leaving the elevator can be identified based on the motion state detection results of the electronic device, thereby causing the electronic device to exit elevator mode.

[0047] In conjunction with the first aspect, some implementations of the first aspect also include:

[0048] Obtain a third detection result and a second network identifier. The third detection result is that the user's motion state is the first motion state and the duration of the first motion state is greater than a fifth preset threshold. The second network identifier is different from the first network identifier.

[0049] Based on the third detection result and the second network identifier, exit the elevator mode.

[0050] In the embodiments of this application, after the electronic device activates elevator mode, the scene of the electronic device leaving the elevator can be identified based on the motion state detection results and network identifier of the electronic device, thereby causing the electronic device to exit elevator mode.

[0051] In conjunction with the first aspect, some implementations of the first aspect also include:

[0052] First operation detected;

[0053] In response to the first operation, a first interface is displayed, which includes a low power mode, and the low power mode includes turning off the elevator mode.

[0054] In conjunction with the first aspect, in some implementations of the first aspect, when the electronic device is operating the elevator mode, it further includes:

[0055] The first prompt message is displayed, which instructs the electronic device to activate the elevator mode.

[0056] In conjunction with the first aspect, in some implementations of the first aspect, when the electronic device is operating the elevator mode, it further includes:

[0057] Display a first icon, which indicates that the electronic device should activate the elevator mode.

[0058] In a second aspect, an electronic device is provided, the electronic device comprising one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the electronic device to execute:

[0059] Acquire first data, first detection result and first network identifier, wherein the first data is data collected by the accelerometer in the electronic device, the first detection result is used to indicate the user's motion state, the user is carrying the electronic device, and the first network identifier is the network identifier of the network currently accessed by the electronic device;

[0060] An identification result is obtained based on the first data, the first detection result, and / or the first network identifier. The identification result includes a first identification result, which is used to indicate that the electronic device is currently in a waiting elevator scenario.

[0061] Based on the first identification result, a first resource is applied for. The first resource is used for the electronic device to operate in elevator mode. The elevator mode refers to the mode in which the electronic device switches networks based on full network aggregation acceleration technology.

[0062] If the electronic device is detected to be in an elevator scenario, the elevator mode is run based on the first resource.

[0063] In conjunction with 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 execute:

[0064] The first identification result is obtained based on the first data, the first detection result, and the first network identifier.

[0065] In conjunction with the second aspect, in some implementations of the second aspect, the identification result includes a second identification result, and the one or more processors invoke the computer instructions to cause the electronic device to execute:

[0066] The value of the counting parameter is obtained based on the first data, and the counting parameter is used to indicate that the electronic device is moving in a first direction and has acceleration;

[0067] The second identification result is obtained based on the value of the counting parameter, and the second identification result is used to indicate whether the electronic device is in the elevator scene.

[0068] In conjunction with 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 execute:

[0069] If the value of the counting parameter is greater than a first preset threshold, the second identification result is used to indicate that the electronic device is in the elevator scene;

[0070] If the value of the counting parameter is less than or equal to the first preset threshold, the second identification result is used to indicate that the electronic device is not in the elevator scenario.

[0071] In conjunction with 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 execute:

[0072] The first data is filtered to obtain the second data;

[0073] Based on the second data, the value of the counting parameter is obtained.

[0074] In conjunction with 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 execute:

[0075] The second data is obtained by processing the first data with a bandpass filter and a lowpass filter.

[0076] In conjunction with 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 execute:

[0077] The first detection result is obtained by using a gradient boosting tree model.

[0078] In conjunction with 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, wherein the speed of the second motion state is greater than the speed of the first motion state.

[0079] In conjunction with 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 execute:

[0080] When the first data meets the first preset condition, the first detection result meets the second preset condition, and the first network identifier meets the third preset condition, the first identification result is obtained;

[0081] Wherein, the first preset condition refers to the predicted acceleration of the electronic device obtained based on the first data being greater than the second preset threshold; the second preset condition refers to the duration of the user exiting the first motion state or the duration of the user exiting the second motion state being less than the third threshold; the third preset condition is that the first network identifier matches the network identifier in the network identifier feature library, which includes the identifiers of the local area networks covered by the area where the elevator is located.

[0082] In conjunction with 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 execute:

[0083] Obtain a second detection result, wherein the user's motion state is the first motion state and the duration of the first motion state is greater than a fourth preset threshold.

[0084] Exit the elevator mode based on the second detection result.

[0085] In conjunction with 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 execute:

[0086] Obtain a third detection result and a second network identifier. The third detection result is that the user's motion state is the first motion state and the duration of the first motion state is greater than a fifth preset threshold. The second network identifier is different from the first network identifier.

[0087] Based on the third detection result and the second network identifier, exit the elevator mode.

[0088] In conjunction with 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 execute:

[0089] First operation detected;

[0090] In response to the first operation, a first interface is displayed, which includes a low power mode, and the low power mode includes turning off the elevator mode.

[0091] In conjunction with the second aspect, in some implementations of the second aspect, when the electronic device is operating in the elevator mode, the one or more processors invoke the computer instructions to cause the electronic device to execute:

[0092] The first prompt message is displayed, which instructs the electronic device to activate the elevator mode.

[0093] In conjunction with the second aspect, in some implementations of the second aspect, when the electronic device is operating in the elevator mode, the one or more processors invoke the computer instructions to cause the electronic device to execute:

[0094] Display a first icon, which indicates that the electronic device should activate the elevator mode.

[0095] Thirdly, an electronic device is provided, including a module / unit for performing the method of recognizing an elevator scene as described in the first aspect or any of the methods described in the first aspect.

[0096] Fourthly, an electronic device is provided, the electronic device including one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the electronic device to perform the first aspect or any one of the methods in the first aspect.

[0097] Fifthly, a chip system is provided, the chip system being applied to an electronic device, the chip system including one or more processors, the processors being configured to invoke computer instructions to cause the electronic device to perform the first aspect or any of the methods in the first aspect.

[0098] In a sixth aspect, a computer-readable storage medium is provided, the computer-readable storage medium storing computer program code that, when executed by an electronic device, causes the electronic device to perform the first aspect or any one of the methods in the first aspect.

[0099] In a seventh aspect, a computer program product is provided, the computer program product comprising: computer program code, which, when executed by an electronic device, causes the electronic device to perform the method of the first aspect or any one of the first aspects.

[0100] In the embodiments of this application, an identification result can be obtained through first data, a first detection result, and / or a first network identifier. The identification result includes a first identification result, that is, the electronic device can identify a waiting elevator scenario. When the identification result is a waiting elevator scenario, the electronic device can pre-apply for a first resource. When the identification result is an elevator scenario, the electronic device can directly activate the full network aggregation acceleration technology through the pre-applied first resource. Since the method of this application embodiment can identify that the electronic device is in a waiting elevator scenario, and the electronic device can apply for a first resource to execute the full network aggregation acceleration technology when it is in an elevator scenario, the electronic device can quickly run elevator mode through the first resource after entering the elevator scenario. Therefore, the method of identifying elevator scenarios in this application embodiment can accurately identify elevator scenarios and shorten the time users wait for signals in elevator scenarios. This enables the electronic device to quickly trigger the full network aggregation acceleration technology after entering the elevator, improving the internet experience. Attached Figure Description

[0101] Figure 1 This is a schematic diagram of a hardware system for an electronic device applicable to this application;

[0102] Figure 2 This is a schematic diagram of a software system applicable to an electronic device of this application;

[0103] Figure 3 This is a schematic diagram illustrating an application scenario applicable to an embodiment of this application;

[0104] Figure 4 This is a schematic diagram illustrating an application scenario applicable to an embodiment of this application;

[0105] Figure 5 This is a schematic diagram illustrating an application scenario applicable to an embodiment of this application;

[0106] Figure 6 This is a schematic flowchart illustrating a method for identifying elevator scenes provided in an embodiment of this application;

[0107] Figure 7 This is a schematic flowchart illustrating a method for identifying elevator scenes provided in an embodiment of this application;

[0108] Figure 8 This is a schematic flowchart illustrating a method for identifying elevator scenes provided in an embodiment of this application;

[0109] Figure 9 This is a schematic flowchart illustrating a method for exiting elevator mode provided in an embodiment of this application;

[0110] Figure 10This is a schematic diagram of a graphical user interface applicable to embodiments of this application;

[0111] Figure 11 This is a schematic diagram of a graphical user interface applicable to embodiments of this application;

[0112] Figure 12 This is a schematic diagram of a graphical user interface applicable to embodiments of this application;

[0113] Figure 13 This is a schematic diagram of a graphical user interface applicable to embodiments of this application;

[0114] Figure 14 This is a schematic diagram of a graphical user interface applicable to embodiments of this application;

[0115] Figure 15 This is a schematic diagram of a graphical user interface applicable to embodiments of this application;

[0116] Figure 16 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0117] Figure 17 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0118] In the embodiments of this application, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this embodiment, unless otherwise stated, "multiple" means two or more.

[0119] To facilitate understanding of the embodiments of this application, the relevant concepts involved in the embodiments of this application will be briefly explained first.

[0120] 1. Full-network aggregation acceleration technology (Link Turbo)

[0121] Link Turbo refers to a technology that integrates mobile data communication and fixed-line data communication. Through end-to-end cloud-based network aggregation, it brings users a high-speed, stable, and low-latency mobile internet experience under varying network conditions.

[0122] For example, Link Turbo has an "intelligent link offloading mode" that can intelligently determine the wireless network status. When it detects poor wireless network conditions (e.g., weak signal, or strong signal but multiple devices and applications sharing the network causing network congestion), and an application needs to be used, Link Turbo can intelligently switch these applications to the mobile network (automatically switching back to the wireless network after use). Other background applications still maintain wireless network communication, enabling parallel processing of mobile cellular data and wireless network data, serving different applications simultaneously, and speeding up applications that need to be used instantly for a short period of time with minimal data usage.

[0123] Secondly, Link Turbo also supports "intelligent link aggregation mode." When poor wireless network conditions are detected, and large data throughput such as game downloads and online video playback is required, Link Turbo will simultaneously activate the cellular network, allowing both cellular and wireless connections to send and receive data simultaneously. This parallel acceleration meets the needs of high-throughput business scenarios, effectively reducing latency and improving communication bandwidth. For example, when playing games and the wireless network fluctuates, the mobile cellular network will quickly intervene to reduce latency caused by the fluctuations and ensure smooth gameplay. Similarly, when downloading a game or video and the wireless network is poor, resulting in slow download speeds, the mobile cellular network will automatically activate, allowing both networks to run in parallel and accelerating the download speed.

[0124] It should be understood that full-network aggregation acceleration technology can also be called multi-network collaborative technology.

[0125] 2. Elevator railing

[0126] The scope of an elevator fence can refer to the area where the elevator entrance is located, or the area where the elevator is located.

[0127] 3. Bandpass filter

[0128] A band-pass filter is a device that allows waves of a specific frequency band to pass through while blocking other frequency bands; for example, an oscillating circuit composed of resistors, inductors, and capacitors can be an analog band-pass filter.

[0129] 4. Low-pass filter

[0130] A low-pass filter is a filtering method that allows low-frequency signals to pass through normally, while high-frequency signals exceeding a set threshold are blocked or weakened.

[0131] 5. Low-pass filter

[0132] A low-pass filter is an electronic filter that allows signals below the cutoff frequency to pass through, but blocks signals above the cutoff frequency.

[0133] 6. Moving average

[0134] An exponential moving average, also known as an exponentially weighted moving average, is used to estimate the local mean of a variable, making the variable's updates related to its historical values ​​over a period of time. Moving averages are typically used to eliminate the influence of random changes.

[0135] 7. Sliding standard deviation

[0136] Moving standard deviation is used to measure the degree of dispersion from the moving average.

[0137] The method and electronic device for recognizing elevator scenes in the embodiments of this application will now be described with reference to the accompanying drawings.

[0138] Figure 1 A hardware system for an electronic device applicable to this application is shown.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] For example, in an embodiment of this application, the audio module 170 can send audio data collected by the microphone to the processor 110.

[0143] 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 The components shown may be a combination of certain components, or the electronic device 100 may include... Figure 1 Sub-components of some of the components shown. Figure 1 The components shown can be implemented in hardware, software, or a combination of software and hardware.

[0144] Processor 110 may include one or more processing units. For example, processor 110 may include at least one of the following processing units: application processor (AP), modem processor, graphics processing unit (GPU), image signal processor (ISP), controller, video codec, digital signal processor (DSP), baseband processor, and neural network processing unit (NPU). These different processing units may be independent devices or integrated devices. The controller can generate operation control signals based on instruction opcodes and timing signals to control instruction fetching and execution.

[0145] The processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. This memory can store instructions or data that the processor 110 has just used or that are used repeatedly. If the processor 110 needs to use the instruction or data again, it can retrieve it directly from the memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0146] For example, the processor 110 can be used to execute the method for identifying elevator scenarios according to the embodiments of this application; for example, acquiring first data, a first detection result, and a first network identifier, wherein the first data is data collected by an accelerometer in an electronic device, the first detection result is used to indicate the user's motion state, the user is carrying an electronic device, and the first network identifier is the network identifier of the network currently accessed by the electronic device; obtaining an identification result based on the first data, the first detection result, and / or the first network identifier, the identification result including a first identification result, the first identification result being used to indicate that the electronic device is currently in a waiting elevator scenario; applying for a first resource based on the first identification result, the first resource being used for the electronic device to run an elevator mode, the elevator mode referring to the mode in which the electronic device switches networks based on full-network aggregation acceleration technology; and running the elevator mode based on the first resource when the electronic device is detected to be in an elevator scenario.

[0147] Figure 1 The connection relationships between the modules shown are merely illustrative and do not constitute a limitation on the connection relationships between the modules of the electronic device 100. Optionally, the modules of the electronic device 100 may also adopt a combination of various connection methods described in the above embodiments.

[0148] The wireless communication function of electronic device 100 can be realized through devices such as antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor and baseband processor.

[0149] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 100 can be used to cover one or more communication frequency bands. Different antennas can also be multiplexed to improve antenna utilization. For example, antenna 1 can be multiplexed as a diversity antenna for a wireless local area network. In some other embodiments, the antennas can be used in conjunction with a tuning switch.

[0150] Electronic device 100 can implement display functions through a GPU, a display screen 194, and an 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 and for graphics rendering. Processor 110 may include one or more GPUs, which execute program instructions to generate or modify display information.

[0151] Display screen 194 can be used to display images or videos.

[0152] Electronic device 100 can perform shooting functions through ISP, camera 193, video codec, GPU, display screen 194 and application processor.

[0153] The ISP (Image Signal Processor) is used to process data fed back from the camera 193. For example, when taking a picture, the shutter is opened, and light is transmitted through the lens to the camera's photosensitive element. The light signal is converted into an electrical signal, and the camera's photosensitive element transmits the electrical signal to the ISP for processing, transforming it into an image visible to the naked eye. The ISP can perform algorithmic optimization of image noise, brightness, and color. The ISP can also optimize parameters such as exposure and color temperature of the shooting scene. In some embodiments, the ISP can be set in the camera 193.

[0154] Camera 193 is used to capture still images or videos. An object is projected onto a photosensitive element by generating an optical image through the lens. The photosensitive element can be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, which is then passed to an ISP for conversion 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 other image signal format. In some embodiments, the electronic device 100 may include one or N cameras 193, where N is a positive integer greater than 1.

[0155] Digital signal processors (DSPs) are used to process digital signals. Besides digital image signals, they can also process other digital signals. For example, when electronic device 100 selects a frequency, the DSP performs Fourier transforms on the frequency energy.

[0156] Video codecs are used to compress or decompress digital video. Electronic device 100 may support one or more video codecs. Thus, electronic device 100 can play or record video in various encoding formats, such as Moving Picture Experts Group (MPEG) 1, MPEG 2, MPEG 3, and MPEG 4.

[0157] The gyroscope sensor 180B can be used to determine the motion attitude of the electronic device 100. In some embodiments, the gyroscope sensor 180B can determine the angular velocity of the electronic device 100 around three axes (i.e., the x-axis, y-axis, and z-axis). The gyroscope sensor 180B can be used for image stabilization. For example, when the shutter is pressed, the gyroscope sensor 180B detects the angle of the shake of the electronic device 100, calculates the distance that the lens module needs to compensate based on the angle, and allows the lens to counteract the shake of the electronic device 100 by moving in the opposite direction, thus achieving image stabilization. The gyroscope sensor 180B can also be used in scenarios such as navigation and motion-sensing games.

[0158] The accelerometer 180E can detect the magnitude of acceleration of the electronic device 100 in various directions (typically the x-axis, y-axis, and z-axis). When the electronic device 100 is stationary, it can detect the magnitude and direction of gravity. The accelerometer 180E can also be used to identify the attitude of the electronic device 100, serving as input parameters for applications such as screen orientation switching and pedometers.

[0159] For example, in an embodiment of this application, the acceleration sensor may include an accelerometer.

[0160] The distance sensor 180F is used to measure distance. The electronic device 100 can measure distance using infrared or laser. In some embodiments, such as in a shooting scenario, the electronic device 100 can utilize the distance sensor 180F to measure distance for fast focusing.

[0161] The ambient light sensor 180L is used to sense the brightness of ambient light. The electronic device 100 can adaptively adjust the brightness of the display screen 194 based on 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 work with the proximity sensor 180G to detect whether the electronic device 100 is in a pocket to prevent accidental touches.

[0162] The fingerprint sensor 180H is used to collect fingerprints. The electronic device 100 can use the collected fingerprint characteristics to perform functions such as unlocking, accessing application locks, taking photos, and answering calls.

[0163] Touch sensor 180K, also known as a touch device, can be disposed on display screen 194. The touch sensor 180K and display screen 194 together form a touchscreen, also known as a touch screen. Touch sensor 180K is used to detect touch operations applied to or near it. Touch sensor 180K can transmit the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through display screen 194. In other embodiments, touch sensor 180K may also be disposed on the surface of electronic device 100, and in a different location from display screen 194.

[0164] Currently, Link Turbo, a full-network aggregation acceleration technology, integrates mobile and fixed-line data communication technologies. Through edge-cloud collaborative network aggregation, it delivers a high-speed, stable, and low-latency mobile internet experience to users under varying network conditions. However, in certain scenarios, such as elevators, subways, or tunnels, the accuracy of current electronic devices in recognizing these scenarios is relatively low. They cannot accurately identify these scenarios and quickly activate the full-network aggregation acceleration technology, resulting in a poor internet experience for users in these specific situations; for example, users may experience buffering or stuttering when browsing the internet in these scenarios.

[0165] In view of this, embodiments of this application provide a method for identifying elevator scenarios. In embodiments of this application, the identification result obtained when identifying an elevator scenario includes waiting for an elevator. When the identification result is waiting for an elevator, the electronic device can request Link Turbo resources. When the identification result is entering an elevator scenario, the electronic device can directly and quickly activate Link Turbo technology through the pre-requested resources. Therefore, the method for identifying elevator scenarios in embodiments of this application can shorten the time a user waits for a signal in an elevator scenario, enabling the electronic device to quickly trigger the full network aggregation acceleration technology of the electronic device after entering the elevator, thereby improving the internet browsing experience.

[0166] Furthermore, in the embodiments of this application, elevator scenes are identified by the value of a counting parameter (e.g., Move Count). Since identifying elevator scenes directly using data from an accelerometer cannot avoid errors caused by accidental user touches leading to incorrect data collection by the accelerometer in the electronic device, the accuracy of elevator scene identification is low. Identifying elevator scenes using the value of the counting parameter significantly improves accuracy compared to directly using accelerometer data. Secondly, when directly identifying elevator scenes based on accelerometer data, multiple frames of data collected by the accelerometer are required to avoid accidental touches by the electronic device, resulting in a longer waiting time for the electronic device and hindering rapid elevator scene identification. In the embodiments of this application, identifying elevator scenes using the value of the counting parameter enables rapid elevator scene identification. Therefore, the elevator scene identification method based on this application can quickly and accurately identify elevator scenes, shortening the user's waiting time and allowing the user to quickly trigger Link Turbo on the electronic device after entering the elevator, improving the user's internet browsing experience.

[0167] The following is combined Figures 2 to 15 The method for identifying elevator scenarios provided in the embodiments of this application will be described in detail.

[0168] Figure 2 This is a schematic diagram of the software system of the electronic device provided in the embodiments of this application.

[0169] like Figure 2 As shown, the system architecture may 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.

[0170] Application layer 210 may include settings applications or other applications; other applications include, but are not limited to: camera applications, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, SMS and other applications.

[0171] The application framework layer 220 provides application programming interfaces (APIs) and programming frameworks for applications in the application layer; the application framework layer may include some predefined functions.

[0172] For example, in embodiments of this application, the application framework layer 220 may include predefined functions or interfaces of LinkTurbo (full network aggregation). For instance, the application framework layer 220 may obtain the local area network identifier of the electronic device.

[0173] Hardware abstraction layer 230 is used to abstract hardware.

[0174] For example, the hardware abstraction layer 230 may include a smart sensor fusion hardware abstraction module 231; wherein, the smart sensor fusion hardware abstraction module 231 can be used to run algorithms that consume a lot of memory and consume a lot of power; for example, the smart sensor fusion hardware abstraction module 231 can be used to run elevator scene recognition algorithms, subway scene recognition algorithms or tunnel scene recognition algorithms, etc.

[0175] For example, the elevator scene recognition algorithm can refer to the algorithm related to the elevator scene recognition method provided in the embodiments of this application; similarly, the elevator scene recognition method provided in the embodiments of this application can also recognize other scenes with poor Internet experience, such as subway scenes or tunnel scenes.

[0176] The sensor algorithm layer 240 may include low-power underlying algorithm modules running in electronic devices; for example, the underlying algorithm modules may run algorithms with low memory consumption and low power consumption; for example, the underlying algorithm modules may include, but are not limited to, algorithms related to walking motion state detection results, as described later. Figure 7 The step S410 shown; the walking motion state detection result may include, but is not limited to: standing still, walking or running, etc.

[0177] For example, the sensor algorithm layer 240 can transmit data to the smart sensor fusion hardware module 231.

[0178] Optionally, the smart sensor fusion hardware abstraction module 231 and the underlying algorithm module can communicate with each other; for example, the output data of the underlying algorithm module can be used as the input data of the smart sensor fusion hardware abstraction module 231 to optimize the high-power algorithm.

[0179] Optionally, the smart sensor fusion hardware abstraction module 231 and the underlying algorithm module can be located in the same hardware in the electronic device; or, the smart sensor fusion hardware abstraction module 231 and the underlying algorithm module can be located in different hardware in the electronic device.

[0180] For example, the smart sensor fusion hardware abstraction module 231 and the underlying algorithm module may be located on the same chip in the electronic device; or, the smart sensor fusion hardware abstraction module 231 and the underlying algorithm module may be located on different chips in the electronic device.

[0181] Hardware layer 250 is located at the lowest level of the operating system; for example, hardware layer 250 may include an accelerometer.

[0182] 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.

[0183] The following is combined Figures 3 to 5 The application scenarios of the elevator scene identification method provided in the embodiments of this application are illustrated with examples.

[0184] Link Turbo enables electronic devices to achieve a smoother internet browsing experience in data transmission and reception scenarios such as gaming, video playback, and online chatting. The elevator scene identification method provided in this application can shorten the waiting time for enabling Link Turbo, thereby ensuring that electronic devices can better achieve Link Turbo and improve the user experience. For example, if the electronic device identifies that it is in an elevator scene, it can increase the signal search power, thereby reducing or avoiding application lag issues and ensuring a smoother internet browsing experience for the user.

[0185] For example, the identification result obtained by the method for identifying elevator scenarios based on the embodiments of this application may include a waiting elevator scenario, an elevator entry scenario, or an elevator non-entry scenario.

[0186] For example, such as Figure 3 The elevator waiting scenario shown can refer to a situation where the user has not yet entered the elevator; electronic device 260 can identify that the user is located in front of elevator 270 and waiting for the elevator.

[0187] For example, entering an elevator scenario can refer to an electronic device entering an elevator; for instance, entering an elevator scenario could include entering an elevator when the elevator is not in operation, or entering an elevator when the elevator is running; for example, such as Figure 4 As shown, the electronic device is currently inside the elevator and the elevator is not moving, meaning the elevator is neither accelerating upwards nor downwards; for example, as Figure 5 As shown, the electronic device is currently located in the elevator and the elevator is in operation; for example, the elevator may be moving upwards or downwards.

[0188] It should be understood that the elevator scene identification method in this application embodiment can not only identify whether the electronic device has entered the elevator scene or not, but also identify the elevator waiting scene. When the elevator waiting 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 quickly 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.

[0189] 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.

[0190] The following is combined Figures 6 to 15 The method for identifying elevator scenarios provided in the embodiments of this application will be described in detail.

[0191] Figure 6 This is a schematic flowchart of a method for identifying elevator scenes provided in an embodiment of this application. The method 300 can be... Figure 1 The electronic device shown executes the method 300, which includes steps S310 to S340. Steps S310 to S340 are described in detail below.

[0192] Step S310: Obtain the first data, the first detection result, and the first network identifier.

[0193] The first data is the data collected by the accelerometer in the electronic device; the first detection result is used to indicate the user's motion state and the user is carrying the electronic device; the first network identifier is the network identifier of the network currently accessed by the electronic device.

[0194] For example, an acceleration sensor can refer to, for instance, an acceleration sensor. Figure 1 As shown in the 180E, the accelerometer can detect the magnitude of acceleration in various directions (typically the x-axis, y-axis, and z-axis) of an electronic device.

[0195] For example, such as Figure 3 The user carrying the electronic device shown refers to the user of the handheld electronic device 260.

[0196] It should be understood that since the user carries the electronic device, the electronic device is in the same state of motion as the user; for example, when the user is stationary, the electronic device is also stationary; when the user is in motion, the electronic device is also in motion.

[0197] For example, in embodiments of this application, the motion state may include a stationary state, a walking state (an example of a first motion state), or a running state (an example of a second motion state).

[0198] Step S320: Obtain the identification result based on the first data, the first detection result, and / or the first network identifier.

[0199] The identification results include a first identification result, which indicates that the electronic device is currently in a waiting elevator scenario.

[0200] In one example, the recognition result can be obtained based on the first data; for example, based on the first data, it can be determined whether the electronic device is in an elevator scene or not.

[0201] For example, if it is determined from the first data that the electronic device has an acceleration in a certain direction, then the electronic device can be identified as being in an elevator scene.

[0202] In one example, the identification result can be obtained based on the first data and the first detection result; for example, based on the first data and the first detection result, it can be determined whether the electronic device is in an elevator scene or not.

[0203] For example, if the electronic device is identified to have acceleration in a certain direction based on the first data, and the user carrying the electronic device is identified to have exited the motion state based on the first detection result, then the electronic device can be identified as being in an elevator scenario.

[0204] In one example, the identification result can be obtained based on the first data and the first network identifier; for example, based on the first data and the first network identifier, it can be determined whether the electronic device is in an elevator scene or not.

[0205] For example, if the electronic device is identified to have an acceleration in a certain direction based on the first data, and the network identifier of the network covering the vicinity of the elevator can be obtained based on the first network identifier, then the electronic device can be identified as being in an elevator scene.

[0206] In one example, the identification result can be obtained based on the first data, the first detection result, and the first network identifier; for example, the identification result obtained based on the first data, the first detection result, and the first network identifier can indicate that the electronic device is waiting for an elevator.

[0207] For example, based on the first network identifier, it can be identified that the electronic device accesses a network in the network identifier feature library. The network identifiers included in the network identifier feature library can refer to the network identifier of the local area network near the elevator fence (e.g., BSSID). If the electronic device accesses a local area network near the elevator fence, it can be said that the electronic device is located near the elevator fence. If the electronic device is located 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 changes from a walking or running state to a stationary state, it can be said that the user is staying at the elevator fence. Thus, the identification result can be obtained as a waiting elevator scenario; for example, the user is waiting for the elevator.

[0208] Optionally, the identification result is obtained based on the first data, the first detection result, and / or the first network identifier, including:

[0209] The first identification result is obtained based on the first data, the first detection result, and the first network identifier.

[0210] In the embodiments of this application, the recognition result of the elevator scene can be obtained by fusing multiple types of data, such as the first data from the accelerometer, the first detection result, and the first network identifier, i.e., multimodal data. Since the method of the embodiments of this application can obtain the recognition result based on multimodal data, the accuracy of the recognition result can be improved.

[0211] Optionally, the identification result may also include a second identification result, obtained based on the first data, the first detection result, and / or the first network identifier, including:

[0212] The value of the counting parameter is obtained based on the first data. The counting parameter is used to indicate that the electronic device is moving in the first direction and has acceleration.

[0213] The second identification result is obtained based on the value of the counting parameter, and the second identification result is used to indicate whether the electronic device is in an elevator scene.

[0214] It should be understood that the second identification result can be used to indicate that the electronic device is in an elevator scenario; or, the second identification result can be used to indicate that the electronic device is not in an elevator scenario; for example, the electronic device being in an elevator scenario can indicate that the electronic device has entered the elevator enclosure; such as Figure 4 Or such as Figure 5 The scene shown.

[0215] For example, in the embodiments of this application, the counting parameter may refer to MoveCount, which is used to represent movement in one direction with acceleration; for example, if the first upward movement has acceleration, MoveCount = A; then the second upward movement has acceleration, MoveCount = A+1.

[0216] In the embodiments of this application, the value of a counting parameter (e.g., Move Count) can be used to identify whether an electronic device has entered an elevator. Since the elevator scene is directly identified by the data from the accelerometer, it is impossible to avoid the accelerometer of the electronic device collecting error data due to accidental touch by the user, resulting in a low accuracy rate for identifying the elevator scene. Compared with identifying the elevator scene directly by the data from the accelerometer, the accuracy of the identification result can be improved by identifying the elevator scene by the value of the counting parameter.

[0217] Optionally, a second identification result is obtained based on the value of the counting parameter, including:

[0218] If the value of the counting parameter is greater than the first preset threshold, the second recognition result is used to indicate that the electronic device is in an elevator scene;

[0219] If the value of the counting parameter is less than or equal to the first preset threshold, the second identification result is used to indicate that the electronic device is not in an elevator scenario.

[0220] Optionally, the specific implementation method can be found in the following sections. Figure 7 Steps S405 to S408 are shown; or, Figure 8 Steps S510 to S513 are shown.

[0221] In the embodiments of this application, when directly identifying elevator scenes based on accelerometer data, multiple frames of accelerometer data need to be acquired to reduce errors in the data collected by the accelerometer, resulting in a long waiting time and making it difficult to quickly identify elevator scenes. Identifying elevator scenes by using the value of the counting parameter is more efficient and can quickly identify elevator scenes. In the embodiments of this application, the value of the counting parameter can be quickly acquired, and the elevator scene can be identified based on the value of the counting parameter, thereby shortening the time for identifying elevator scenes and reducing the user's waiting time.

[0222] Optionally, in embodiments of this application, the first data can be filtered to obtain the second data; based on the second data, the value of the counting parameter can be obtained.

[0223] For example, in an embodiment of this application, the first data can be processed by a bandpass filter and a lowpass filter to obtain the second data.

[0224] Optionally, the specific implementation method can be found in the following sections. Figure 7 Steps S402 and S403 are shown; or, Figure 8 Steps S503 and S507 are shown.

[0225] For example, a band-pass filter is a device that allows waves of a specific frequency band to pass through while blocking other frequency bands; for instance, an oscillating circuit composed of resistors, inductors, and capacitors can be an analog band-pass filter.

[0226] In the embodiments of this application, a bandpass filter is used to filter the data, thereby avoiding the shaking of the electronic device caused by accidental external factors, thus filtering the acquired accelerometer data and improving the accuracy of the acquired accelerometer data.

[0227] For example, a low-pass filter is a filtering method that allows low-frequency signals to pass through normally, while high-frequency signals exceeding a set threshold are blocked or weakened.

[0228] In the embodiments of this application, the data is filtered by a low-pass filter to avoid changes in the accelerometer data caused by minute internal movements of the electronic device. In other words, in order to eliminate the error data of the accelerometer introduced by minute internal movements of the electronic device, the acquired accelerometer data is filtered to improve the accuracy of the acquired accelerometer data.

[0229] Optionally, in embodiments of this application, the first detection result can be obtained through a gradient boosting tree model.

[0230] For example, 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.

[0231] In one example, data features are extracted by obtaining the variance, mean, first-order difference, second-order difference, or third-order difference of the data from the accelerometer over a preset duration. These data features are then fed into a pre-trained GBDT model to obtain motion state detection results. The motion state detection results may include: stationary, running (e.g., walking or running). Optionally, the motion state detection results may include just exiting the movement (e.g., just exiting walking or just exiting running).

[0232] Optionally, in embodiments of this application, obtaining a first identification result based on first data, a first detection result, and a first network identifier includes:

[0233] When the first data meets the first preset condition, the first detection result meets the second preset condition, and the first network identifier meets the third preset condition, the first identification result is obtained.

[0234] The first preset condition refers to the predicted acceleration of the electronic device obtained based on the first data being greater than the second preset threshold; the second preset condition refers to the duration of the user exiting the first motion state or the user exiting the second motion state being less than the third threshold; the third preset condition is that the first network identifier matches the network identifier in the network identifier feature library, which includes the identifiers of the local area network covered by the area where the elevator is located.

[0235] For example, based on the first network identifier, it can be identified that the electronic device accesses a network in the network identifier feature library. The network identifiers included in the network identifier feature library can refer to the network identifier of the local area network near the elevator fence (e.g., BSSID). If the electronic device accesses a local area network near the elevator fence, it can be said that the electronic device is located near the elevator fence. If the electronic device is located 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 changes from a walking or running state to a stationary state, it can be said that the user is staying at the elevator fence. Thus, the identification result can be obtained as a waiting elevator scenario; for example, the user is waiting for the elevator.

[0236] For example, if the predicted acceleration of the electronic device is greater than a second preset threshold, the user carrying the electronic device may be in a state of just exiting walking or running, and the network identifier of the network currently accessed by the electronic device matches the network identifier in the network identifier feature database. This indicates that the user carrying the electronic device is currently waiting for an elevator. Waiting for an elevator can mean that the user is in the vicinity of the elevator and is stationary. Optionally, specific implementation methods can be found in subsequent sections. Figure 7 Steps S409 to S413 are shown below; or, see the following. Figure 8 Steps S514 to S520 are shown.

[0237] Step S330: Apply for the first resource based on the first identification result.

[0238] The first resource is used for electronic devices to operate in elevator mode. Elevator mode refers to the mode in which electronic devices switch networks based on full network aggregation acceleration technology.

[0239] It should be understood that the first resource can refer to the memory resources pre-allocated in the electronic device, and the first resource can be used for the electronic device to run elevator mode.

[0240] It should also be understood that Link Turbo, the full-network aggregation acceleration technology, refers to a technology that integrates mobile and fixed-line data communication. Through edge-cloud collaborative network aggregation, it delivers a high-speed, stable, and low-latency mobile internet experience to users under varying network conditions. For example, when playing games and experiencing Wi-Fi fluctuations, the mobile cellular network quickly intervenes to reduce latency caused by these fluctuations, ensuring smooth gameplay. Similarly, when downloading a game or video and experiencing poor Wi-Fi speeds, the mobile cellular network automatically activates, allowing both networks to operate in parallel and accelerating the download.

[0241] In the embodiments of this application, when the electronic device detects that it is currently in an elevator waiting scenario, it can request memory resources for elevator mode operation. When the electronic device detects that it is in an elevator scenario, it can directly and quickly execute the full network aggregation acceleration technology (Link Turbo) through the pre-requested resources. Since the embodiments of this application can detect the elevator waiting scenario of the electronic device and request Link Turbo resources in advance when the electronic device is in an elevator waiting scenario, the Link Turbo of the electronic device can be quickly triggered after the user enters the elevator, thereby shortening the user's waiting time and improving the user's Internet experience.

[0242] Step S340: When the electronic device is detected to be in an elevator scene, the elevator mode is run based on the first resource.

[0243] For example, when the identification result indicates that the electronic device is in an elevator scenario, the electronic device can quickly run the full network aggregation acceleration technology (Link Turbo) based on pre-requested resources, thereby avoiding problems such as lag in the user's electronic device in the elevator scenario and improving the user's Internet experience.

[0244] For example, entering an elevator scenario can refer to an electronic device entering an elevator; for instance, entering an elevator scenario could include entering an elevator when the elevator is not in operation, or entering an elevator when the elevator is running; for example, such as Figure 4 As shown, the electronic device is currently inside the elevator and the elevator is not moving, meaning the elevator is neither accelerating upwards nor downwards; for example, as Figure 5 As shown, the electronic device is currently located in the elevator and the elevator is in operation; for example, the elevator may be moving upwards or downwards.

[0245] For example, since operating in elevator mode increases the signal search power of the electronic device, it results in higher power consumption. After the electronic device operates in elevator mode, one or more of the following can be acquired: first data, motion state detection results, network identifier, or second data, to determine whether the electronic device should exit elevator mode. Optionally, see the following... Figure 9 Related descriptions.

[0246] Optionally, a second detection result is obtained, wherein the user's motion state is a first motion state and the duration of the first motion state is greater than a fourth preset threshold; and the elevator mode is exited based on the second detection result.

[0247] For example, if the system detects that the user is walking and that the walking state lasts for more than 6 seconds, the electronic device can exit elevator mode.

[0248] Optionally, a third detection result and a second network identifier are obtained. The third detection result indicates that the user's motion state is a first motion state and the duration of the first motion state is greater than a fifth preset threshold. The second network identifier is different from the first network identifier. The user exits the elevator mode based on the third detection result and the second network identifier.

[0249] Optionally, the fifth preset threshold is less than the fourth preset threshold.

[0250] For example, if the user's movement is detected as walking and the walking state lasts for more than 4 seconds, and the network identifier of the local area network accessed by the electronic device also changes, the electronic device can exit elevator mode.

[0251] For example, after an electronic device operates in elevator mode, the low power mode in the electronic device's battery settings interface can display "Turn off elevator mode" (e.g., "Turn off smart application elevator mode"); see below for example. Figure 13 As shown in (d) below; or, see below. Figure 15 As shown in (b) of the diagram.

[0252] Optionally, the above method further includes: the electronic device detecting the first operation; and in response to the first operation, displaying a first interface, the first interface including a low power mode, the low power mode including an elevator off mode.

[0253] For example, after the electronic device operates in elevator mode, a prompt message can be displayed on the electronic device; for example, the prompt message "Activate Smart Application Elevator Mode" can be displayed; see below. Figure 11 As shown.

[0254] Optionally, when the electronic device is running in elevator mode, a first prompt message is displayed, which instructs the electronic device to activate elevator mode.

[0255] For example, after the electronic device operates in elevator mode, a first icon can be displayed on the electronic device; for example, the first icon can be as follows: Figure 12 The icon shown is 670.

[0256] Optionally, when the electronic device is running elevator mode, a first icon is displayed to indicate that the electronic device has activated elevator mode. In the embodiments of this application, the identification result obtained when identifying an elevator scene includes a waiting elevator scene; when the identification result is a waiting elevator scene, the electronic device can pre-apply for a first resource; when the identification result is in an elevator scene, the electronic device can directly activate the full network aggregation acceleration technology through the pre-applied first resource; since the method of the embodiments of this application can identify that the electronic device is in a waiting elevator scene; and when the electronic device is in a waiting elevator scene, the electronic device can apply for the first resource for executing the full network aggregation acceleration technology; therefore, the method of identifying elevator scenes in the embodiments of this application can accurately identify elevator scenes; and shorten the time that users wait for signals in elevator scenes; enabling the electronic device to quickly trigger the full network aggregation acceleration technology of the electronic device after entering the elevator, thereby improving the Internet experience.

[0257] Furthermore, in the embodiments of this application, elevator scenes can be identified using the value of a counting parameter (e.g., Move Count). Since identifying elevator scenes directly using accelerometer data is prone to errors due to user accidental touches causing the accelerometer to collect incorrect data, the accuracy of elevator scene identification is low. Identifying elevator scenes using the value of the counting parameter improves the accuracy of the identification results compared to directly using accelerometer data. Secondly, when directly identifying elevator scenes based on accelerometer data, multiple frames of accelerometer data are required to reduce errors in the collected data, resulting in longer waiting times for the electronic device and hindering rapid elevator scene identification. The elevator scene identification method of this application, using the value of the counting parameter, enables rapid elevator scene identification. Therefore, the elevator scene identification method of this application can quickly and accurately identify elevator scenes, shortening user waiting times and enabling the electronic device to quickly trigger Link Turbo upon entering the elevator, improving the user's internet browsing experience.

[0258] It should be understood that the above example is based on an elevator scenario; the method 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; by identifying these scenarios, electronic devices can enable full network aggregation technology to switch networks and ensure a smooth internet experience.

[0259] Figure 7 This is a schematic flowchart of a method for recognizing elevator scenes provided in an embodiment of this application. The method 400 can be... Figure 1The electronic device shown executes the method 400, which includes steps S401 to S413, and steps S401 to S413 are described in detail below.

[0260] Step S401: Acquire data from the accelerometer.

[0261] For example, an acceleration sensor can refer to, for instance, an acceleration sensor. Figure 1 As shown in the 180E, the accelerometer can detect the magnitude of acceleration in various directions (typically the x-axis, y-axis, and z-axis) of an electronic device.

[0262] Step S402: Process the data from the accelerometer using a bandpass filter.

[0263] It should be understood that a bandpass filter is a device that allows waves of a specific frequency band to pass through while blocking other frequency bands; for example, an oscillating circuit composed of resistors, inductors, and capacitors can be an analog bandpass filter.

[0264] In the embodiments of this application, a bandpass filter is used to filter the data, thereby avoiding the shaking of the electronic device caused by accidental external factors, thus filtering the acquired accelerometer data and improving the accuracy of the acquired accelerometer data.

[0265] Optionally, after processing the accelerometer data with a bandpass filter, a moving average and a moving standard deviation can be obtained. Since the data processed by the bandpass filter may contain some noise, the moving standard deviation and moving standard deviation can remove this noise and improve the accuracy of the processed data.

[0266] Optionally, see the following. Figure 8 The relevant description of step S504 shown.

[0267] Step S403: Process the data from the accelerometer using a low-pass filter.

[0268] It should be understood that a low-pass filter is an electronic filtering device that allows signals below the cutoff frequency to pass through, but prevents signals above the cutoff frequency from passing through.

[0269] In the embodiments of this application, the data is filtered by a low-pass filter to avoid changes in the accelerometer data caused by minute internal movements of the electronic device. In other words, in order to eliminate the error data of the accelerometer introduced by minute internal movements of the electronic device, the acquired accelerometer data is filtered to improve the accuracy of the acquired accelerometer data.

[0270] Step S404: Calculate the combined speed based on the data processed by the bandpass filter and the data processed by the lowpass filter.

[0271] For example, the resultant velocity of an electronic device can be expressed as x 2 +y 2 +z 2 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.

[0272] For example, the triaxial data processed by the bandpass filter can be used to obtain the resultant velocity 1; the triaxial data processed by the low-pass filter can be used to 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 can be added together to obtain the resultant velocity.

[0273] In the embodiments of this application, the combined velocity is calculated based on the data processed by the bandpass filter and the data processed by the lowpass filter in order to determine whether there is acceleration or deceleration in a certain direction.

[0274] Optionally, by fusing the sliding standard deviation with the resultant velocity, the presence or absence of upward or downward acceleration can be calculated, thus obtaining the value of the counting parameter.

[0275] Step S405: When the resultant velocity meets the first preset condition, record the value of the counting parameter in a certain direction.

[0276] For example, the resultant velocity satisfying the first preset condition may mean that the resultant velocity is greater than a threshold value of 2; alternatively, see the following. Figure 8 The relevant description of step S509 is shown.

[0277] For example, in an embodiment of this application, the counting parameter may refer to MoveCount, which is used to indicate movement in one direction with acceleration; for example, if the first upward movement has acceleration, MoveCount = A; then the second upward movement has acceleration, MoveCount = A+1.

[0278] Optionally, by fusing the sliding standard deviation with the resultant velocity, the presence or absence of upward or downward acceleration can be calculated, thus obtaining the value of the counting parameter.

[0279] Step S406: Determine whether the value of the counting parameter is greater than the target threshold; if the value of the counting parameter is greater than the target threshold, proceed to step S407; if the value of the counting parameter is less than or equal to the target threshold, proceed to step S408.

[0280] It should be understood that, in the embodiments of this application, by determining whether the value of the counting parameter is greater than the target threshold, the problem of inaccurate elevator scene recognition results caused by the electronic device incorrectly recording the value of the counting parameter in a certain direction due to user accidental touch can be avoided.

[0281] In the embodiments of this application, elevator scenes are identified by the value of a counting parameter (e.g., Move Count) to obtain the identification result. For example, the identification result may include entering an elevator scene or not entering an elevator scene. Since elevator scenes are directly identified by data from an accelerometer, it is impossible to avoid errors in the accelerometer data collection due to user accidental touches, resulting in a low accuracy rate for identifying elevator scenes. Compared with identifying elevator scenes directly by data from an accelerometer, identifying elevator scenes by the value of the counting parameter can improve the accuracy of the identification result. Secondly, when identifying elevator scenes directly based on data from an accelerometer, multiple frames of data from the accelerometer need to be acquired to reduce errors in the data collected by the accelerometer, resulting in a long waiting time and making it difficult to quickly identify elevator scenes. Identifying elevator scenes by the value of the counting parameter is more efficient, that is, it can quickly identify elevator scenes. In the embodiments of this application, the value of the counting parameter can be quickly acquired, and elevator scenes can be identified based on the value of the counting parameter, thereby shortening the time for identifying elevator scenes and reducing the user's waiting time.

[0282] Step S407: Output the recognition result as "The electronic device is not in the elevator scene".

[0283] It should be understood that "electronic device not in elevator scene" can mean that the electronic device has not entered the elevator scene, that is, the electronic device has not entered the elevator enclosure.

[0284] Step S408: Output the recognition result as the electronic device being in an elevator scene.

[0285] It should be understood that an electronic device being in an elevator scenario can mean that the electronic device has entered the elevator enclosure; since the user is carrying an electronic device, the electronic device being in an elevator scenario can mean that the user is in an elevator scenario, that is, the user has entered the elevator enclosure; through the embodiments of this application, after the electronic device recognizes that the user has entered the elevator enclosure, the electronic device can activate the full network aggregation acceleration technology (Link Turbo) to ensure a smooth Internet experience for the user in the elevator scenario.

[0286] For example, in an elevator scenario, it can be as follows: Figure 4 As shown, or Figure 5 As shown.

[0287] Step S409: Calculate acceleration based on resultant velocity.

[0288] For example, acceleration = abs (resultant velocity) / sqrt (sliding standard deviation); where abs represents the absolute value function; sqrt represents the square root function; the sliding standard deviation can be calculated based on the data processed by the bandpass filter; optionally, the specific implementation method is as follows: Figure 8 The relevant description of step S504 shown.

[0289] Step S410: Obtain motion state detection results.

[0290] For example, 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.

[0291] In one example, 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 over a preset duration. The data features are then fed into a pre-trained GBDT model to obtain motion state detection results. The motion state detection results may include: stationary, running (e.g., walking or running). Optionally, the motion state detection results may include just exiting the movement (e.g., just exiting walking or just exiting running).

[0292] It should be understood that the GBDT model is a decision tree model based on the idea of ​​ensemble learning, and its essence is based on residual learning.

[0293] Optionally, the user can carry an electronic device, and obtaining motion state detection results can refer to obtaining motion state detection results of the user carrying the electronic device.

[0294] Optionally, other mobile devices (e.g., intelligent robots) may carry electronic devices, and obtaining motion state detection results may refer to obtaining motion state detection results of mobile devices carrying electronic devices.

[0295] Step S411: Obtain the local area network identifier.

[0296] For example, 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 to which the electronic device is connected can be determined by the identifier of the local area network; different local area networks can cover different ranges.

[0297] For example, if the local area network identifier of an electronic device matches the local area network identifier feature library of an elevator, it can indicate the coverage area of ​​the local area network near the elevator, that is, it can indicate that the electronic device is near the elevator.

[0298] Optionally, the MAC addresses of the local area network near the elevator can be obtained in advance to obtain the elevator's local area network identifier feature database.

[0299] Step S412: Determine whether the acceleration, motion state detection results and local area network identifier all meet the preset conditions.

[0300] For example, determine whether the acceleration, walking state recognition result and local area network identifier satisfy conditions 1, 2 and 3 respectively; if conditions 1, 2 and 3 are satisfied, then execute step S413.

[0301] Among them, condition 1 can refer to acceleration greater than threshold 5; condition 2 can refer to motion state detection result of exiting motion; and condition 3 can refer to the local area network identifier of electronic device matching the local area network identifier feature library of elevator.

[0302] It should be understood that the acceleration and motion state detection results are used to determine whether a user carrying an electronic device has changed 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 a state of exiting motion, it can indicate that the user carrying the electronic device has stopped from a walking or running state.

[0303] It should also be understood that if the local area network identifier of an electronic device matches the local area network identifier feature library of an elevator, it can indicate the coverage area of ​​the local area network of the electronic device near the elevator, that is, it can indicate that the electronic device is near the elevator.

[0304] Step S413: Output the recognition result as a waiting elevator scene.

[0305] In the embodiments of this application, the identification result includes a scenario of waiting for an elevator; when the identification result is a scenario of waiting for an elevator, the electronic device can pre-apply for a first resource; when the identification result is an elevator scenario, the electronic device can directly activate the full network aggregation acceleration technology through the pre-applied first resource; since the method of this application embodiment can identify that the electronic device is in a scenario of waiting for an elevator; when the electronic device is in a scenario of waiting for an elevator, the electronic device can apply for a first resource to execute the full network aggregation acceleration technology, and when the electronic device is in an elevator scenario, the electronic device can quickly run the elevator mode through the first resource; therefore, the method of identifying elevator scenarios in this application embodiment can accurately identify elevator scenarios; and shorten the time that users wait for signals in elevator scenarios; enabling the electronic device to quickly trigger the full network aggregation acceleration technology of the electronic device after entering the elevator, thereby improving the Internet experience.

[0306] Furthermore, in the embodiments of this application, elevator scenes can be identified by the value of a counting parameter (e.g., Move Count). Since identifying elevator scenes directly using data from an accelerometer cannot avoid errors caused by user accidental touches leading to incorrect data collection by the accelerometer in the electronic device, the accuracy of elevator scene identification is low. Identifying elevator scenes using the value of the counting parameter improves the accuracy of the identification results compared to directly using accelerometer data. Secondly, when directly identifying elevator scenes based on accelerometer data, multiple frames of accelerometer data need to be acquired to reduce errors in the collected data, resulting in a longer waiting time for the electronic device and hindering rapid elevator scene identification. The elevator scene identification method of this application, which identifies elevator scenes using the value of the counting parameter, can quickly identify elevator scenes. Therefore, the elevator scene identification method of this application can quickly and accurately identify elevator scenes.

[0307] It should be understood that the above example is based on an elevator scenario; the method 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; by identifying these scenarios, electronic devices can enable full network aggregation technology to switch networks and ensure a smooth internet experience.

[0308] Figure 8 This is a schematic flowchart of a method for identifying elevator scenes provided in an embodiment of this application. The method 500 can be... Figure 1 The electronic device shown executes the method 500, which includes steps S501 to S520. Steps S501 to S520 are described in detail below.

[0309] Step S501: Acquire data from the accelerometer.

[0310] For example, an acceleration sensor can refer to, for instance, an acceleration sensor. Figure 1 As shown in the 180E, the accelerometer can detect the magnitude of acceleration in various directions (typically the x-axis, y-axis, and z-axis) of an electronic device.

[0311] Optionally, in embodiments of this application, parameter verification can be performed on the acquired accelerometer data. Parameter verification can determine whether the acquired data is abnormal, thereby ensuring the accuracy of the acquired data.

[0312] Step S502: Perform data normalization.

[0313] In the embodiments of this application, data can be converted from integer data to floating-point data by performing unitization processing, thereby facilitating the unification of data units and benefiting subsequent calculations.

[0314] Optionally, step S503 can be executed directly after step S501, and this application does not impose any limitations on this.

[0315] Step S503: Process the data using a bandpass filter.

[0316] In the embodiments of this application, a bandpass filter is used to filter the data, thereby avoiding the shaking of the electronic device caused by accidental external factors, thus filtering the acquired accelerometer data and improving the accuracy of the acquired accelerometer data.

[0317] Step S504: Obtain the moving average and moving standard deviation based on the data processed by the bandpass filter.

[0318] The exponential moving average, also known as the exponentially weighted moving average, is used to estimate the local mean of a variable, making the variable's updates related to its historical values ​​over a period of time. Typically, the moving average is used to eliminate the influence of random factors; the moving standard deviation measures the degree of dispersion from the moving average.

[0319] In the embodiments of this application, since the data processed by the bandpass filter may contain some noise data, the noise data can be removed by using the sliding standard and sliding standard deviation, thereby improving the accuracy of the processed data.

[0320] Step S505: Determine whether the sliding standard deviation is greater than the threshold 1; if the sliding standard deviation is less than or equal to the threshold 1, then proceed to step S506.

[0321] Step S506: Set the value of the counting parameter to zero.

[0322] In the embodiments of this application, when the sliding standard deviation is less than or equal to the threshold 1, it indicates that the electronic device is not moving up or down, and the value of the counting parameter can be set to zero.

[0323] For example, in an embodiment of this application, the counting parameter may refer to MoveCount, which is used to indicate movement in one direction with acceleration.

[0324] For example, the sliding standard deviation can be output every second, and it can be determined whether the sliding standard deviation is greater than the threshold 1.

[0325] Step S507: Process the data using a low-pass filter.

[0326] In the embodiments of this application, the data is filtered by a low-pass filter to avoid changes in the accelerometer data caused by minute internal movements of the electronic device. In other words, in order to eliminate the accelerometer data introduced by minute internal movements of the electronic device, the acquired accelerometer data is filtered to improve the accuracy of the acquired accelerometer data.

[0327] Step S508: Based on the data processed by the low-pass filter and the moving average and moving standard deviation, the resultant velocity of the electronic device is obtained.

[0328] For example, the resultant velocity 1 can be obtained from the triaxial data processed by the bandpass filter; the resultant velocity 2 can be obtained from the triaxial data processed by the lowpass filter; 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 can be added together to obtain the resultant velocity.

[0329] In the embodiments of this application, the combined velocity is calculated based on the data processed by the bandpass filter and the data processed by the lowpass filter in order to determine whether there is acceleration or deceleration in a certain direction.

[0330] In the embodiments of this application, there may be some noisy data in the data processed by the filter processor; this noisy data can be removed by using moving average and moving standard deviation.

[0331] Step S509: Determine whether the resultant velocity is greater than threshold 2 and the sliding standard deviation is less than threshold 3; if the resultant velocity is greater than threshold 2 and the sliding standard deviation is less than threshold 3, then proceed to step S510; if the resultant velocity is less than or equal to threshold 2, or the sliding standard deviation is greater than or equal to threshold 3, then continue to wait to obtain the updated accelerometer data.

[0332] Step S510: Record the value of the counting parameter in a certain direction.

[0333] For example, in an embodiment of this application, the counting parameter can refer to MoveCount, which represents movement in one direction with acceleration; for example, if the movement is upward for the first time with acceleration, MoveCount = A; then, if the movement is upward for the second time with acceleration, MoveCount = A+1. Step S511: Determine whether the value of the counting parameter is greater than the threshold 4; if the value of the counting parameter is greater than the threshold 4, then execute step S512; if the value of the counting parameter is less than or equal to the threshold 4, then execute step S513.

[0334] For example, the threshold 4 can be 4.

[0335] In the embodiments of this application, by determining whether the value of the counting parameter is greater than the threshold 4, the problem of inaccurate elevator scene recognition results caused by the electronic device incorrectly recording the value of the counting parameter in a certain direction due to accidental touch by the user can be avoided.

[0336] Step S512: Output the recognition result as "entering the elevator scene".

[0337] It should be understood that an electronic device being in an elevator scenario can mean that the electronic device has entered the elevator enclosure; since the user is carrying an electronic device, the electronic device being in an elevator scenario can mean that the user is in an elevator scenario, that is, the user has entered the elevator enclosure; through the embodiments of this application, after the electronic device recognizes that the user has entered the elevator enclosure, the electronic device can activate the full network aggregation acceleration technology (Link Turbo) to ensure a smooth Internet experience for the user in the elevator scenario.

[0338] For example, in an elevator scenario, it can be as follows: Figure 4 As shown, or Figure 5 As shown.

[0339] Step S513: Output the recognition result as "not entering the elevator scene".

[0340] It should be understood that "electronic device not in elevator scene" can mean that the electronic device has not entered the elevator scene, that is, the electronic device has not entered the elevator enclosure.

[0341] In the embodiments of this application, elevator scenes can be identified by the value of a counting parameter (e.g., Move Count). However, if elevator scenes are identified directly using data from an accelerometer, errors in the accelerometer data collected by the electronic device due to user accidental touches cannot be avoided, resulting in low accuracy in identifying elevator scenes. Identifying elevator scenes using the value of the counting parameter improves the accuracy of the identification results compared to directly using accelerometer data. Furthermore, when directly identifying elevator scenes based on accelerometer data, multiple frames of accelerometer data need to be acquired to reduce errors in the collected data, leading to a longer waiting time for the electronic device and hindering rapid elevator scene identification. The elevator scene identification method of this application, which identifies elevator scenes using the value of the counting parameter, enables rapid elevator scene identification. Therefore, the elevator scene identification method of this application can quickly and accurately identify elevator scenes, shortening the user's waiting time. This allows the electronic device to quickly trigger Link Turbo after entering the elevator, improving the user's internet browsing experience.

[0342] Step S514: The predicted acceleration of the electronic device can be obtained based on the resultant velocity.

[0343] For example, the predicted acceleration = abs (resultant velocity) / sqrt (sliding standard deviation); where abs represents the absolute value function; sqrt represents the square root function; and the sliding standard deviation can be calculated based on the data processed by the bandpass filter.

[0344] Step S515: Obtain motion state detection results.

[0345] For example, 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.

[0346] In one example, 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 over a preset duration. The data features are then fed into a pre-trained GBDT model to obtain motion state detection results. The motion state detection results may include: stationary, running (e.g., walking or running). Optionally, the motion state detection results may include just exiting the movement (e.g., just exiting walking or just exiting running).

[0347] It should be understood that the GBDT model is a decision tree model based on the idea of ​​ensemble learning, and its essence is based on residual learning.

[0348] It should also be understood that, since the user is carrying an electronic device, the motion state result can be represented as the motion state result of the electronic device; or, the motion state result of the user carrying the electronic device.

[0349] Step S516: Determine whether the motion state detection result indicates that the exercise has just ended; if the motion state detection result indicates that the exercise has just ended, for example, the exercise has just ended or the exercise has just ended, then proceed to step S519.

[0350] Step S517: Obtain the local area network identifier.

[0351] For example, 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 to which the electronic device is connected can be determined by the identifier of the local area network; different local area networks can cover different ranges.

[0352] Step S518: Determine 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, then proceed to step S519.

[0353] For example, if the local area network identifier of an electronic device matches the local area network identifier feature library of an elevator, it can indicate the coverage area of ​​the local area network near the elevator, that is, it can indicate that the electronic device is near the elevator.

[0354] Optionally, the MAC addresses of the local area network near the elevator can be obtained in advance to obtain the elevator's local area network identifier feature database.

[0355] Step S519: Determine whether conditions 1, 2 and 3 are met; if conditions 1, 2 and 3 are met, then proceed to step S520.

[0356] Among them, condition 1 can be that the predicted acceleration is greater than the threshold 5; condition 2 can be that the walking state recognition result is the state of exiting movement; and condition 3 can be that the local area network identifier of the electronic device matches the local area network identifier feature library of the elevator.

[0357] Step S520: Output the recognition result as a waiting elevator scene.

[0358] It should be understood that the "waiting for an elevator" scenario can refer to a situation where an electronic device is near the elevator but has not entered it; for example, a user carrying an electronic device is near the elevator but has not entered it.

[0359] In the embodiments of this application, the identification result includes a scenario of waiting for an elevator; when the identification result is a scenario of waiting for an elevator, the electronic device can pre-apply for a first resource; when the identification result is an elevator scenario, the electronic device can directly activate the full network aggregation acceleration technology through the pre-applied first resource; since the method of this application embodiment can identify that the electronic device is in a scenario of waiting for an elevator; when the electronic device is in a scenario of waiting for an elevator, the electronic device can apply for a first resource to execute the full network aggregation acceleration technology, and when the electronic device is in an elevator scenario, the electronic device can quickly run the elevator mode through the first resource; therefore, the method of identifying elevator scenarios in this application embodiment can accurately identify elevator scenarios; and shorten the time that users wait for signals in elevator scenarios; enabling the electronic device to quickly trigger the full network aggregation acceleration technology of the electronic device after entering the elevator, thereby improving the Internet experience.

[0360] Furthermore, in the embodiments of this application, elevator scenes can be identified by the value of a counting parameter (e.g., Move Count). Since identifying elevator scenes directly using data from an accelerometer cannot avoid errors caused by user accidental touches leading to incorrect data collection by the accelerometer in the electronic device, the accuracy of elevator scene identification is low. Identifying elevator scenes using the value of the counting parameter improves the accuracy of the identification results compared to directly using accelerometer data. Secondly, when directly identifying elevator scenes based on accelerometer data, multiple frames of accelerometer data need to be acquired to reduce errors in the collected data, resulting in a longer waiting time for the electronic device and hindering rapid elevator scene identification. The elevator scene identification method of this application, which identifies elevator scenes using the value of the counting parameter, can quickly identify elevator scenes. Therefore, the elevator scene identification method of this application can quickly and accurately identify elevator scenes.

[0361] It should be understood that the above example is based on an elevator scenario; the method 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; by identifying these scenarios, electronic devices can enable full network aggregation technology to switch networks and ensure a smooth internet experience.

[0362] Figure 9 This is a schematic flowchart illustrating the method for exiting elevator mode provided in this application embodiment. The method 600 can be... Figure 1 The electronic device shown executes the method 600, which includes steps S601 to S608. Steps S601 to S608 are described in detail below.

[0363] Step S601: The electronic device operates in elevator mode.

[0364] Optionally, it can be based on Figure 6 , Figure 7 or Figure 8 The method shown identifies when an electronic device enters an elevator scene and the electronic device operates in elevator mode; further details will not be provided here.

[0365] Step S602: Obtain motion state detection results.

[0366] Optionally, the user can carry an electronic device, and obtaining motion state detection results can refer to obtaining motion state detection results of the user carrying the electronic device.

[0367] Optionally, other mobile devices may carry electronic devices, and obtaining motion state detection results may refer to obtaining motion state detection results of other mobile devices carrying electronic devices.

[0368] Step S603: Determine whether the motion state indicated by the motion state detection result is the first motion state and the duration is greater than the threshold 5; if the motion state is the first motion state and the duration is greater than the threshold 5, then execute step S604; if the motion state is not the first motion state and / or the duration is not greater than the threshold 5, then execute step S605.

[0369] For example, the first motion state can refer to a motion state with a speed greater than a preset threshold; for example, if the user is carrying an electronic device, the first motion state can refer to the user's walking state; for example, the first motion state and the duration of the first motion state is greater than the threshold 5 can be a walking state, and the duration of the walking state is greater than 6 seconds.

[0370] It should be understood that if a user is carrying an electronic device and is currently in a walking state for a period of time, it indicates that the user has left the elevator railing, at which point the electronic device can exit elevator mode.

[0371] Step S604: The electronic device exits elevator mode.

[0372] For example, exiting elevator mode can mean that the electronic device exits Link Turbo; for instance, the electronic device can switch to mobile data or other local area networks.

[0373] Step S605: The electronic device operates in elevator mode.

[0374] For example, running elevator mode can refer to an electronic device increasing its signal search power to ensure a smooth internet browsing experience.

[0375] Step S606: Obtain the local area network identifier of the electronic device.

[0376] For example, the network identifier of the local area network currently connected to the electronic device can be obtained.

[0377] Optionally, in embodiments of this application, it can be determined whether the electronic device has left the elevator fence based on its motion state and network identifier; if the electronic device leaves the elevator fence, the electronic device can exit elevator mode.

[0378] For example, since the network identifier of the electronic device is different from the network identifier of the electronic device when it enters the elevator fence; if the local area network identifier that the electronic device accessed before entering the elevator scene is local area network 1; if the current local area network identifier of the electronic device is local area network 2, it can be indicated that the electronic device is currently leaving the elevator scene.

[0379] Step S607: Determine whether the duration of the first motion state is greater than the threshold 6 and whether the network identifier changes; if the duration of the first motion state is greater than the threshold 6 and the network identifier changes, proceed to step S608; if the duration of the first motion state is less than or equal to the threshold 6 and / or the network identifier remains unchanged, proceed to step S609.

[0380] Optionally, threshold 6 can be less than threshold 5.

[0381] 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 6; 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.

[0382] 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 S604 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.

[0383] It should also be understood that the above examples are based on a threshold of 6 seconds for threshold 5 and 4 seconds for threshold 6; this application does not impose any limitations on this.

[0384] Step S608: The electronic device exits elevator mode.

[0385] For example, exiting elevator mode can mean that the electronic device exits Link Turbo; for instance, the electronic device can switch to mobile data or other local area networks.

[0386] Step S609: The electronic device operates in elevator mode.

[0387] For example, running elevator mode can refer to an electronic device increasing its signal search power to ensure a smooth internet browsing experience.

[0388] The following is combined Figures 10 to 15 The following is an example description of the interface diagram for activating elevator mode in an electronic device, which is an example of the interface diagram for an electronic device to activate elevator mode when the electronic device executes the method for identifying elevator scenes according to the embodiments of this application.

[0389] In one example, such as Figure 10 As shown, Figure 10 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 10 Another GUI is shown in (b) above; Figure 10 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, control 630 including mobile network, such as... Figure 10 As shown in (b); the electronic device detects an operation on control 630 of the mobile network, such as Figure 10 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 10 As shown in (d) in the diagram; the electronic device detects an operation on the network acceleration control 640, such as... Figure 10 As shown in (e); after the electronic device detects an operation on the network acceleration control 640, a network acceleration settings display interface is displayed; the network acceleration settings display interface may include a control 650 for enabling network acceleration and applications that support network acceleration; the electronic device detects an operation on the control 650 for enabling network acceleration, such as... Figure 10 As shown in (f) in the figure; after the electronic device detects the operation of the control 650 for enabling network acceleration, it can enable the Link Turbo function of the electronic device; that is, the electronic device can identify whether the user is in an elevator scene by the method of identifying elevator scene in the embodiment of the application, and enable the elevator mode of the electronic device based on the identification result; for example, the electronic device enables the Link Turbo function.

[0390] For example, if the identification result obtained by the method for identifying elevator scenes based on the embodiments of this application is that an elevator scene has been entered, the electronic device can activate elevator mode; that is, in order to ensure a smooth internet experience for the user, the signal search power of the electronic device can be increased to realize the Link Turbo function; after activating elevator mode, the electronic device can display the prompt message "Activate Smart Application Elevator Mode", such as Figure 11 The prompt box shown is 660.

[0391] Optionally, the prompt box 660 can be displayed on the electronic device's display interface for a preset duration and then automatically close.

[0392] For example, if the identification result obtained by the elevator scene identification method based on the embodiments of this application is "entering an elevator scene", the electronic device can activate elevator mode; that is, in order to ensure a smooth internet experience for users, the signal search power of the electronic device can be increased to realize the Link Turbo function; after activating elevator mode, the electronic device can display a control for activating the smart application elevator mode, such as... Figure 12 The icon shown is 670.

[0393] For example, after an electronic device activates the smart application elevator mode, the specific information of the smart application elevator mode can be viewed through the battery usage of the electronic device; for example, the specific information may include, but is not limited to: number of times it was launched, background usage time / power consumption, activity time distribution, etc.

[0394] For example, such as Figure 13 As shown, Figure 13 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 13 As shown in (b); the electronic device detects an operation on the battery control 730, such as Figure 13 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 13 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 13As 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 13 As shown in (e) in the diagram.

[0395] Optionally, such as Figure 14 As shown in (a), the electronic device detects an operation on the control 740 of the smart application elevator mode; after detecting the operation on the control 740 of the smart application elevator mode, the electronic device 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 14 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 in the elevator scene 5 times; the electronic device detected the operation of the launch management control 750, such as Figure 14 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 14 As 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.

[0396] For example, such as Figure 15 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; 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.

[0397] 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 the electronic device uses the elevator scene recognition method of the embodiments of this application; for example, recognizing that the user is waiting for the elevator, or recognizing that the user is in the elevator and the elevator has not started, or recognizing that the user is in the elevator and the elevator is starting. The electronic device can enhance the signal search power so that the user can have a smooth Internet experience in the elevator scene.

[0398] It should 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.

[0399] The above text combined Figures 1 to 15 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 16 and Figure 17 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.

[0400] Figure 16 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.

[0401] The acquisition module 810 is used to acquire first data, a first detection result, and a first network identifier. The first data is data collected by an accelerometer in the electronic device. The first detection result indicates 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. The processing module 820 is used to obtain an identification result based on the first data, the first detection result, and / or the first network identifier. The identification result includes a first identification result, which indicates that the electronic device is currently in a waiting elevator scenario. Based on the first identification result, a first resource is requested. The first resource is used for the electronic device to run an elevator mode. The elevator mode refers to a mode in which the electronic device switches networks based on full-network aggregation acceleration technology. When the electronic device is detected to be in an elevator scenario, the elevator mode is run based on the first resource.

[0402] Optionally, as an embodiment, the processing module 820 is specifically used for:

[0403] The first identification result is obtained based on the first data, the first detection result, and the first network identifier.

[0404] Optionally, as an embodiment, the identification result includes a second identification result, and the processing module 820 is specifically used for:

[0405] The value of the counting parameter is obtained based on the first data, and the counting parameter is used to indicate that the electronic device is moving in a first direction and has acceleration;

[0406] The second identification result is obtained based on the value of the counting parameter, and the second identification result is used to indicate whether the electronic device is in the elevator scene.

[0407] Optionally, as an embodiment, the processing module 820 is specifically used for:

[0408] If the value of the counting parameter is greater than a first preset threshold, the second identification result is used to indicate that the electronic device is in the elevator scene;

[0409] If the value of the counting parameter is less than or equal to the first preset threshold, the second identification result is used to indicate that the electronic device is not in the elevator scenario.

[0410] Optionally, as an embodiment, the processing module 820 is specifically used for:

[0411] The first data is filtered to obtain the second data;

[0412] Based on the second data, the value of the counting parameter is obtained.

[0413] Optionally, as an embodiment, the processing module 820 is specifically used for:

[0414] The second data is obtained by processing the first data with a bandpass filter and a lowpass filter.

[0415] Optionally, as an embodiment, the processing module 820 is further configured to:

[0416] The first detection result is obtained by using a gradient boosting tree model.

[0417] Optionally, as an embodiment, the motion state includes a stationary state, a first motion state, and a second motion state, wherein the speed of the second motion state is greater than the speed of the first motion state.

[0418] Optionally, as an embodiment, the processing module 820 is specifically used for:

[0419] When the first data meets the first preset condition, the first detection result meets the second preset condition, and the first network identifier meets the third preset condition, the first identification result is obtained;

[0420] Wherein, the first preset condition refers to the predicted acceleration of the electronic device obtained based on the first data being greater than the second preset threshold; the second preset condition refers to the duration of the user exiting the first motion state or the duration of the user exiting the second motion state being less than the third threshold; the third preset condition is that the first network identifier matches the network identifier in the network identifier feature library, which includes the identifiers of the local area networks covered by the area where the elevator is located.

[0421] Optionally, as an embodiment, the processing module 820 is further configured to:

[0422] Obtain a second detection result, wherein the user's motion state is the first motion state and the duration of the first motion state is greater than a fourth preset threshold.

[0423] Exit the elevator mode based on the second detection result.

[0424] Optionally, as an embodiment, the processing module 820 is further configured to:

[0425] Obtain a third detection result and a second network identifier. The third detection result is that the user's motion state is the first motion state and the duration of the first motion state is greater than a fifth preset threshold. The second network identifier is different from the first network identifier.

[0426] Based on the third detection result and the second network identifier, exit the elevator mode.

[0427] Optionally, as an embodiment, the processing module 820 is further configured to:

[0428] First operation detected;

[0429] In response to the first operation, a first interface is displayed, which includes a low power mode, and the low power mode includes turning off the elevator mode.

[0430] Optionally, as an embodiment, when the electronic device is operating the elevator mode, the processing module 820 is further configured to:

[0431] The first prompt message is displayed, which instructs the electronic device to activate the elevator mode.

[0432] Optionally, as an embodiment, when the electronic device is operating the elevator mode, the processing module 820 is further configured to:

[0433] Display a first icon, which indicates that the electronic device should activate the elevator mode.

[0434] It should be noted that the aforementioned electronic device 800 is embodied in the form of functional modules. The term "module" here can be implemented in software and / or hardware, without specific limitations.

[0435] For example, a "module" can be a software program, a hardware circuit, or a combination of both that implements the above functions. The hardware circuit may include an application-specific integrated circuit (ASIC), electronic circuitry, a processor (e.g., a shared processor, a proprietary processor, or a group processor) and memory for executing one or more software or firmware programs, integrated logic circuitry, and / or other suitable components that support the described functions.

[0436] Therefore, the units of the various examples described in the embodiments of this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these 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 this application.

[0437] Figure 17 A schematic diagram of the structure of an electronic device provided in this application is shown. Figure 17 The dashed lines in the diagram indicate that the unit or module is optional; the electronic device 900 can be used to implement the methods described in the above method embodiments.

[0438] The electronic device 900 includes one or more processors 901, which support the implementation of the method for recognizing elevator scenes 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, transistor logic devices, or discrete hardware components.

[0439] The processor 901 can be used to control the electronic device 900, execute software programs, and process data from the software programs. The electronic device 900 may also include a communication unit 905 for inputting (receiving) and outputting (transmitting) signals.

[0440] For example, electronic device 900 can be a chip, communication unit 905 can be the input and / or output circuit of the chip, or communication unit 905 can be the communication interface of the chip, and the chip can be a component of terminal device or other electronic device.

[0441] For example, electronic device 900 can be a terminal device, communication unit 905 can be the transceiver of the terminal device, or communication unit 905 can be the transceiver circuit of the terminal device.

[0442] The electronic device 900 may include one or more memories 902, which store a program 904. The program 904 can be executed by the processor 901 to generate instructions 903, causing the processor 901 to execute the method for recognizing elevator scenes described in the above method embodiments according to the instructions 903.

[0443] Optionally, the memory 902 may also store data.

[0444] Optionally, the processor 901 can also read data stored in the memory 902, which may be stored at the same memory address as the program 904, or the data may be stored at a different memory address than the program 904.

[0445] The processor 901 and memory 902 can be configured separately or integrated together, for example, integrated on the system-on-chip (SOC) of the terminal device.

[0446] For example, the memory 902 can be used to store the relevant program 904 of the method for identifying elevator scenarios provided in the embodiments of this application, and the processor 901 can be used to call the relevant program 904 of the method stored in the memory 902 when executing the method for identifying elevator scenarios, and execute the method of the embodiments of this application; for example, obtaining first data, first detection result and first network identifier, wherein the first data is data collected by the accelerometer in the electronic device, the first detection result is used to indicate the user's motion state, the user is carrying the electronic device, and the first network identifier is the network identifier of the network currently accessed by the electronic device; obtaining an identification result based on the first data, the first detection result and / or the first network identifier, the identification result including a first identification result, the first identification result is used to indicate that the electronic device is currently in a waiting elevator scenario; applying for a first resource based on the first identification result, the first resource is used for the electronic device to run elevator mode, the elevator mode refers to the mode in which the electronic device switches networks based on full network aggregation acceleration technology; when the electronic device is detected to be in an elevator scenario, running elevator mode based on the first resource.

[0447] This application also provides a computer program product that, when executed by processor 901, implements the method for recognizing elevator scenes in any of the method embodiments of this application.

[0448] The computer program product can be stored in memory 902, for example, program 904. Program 904 is finally converted into an executable object file that can be executed by processor 901 after processing such as preprocessing, compilation, assembly and linking.

[0449] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a computer, implements the method for recognizing elevator scenes as described in any of the method embodiments of this application. The computer program may be a high-level language program or an executable object program.

[0450] The computer-readable storage medium is, for example, memory 902. Memory 902 can be volatile memory or non-volatile memory, or memory 902 can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0451] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these 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 this application.

[0452] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0453] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the embodiments of the electronic devices described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0454] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0455] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0456] It should be understood that in the various embodiments of this application, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0457] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0458] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0459] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of protection of the claims. In conclusion, the above description is merely a preferred embodiment of the technical solution of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method of identifying an elevator scenario, characterized by Applied to electronic devices, including: Acquire first data, first detection result and first network identifier, wherein the first data is data collected by the accelerometer in the electronic device, the first detection result is used to indicate the user's motion state, the user is carrying the electronic device, and the first network identifier is the network identifier of the network currently accessed by the electronic device; The identification result is obtained based on the first data, the first detection result and / or the first network identifier. The identification result includes a first identification result, a second identification result and a third identification result. The first identification result is used to indicate whether the electronic device is currently in a waiting elevator scenario. The second identification result is used to indicate whether the electronic device is in an elevator scenario. The third identification result is used to indicate whether the electronic device is in a scenario where it has not entered an elevator. If the electronic device is currently in the elevator waiting scenario, it requests a first resource. The first resource is used for the electronic device to run elevator mode. Elevator mode refers to the mode in which the electronic device switches networks based on full network aggregation acceleration technology. If the electronic device is detected to be in an elevator scenario, the elevator mode is run based on the first resource.

2. The method of claim 1, wherein, The identification result obtained based on the first data, the first detection result, and / or the first network identifier includes: The first identification result is obtained based on the first data, the first detection result, and the first network identifier.

3. The method of claim 1 or 2, wherein, The identification result includes a second identification result, and the identification result obtained based on the first data, the first detection result, and / or the first network identifier includes: The value of the counting parameter is obtained based on the first data, and the counting parameter is used to indicate that the electronic device is moving in a first direction and has acceleration; The second identification result is obtained based on the value of the counting parameter, and the second identification result is used to indicate whether the electronic device is in the elevator scene.

4. The method of claim 3, wherein, The process of obtaining the second identification result based on the value of the counting parameter includes: If the value of the counting parameter is greater than a first preset threshold, the second identification result is used to indicate that the electronic device is in the elevator scene; If the value of the counting parameter is less than or equal to the first preset threshold, the second identification result is used to indicate that the electronic device is not in the elevator scenario.

5. The method of claim 3, wherein, The process of obtaining the value of the counting parameter based on the first data includes: The first data is filtered to obtain the second data; Based on the second data, the value of the counting parameter is obtained.

6. The method of claim 5, wherein, The step of filtering the first data to obtain the second data includes: The first data is processed by a bandpass filter and a lowpass filter to obtain the second data.

7. The method of claim 1 or 2, wherein, Also includes: The first detection result is obtained by using a gradient boosting tree model.

8. The method of claim 2, wherein, The motion states include a stationary state, a first motion state, and a second motion state, wherein the speed of the second motion state is greater than the speed of the first motion state.

9. The method of claim 8, wherein, The process of obtaining the first identification result based on the first data, the first detection result, and the first network identifier includes: The first identification result is obtained when the first data meets the first preset condition, the first detection result meets the second preset condition, and the first network identifier meets the third preset condition; The first preset condition refers to the predicted acceleration of the electronic device obtained based on the first data being greater than the second preset threshold; the second preset condition refers to the user exiting the first motion state, or the duration of the user exiting the second motion state being less than the third threshold; the third preset condition is that the first network identifier matches a network identifier in a network identifier feature library, which includes identifiers of local area networks covered by the elevator.

10. The method of claim 8 or 9, wherein, Also includes: Obtain a second detection result, wherein the second detection result is that the user's motion state is the first motion state and the duration of the first motion state is greater than a fourth preset threshold; Exit the elevator mode based on the second detection result.

11. The method of claim 8 or 9, wherein, Also includes: Obtain a third detection result and a second network identifier. The third detection result is that the user's motion state is the first motion state and the duration of the first motion state is greater than a fifth preset threshold. The second network identifier is different from the first network identifier. Based on the third detection result and the second network identifier, exit the elevator mode.

12. The method of claim 1 or 2, wherein, Also includes: First operation detected; In response to the first operation, a first interface is displayed, which includes a low power mode, and the low power mode includes turning off the elevator mode.

13. The method of claim 1 or 2, wherein, When the electronic device is operating in the elevator mode, it also includes: The first prompt message is displayed, which instructs the electronic device to activate the elevator mode.

14. The method of claim 1 or 2, wherein, When the electronic device is operating in the elevator mode, it also includes: Display a first icon, which indicates that the electronic device should activate the elevator mode.

15. An electronic device, comprising: include: One or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the electronic device to perform the method as described in any one of claims 1 to 14.

16. A chip system, characterized by The chip system is applied to an electronic device, the chip system including one or more processors, the processors being configured to invoke computer instructions to cause the electronic device to perform the method as described in any one of claims 1 to 14.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to perform the method of any one of claims 1 to 14.

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