Network access method and related device

Abstract

The invention provides a network access method and a related device, the method is applied to electronic equipment, and the method comprises the following steps: when it is predicted that an aircraft lands after a first duration, scanning a country code; if the first country code is scanned, network searching is carried out based on network searching parameters of candidate airports corresponding to the first country code, and first network searching information is obtained, and the candidate airports comprise one or more airports; and accessing the first network based on the first network searching information. In this way, when it is predicted that the aircraft is about to land, the network of the airport of the landing site can be searched in a targeted manner, so that the reliable network of the landing site is accurately accessed, the network return time required by the electronic equipment in an aircraft travel scene is effectively shortened, and the user experience is improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a network access method and related apparatus. Background Technology

[0002] In air travel scenarios, mobile phones and other electronic devices carried by passengers are without cellular signals while flying at high altitudes. Therefore, how these devices quickly reconnect to the network after landing is a crucial issue affecting user experience. Currently, after landing, electronic devices first search for networks based on the frequencies of the previously registered public land mobile network (PLMN), i.e., searching for previously registered frequencies. However, the landing site may be far from the takeoff site, so the frequencies of the historical frequencies and the landing site generally do not overlap. This often results in the electronic device not being able to find the historical frequencies. In this case, the electronic device needs to perform a full-band network search to find available frequencies at the landing site and connect to the network corresponding to those available frequencies. Thus, the reconnection time for electronic devices in air travel scenarios is quite long, impacting the user experience. Summary of the Invention

[0003] This application discloses a network access method and related apparatus, which can specifically search for the network of the airport at the landing site when it is predicted that the aircraft is about to land, thereby accurately accessing a reliable network, effectively reducing the network access time required for electronic devices in air travel scenarios, and improving the user experience.

[0004] In a first aspect, this application provides a network access method applied to an electronic device. The method includes: predicting that an aircraft will land after a first time period, scanning a country code; if a first country code is scanned, performing a network search based on the network search parameters of candidate airports corresponding to the first country code, and obtaining first network search information, wherein the candidate airports include one or more airports; and accessing a first network based on the first network search information.

[0005] In some examples, the prediction that the aircraft will land after a certain time interval can also be understood as detecting an imminent landing scenario. Specifically, "imminent landing" refers to the aircraft beginning its descent but before it touches down.

[0006] In some examples, the first duration is between a first duration value and a second duration value. Optionally, the first duration value is greater than 0, and the second duration value is less than the duration from the start of the descent to the landing of the aircraft. For example, the first duration is in the range of 5 minutes to 15 minutes.

[0007] In some examples, network search parameters include one or more of the following: Public Land Mobile Network (PLMN), Radio Access Technology (RAT), frequency band, and frequency point.

[0008] In the above method, the electronic device can accurately predict the landing scenario shortly before the aircraft lands. Furthermore, as the aircraft approaches landing, the electronic device scans the country code of its location and then precisely searches for the network of the candidate airport corresponding to that country code, based on the network search parameters. This targeted search of the landing airport's network ensures accurate access to a reliable network (e.g., a high-quality network at the landing airport), rather than searching the entire frequency band. This effectively reduces the network reconnection time required by the electronic device during air travel, ensuring rapid network reconnection and significantly improving the user experience.

[0009] In one possible implementation, the method further includes: acquiring first acceleration data and first gyroscope data through a sensor module; determining flight characteristic data based on the first acceleration data and first gyroscope data, wherein the flight characteristic data includes one or more of the following: aircraft turning information, aircraft weightlessness information, data obtained by statistically analyzing and / or calculating the first acceleration data, and data obtained by statistically analyzing and / or calculating the first gyroscope data; inputting the flight characteristic data into a landing prediction model and obtaining the prediction result of the landing prediction model; and scanning the country code when the aircraft is predicted to land after a first duration, including: scanning the country code if the prediction result of the landing prediction model indicates that the aircraft will land after a first duration.

[0010] In some examples, the above-mentioned determination of flight characteristic data based on first acceleration data and first gyroscope data includes: preprocessing the first acceleration data and first gyroscope data, then analyzing and processing the preprocessed first acceleration data and first gyroscope data to obtain flight characteristic data. The data preprocessing includes one or more of the following: removing attitude change data, noise filtering, signal smoothing, normalization, and bias removal. In this way, the preprocessed first acceleration data and first gyroscope data can better reflect the aircraft's state changes, remove noise and interference, and make the data more stable. Predicting the aircraft's imminent landing based on the preprocessed data can improve accuracy.

[0011] In some examples, the aircraft turning information mentioned above includes one or more of the following: number of turns, turning time, and turning angle. The aircraft weightlessness information mentioned above includes one or more of the following: number of weightlessness events, duration of weightlessness, and acceleration data during weightlessness. The statistics and / or operations mentioned above include one or more of the following: calculating the mean, calculating the variance, calculating the components of a vector in one direction, calculating the cumulative value over a period of time, calculating the change over a period of time, calculating the minimum value over a period of time, and calculating the maximum value over a period of time. Thus, the types of flight characteristic data are diverse and can effectively reflect changes in the aircraft's state. Predicting an aircraft's imminent landing based on such flight characteristic data can improve accuracy.

[0012] In the above method, after the electronic device acquires the first acceleration data and the first gyroscope data, it processes and analyzes them to obtain flight feature data. Then, the electronic device uses a pre-trained landing prediction model to detect whether the aircraft is in an imminent landing scenario based on the flight feature data, and when an imminent landing scenario is detected, it obtains the predicted imminent landing duration (i.e., the first duration). The landing prediction model can be based on a large amount of real-world flight data from imminent landing scenarios. Furthermore, the electronic device uses flight feature data that effectively reflects important characteristics of the aircraft's flight process to detect imminent landing scenarios, rather than simply using acceleration and gyroscope data. Therefore, the electronic device achieves a high-accuracy and low-latency aircraft imminent landing detection algorithm.

[0013] In one possible implementation, after inputting flight characteristic data into the landing prediction model and obtaining the prediction result of the landing prediction model, the method further includes: obtaining aircraft jitter based on second acceleration data and second gyroscope data; correcting the prediction result of the landing prediction model based on the aircraft jitter; and scanning the country code if the prediction result of the landing prediction model indicates that the aircraft will land after a first duration, which includes: scanning the country code if the prediction result of the corrected landing prediction model indicates that the aircraft will land after a first duration.

[0014] In some examples, the first acceleration data and the first gyroscope data are acquired in a first time period, and the second acceleration data and the second gyroscope data are acquired in a second time period. The range of the second time period is greater than or equal to the range of the first time period, wherein the second time period includes the first time period, optionally, and the time period following the first time period.

[0015] In some examples, the uncorrected landing prediction model indicates that the aircraft will land after the seventh hour; the correction of the landing prediction model based on the aircraft jitter includes: correcting the prediction that the aircraft will land after the seventh hour to the prediction that the aircraft will land after the first hour based on the aircraft jitter.

[0016] In the above method, considering that in the period before landing, the aircraft will generally experience frequent left and right shaking due to factors such as low altitude, unstable low airflow, low speed, and decreased acceleration. Therefore, the electronic equipment can correct and compensate the prediction results of the landing prediction model based on the aircraft shaking situation, thereby further improving the detection accuracy of the aircraft's imminent landing scenario.

[0017] In one possible implementation, the above-mentioned scanning of the country code includes scanning the country code in a preset frequency band. For example, the preset frequency band is a "golden" frequency band determined by the device (such as a frequency band with good propagation characteristics, wide coverage, and strong penetration). Scanning the country code by scanning the golden frequency band can more accurately scan the country code and the scanning time is shorter.

[0018] In one possible implementation, the method further includes: before the predicted landing time of the aircraft after the first duration, acquiring first flight information, the first flight information including a first destination and a first landing airport; determining a second country code for the first destination, and search parameters for candidate airports corresponding to the second country code, wherein the candidate airports corresponding to the second country code include the first landing airport; the above-mentioned searching based on the search parameters of the candidate airports corresponding to the first country code if the first country code is scanned includes: if the scanned first country code and second country code are the same, searching based on the search parameters of the first landing airport; if searching based on the search parameters of the first landing airport fails, searching based on the search parameters of the first candidate airport, wherein the first candidate airport includes one or more other candidate airports besides the first landing airport among the candidate airports corresponding to the second country code.

[0019] In the above method, if the electronic device obtains the information of the first flight, and the first country code scanned by the electronic device when the aircraft is about to land is the same as the second country code of the first destination in the first flight information, then it can prioritize scanning the network of the first landing airport in the first flight information. This can more accurately search for the network of the airport at the landing point, thereby more accurately accessing the reliable network of the landing point (such as the network of the first landing airport), further reducing the network access time required by the electronic device in the air travel scenario, and thus improving the user experience.

[0020] In one possible implementation, the above-mentioned search based on the search parameters of the candidate airport corresponding to the first country code when a first country code is scanned includes: if the scanned first country code and second country code are different, obtaining the search parameters of the candidate airport corresponding to the first country code, and performing a search based on the search parameters of the candidate airport corresponding to the first country code.

[0021] In one possible implementation, the electronic device does not obtain flight information; if the first country code is scanned, the search network is performed based on the search network parameters of the candidate airport corresponding to the first country code, including: obtaining the search network parameters of the candidate airport corresponding to the first country code, and performing a search network based on the search network parameters of the candidate airport corresponding to the first country code.

[0022] In the above method, the electronic device can select a network search method suitable for the current scenario based on whether flight information has been obtained, and whether the first country code scanned when the first flight information has been obtained is the same as the second country code of the first destination in the first flight information. This ensures accurate network search and network connection in various scenarios, thereby ensuring that the electronic device can quickly return to the network in the air travel scenario.

[0023] In one possible implementation, the above-mentioned search based on the candidate airport search parameters corresponding to the first country code if the first country code is scanned includes: if the first country code and the first search parameters corresponding to the first country code (e.g., PLMN and frequency point) are scanned, a search is performed based on the first search parameters, and a search is performed based on the candidate airport search parameters corresponding to the first country code.

[0024] In the above method, if the scanning result obtained by the electronic device from scanning the country code includes a first country code and the first network search parameters corresponding to the first country code, then when the electronic device searches for a network, it can search not only based on the network search parameters of the candidate airports corresponding to the first country code, but also based on the first network search parameters. The first network search parameters corresponding to the first country code can be understood as the network search parameters of the location scanned by the electronic device when the aircraft is about to land. Therefore, the success rate of the electronic device searching for a network based on the first network search parameters is relatively high, which further ensures that the electronic device can quickly return to the network in air travel scenarios.

[0025] In one possible implementation, before performing a network search based on the search parameters of the candidate airports corresponding to the first country code and obtaining the first network search information, the method further includes: if the first country code is scanned, performing a network search based on the first country code (e.g., performing a network search based on the search parameters of the candidate airports corresponding to the first country code) and obtaining the second network search information; the above-mentioned performing a network search based on the search parameters of the candidate airports corresponding to the first country code includes: if the first country code is scanned, performing a network search based on the search parameters of the candidate airports corresponding to the first country code, and searching the network in the second network search information.

[0026] In the above method, after the electronic device scans the first country code, it can first perform a network search based on the first country code to obtain second network search information, but it can choose not to camp on the network at this time. This avoids the situation where, if the first search duration is relatively long (e.g., 15 minutes), the second network search information obtained after scanning the country code cannot effectively represent the network situation at the landing site, resulting in a poor user experience when camping on the network based on the second network search information. After a period of time has passed since the network search based on the first country code, such as during the first period before the aircraft lands, or during the aircraft landing, the electronic device combines the second network search information with the network search parameters of the candidate airports corresponding to the first country code to perform a network search and camp on the network, further improving the reliability of the network response of the electronic device in the air travel scenario, thereby improving the user experience.

[0027] In one possible implementation, the above-mentioned prediction that the aircraft will land after a first duration, scanning the country code, includes: with the flight mode of the electronic device enabled, predicting that the aircraft will land after a first duration, and scanning the country code; if the first country code is scanned, performing a network search based on the network search parameters of the candidate airports corresponding to the first country code, and obtaining first network search information, wherein the candidate airports include one or more airports; accessing the first network based on the first network search information includes: in response to disabling the flight mode of the electronic device, if the first country code is scanned, performing a network search based on the network search parameters of the candidate airports corresponding to the first country code, and obtaining first network search information, and then accessing the first network based on the first network search information.

[0028] In some examples, when the electronic device's flight mode is enabled, the electronic device predicts that the aircraft will land after a certain time interval, scans the country code, and obtains a first country code and its corresponding first network search parameters. The electronic device then determines the network search parameters for candidate airports corresponding to the first country code. In response to disabling the electronic device's flight mode, the electronic device performs a network search based on the first network search parameters and the network search parameters for the candidate airports corresponding to the first country code, obtaining first network search information. It then accesses the first network based on this first network search information. For example, when the electronic device's flight mode is enabled, the semaphore bar indicates that it is not connected to the network; shortly after disabling the flight mode, the semaphore bar indicates that it is connected to the network.

[0029] In some examples, when the electronic device's flight mode is enabled, the electronic device predicts that the aircraft will land after a certain period of time, scans the country code and obtains a first country code, performs a network search based on the first country code and obtains second network search information, and determines the network search parameters of the candidate airport corresponding to the first country code based on the first country code; then, in response to disabling the electronic device's flight mode, the electronic device performs a network search based on the network search parameters of the candidate airport corresponding to the first country code, searches for networks in the second network search information, obtains first network search information, and then accesses the first network based on the first network search information.

[0030] In one possible implementation, when the aircraft is predicted to land after a first duration, the country code is scanned; if the first country code is scanned, a network search is performed based on the search parameters of the candidate airports corresponding to the first country code, and first network search information is obtained, wherein the candidate airports include one or more airports; accessing the first network based on the first network search information includes: when the flight mode of the electronic device is off, when the aircraft is predicted to land after a first duration, the country code is scanned; if the first country code is scanned, a network search is performed based on the search parameters of the candidate airports corresponding to the first country code, and first network search information is obtained, and then accessing the first network based on the first network search information.

[0031] In some examples, when the electronic device's flight mode is off, the electronic device predicts that the aircraft will land after a certain period of time, scans the country code, and obtains the first country code and the first search network parameters corresponding to the first country code. The electronic device then determines the search network parameters of the candidate airports corresponding to the first country code based on the first country code. Then, the electronic device begins to search the network based on the first search network parameters and the search network parameters of the candidate airports corresponding to the first country code, for example, by periodically searching the network, until it obtains the first search network information corresponding to the first network that it can camp on, and then accesses the first network based on the first search network information.

[0032] In one possible implementation, the method further includes: receiving a search list sent by a cloud server before the predicted landing time of the aircraft after the first time interval, wherein the search list includes one or more country codes and search parameters for candidate airports corresponding to each of the one or more country codes, the search parameters including one or more of the following: Public Land Mobile Network (PLMN), Radio Access Technology (RAT), frequency band or frequency point, and the search parameters for candidate airports corresponding to the first country code are obtained by electronic devices from the search list.

[0033] In some examples, the network search parameters for candidate airports corresponding to any country code in the network search list can have a priority order. For example, the network search parameters of different candidate airports may have different priorities, and / or, the network search parameters of different networks within the same candidate airport may have different priorities. The network search parameters for candidate airports corresponding to the first country code obtained from the network search list can also have a priority order. The above-mentioned network search based on the network search parameters of candidate airports corresponding to the first country code includes: performing network search according to the priority order based on the network search parameters of candidate airports corresponding to the first country code.

[0034] In the above method, the electronic device can use the search list sent by the cloud server to determine the search parameters of the candidate airports corresponding to the first country code used during the search. The source of the search parameters is reliable, and the electronic device automatically downloads the search list without requiring active user operation.

[0035] In one possible implementation, the method further includes: after accessing the first network based on the first search network information, sending the network information of the first network to the cloud server, wherein the network information of the first network includes one or more of the following: the first country code corresponding to the first network, the PLMN corresponding to the first network, the PLMN registration information corresponding to the first network, the standard of the first network, the frequency band of the first network, the frequency point of the first network, the cell identifier corresponding to the first network, the location information of the electronic device accessing the first network, and the service experience information of the electronic device using the first network.

[0036] In some examples, the list of networks sent by the cloud server is determined by the cloud server based on crowdsourced data, which includes network information on network access sent by multiple devices.

[0037] In some examples, the network information of the first network mentioned above is used by the cloud server to update the network search list.

[0038] In the above method, the cloud server can automatically generate and update the search parameters of candidate airports corresponding to each country code in the search list based on crowdsourced data, without the need for manual collection and updating of airport search parameters. The airport search parameters can be updated in a timely manner and with high accuracy, effectively reducing the consumption of manpower and material resources.

[0039] In one possible implementation, the search parameters for the candidate airports corresponding to the first country code are preset preferred search parameters. For example, the search parameters for the candidate airports corresponding to the first country code are obtained by the electronic device from the search list, and the search parameters for the candidate airports corresponding to any country code in the search list are preferred search parameters determined by the cloud server.

[0040] In some examples, the candidate airports corresponding to the first country code are preset preferred airports. For example, the candidate airports include one or more of the following: airports with passenger flow determined by the device to be greater than or equal to a preset passenger flow threshold, airports with a size determined by the device to be greater than or equal to a preset size threshold, and airports with an importance determined by the device to be greater than or equal to a preset importance threshold.

[0041] In some examples, the network search parameters of any candidate airport corresponding to the first country code mentioned above include the network search parameters of the preset preferred network in the candidate airport. For example, the preset preferred network in the candidate airport is: a network whose network quality is greater than or equal to a preset quality threshold among one or more networks of the candidate airport determined by the device, and / or a network whose user usage frequency is greater than or equal to a preset frequency threshold among one or more networks of the candidate airport determined by the device.

[0042] In the above method, after the electronic device scans the first country code, the network search parameters for the candidate airport corresponding to the first country code can be the preferred network search parameters. This can more accurately search for the preferred network of the landing point, thereby more accurately accessing the reliable network of the landing point, further reducing the network return time required by the electronic device in the air travel scenario, and thus improving the user experience.

[0043] In one possible implementation, before scanning the country code when the aircraft is predicted to land after a first duration, the method further includes: detecting an aircraft takeoff scenario, and / or detecting an aircraft cruise scenario; and predicting the aircraft landing time in response to the detected aircraft takeoff scenario and / or aircraft cruise scenario.

[0044] In the above method, the electronic device can trigger the prediction of the aircraft's landing time when it determines that an aircraft takeoff scenario and / or an aircraft cruise scenario has been detected, instead of continuously predicting the aircraft's landing time, which effectively reduces the power consumption of the electronic device and improves the availability of the device.

[0045] In one possible implementation, before scanning the country code when the aircraft is predicted to land after a certain time interval, the method further includes: predicting the aircraft's landing time in response to the electronic device being powered on. For example, the electronic device is powered off before takeoff and powered on after takeoff or cruise. This way, even if the electronic device does not detect the aircraft takeoff scenario and / or the aircraft cruise scenario, it can still detect the aircraft's impending landing scenario, thereby accurately searching for and registering on the network, ensuring that the electronic device can quickly return to the network in air travel scenarios.

[0046] In one possible implementation, the method further includes: detecting an aircraft landing scenario after the aircraft is predicted to land after a first time period; and accessing the first network based on the first search network information includes: accessing the first network based on the first search network information after detecting the aircraft landing scenario.

[0047] In some examples, when the landing of an aircraft is predicted to occur after a certain time interval, the electronic device scans the country code and obtains the first country code. After detecting the aircraft landing scenario, the electronic device performs a network search based on the network search parameters of the candidate airports corresponding to the first country code and obtains the first network search information. Then, it accesses the first network based on the first network search information. This avoids the situation where, when the first time interval is long, the network search information obtained after scanning the country code cannot effectively represent the network situation at the landing site, resulting in a poor user experience on the network where the device resides.

[0048] In one possible implementation, the above-mentioned detection of an aircraft takeoff scenario includes: acquiring third acceleration data through a sensor module; detecting whether the aircraft is in a taxiing state based on the third acceleration data; if the aircraft is in a taxiing state, detecting whether the aircraft is in a climb state based on fourth acceleration data and third gyroscope data; if the aircraft is in a climb state, detecting an aircraft takeoff scenario.

[0049] In the above method, the electronic device can construct a state machine for the three states of the aircraft takeoff scenario (i.e., stationary state, taxiing state, and climb state), and use sensor data as the basis for switching between the various states, thus realizing an aircraft takeoff detection algorithm with high accuracy and low detection latency.

[0050] In one possible implementation, the above-mentioned detection of whether the aircraft is in a taxiing state based on the third acceleration data includes: determining whether the duration of the magnitude of the third acceleration data within a first threshold range is greater than or equal to a second duration; if the duration of the magnitude of the third acceleration data within the first threshold range is greater than or equal to the second duration, the aircraft is detected to be in a taxiing state; the above-mentioned detection of whether the aircraft is in a climb state based on the fourth acceleration data and the third gyroscope data includes: determining whether preset climb conditions are met based on the fourth acceleration data and the third gyroscope data, the climb conditions including one or more of the following: the duration of the magnitude of the fourth acceleration data within the second threshold range is greater than or equal to the third duration, the duration of the first gravitational acceleration within the third threshold range is greater than or equal to the fourth duration, the duration of the variance of the fourth acceleration data within the fourth threshold range is greater than or equal to the fifth duration, wherein the first gravitational acceleration is determined based on the fourth acceleration data and the third gyroscope data, and the first gravitational acceleration is the component of the fourth acceleration data in the direction of gravity; if the climb conditions are met, the aircraft is detected to be in a climb state.

[0051] In the above method, electronic devices can accurately label the taxiing and climb states during takeoff by setting value ranges and durations for acceleration features (such as acceleration magnitude, gravitational acceleration, and acceleration variance) that effectively reflect the aircraft's takeoff state. The climb conditions used for climb detection can be multi-condition constraints based on various acceleration features. This aircraft takeoff detection algorithm can effectively identify key states (taxiing and climb) during takeoff, thereby achieving higher accuracy and lower detection latency.

[0052] In one possible implementation, the above-mentioned detection of an aircraft cruise scenario includes: after detecting an aircraft takeoff scenario, determining whether a preset waiting condition is met, wherein the waiting condition includes: the aircraft is in a stable state, and / or, the elapsed time after detecting the aircraft takeoff scenario is greater than or equal to a sixth time period; if the waiting condition is met, collecting fifth acceleration data through a sensor module within a first time window, and determining the range of the magnitude values ​​of the fifth acceleration data; determining whether the range of the magnitude values ​​of the fifth acceleration data is less than a preset range threshold; if the range of the magnitude values ​​of the fifth acceleration data is less than the preset range threshold, an aircraft cruise scenario is detected.

[0053] In the above method, considering that an aircraft needs sufficient time to climb after takeoff before entering cruise mode, and that takeoff detection is typically determined when the aircraft begins its climb, the electronic equipment performs cruise detection based on the fifth acceleration data only when the waiting conditions are met. This avoids detection errors caused by prematurely performing cruise detection based on the fifth acceleration data. Furthermore, the electronic equipment measures the fluctuation of the aircraft's acceleration by the range of the modulus values ​​of the fifth acceleration data within the first time window, thus performing cruise detection. This approach aligns with real-world scenarios and achieves a cruise detection algorithm with high accuracy and low detection latency.

[0054] In one possible implementation, the above-mentioned detection of an aircraft landing scenario includes: collecting sixth acceleration data and fourth gyroscope data through a sensor module; detecting whether the aircraft is in a g-force state during landing based on the sixth acceleration data and fourth gyroscope data; if the aircraft is in a g-force state during landing, detecting whether the aircraft is in a grounding state based on the seventh acceleration data and fifth gyroscope data; if the aircraft is in a grounding state, detecting an aircraft landing scenario.

[0055] In the above method, electronic devices can construct a state machine for the key states in the aircraft landing scenario (i.e., the overweight state and the grounding state of the aircraft during landing) and use sensor data as the basis for switching between the various states, thus realizing an aircraft landing detection algorithm with high accuracy and low detection latency.

[0056] In one possible implementation, the above-mentioned detection of whether the aircraft is in a g-force state during landing based on the sixth acceleration data and the fourth gyroscope data includes: determining a second gravitational acceleration based on the sixth acceleration data and the fourth gyroscope data, wherein the second gravitational acceleration is the component of the sixth acceleration data in the direction of gravity; determining whether the second gravitational acceleration is greater than or equal to a preset g-force threshold; if the second gravitational acceleration is greater than or equal to the g-force threshold, detecting that the aircraft is in a g-force state during landing; the above-mentioned detection of whether the aircraft is in a grounding state based on the seventh acceleration data and the fifth gyroscope data includes: determining whether a preset condition is met based on the seventh acceleration data and the fifth gyroscope data. The grounding conditions include: the variance of the first horizontal acceleration is greater than or equal to a preset grounding threshold, and / or, the magnitude of the seventh acceleration data satisfies a preset magnitude condition, wherein the first horizontal acceleration is determined based on the seventh acceleration data and the fifth gyroscope data, the first horizontal acceleration is the horizontal component of the seventh acceleration data, and the preset magnitude condition includes: the sum of the maximum and minimum values ​​of the magnitude of the seventh acceleration data is within a first value range (e.g., a first value), and / or, the difference between the maximum and minimum values ​​of the magnitude of the seventh acceleration data is within a second value range (e.g., a second value); if the grounding conditions are met, the aircraft is detected to be in a grounding state.

[0057] In the above method, electronic devices can accurately mark the overload state and the aircraft's touchdown state during landing by setting value ranges for acceleration characteristics (such as the variance and magnitude of horizontal acceleration) that effectively reflect the aircraft's landing state. The touchdown conditions used for touchdown detection can be multi-condition constraints based on various acceleration characteristics. Such an aircraft landing detection algorithm can effectively identify key states during the landing process (i.e., the overload state and the aircraft's touchdown state), thereby achieving higher accuracy and lower detection latency.

[0058] In one possible implementation, the method further includes: after detecting an aircraft takeoff scenario, before predicting that the aircraft will land after a first duration, using a first search method; and after predicting that the aircraft will land after a first duration, using a second search method, wherein the search frequency in the first search method is less than the search frequency in the second search method, or the first search method is no search and the second search method is search.

[0059] In the above method, the electronic device does not search for the network or searches at a low frequency after detecting the aircraft takeoff scenario, until it predicts that the aircraft will land after the first time interval (i.e. when the aircraft is about to land scenario is detected), and then resumes searching for the network or resumes a higher network search frequency, instead of searching for the network continuously or using a high network search frequency continuously. This effectively reduces the unnecessary power consumption caused by the normal network search when the aircraft is flying at high altitude without a cellular network, and improves the user experience.

[0060] In one possible implementation, the method further includes: after detecting an aircraft cruise scenario, before the predicted aircraft landing after a first duration, using a first search-the-net method; after the predicted aircraft landing after a first duration, using a second search-the-net method, wherein the search-the-net frequency in the first search-the-net method is less than the search-the-net frequency in the second search-the-net method, or the first search-the-net method is no search-the-net method and the second search-the-net method is a search-the-net method.

[0061] In the above method, the electronic device either stops searching for a network or searches at a low frequency after detecting an aircraft cruising scenario, until it predicts that the aircraft will land after a certain time interval (i.e., when the imminent landing scenario is detected), at which point it resumes searching for a network or resumes a higher frequency of network search, instead of searching for a network continuously or using a high frequency continuously. This effectively reduces unnecessary power consumption caused by the aircraft searching for a network normally when there is no cellular network available at high altitudes, thus improving the user experience. Furthermore, compared to stopping searching for a network or searching at a low frequency after detecting an aircraft takeoff scenario, the method of not searching for a network or searching at a low frequency after detecting an aircraft cruising scenario allows users to access the internet after takeoff and before the aircraft cruising, which can meet the needs of some specific users.

[0062] In one possible implementation, the method further includes: after detecting an aircraft takeoff scenario and an aircraft cruise scenario, before the aircraft is predicted to land after a first duration, using a first search network method; after the aircraft is predicted to land after a first duration, using a second search network method, wherein the search network frequency in the first search network method is less than the search network frequency in the second search network method, or the first search network method is no search network and the second search network method is a search network.

[0063] In the above method, after detecting aircraft takeoff and cruise scenarios, the electronic device either stops searching for a network or searches at a low frequency until it predicts that the aircraft will land after a certain time interval (i.e., when the imminent landing scenario is detected). At this point, it resumes searching for a network or at a higher frequency, rather than continuously searching for a network or using a consistently high frequency. This effectively reduces unnecessary power consumption caused by the aircraft searching for a network when there is no cellular network available at high altitudes, thus improving the user experience. Furthermore, the accuracy of dual-scenario detection (i.e., detection of aircraft takeoff and cruise scenarios) is higher, avoiding situations where a single scenario detection error prevents the electronic device from searching for and reconnecting to the network in a timely manner, further ensuring a better user experience.

[0064] Secondly, this application provides an electronic device, including a processor and a memory; the memory is used to store a computer program, and the processor calls the computer program to execute the network access method provided in the first aspect and any implementation thereof.

[0065] Thirdly, this application provides a computer storage medium storing a computer program, which, when executed by a processor, is used to perform the network access method provided in the first aspect and any implementation thereof.

[0066] Fourthly, this application provides a computer program product, including a computer program that, when run on a processor, implements the network access method provided by the first aspect and any implementation thereof.

[0067] Fifthly, this application provides a chip system including a processing circuit and an interface circuit. The interface circuit is used to receive code instructions and transmit them to the processing circuit. The processing circuit is used to execute the code instructions to perform the network access method provided in the first aspect and any implementation thereof.

[0068] Sixthly, this application provides an electronic device that includes the methods or apparatus described in any aspect or embodiment of this application. The aforementioned electronic device is, for example, a chip.

[0069] It should be understood that the descriptions of technical features, technical solutions, beneficial effects, or similar language in this application do not imply that all features and advantages can be achieved in any single implementation. Rather, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution, or beneficial effect is included in at least one implementation. Therefore, the descriptions of technical features, technical solutions, or beneficial effects in this application do not necessarily refer to the same implementation. Furthermore, the technical features, technical solutions, and beneficial effects described in this application can be combined in any suitable manner. Those skilled in the art will understand that this application can be implemented without one or more specific technical features, technical solutions, or beneficial effects of a particular implementation. In other implementations, additional technical features and beneficial effects may be identified in specific implementations that do not embody all implementations. Attached Figure Description

[0070] The following describes the accompanying drawings used in this application.

[0071] Figure 1 This is a schematic diagram of an air travel scenario provided in this application;

[0072] Figure 2 This is a schematic diagram of the architecture of a communication system provided in this application;

[0073] Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in this application;

[0074] Figure 4 This is a schematic diagram of the software architecture of an electronic device provided in this application;

[0075] Figure 5 This is a schematic diagram of the hardware structure of a cloud server provided in this application;

[0076] Figure 6 This is a flowchart illustrating a network access method provided in this application;

[0077] Figure 7 This is a schematic diagram of the architecture of another communication system provided in this application;

[0078] Figure 8 An example diagram illustrating the acceleration during an aircraft takeoff is shown.

[0079] Figure 9 This is a flowchart illustrating an aircraft takeoff detection algorithm provided in this application;

[0080] Figure 10 This is a flowchart illustrating an aircraft cruise detection algorithm provided in this application;

[0081] Figure 11This is a schematic diagram of the architecture of an electronic device provided in this application;

[0082] Figure 12A This is a flowchart illustrating the process of acquiring aircraft turning information provided in this application;

[0083] Figure 12B This is a flowchart illustrating the process of acquiring aircraft weightlessness information provided in this application;

[0084] Figure 13 This is a flowchart illustrating an aircraft landing detection algorithm provided in this application;

[0085] Figure 14 An exemplary diagram illustrating a web search process is provided.

[0086] Figures 15A-15B These are schematic diagrams illustrating some of the web search processes provided in this application;

[0087] Figures 16A-16B This is a diagram illustrating some of the web-searching processes provided in this application. Detailed Implementation

[0088] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings. The terminology used in the implementation section of this application is only for explaining specific embodiments of this application and is not intended to limit this application.

[0089] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0090] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0091] The term "user interface (UI)" used in the following embodiments of this application refers to the medium interface through which an application or operating system interacts and exchanges information with the user. It realizes the conversion between the internal form of information and the form that the user can accept. The user interface is source code written in a specific computer language such as Java or Extensible Markup Language (XML). The interface source code is parsed and rendered on the electronic device, ultimately presenting content that the user can recognize. A common form of user interface is the graphical user interface (GUI), which refers to a user interface related to computer operation displayed graphically. It can be visible interface elements such as text, icons, buttons, menus, tabs, text boxes, dialog boxes, status bars, navigation bars, and widgets displayed on the screen of an electronic device.

[0092] The following is an exemplary description of an air travel scenario applied to the embodiments of this application.

[0093] Figure 1 This is a schematic diagram of an air travel scenario provided in an embodiment of this application.

[0094] like Figure 1 As shown, a user can carry electronic device 100 and travel by plane from the departure point (also known as the takeoff point) to the destination (also known as the landing point), i.e., the flight route is from the departure point to the destination. For example, in chronological order from morning to night, the flight process can include, but is not limited to, the following stages: takeoff (i.e., the plane takes off from the departure point), cruise (i.e., the plane enters a relatively stable flight state after takeoff), descent begins, imminent landing, and landing (i.e., the plane arrives at / lands at the destination). The imminent landing stage is the stage after the descent begins and before the landing stage, and the imminent landing stage is generally short, for example, 5 to 15 minutes apart.

[0095] In this application embodiment, the electronic device 100 can be any of the following: mobile phone, tablet computer, handheld computer, desktop computer, laptop computer, ultra-mobile personal computer (UMPC), netbook, cellular phone, personal digital assistant (PDA), as well as smart home devices such as smart screens and smart speakers, wearable devices such as smart bracelets, smartwatches, and smart glasses, extended reality (XR) devices such as augmented reality (AR), virtual reality (VR), and mixed reality (MR), in-vehicle devices, or smart city devices.

[0096] Understandably, electronic devices 100 carried by users when flying at high altitudes do not have cellular signals. Therefore, how electronic devices 100 can quickly reconnect to the network (i.e., reconnect to the network) after the plane lands is an important issue affecting user experience.

[0097] Currently, electronic device 100 can collect air pressure values ​​and determine the rate of change of air pressure values ​​using a barometric pressure sensor. It then identifies aircraft takeoff and landing scenarios based on the air pressure values ​​and their rate of change. After detecting an aircraft landing scenario and disabling flight mode, electronic device 100 begins network searching. This search process may include initially searching for frequencies on the previously registered public land mobile network (PLMN), i.e., searching for previously used historical frequencies. However, the destination may be far from the departure point, meaning historical frequencies and destination frequencies often do not overlap. This often results in electronic device 100 failing to find historical frequencies, requiring a full-band search to locate available frequencies at the destination and connect to the network corresponding to those frequencies. Consequently, the network reconnection time required by electronic device 100 during air travel is lengthy, impacting the user experience. Furthermore, some electronic devices 100 are not equipped with barometric pressure sensors, so they cannot recognize the aircraft landing scenario. Users need to perform manual operations such as turning the flight mode on and / or off to trigger the network search, which further prolongs the network reconnection time.

[0098] This application provides a network access method and related apparatus. The method includes: an electronic device 100 detecting that an aircraft is about to land (e.g., ...). Figure 1As shown in the diagram, during the aircraft's imminent landing phase (for example, when the aircraft is detected landing after a certain time interval), electronic device 100 can scan the mobile country code (MCC) (hereinafter referred to as the country code) and obtain the first country code. Electronic device 100 can determine the network search parameters for the candidate airport corresponding to the first country code and perform a network search based on these parameters, obtaining the corresponding network search results (also called network search information). Then, electronic device 100 can determine the first network that can be accessed / stayed on based on this network search information and access / stay on the first network. The first time interval can be a relatively small value, between a first time interval and a second time interval. In this way, in an air travel scenario, electronic device 100 accurately predicts the aircraft's imminent landing shortly before landing and specifically searches for the network of the airport at its location when the aircraft is about to land, thereby accurately accessing a reliable network at its location. This effectively reduces the network access time required by electronic device 100 in air travel scenarios, ensuring that electronic device 100 can quickly access the network and greatly improving the user experience.

[0099] In one possible implementation, the electronic device 100 can combine acceleration data and gyroscope data to identify / predict / detect an aircraft about to land. The acceleration data and gyroscope data can be acquired using conventional acceleration sensors and gyroscope sensors, rather than using unconventional barometric pressure sensors, thus broadening the application scenarios.

[0100] In one possible implementation, the electronic device 100 can not only recognize / predict / detect the scenario of an aircraft about to land, but also the scenario of an aircraft taking off (e.g. Figure 1 The aircraft takeoff phase shown), aircraft cruise scenario (e.g.) Figure 1 The aircraft cruise phase shown), aircraft landing scenario (e.g.) Figure 1 The aircraft begins its descent phase, and the aircraft lands (e.g., the landing phase). Figure 1 The identification / prediction / detection of one or more scenarios during the aircraft landing phase (as shown). The identification / prediction / detection of any of the above scenarios can be achieved through a sensor module of the electronic device 100, for example, by combining an accelerometer and a gyroscope sensor.

[0101] In this application embodiment, air travel scenarios may include, but are not limited to: domestic to overseas, overseas to domestic, domestic to domestic (e.g., from domestic city A to domestic city B), and overseas to overseas (e.g., from overseas country C to overseas country D, or from overseas country C city E to overseas country C city F). It is understood that "domestic" or "overseas" is relative, and "domestic" and "overseas" refer to different countries.

[0102] Figure 2 This is a schematic diagram of the architecture of a communication system 10 provided in an embodiment of this application.

[0103] like Figure 2 As shown, the communication system 10 may include an electronic device 100 and a cloud server 200. In one possible implementation, the cloud server 200 may include at least one server; for example, the cloud server 200 may be a server cluster consisting of multiple servers. Any one of these servers may be a hardware server or a cloud server, such as a web server, backend server, application server, download server, etc.

[0104] In one possible implementation, electronic device 100 can download a search list from cloud server 200. The search list can be used by electronic device 100 to search for networks during air travel. The search list can be determined by cloud server 200 based on crowdsourced data received from multiple devices. The search list may include one or more country codes (e.g., global country codes), and search parameters corresponding to each country code. The search parameters corresponding to each country code may include search parameters for one or more airports corresponding to that country code (which can be simply referred to as candidate airports corresponding to that country code), where an airport corresponding to a country code is the airport of the country to which that country code belongs. Furthermore, the search parameters corresponding to each country code may also include search parameters for candidate networks corresponding to that country code (i.e., candidate networks of the country to which that country code belongs), and so on. In some examples, candidate airports may include airports with high passenger traffic as determined by cloud server 200 or electronic device, but this is not limited to these. In other examples, candidate airports may also include large-scale airports as determined by cloud server 200 or electronic device, or airports of high importance as determined by cloud server 200 or electronic device. This application embodiment does not limit the candidate airports. In some examples, candidate networks may include networks with good network quality as determined by cloud server 200 or electronic device, but this is not limited to these. In other examples, candidate networks may also include networks with high user frequency as determined by cloud server 200 or electronic device 100. This application embodiment does not limit the candidate networks.

[0105] In this application embodiment, the network search parameters may include, but are not limited to, one or more of the following: public land mobile network (PLMN), radio access technology (RAT), band, and frequency (freq). For example, network search parameters include PLMN and frequency.

[0106] The PLMN can be composed of a mobile network code (MNC) and a mobile country code (MCC), which can be used to identify and select operator networks. The RAT can be used to determine the type of communication technology (also known as network standard) used by the electronic device 100, such as second-generation (2G), third-generation (3G), fourth-generation (4G), fifth-generation (5G), and sixth-generation (6G). A band refers to a specific frequency range; different bands can be used to select different communication technologies and regions. A frequency point refers to a specific frequency value, which can be used to determine the specific frequency at which the electronic device 100 communicates with network equipment such as base stations. For example, the network search parameters of a network can include the network's PLMN, one or more RATs of the network, and the frequency bands and / or frequency points under one or more RATs.

[0107] In one possible implementation, cloud server 200 can receive network information from multiple electronic devices accessing the network, and clean and process this network information to generate or update a list of networks available for service use. For example, when authorized by a user to report network information, electronic device 100 can send its network access information to cloud server 200 after accessing the network in an air travel scenario, so that cloud server 200 can generate or update the network search list based on this network information. In some examples, cloud server 200 can update the network search list periodically, for example, once every three months.

[0108] The network information may include, but is not limited to, one or more of the following: the country code corresponding to the access network, the PLMN corresponding to the access network, the PLMN registration information corresponding to the access network, the network standard (RAT), the frequency band of the access network, the frequency point of the access network, the cell identifier corresponding to the access network, the location information corresponding to the access network, and the service experience information of the access network. PLMN registration information includes, but is not limited to, the registration success rate and registration latency of the PLMN corresponding to the access network. Location information corresponding to the access network includes, for example, the location information of the electronic device triggering access and maintaining access to the access network; in the context of air travel, location information may include the airport location. Service experience information includes, but is not limited to, call connection rate, call drop rate, data service lag rate, average latency, reference signal received power (RSRP), received signal strength indicator (RSSI), reference signal received quality (RSRQ), signal-to-noise ratio, and quality of experience (QoE), etc.

[0109] In one possible implementation, the communication system 10 may further include a network. In an air travel scenario, as a user carrying electronic device 100 travels by plane from their departure point to their destination, the electronic device 100 can scan a country code when it detects that the aircraft is about to land (e.g., specifically, when it detects that the aircraft will land after a certain time interval). If a first country code is detected, the electronic device 100 can perform a network search based on the network search parameters of the candidate airports corresponding to the first country code, and obtain the corresponding network search information. Based on the obtained network search information, the electronic device 100 can determine a target network that can be accessed / hosted (e.g., a network with good signal quality in the airport where the electronic device 100 is located), and access / host that target network.

[0110] The following is an exemplary description of the electronic device 100 provided in an embodiment of this application.

[0111] It should be understood that the electronic device 100 illustrated in the embodiments of this application is merely an example, and the electronic device 100 may have more or fewer components than those illustrated in the embodiments of this application, may combine two or more components, or may have different component configurations. The various components shown in the figures may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and / or application-specific integrated circuits.

[0112] Figure 3This is a schematic diagram of the hardware structure of an electronic device 100 provided in an embodiment of this application.

[0113] like Figure 3 As shown, the electronic device 100 may include a processor 110, internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, antenna 1, antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a microphone 170B, a sensor module 180, buttons 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, a barometric pressure sensor 180C, a magnetic sensor 180D, an accelerometer sensor 180E, a distance sensor 180F, a proximity sensor 180G, a fingerprint sensor 180H, a humidity sensor 180I, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a heart rate sensor 180M, and an electrocardiogram sensor 180N, etc.

[0114] Processor 110 may include one or more processing units, such as: application processor (AP), microcontroller unit (MCU), modem processor, graphics processing unit (GPU), image signal processor (ISP), controller, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors. For example, the application processor may include a graphics processor and a digital signal processor, and the microcontroller unit may include a graphics processor.

[0115] The controller can generate operation control signals based on the instruction opcode and timing signals to complete the control of instruction fetching and execution.

[0116] 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.

[0117] In some embodiments, the processor 110 may include one or more interfaces. Interfaces may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0118] Internal memory 121 may include one or more random access memory (RAM) and one or more non-volatile memory (NVM). The RAM can be directly read and written by the processor 110 and can be used to store executable programs (e.g., machine instructions) of the operating system or other running programs, as well as user and application data. The NVM can also store executable programs and user and application data, and can be pre-loaded into the RAM for direct read and write operations by the processor 110.

[0119] The charging management module 140 receives charging input from the charger. While charging the battery 142, the charging management module 140 can also supply power to the electronic device 100 through the power management module 141.

[0120] The power management module 141 connects the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, and supplies power to the processor 110, internal memory 121, display screen 194, wireless communication module 160, and sensor module 180, etc. In some other embodiments, the power management module 141 may also be located within the processor 110. In still other embodiments, the power management module 141 and the charging management module 140 may be located in the same device.

[0121] The wireless communication function of electronic device 100 can be realized through antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor and baseband processor, etc.

[0122] 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 tuning switches.

[0123] The mobile communication module 150 can provide solutions for wireless communication, including 2G / 3G / 4G / 5G / 6G, applied to the electronic device 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves via antenna 1, and perform filtering, amplification, and other processing on the received electromagnetic waves before transmitting them to a modem processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modem processor and convert it into electromagnetic waves for radiation via antenna 1. In some embodiments, at least some functional modules of the mobile communication module 150 may be housed in the processor 110. In some embodiments, at least some functional modules of the mobile communication module 150 and at least some modules of the processor 110 may be housed in the same device.

[0124] The modem processor may include a modulator and a demodulator. The modulator modulates the low-frequency baseband signal to be transmitted into a mid-to-high frequency signal. The demodulator demodulates the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After processing by the baseband processor, the low-frequency baseband signal is transmitted to an application processor or microcontroller unit. The application processor or microcontroller unit outputs sound signals through an audio device (not limited to speaker 170A, microphone 170B, etc.) or displays images or videos through a display screen 194. In some embodiments, the modem processor may be a separate device. In other embodiments, the modem processor may be independent of the processor 110 and housed within the same device as the mobile communication module 150 or other functional modules.

[0125] The wireless communication module 160 can provide solutions for wireless communication applications on the electronic device 100, including wireless local area networks (WLANs) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), Sparklink Alliance-specific wireless communication technologies (such as Sparklink Low Energy (SLE) and Sparklink Basic (SLB)), and intrabody communication (IBC). The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via antenna 2, performs frequency modulation and filtering of the electromagnetic wave signals, and sends the processed signal to processor 110. The wireless communication module 160 can also receive signals to be transmitted from processor 110, perform frequency modulation and amplification, and convert them into electromagnetic waves for radiation via antenna 2.

[0126] In some embodiments, antenna 1 of electronic device 100 is coupled to mobile communication module 150, and antenna 2 is coupled to wireless communication module 160, enabling electronic device 100 to communicate with networks and other devices via wireless communication technology. The wireless communication technology may include Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Time-Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), BT, GNSS, WLAN, NFC, FM, IR, Starflash, and / or IBC technology, etc. The GNSS may include the Global Positioning System (GPS), the Global Navigation Satellite System (GLONASS), the BeiDou Navigation Satellite System (BDS), the Quasi-Zenith Satellite System (QZSS), and / or satellite-based augmentation systems (SBAS).

[0127] Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel may be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a miniature LED, a microLED, a quantum dot light-emitting diode (QLED), etc. In some embodiments, electronic device 100 may include one or N displays 194, where N is a positive integer greater than 1.

[0128] Electronic device 100 can perform shooting functions through ISP, camera 193, video codec, GPU, display 194 and application processor.

[0129] 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 also 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.

[0130] 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 image signals in standard RGB, YUV, or other formats. In some embodiments, the electronic device 100 may include one or N cameras 193, where N is a positive integer greater than 1.

[0131] A digital signal processor is used to process digital signals.

[0132] Video codecs are used to compress or decompress digital video.

[0133] An NPU (Neural Processing Unit) is a computational processor for neural networks (NNs). By borrowing the structure of biological neural networks, such as the transmission patterns between neurons in the human brain, it can rapidly process input information and continuously learn on its own. NPUs enable intelligent cognitive applications in electronic devices, such as image recognition, facial recognition, speech recognition, and text understanding.

[0134] Electronic device 100 can implement audio functions such as music playback and recording through audio module 170, speaker 170A, microphone 170B, and processor 110.

[0135] The audio module 170 is used to convert digital audio information into analog audio signals for output, and also to convert analog audio input into digital audio signals. The audio module 170 can also be used for encoding and decoding audio signals. In some embodiments, the audio module 170 may be located in the processor 110, or some functional modules of the audio module 170 may be located in the processor 110.

[0136] The speaker 170A, also known as a "loudspeaker," is used to convert audio electrical signals into sound signals. The electronic device 100 can listen to music or make hands-free calls through the speaker 170A.

[0137] Microphone 170B, also known as a "microphone" or "voice transducer," is used to convert sound signals into electrical signals. When making a phone call or sending a voice message, the user can speak by bringing their mouth close to microphone 170B, inputting the sound signal into microphone 170B. Electronic device 100 may be equipped with at least one microphone 170B.

[0138] Pressure sensor 180A is used to sense pressure signals and convert them into electrical signals. In some embodiments, pressure sensor 180A may be disposed on display screen 194. There are many types of pressure sensors 180A, such as resistive pressure sensors, inductive pressure sensors, and capacitive pressure sensors. A capacitive pressure sensor may include at least two parallel plates with conductive material. When a force is applied to pressure sensor 180A, the capacitance between the electrodes changes. Electronic device 100 determines the pressure intensity based on the change in capacitance. When a touch operation is applied to display screen 194, electronic device 100 detects the intensity of the touch operation based on pressure sensor 180A. Electronic device 100 may also calculate the touch position based on the detection signal from pressure sensor 180A.

[0139] The gyroscope sensor 180B can be used to detect gyroscope data (e.g., but not limited to angular velocity data) of the electronic device 100 in various directions (generally three axes, namely x, y, and z axes). For example, the gyroscope sensor 180B can be used to identify the attitude of the electronic device, for image stabilization, navigation, motion-sensing gaming scenarios, and air travel scenarios.

[0140] Accelerometer 180E can be used to detect acceleration data of electronic device 100 in various directions (generally three axes, namely x, y, and z axes). For example, accelerometer 180E can be used to identify the attitude of electronic device, screen orientation switching, pedometer, and air travel scenarios.

[0141] In one possible implementation, the electronic device 100 can identify one or more of the following aircraft scenarios based on the gyroscope data of the electronic device 100 obtained by the gyroscope sensor 180B and / or the acceleration data of the electronic device 100 obtained by the accelerometer sensor 180E: aircraft takeoff scenario, aircraft cruise scenario, aircraft beginning to land scenario, aircraft about to land scenario, and aircraft landing scenario.

[0142] Not limited to Figure 3 In some other examples, the gyroscope sensor 180B and the accelerometer sensor 180E can also be integrated into the structure shown, and the resulting module can be called an inertial sensor.

[0143] Understandably, the acceleration data and gyroscope data acquired by the sensor module can be from various directions. For ease of description, we will take a three-axis (x-axis, y-axis and z-axis) approach as an example. The z-axis can be assumed to be the axis of gravity, and the x-axis and y-axis can be assumed to be the horizontal axes.

[0144] The barometric pressure sensor 180C is used to measure air pressure. In some embodiments, the electronic device 100 calculates altitude using the air pressure value measured by the barometric pressure sensor 180C, assisting in positioning, navigation, and air travel scenarios. The barometric pressure sensor 180C can also be referred to as an altitude sensor. The electronic device 100 in this embodiment may not include the barometric pressure sensor 180C.

[0145] Touch sensor 180K, also known as a "touch device," can be located on display screen 194. The touch sensor 180K and display screen 194 together form a touchscreen, also known as a "touchscreen." Touch sensor 180K detects touch operations applied to or near it. The touch sensor can transmit the detected touch operation to processor 110 (such as an application processor or microcontroller unit) 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 located on the surface of electronic device 100, in a different position than display screen 194.

[0146] Buttons 190 include a power button, volume buttons, etc. Buttons 190 can be mechanical buttons or touch-sensitive buttons. Electronic device 100 can receive button input and generate key signal inputs related to user settings and function control of electronic device 100.

[0147] The SIM card interface 195 is used to connect a SIM card. The SIM card can be inserted into or removed from the SIM card interface 195 to achieve contact and separation with the electronic device 100. In some embodiments, the electronic device 100 uses an eSIM, i.e., an embedded SIM card. The eSIM card can be embedded in the electronic device 100 and cannot be separated from it.

[0148] The electronic device 100 provided in this application embodiment can run an operating system (OS). This operating system can be various operating systems used in industry, such as operating systems developed based on OpenHarmony, like HarmonyOS; or other operating systems such as Android™, iOS mobile operating systems; it can also be various open-source operating systems or their derivatives, such as Linux OS, and other embedded operating systems; or it can be a future new operating system, such as an AI operating system based on artificial intelligence. An operating system is a set of interconnected system software programs that manage and control the operation of electronic devices, utilize and run hardware and software resources, and provide public services to organize user interaction. In the electronic device 100, the operating system connects downwards to the physical devices at the hardware layer and provides a runtime environment for application software upwards.

[0149] An operating system typically includes a kernel layer, a middleware layer, and an application layer. The application layer includes applications, which can include system applications and third-party applications. The middleware layer includes a suite of software providing various services to application developers, or frameworks providing services such as databases, multimedia, and graphics, or capabilities such as distributed scheduling and system scaling. For example, the middleware layer may include a framework layer and / or a system service layer. The framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer. The system service layer includes the system's core capabilities, providing services to applications through the framework layer. The kernel layer is the layer between hardware and software. The kernel layer may include hardware drivers and the operating system kernel. In addition to providing hardware drivers, the kernel layer also supports functions such as memory management and system process management.

[0150] The electronic devices we use in our daily lives come in various types and forms, and are applied in a wide range of scenarios. Therefore, based on the different forms and functions of electronic devices, different application scenarios, and different user needs, the operating systems used in these devices may also differ. The basic functions implemented by the electronic device 100 provided in this application can be implemented using a general-purpose operating system or a dedicated operating system. To more clearly illustrate the implementation of the embodiments of this application under a specific operating system, the architecture of HarmonyOS is shown below. Those skilled in the art can deduce the implementation of the embodiments of this application under other specific operating systems, such as Android™.

[0151] Figure 4 This is a schematic diagram of the software architecture of an electronic device 100 provided in an embodiment of this application.

[0152] like Figure 4 As shown, the software architecture of electronic device 100 can be divided into several layers. In some embodiments, from bottom to top, these layers are: kernel layer, system service layer, framework layer, and application layer. Layers communicate with each other through software interfaces. System functions can be tailored, added, or combined at the subsystem granularity in different device deployment scenarios, and each subsystem can also be tailored, added, or combined at the functional granularity.

[0153] The kernel layer can include: Kernel Abstract Layer (KAL), kernel subsystem, driver subsystem, etc.

[0154] Kernel Abstraction Layer: By shielding the differences between multiple kernels, it provides basic kernel capabilities to the upper layers, including but not limited to process / thread management, memory management, file system, network management, and peripheral device management.

[0155] Kernel Subsystem: Supports the selection of a suitable OS kernel for different resource-constrained devices, including but not limited to Linux kernel, HarmonyOS kernel, LiteOS (Lite Operating System), etc.

[0156] Driver Subsystem: The driver framework is the foundation for the open system hardware ecosystem, providing unified peripheral access capabilities and a framework for driver development and management. The driver framework includes: display drivers, camera drivers, audio drivers, Bluetooth drivers, sensor drivers, etc.

[0157] The system service layer may include the core capabilities of the system, providing services to applications through the framework layer. This layer includes, but is not limited to, the following subsystems:

[0158] The system's basic capability subsystem set provides fundamental capabilities for the operation, scheduling, and migration of distributed applications across multiple devices. This set may include distributed soft bus, distributed data management, distributed task scheduling, and Ark multi-language runtime; it may also include multi-modal input subsystem, graphics subsystem, security subsystem, and artificial intelligence (AI) subsystem.

[0159] Basic software service subsystem set: provides public and general software services; the basic software service subsystem set may include event notification subsystem, telephone service subsystem, multimedia subsystem, audio framework system, etc.

[0160] Enhanced software service subsystem suite: Provides differentiated enhanced software services for different devices; the enhanced software service subsystem suite may include smart screen proprietary business subsystem, wearable proprietary business subsystem, IoT proprietary business subsystem, etc.

[0161] Hardware service subsystem set: Provides hardware services; the hardware service subsystem set may include location service subsystem, user IAM (identity and access management) subsystem, wearable proprietary hardware service subsystem, biometric identification, IoT proprietary hardware service subsystem, etc.

[0162] Distributed task scheduling enables distributed service management (discovery, synchronization, registration, and invocation), supporting remote startup, remote invocation, remote connection, and migration of applications across devices.

[0163] Distributed data management enables data synchronization, data storage, data sharing, and data access across all scenarios and devices.

[0164] The distributed soft bus provides communication-related capabilities for seamless interconnection between multiple devices, including: WLAN service capabilities, Bluetooth service capabilities, soft bus, inter-process communication RPC (Remote Procedure Call), and StarFlash communication capabilities.

[0165] Ark Multilingual Runtime is a unified compilation runtime platform designed to support the joint compilation and execution of multiple programming languages ​​and multiple chip platforms.

[0166] The framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer. The framework layer includes: the ArkUI framework (which provides a complete infrastructure for UI development of system applications, including UI functions such as components, layouts, animations, and interactive events, as well as a real-time interface preview tool), the user application framework, and the Ability framework (an Ability is a lightweight application; the Ability framework schedules and manages the operation and lifecycle of Abilities). Different devices may have different operating systems, and therefore support different APIs.

[0167] The HarmonyOS API is a series of open capabilities provided to support HarmonyOS application development. The HarmonyOS API can be set at the framework layer or independently of the framework layer. The HarmonyOS API includes the Audio API (audio service), Push API (push service), and Account API (account service), among others.

[0168] Applications can include system applications (APPs) and extended / third-party apps. System applications can include the desktop, control bar, settings, phone, camera, SMS, etc., while extended / third-party apps can include travel, social networking, etc.

[0169] The cloud server 200 provided in the embodiments of this application will be described below by way of example.

[0170] Figure 5 This is a schematic diagram of the hardware structure of a cloud server 200 provided in an embodiment of this application.

[0171] like Figure 5 As shown, the cloud server 200 may include one or more processors 201, communication interfaces 202, and memory 203. The processors 201, communication interfaces 202, and memory 203 can be connected via a bus or other means. This embodiment of the application takes a connection via bus 204 as an example. Wherein:

[0172] Processor 201 may consist of one or more general-purpose processors, such as a central processing unit (CPU). Processor 201 can be used to run program code related to network access methods, such as generating or updating a network search list based on crowdsourced data (including network information) received from multiple electronic devices.

[0173] The communication interface 202 can be a wired interface (e.g., an Ethernet interface) or a wireless interface (e.g., a cellular network interface or a wireless LAN interface) for communicating with other nodes. In this embodiment, the communication interface 202 can be used to communicate with multiple electronic devices (e.g., including electronic device 100), for example, to receive network information sent by multiple electronic devices, and / or to send a network search list stored by cloud server 200 to one or more electronic devices.

[0174] Memory 203 may include volatile memory, such as random access memory (RAM); memory may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state disk (SSD). Memory 203 may also include combinations of the above types of memory. In this embodiment, memory 203 may also be a storage array, etc. Memory 203 can be used to store a set of program code so that processor 201 can call the program code stored in memory 203 to implement the implementation method of this embodiment on cloud server 200. Memory 203 can also be used to store a search list, optional crowdsourcing data reported by multiple electronic devices (such as network information including network access).

[0175] In one possible implementation, the cloud server 200 may include multiple servers, wherein the hardware structure of any one server can be referred to Figure 5 The hardware structure of the cloud server 200 is shown.

[0176] Understandably, Figure 5 The cloud server 200 shown is one implementation of an example embodiment of this application. In actual applications, the cloud server 200 may include more or fewer components, and this application does not impose any restrictions on this.

[0177] The network access method provided in the embodiments of this application is described below by way of example.

[0178] Figure 6 This is a flowchart illustrating a network access method provided in an embodiment of this application. Figure 6 The method shown can be applied to Figure 2 The communication system 10 shown. Figure 6 The electronic device 100 in the method shown can be Figure 3 The electronic device 100 shown. Figure 6 The electronic device 100 in the method shown can also be Figure 4 The electronic device 100 shown. Figure 6 The cloud server 200 in the method shown can be Figure 5 The cloud server shown is 200.

[0179] Figure 6 The method shown may include, but is not limited to, the following steps:

[0180] S101: The cloud server 200 sends a search list to the electronic device 100, wherein the search list includes one or more country codes and search parameters for candidate airports corresponding to each country code.

[0181] In one possible implementation, the search list may include one or more country codes, and search parameters for candidate airports (one or more airports) corresponding to each of these country codes. These search parameters may include, but are not limited to, one or more of the following: PLMN, RAT, frequency band, or frequency point.

[0182] In one possible implementation, in the search list, any country code may correspond to search parameters for one or more candidate airports, and the search parameters for a candidate airport may include search parameters for one or more networks within that candidate airport. Optionally, in the search list, when any country code corresponds to search parameters for multiple candidate airports, these search parameters may have a priority order, which can be used by the electronic device to search for the search parameters of these multiple candidate airports according to this priority order during network search. Optionally, in the search list, when any candidate airport for any country code includes search parameters for multiple networks within that candidate airport, these networks may have a priority order, which can be used by the electronic device to search for the search parameters of these multiple networks according to this priority order during network search.

[0183] In some examples, the candidate airports mentioned above may include airports with large passenger flow as determined by the cloud server 200 or electronic devices. However, this is not the only one. In other examples, the candidate airports may also include airports of a large scale as determined by the cloud server 200 or electronic devices. In still other examples, the candidate airports may also include airports of high importance as determined by the cloud server 200 or electronic devices. This application does not limit the candidate airports.

[0184] In one possible implementation, the search list may be generated and maintained by a cloud server 200 based on crowdsourced data sent by multiple electronic devices. The crowdsourced data may include, but is not limited to, network information of the network accessed by the electronic devices; a specific example can be found in the network information of the first network in S108 below.

[0185] In one possible implementation, the cloud server 200 can periodically send a search list to the electronic device 100, for example, once a month. In some examples, the electronic device 100 can send a download request to the cloud server 200 according to a preset download cycle. After receiving the download request, the cloud server 200 can send the search list maintained by the cloud server 200 to the electronic device 100. Optionally, the preset download cycle is configurable.

[0186] In one possible implementation, the electronic device 100 can also download a search list from the cloud server 200 when preset download conditions are met. Preset download conditions include, but are not limited to, one or more of the following: being in an environment suitable for downloading the search list, determining that it will enter an air travel scenario in the future, and detecting a trigger condition for obtaining target search parameters. For example, the target search parameters can be search parameters for candidate airports corresponding to the target country code, or search parameters for the target airport itself. The aforementioned environment suitable for downloading the search list includes, but is not limited to, being in a locked or off state and connected to a Wi-Fi network. In some examples, when the electronic device 100 obtains flight information, if the current time is close to the departure time of the flight (e.g., one day apart), the electronic device 100 can determine that it will enter an air travel scenario in the future. In other examples, the electronic device 100 determines that it will enter an air travel scenario in the future when it enters an airport fence.

[0187] In one possible implementation, the search list sent by the cloud server 200 to the electronic device 100 may include global country codes and corresponding search parameters for candidate airports. In another possible implementation, the electronic device 100 may request a target country code from the cloud server 200; therefore, in S101, the cloud server 200 may send the target country code and corresponding search parameters for candidate airports to the electronic device 100 according to the request. In yet another possible implementation, the electronic device 100 may request search parameters for target airports from the cloud server 200; therefore, in S101, the cloud server 200 may send search parameters for target airports to the electronic device 100 according to the request.

[0188] For example, such as Figure 7 The communication system 10 shown includes a cloud server 200 that can maintain a web search list database, which is used to store web search lists. The electronic device 100 may include an application processor (AP) and a modem. An example of S101 can be found... Figure 7 Step 1 is shown. As shown in Step 1, the search list download module in the AP of electronic device 100 can download the search list from the cloud server 200. The cloud server 200 can obtain the search list from the search list database and send it to the search list download module in the AP of electronic device 100.

[0189] The network search list received by electronic device 100 from cloud server 200 in S101 can be used by electronic device 100 to search for networks in the context of air travel, so as to quickly return to the network. For specific examples, please refer to S104-S107 below.

[0190] S102: Electronic device 100 detected an aircraft takeoff scenario.

[0191] S102 is an optional step. In some examples, the electronic device 100 is powered off before the aircraft takes off, so S102 is not executed.

[0192] In one possible implementation, based on an aircraft takeoff detection algorithm, the electronic device 100 can collect data (such as acceleration data and gyroscope data) through a sensor module and detect whether it is in an aircraft takeoff scenario based on the collected data.

[0193] In one possible implementation, the aircraft takeoff detection algorithm may include the following steps: Electronic device 100 first collects acceleration data 1 via a sensor module and detects whether the aircraft is in a taxiing state based on the acceleration data 1. If the aircraft is in a taxiing state, electronic device 100 then collects acceleration data 2 and gyroscope data 1 via the sensor module and detects whether the aircraft is in a climb state based on the acceleration data 2 and gyroscope data 1 (optionally, plus acceleration data 1). If the aircraft is in a climb state, electronic device 100 detects an aircraft takeoff scenario. Specifically, if electronic device 100 determines that the aircraft is in a takeoff scenario after first being in a taxiing state and then in a climb state, it can determine that the aircraft is in a takeoff scenario. A specific implementation example of the aircraft takeoff detection algorithm can be found below. Figure 9 Details will not be elaborated here.

[0194] S103: Electronic device 100 detected an aircraft cruise scenario.

[0195] S103 is an optional step. In some examples, electronic device 100 is powered off before the aircraft cruises (such as before takeoff), so S103 is not executed.

[0196] In one possible implementation, based on an aircraft cruise detection algorithm, the electronic device 100 can collect data (such as acceleration data and gyroscope data) through a sensor module and detect whether it is in an aircraft cruise scenario based on the collected data.

[0197] In one possible implementation, the aircraft cruise detection algorithm may include the following steps: After detecting an aircraft takeoff scenario (i.e., after S102), the electronic device 100 may determine whether a preset waiting condition is met. This waiting condition includes: the aircraft is in a stable state (e.g., determined based on data collected by the sensor module), and / or the elapsed time after detecting the aircraft takeoff scenario is greater than or equal to a preset time threshold. If the waiting condition is met, the electronic device 100 may collect acceleration data 3 through the sensor module within a first time window and determine the range of the magnitude of the acceleration data 3. The electronic device 100 may determine whether the range of the magnitude of the acceleration data 3 is less than a preset range threshold. If the range of the magnitude of the acceleration data 3 is less than the preset range threshold, the electronic device 100 detects an aircraft cruise scenario. A specific implementation example of the aircraft cruise detection algorithm can be found below. Figure 10 Details will not be elaborated here.

[0198] S104: Electronic device 100 detects an imminent landing scenario for the aircraft, predicting that the aircraft will land after a first duration.

[0199] In one possible implementation, based on an algorithm for detecting an aircraft's imminent landing, the electronic device 100 can collect data (e.g., acceleration data and gyroscope data) through sensor modules and detect whether it is in an aircraft imminent landing scenario based on the collected data. When the electronic device 100 detects that it is in an aircraft imminent landing scenario, it can predict that the aircraft will land after a first duration, that is, predict that the time from the current time to the aircraft's landing is the first duration, which can also be understood as predicting the time of the aircraft's landing (i.e., the time after the current time has elapsed for the first duration).

[0200] In one possible implementation, the process of the aircraft imminent landing detection algorithm may include: the electronic device 100 can collect acceleration data 4 and gyroscope data 2 through a sensor module, and determine corresponding flight characteristic data based on the acceleration data 4 and gyroscope data 2. The flight characteristic data includes one or more of the following: aircraft turning information, aircraft weightlessness information, data obtained by statistically analyzing and / or calculating the acceleration data 4, and data obtained by statistically analyzing and / or calculating the gyroscope data 2. Specific examples can be found below. Figure 11 An example of flight feature data obtained by the feature extraction module 1030. Then, the electronic device 100 can input the aircraft feature data into the landing prediction model and obtain the prediction result output by the landing prediction model. The prediction result output by the landing prediction model can indicate whether the aircraft is in a landing scenario, for example, the prediction result output by the landing prediction model indicates that the aircraft is in a landing scenario (including the aircraft landing after a first duration). Optionally, the electronic device 100 can also correct the prediction result output by the landing prediction model based on aircraft shaking conditions. The corrected prediction result can indicate whether the aircraft is in a landing scenario, where aircraft shaking conditions can be obtained based on data collected by sensor modules (e.g., acceleration data and gyroscope data). In some examples, the uncorrected prediction result indicates that the aircraft is in a landing scenario (including the aircraft landing after duration t1, where t1 is a positive number), while the corrected prediction result indicates that the aircraft is not in a landing scenario. In other examples, the uncorrected prediction indicates an imminent landing scenario (including landing after duration t1, where t1 is a positive number). The electronic device 100 can correct t1 to t2 based on aircraft jitter. Therefore, the corrected prediction indicates an imminent landing scenario (including landing after duration t2, where t2 is a positive number). Understandably, when the electronic device 100 does not correct the prediction output of the landing prediction model, the first duration is the imminent landing duration t1 in the prediction output of the landing prediction model. When the electronic device 100 corrects the prediction output of the landing prediction model, the first duration is the imminent landing duration t2 in the corrected prediction. A specific implementation example of the aircraft imminent landing detection algorithm can be found below. Figure 11 , Figure 12A and Figure 12B Details will not be elaborated here.

[0201] In one possible implementation, after executing S102 and / or S103, the electronic device 100 can predict the landing time of the aircraft in response to the detected aircraft takeoff scenario and / or aircraft cruise scenario, i.e., S102 and / or S103 can trigger the detection of whether the aircraft is about to land.

[0202] S105: Electronic device 100 scans the country code and obtains the first country code.

[0203] In one possible implementation, when an aircraft is detected to be about to land (including a prediction that the aircraft will land after a first duration), the electronic device 100 can scan the country code and obtain the first country code.

[0204] In one possible implementation, if the electronic device 100 fails to scan the country code, it can try scanning again after a certain period of time (e.g., 1 minute) to avoid the electronic device 100 mistakenly believing that it cannot scan the country code when the aircraft is at high altitude and there is no cellular signal, which may cause a short-term failure to scan the country code.

[0205] In one possible implementation, the electronic device 100 can scan for the country code within a preset frequency band. That is, the electronic device 100 can scan the preset frequency band to obtain system messages and parse the system messages to obtain the first country code. This can be understood as scanning the country code by scanning the preset frequency band. In some examples, the preset frequency band can be a "golden" frequency band determined by the electronic device 100, i.e., a frequency band with good propagation characteristics, wide coverage, and strong penetration. However, this is not a limitation; the electronic device 100 may also scan for the country code without using a preset frequency band. This application does not limit the specific method of scanning the country code in its embodiments.

[0206] For example, such as Figure 7 The communication system 10 shown includes an application processor (AP) for electronic device 100, which includes an aircraft scene recognition module. The modem for electronic device 100 includes a country code scanning module and a network search module. Examples of S102-S105 can be found in [reference needed]. Figure 7Steps 2-3 are shown. The aircraft scene recognition module in the AP of electronic device 100 can execute S104 (optionally, as well as S102 and / or S103), as shown in step 2, when the aircraft scene recognition module detects an aircraft about to land, it triggers a country code scanning module in the modem to scan the country code. Therefore, the country code scanning module in the modem can execute S105. Then, as shown in step 3, the country code scanning module can send the scanned first country code to the network search module in the modem, so that the network search module can perform a network search based on the first country code.

[0207] S106: Electronic device 100 performs a network search based on the network search parameters of the candidate airports corresponding to the first country code and obtains the first network search information.

[0208] S107: Electronic device 100 accesses the first network based on the first search network information.

[0209] In one possible implementation, the network search parameters for the candidate airport corresponding to the first country code in S106 can be understood as preferred network search parameters. In some examples, the candidate airport corresponding to the first country code in S106 can be a preferred airport. For example, the candidate airport can be an airport with high passenger flow, a large scale, or a high level of importance, as determined by the cloud server 200 or electronic device 100. In some examples, the network search parameters for the candidate airport corresponding to the first country code in S106 can be the network search parameters of a preferred network among the candidate airports corresponding to the first country code. For example, the preferred network can be a network with good network quality or a network with high user frequency. This application embodiment does not limit the preferred network search parameters.

[0210] In one possible implementation, the first network search information may include whether a network corresponding to the search parameters was found, optional information such as the order in which networks were found, and signal quality information of the found networks. After obtaining the first network search information, the electronic device 100 can determine the target network (i.e., the first network) to access / stay based on the first network search information and access the first network. In some examples, if the first network search information indicates that only one first network was found, the electronic device 100 can determine to access the first network. In other examples, if the first network search information indicates that multiple networks were found, the electronic device 100 can determine the network found first and / or the network with better signal quality as the target network based on the first network search information. Not limited thereto, in specific implementations, the first network search information may include more or less content, and this application embodiment does not limit the specific content included in the first network search information. In specific implementations, the electronic device 100 may also determine the target network to access / stay based on the device's own situation (e.g., the operator information of the configured SIM card / eSIM module), the current scenario, etc., and this application embodiment does not limit the specific implementation method for determining the target network to access / stay.

[0211] In one possible implementation, after S104 and before S106, electronic device 100 may perform one or more network searches and obtain second network search information (at this time, the flight mode of electronic device 100 may be on or off), but it is not registered on the network. Then, electronic device 100 can refer to the second network search information and perform network search and registration in S106-S107. For example, if the flight mode of electronic device 100 is on, and electronic device 100 detects an aircraft landing scenario in S104, electronic device 100 can execute S105 and perform a network search based on the first country code to obtain second network search information. Subsequently, if the flight mode of electronic device 100 is turned off, electronic device 100 can refer to the second network search information and perform network search and registration in S106-S107.

[0212] In one possible implementation, in S106, the electronic device 100 can perform network search not only based on the network search parameters of the candidate airports corresponding to the first country code, but also based on other network search parameters. For example, after S104 and before S106, the electronic device 100 performs network search based on the first country code and obtains second network search information. In S106, the electronic device 100 can perform network search based on the network search parameters of the candidate airports corresponding to the first country code, and also perform network search based on the second network search information (such as searching for networks in the second network search information).

[0213] In one possible implementation, when the electronic device 100 is powered on and its flight mode is off, if the electronic device 100 detects an imminent aircraft landing scenario (i.e., executes S104), it can execute S105. After scanning the first country code in S105, it executes S106-S107. For example, in... Figure 1 The phases from the aircraft's imminent landing phase (during which electronic device 100 executes S104) to the aircraft's landing phase are executed from S105 to S107. For example, electronic device 100 executes S106 immediately after executing S105. It is understandable that S105 is generally executed very quickly, so it can be understood that S106 is executed when the aircraft's imminent landing scenario is detected. Since the time between detecting the aircraft's imminent landing scenario and the aircraft completing its landing requires a certain amount of time, S106 may need to be executed for a certain period of time to obtain valid first search network information. When executing S106, electronic device 100 can perform a search network at intervals (e.g., periodic search network) until valid first search network information is obtained, and then execute S107.

[0214] In another possible implementation, when the electronic device 100 is powered on and its flight mode is enabled, and the electronic device 100 detects an imminent aircraft landing scenario (i.e., executes S104), it can execute S105. Optionally, after scanning the first country code in S105, a network search can be performed based on the first country code to obtain second network search information. For example, a network search can be performed based on the network search parameters of the candidate airports corresponding to the first country code (specific examples are similar to those in S106), and / or, a network search can be performed based on the first network search parameters obtained when scanning the country code in S105, etc. Subsequently, the electronic device 100 turns off its flight mode, and the electronic device 100 can execute S106-S107. Optionally, S106-S107 can be executed with reference to the second network search information. For example, in S106, the network in the second network search information can be searched again, and / or, a network search can be performed based on the first network search parameters. For example, in Figure 1 The aircraft is about to land (electronic equipment 100 performs S104 during this phase) and between the aircraft landing phase and S105, S105 is performed, optionally performing a search and obtaining second search information. Figure 1 During the aircraft landing phase, electronic device 100 deactivates flight mode, allowing S106-S107 to be executed. For example, since electronic device 100 scans the country code and obtains the second network information before deactivating flight mode, S106-S107 are executed quickly after deactivating flight mode, and the network in the signal bar of electronic device 100 can be restored quickly, thus providing users with a good experience of rapid network restoration after deactivating flight mode.

[0215] In one possible implementation, when the electronic device 100 performs a network search in S106, it can search multiple networks at a time and obtain search results for multiple networks. Then, it parses these search results to determine whether to reside in any of these networks. Optionally, if the search results for multiple networks all indicate a failed search, the next search (searching for other networks) is performed. Optionally, if the search results for multiple networks include successfully searched networks, the network to reside in can be determined from these multiple networks. For example, if P networks (where P is a positive integer) have high frequency energy among the search results obtained by the electronic device 100, the target network to reside in can be determined from these P networks. If the target network has a higher priority among these P networks, this priority can be determined based on the priority in the aforementioned search list.

[0216] In another possible implementation, the electronic device 100 can perform network search according to priority order in S106. Optionally, the electronic device 100 can perform network search according to priority order, stopping the search after successfully searching the first H networks with higher priority (H is a positive integer), and no longer searching other lower priority networks. Optionally, this priority order can be determined when the cloud server 200 generates the network search list, or it can be determined by the electronic device 100 itself; this embodiment does not limit this. In some examples, the network search parameters of multiple candidate airports corresponding to the first country code can have a priority order. When the electronic device 100 performs network search based on the network search parameters of multiple candidate airports corresponding to the first country code in S106, it can search the network search parameters of multiple candidate airports sequentially according to this priority order. In some examples, the network search parameters of any candidate airport corresponding to the first country code can include the network search parameters of multiple networks in that candidate airport, and the network search parameters of these multiple networks can have a priority order. When electronic device 100 searches for networks in S106 based on the network search parameters of multiple networks in a candidate airport corresponding to the first country code, it can search for the network search parameters of these multiple networks in order of priority.

[0217] In one possible implementation, before S104 (e.g., before takeoff), electronic device 100 obtains first flight information, which may include a first destination (e.g., country G, location H) and a first landing airport. Based on the first flight information, electronic device 100 can determine the second country code of the first destination and the search parameters of the candidate airports corresponding to the second country code from the search list received in S101. The search parameters of the candidate airports corresponding to the second country code include the search parameters of the first landing airport, and electronic device 100 can determine the search parameters of the first landing airport from the search parameters of the candidate airports corresponding to the second country code. Then, after executing S104-S105, electronic device 100 can determine whether the first country code obtained in S105 is the same as the second country code of the first destination.

[0218] In one scenario, in S106, if the first country code and the second country code are the same, the electronic device 100 may prioritize searching for a network based on the network search parameters of the first landing airport. If searching for a network based on the network search parameters of the first landing airport fails (e.g., no corresponding network can be found within a certain period of time), the electronic device 100 may then search for a network based on the network search parameters of the first candidate airport. The first candidate airport includes one or more other candidate airports (e.g., all other candidate airports) other than the first landing airport among the candidate airports corresponding to the second country code mentioned above.

[0219] For example, electronic device 100 obtains first flight information where the first country code and the second country code are the same. After S104 and before S106, electronic device 100 performs one or more network searches and obtains second network search information, but does not reside on the network. In S106, electronic device 100 may prioritize network search based on the network search parameters of the first landing airport and prioritize searching for networks in the second network search information. Optionally, if network search based on the network search parameters of the first landing airport fails, and searching for networks in the second network search information fails, electronic device 100 may then perform network search based on the network search parameters of the first candidate airport corresponding to the first country code. Not limited to this, in other examples, network search may not be performed based on the network search parameters of the first candidate airport corresponding to the first country code, but rather the country code may be rescanned and network search performed based on the rescanned country code. This application embodiment does not limit this.

[0220] In another scenario, in S106, if the first country code and the second country code are different, the electronic device 100 can determine the search parameters of the candidate airport corresponding to the first country code from the search list received in S101, and perform a search based on the search parameters of the candidate airport corresponding to the first country code. Optionally, if the scanned first country code is different from the second country code of the first destination, the electronic device 100 can rescan the country code after a certain period of time and determine whether the currently scanned country code and the second country code are the same. If they are the same, the search can be performed according to the case where the first country code and the second country code are the same. This can avoid the situation where the country code of the area the aircraft passed through before landing is mistakenly scanned, leading to inaccurate search results.

[0221] In another possible implementation, the electronic device 100 does not obtain flight information. In S106, the electronic device 100 can determine the search parameters of the candidate airport corresponding to the first country code scanned in S105 from the search list received in S101, and perform a search based on the search parameters of the candidate airport corresponding to the first country code.

[0222] For example, electronic device 100 obtains first flight information but the first country code and the second country code are different, or electronic device 100 does not obtain flight information. After S104 and before S106, electronic device 100 performs one or more network searches and obtains second network search information, but does not reside on the network. In S106, electronic device 100 can prioritize searching for networks in the second network search information. Optionally, if searching for networks in the second network search information fails, it then searches for networks based on the network search parameters of the candidate airports corresponding to the first country code. Not limited to this, in some other examples, if searching for networks in the second network search information fails, electronic device 100 can also rescan for country codes and search for networks based on the rescanned country codes. This application embodiment does not limit this.

[0223] In one possible implementation, when the electronic device 100 scans the country code in S105, it can scan the first country code and the corresponding first network search parameters. In S106, the electronic device 100 can perform a network search based on the first network search parameters and the network search parameters of the candidate airports corresponding to the first country code. In some examples, in S106, the electronic device 100 can prioritize performing a network search based on the first network search parameters. If the network search based on the first network search parameters fails (e.g., no corresponding network is found within a certain period of time), then it will perform a network search based on the network search parameters of the candidate airports corresponding to the first country code. However, this is not a limitation. In specific implementations, the priority of performing a network search based on the network search parameters obtained when scanning the country code can be set to be higher, but the actual network search order in S106 is not limited. For example, if electronic device 100 obtains the first flight information, and if the first country code scanned by S105 is the same as the second country code of the first destination, electronic device 100 can prioritize searching the network based on the search parameters of the first landing airport. If searching the network based on the search parameters of the first landing airport fails, it will then search the network based on the first search parameters. If searching the network based on the first search parameters fails, it will then search the network based on the search parameters of the first candidate airport. If electronic device 100 does not obtain flight information, electronic device 100 can prioritize searching the network based on the first search parameters. If searching the network based on the first search parameters fails, it will then search the network based on the search parameters of the candidate airport corresponding to the first country code.

[0224] In one possible implementation, when the electronic device 100 performs a network search in S106, it can perform the network search at certain time intervals. Optionally, the network search time interval is configurable. In some examples, the time interval between any two network searches can be equal, that is, the network search time interval is a fixed value. However, this is not limited to this. In other examples, the network search time interval may not be a fixed value. For example, the time interval for the first X network searches is time interval 1, and the time interval for the subsequent Y network searches is time interval 2. Time interval 1 is greater than time interval 2 (e.g., time interval 1 is 2 minutes, and time interval 2 is 1 minute). X and Y are both positive integers greater than 1, which can be understood as the network search interval being longer at first and then shorter. In specific implementations, more network search time intervals and more configuration methods can be configured. This application embodiment does not limit this.

[0225] In one possible implementation, electronic device 100 determines aircraft landing when it detects that one or more of the following conditions are met: electronic device 100 detects an aircraft landing scenario, the time of electronic device 100 matches the time in flight information, electronic device 100 is powered on (optionally and without network), electronic device 100 disables flight mode (optionally and without network), etc. In some examples, the time matching between electronic device 100 and flight information may include: electronic device 100 determining that the aircraft's departure time matches the departure time in flight information, and / or, electronic device 100 determining that the aircraft's landing time matches the arrival time in flight information. The time matching may be a time difference less than or equal to a certain threshold. Electronic device 100 determining aircraft departure may include, but is not limited to, detecting an aircraft takeoff scenario, electronic device 100 being powered off, and electronic device 100 enabling flight mode. Electronic device 100 determining aircraft landing may include, but is not limited to, detecting an aircraft landing scenario, electronic device 100 being powered on (optionally and without network), and electronic device 100 disabling flight mode (optionally and without network), etc.

[0226] In one possible implementation, the electronic device 100 detects an aircraft landing scenario by: based on an aircraft landing detection algorithm, the electronic device 100 collects data (e.g., acceleration data and gyroscope data) through a sensor module, and detects whether it is in an aircraft landing scenario based on the collected data. In another possible implementation, the implementation process of the aircraft landing detection algorithm may include: the electronic device 100 collects acceleration data 5 and gyroscope data 3 through a sensor module, and detects whether it is in a g-force state (which can be simply referred to as an aircraft g-force state) during aircraft landing based on the acceleration data 5 and gyroscope data 3. If an aircraft g-force state is detected, the electronic device 100 then collects acceleration data 6 and gyroscope data 4 through a sensor module, and detects whether it is in an aircraft touchdown state based on the acceleration data 6 and gyroscope data 4 (optionally, as well as acceleration data 5 and gyroscope data 3). If an aircraft touchdown state is detected, the electronic device 100 detects an aircraft landing scenario. Wherein, if the electronic device 100 determines that it is in an aircraft landing scenario after determining that it is in an aircraft g-force state first and then in an aircraft touchdown state, the electronic device 100 can determine that it is in an aircraft landing scenario. A specific implementation example of the aircraft landing detection algorithm can be found below. Figure 13 Details will not be elaborated here.

[0227] For example, such as Figure 7 The communication system 10 shown, the application processor (AP) of the electronic device 100 can download the network search list from the cloud server 200 in step 1. The modem of the electronic device 100 may include a country code scanning module and a network search module. Figure 7In step 4, the network search list download module in the AP can send the network search parameters of the candidate airports in the downloaded network search list to the network search module in the modem (e.g., through nonvolatile (NV) configuration synchronization of the network search parameters). In one case, the electronic device 100 obtains the first flight information before S104. Therefore, before S104, the AP can determine the second country code of the first destination based on the first flight information and determine the network search parameters of the candidate airports corresponding to the second country code from the network search list. Then, the AP can send the network search parameters of the candidate airports corresponding to the second country code to the network search module in the modem so that the network search module can perform network search and network registration. In another case, the electronic device 100 does not obtain flight information. Therefore, after receiving the first country code sent by the country code scanning module in step 3, the network search module in the modem can request the network search parameters of the candidate airports corresponding to the first country code from the AP. The AP can determine the network search parameters of the candidate airports corresponding to the first country code from the network search list and send them to the network search module in the modem so that the network search module can perform network search and network registration. Figure 7 Following steps 3 and 4, the network search module in the modem can, based on the first country code received in step 3 and the network search parameters of the candidate airports received in step 4, [further details needed]. Figure 7 In step 5 shown, a network search is performed based on the network search parameters of the candidate airports corresponding to the first country code, and then network entry is completed, i.e., steps S106-S107 are executed. It is understood that the module names in the embodiments of this application are for illustrative purposes only and are not intended to limit the operations that the modules can perform. For example, Figure 7 The network search module shown is not only used to search for networks, but can also be used to perform operations such as network registration.

[0228] For example, before takeoff, electronic device 100 is not turned off and flight mode is not activated. During flight, electronic device 100 remains powered on and flight mode is off. In this case, electronic device 100 can execute S104 normally, and execute S105-S107 when it detects that the aircraft is about to land.

[0229] For example, before takeoff, electronic device 100 is not turned off but is in flight mode. During flight, electronic device 100 remains powered on and in flight mode. After landing, the user can turn off flight mode. In this case, electronic device 100 can execute S104 normally. Electronic device 100 can execute S105 when it detects an imminent landing scenario, and after landing, if the user turns off flight mode, electronic device 100 can execute S106-S107. However, this is not a limitation. In the above example, during flight, the user can either turn flight mode on or off, for example, turning off flight mode after the cruise phase or turning it on before landing.

[0230] For example, before takeoff, electronic device 100 is not turned off, so it can execute S104 normally, and optionally S102 and / or S103. When electronic device 100 detects that the aircraft is about to land, it can execute S105, but electronic device 100 may be turned off by the user immediately, so electronic device 100 can save the first country code obtained by scanning in S105. After the aircraft lands, electronic device 100 can be turned on. If electronic device 100 does not detect the aircraft landing scenario, it can execute S106-S107 after being turned on. In one case, if electronic device 100 obtains the first flight information before S104, and electronic device 100 is turned on by the user after the aircraft lands, electronic device 100 can determine whether the current time matches the arrival time in the first flight information. If they match, it can execute the network search method obtained from the first flight information in S106 and register on the network. In another scenario, if electronic device 100 fails to obtain flight information, electronic device 100 can be powered on by the user after the aircraft has landed and execute the network search method in S106 for which no flight information has been obtained.

[0231] In one possible implementation, after the electronic device 100 connects to the first network... Figure 6 The method shown also includes the following S108, optionally, and the following S109.

[0232] S108: Electronic device 100 sends network information of the first network to cloud server 200.

[0233] In one possible implementation, the network information of the first network may include, but is not limited to, one or more of the following: the first country code corresponding to the first network, the PLMN corresponding to the first network, the PLMN registration information corresponding to the first network, the standard of the first network, the frequency band of the first network, the frequency point of the first network, the cell identifier corresponding to the first network, the location information of the electronic device 100 accessing the first network, and the service experience information of the electronic device 100 using the first network.

[0234] In one possible implementation, the electronic device 100 can send the network information of the first network to the cloud server 200 immediately after accessing the first network. In another possible implementation, the electronic device 100 can first store the network information of the first network, and then send the stored network information to the cloud server 200 when the amount of stored network information is greater than or equal to a preset storage threshold. In yet another possible implementation, the electronic device 100 can also send the network information of the first network to the cloud server 200 according to a preset reporting cycle. This application embodiment does not limit this approach.

[0235] S109: Cloud server 200 updates the search list based on the network information of the first network.

[0236] In one possible implementation, the cloud server 200 can update the search list using the network information of the first network after receiving it. In another possible implementation, the cloud server 200 can update the search list using crowdsourced data (including the network information of the first network sent by electronic device 100 in S108) sent by multiple electronic devices. In yet another possible implementation, the cloud server 200 can update the search list according to a preset update cycle (e.g., 3 months) based on the network information of the first network. This application embodiment does not limit the specific method by which the cloud server 200 updates the search list.

[0237] For example, such as Figure 7 The communication system 10 shown, the application processor (AP) of the electronic device 100 may include a crowdsourcing data reporting module, and the modem of the electronic device 100 may include a network search module. An example of S108 can be found here. Figure 7 Steps 6-7. As shown in step 6, after the network search module in the modem executes S107, it can send the network information of the first network it has accessed to to the crowdsourced data reporting module in the AP. As shown in step 7, the crowdsourced data reporting module in the AP of the electronic device 100 can send the network information of the first network to the crowdsourced data processing module in the cloud server 200. The crowdsourced data processing module in the cloud server 200 can execute S109.

[0238] In one possible implementation, Figure 6 The method also includes: after electronic device 100 detects an aircraft takeoff scenario and before electronic device 100 detects an aircraft about to land scenario, i.e., after S102 and before S104, electronic device 100 uses a first net-searching method; after electronic device 100 detects an aircraft about to land scenario, i.e., after S104, for example, when performing net-searching in S105-S107, electronic device 100 uses a second net-searching method. In this method, the net-searching frequency 1 in the first net-searching method is less than the net-searching frequency 2 in the second net-searching method, or the first net-searching method is no net-searching, and the second net-searching method is net-searching. That is, after electronic device 100 detects an aircraft takeoff scenario and before electronic device 100 detects an aircraft about to land scenario, electronic device 100 uses a lower net-searching frequency or no net-searching; after electronic device 100 detects an aircraft about to land scenario, electronic device 100 uses a higher net-searching frequency (which can also be understood as normal net-searching). See the following for specific examples. Figures 15A-15B .

[0239] Not limited to this, in another possible implementation, Figure 6 The method also includes: after electronic device 100 detects the aircraft takeoff scenario and the aircraft cruise scenario, and before electronic device 100 detects the aircraft about to land scenario, i.e., after S102-S103 and before S104, electronic device 100 uses the first net-searching method; after electronic device 100 detects the aircraft about to land scenario, i.e., after S104, for example, when performing net-searching in S105-S107, electronic device 100 uses the second net-searching method. In other words, after electronic device 100 detects the aircraft takeoff scenario and the aircraft cruise scenario, and before electronic device 100 detects the aircraft about to land scenario, electronic device 100 uses a lower net-searching frequency or does not search the net; after electronic device 100 detects the aircraft about to land scenario, electronic device 100 uses a higher net-searching frequency (which can also be understood as normal net-searching). See section 16A for specific examples. Figure 16B .

[0240] exist Figure 6 In the network access method shown, when the aircraft is about to land, the electronic device 100 can scan the country code of its location and accurately scan the network of the candidate airport corresponding to the first country code, thereby accurately accessing the reliable network of the airport to which it is about to land. This effectively reduces the network access time required for the electronic device 100 in the air travel scenario, thus ensuring that the electronic device 100 can quickly access the network in the air travel scenario and greatly improving the user experience.

[0241] Furthermore, in air travel scenarios, electronic device 100 can use the search list sent by cloud server 200 to determine the search parameters for candidate airports corresponding to the first country code used during the search. Electronic device 100 automatically downloads the search list without requiring active user intervention. The search list sent by cloud server 200 is determined by cloud server 200 based on crowdsourced data. This means cloud server 200 can automatically generate and update the search parameters for candidate airports corresponding to each country code, eliminating the need for manual collection and updating of airport search parameters. The airport search parameters are updated promptly and with high accuracy, effectively reducing the consumption of manpower and resources.

[0242] exist Figure 6 In the network access method shown, the electronic device 100 detects an impending aircraft landing scenario. Therefore, after detecting the impending landing, it can perform country code scanning, network search, and network registration (i.e., execute S105-S107). For example, the electronic device 100 is powered on before the aircraft's impending landing phase. However, this is not a limitation. In other embodiments, the electronic device 100 may not detect an impending aircraft landing scenario. For example, the electronic device 100 may be powered off before and during the impending landing phase, thus the electronic device 100 will not scan the country code during the impending landing phase. The following exemplarily illustrates the network access method when the electronic device 100 does not detect an impending aircraft landing scenario.

[0243] In one possible implementation, before takeoff, electronic device 100 acquires first flight information, which may include a first destination (e.g., country G, location H) and a first landing airport. Electronic device 100 can then search a web list based on the first flight information (see [link to web search method] for details). Figure 6In step S101, the second country code of the first destination and the network search parameters of the candidate airports corresponding to the second country code are determined. The network search parameters of the candidate airports corresponding to the second country code include the network search parameters of the first landing airport. Electronic device 100 is powered off before and during the landing phase. When the aircraft lands, electronic device 100 is powered on. Electronic device 100 can determine whether its time matches the time of the first flight information. If they match, electronic device 100 can prioritize network search based on the network search parameters of the first landing airport. Optionally, if network search based on the first landing airport's network search parameters fails (e.g., no corresponding network is found within a certain time), electronic device 100 can then search based on the network search parameters of the first candidate airports. The first candidate airports include one or more other candidate airports (e.g., all other candidate airports) besides the first landing airport among the candidate airports corresponding to the second country code. Then, electronic device 100 can access the corresponding network based on the network search results. The determination of whether the time of the electronic device 100 matches the time of the first flight information may include: whether the electronic device 100 determines whether the landing time of the aircraft matches the arrival time in the first flight information, and / or whether the electronic device 100 determines whether the takeoff time of the aircraft matches the departure time in the first flight information.

[0244] For example, electronic device 100 is turned off before takeoff, remains off during flight, and is turned on after landing. In this scenario, electronic device 100 does not recognize the takeoff, cruise, imminent landing, or landing scenarios. Assuming electronic device 100 obtains the first flight information in advance, upon turning on after landing, it can determine if the current time matches the arrival time in the first flight information. If they match, electronic device 100 can perform a network search based on the network search parameters of the first landing airport. Optionally, if the network search based on the first landing airport's parameters fails, it can then perform a network search based on the network search parameters of a first candidate airport.

[0245] For example, the electronic device 100 is not turned off before takeoff, is turned off before the landing phase, and is turned on after landing. In this case, the electronic device 100 can recognize the takeoff scenario (optionally, and the cruise scenario), but it cannot recognize the landing scenario or the landing scenario. Assuming the electronic device 100 obtains the first flight information in advance, when it is turned on after landing, it can determine whether the current time matches the arrival time in the first flight information, and whether the time when the takeoff scenario is detected matches the departure time in the first flight information. If both match, the electronic device 100 can perform a network search based on the network search parameters of the first landing airport. Optionally, if the network search based on the first landing airport's network search parameters fails, it can then perform a network search based on the network search parameters of the first candidate airport.

[0246] In another possible implementation, electronic device 100 does not obtain flight information. Electronic device 100 is powered off before and during the landing phase. After landing, electronic device 100 is powered on. It can first search historical frequency points. If the search fails, it then scans for country codes. If a first country code is found, electronic device 100 can determine the network search parameters for the candidate airports corresponding to the first country code from the network search list and perform a network search based on those parameters. Then, electronic device 100 can access the corresponding network based on the search results.

[0247] Not limited to the above-described embodiments, in another possible embodiment, the aircraft landing may not necessarily involve powering on. The aircraft landing may include one or more of the following: the electronic device 100 detects the aircraft landing scenario; the time of the electronic device 100 matches the time of the flight information; the electronic device 100 is powered on (optionally, and without network); the electronic device 100 deactivates flight mode (optionally, and without network), etc. In another possible embodiment, after the aircraft lands, the electronic device 100 can scan for country codes. If a first country code is detected, the electronic device 100 can determine the search parameters of the candidate airport corresponding to the first country code from the search list and perform a network search based on the search parameters of the candidate airport corresponding to the first country code. Then, the electronic device 100 can access the corresponding network based on the search results. In another possible embodiment, if searching for historical frequency points fails, and searching based on the search parameters of the candidate airport corresponding to the scanned country code fails, the electronic device 100 may also perform other network search methods such as full-band network search.

[0248] Understandably, Figure 6The implementation of S105-S107 can also be applied to network access when electronic device 100 does not detect that the aircraft is about to land. To avoid going into detail, examples will not be provided one by one.

[0249] This application embodiment does not limit the network access method when the electronic device 100 does not detect the scenario of the aircraft about to land.

[0250] In this embodiment, the electronic device 100 can collect acceleration data and gyroscope data through a sensor module, and detect one or more of the following aircraft scenarios based on the collected acceleration data and gyroscope data: aircraft takeoff, aircraft cruise, aircraft about to land, and aircraft landing. Specific implementation examples are provided below. Figures 8-11 , Figures 12A-12B , Figure 13 Electronic device 100 can perform relevant operations based on the detected scene (see specific examples). Figure 6 , Figure 7 , Figures 15A-15B , Figures 16A-16B To improve the user experience.

[0251] The following example illustrates the patterns of acceleration data collected by electronic device 100 during aircraft takeoff, as well as the process by which electronic device 100 detects aircraft takeoff scenarios.

[0252] Figure 8 An example diagram illustrating the acceleration during an aircraft takeoff is shown.

[0253] like Figure 8 As shown, the horizontal axis represents time, with the unit of time on the horizontal axis being seconds (s). The vertical axis represents the magnitude of acceleration data in various directions collected by the electronic device 100 through the sensor module (e.g., an accelerometer) (which can be simply referred to as acceleration magnitude). The unit of acceleration magnitude on the vertical axis is meters per second squared (m / s²). 2 Let's take an example. The magnitude of acceleration can be used to reflect how quickly the velocity changes. In some examples, the magnitude of acceleration on the vertical axis can be obtained after a moving average, for example, a moving average with a window size of 10 seconds.

[0254] like Figure 8 As shown, before takeoff, the aircraft is stationary on the runway, with its fuselage maintaining a horizontal attitude and its angle of attack close to 0. At this time, the acceleration detected by the electronic devices carried by passengers is close to standard gravitational acceleration (approximately 9.8 m / s²). 2 And the fluctuations are relatively small. For example... Figure 8 The acceleration modulus is shown to be 9.8 m / s² from approximately 0 to 20 seconds. 2 Fluctuations within a relatively small area nearby.

[0255] like Figure 8 As shown, after coming to a standstill, the aircraft enters the taxiing phase. During taxiing, as the engine thrust increases, the aircraft begins to accelerate on the runway, its nose lifts slightly, and the angle of attack gradually increases, but the main landing gear remains in contact with the ground. At this time, the acceleration magnitude value acquired by the electronic equipment 100 continuously increases and fluctuates. The taxiing phase lasts, for example, approximately 30 seconds. Figure 8 As shown, from approximately 20 to 60 seconds, the acceleration modulus first increases and then fluctuates within the acceleration range, which is approximately 9.9 m / s². 2 Up to 10.15 m / s 2 .

[0256] like Figure 8 As shown, when an aircraft reaches a certain speed during its runway roll, the lift generated by the wings equals the aircraft's weight. At this point, the aircraft continues to adjust its attitude, increasing its angle of attack to lift off the ground, thus entering a climb phase. During the climb, the aircraft maintains a large positive pitch angle and accelerates upwards. During this climb, the acceleration modulus value acquired by the electronic equipment 100 may increase, but it may also decrease due to changes in air resistance and thrust, resulting in fluctuations in the acceleration modulus value. For example... Figure 8 As shown, the acceleration modulus will first increase after approximately 60 to 80 seconds, and then fluctuate within the liftoff acceleration range, which is approximately 10.5 m / s². 2 Up to 11 m / s 2 For example, it may increase to a larger value within the takeoff acceleration range and then fall back, or even continue to fall back to a smaller value below the takeoff acceleration range.

[0257] In some embodiments of this application, the aircraft takeoff detection algorithm can monitor the changing characteristics of acceleration data acquired by the electronic device 100 during aircraft takeoff (e.g., Figure 8 The acceleration diagram shown illustrates a state machine constructed for three states of an aircraft takeoff scenario (stationary, taxiing, and climb). It utilizes processed sensor data (referred to as sensor feature data) as the basis for switching between states, achieving high accuracy (over 95%) and low detection latency. Optionally, the taxiing state can be detected using continuous acceleration fluctuations over a longer time window, resulting in high accuracy. Optionally, the climb state can be detected using one or more sensor feature data points within a shorter time window, ensuring accuracy while reducing detection latency. An implementation example of the above flight takeoff detection algorithm can be found below. Figure 9 .

[0258] Figure 9This is a flowchart illustrating an aircraft takeoff detection algorithm provided in an embodiment of this application. Figure 9 The aircraft takeoff detection algorithm shown can be applied to Figure 3 The electronic device 100 shown. Figure 9 The aircraft takeoff detection algorithm shown can be applied to Figure 4 The electronic device 100 shown.

[0259] In one possible implementation, when a preset trigger condition for aircraft takeoff detection is met, the electronic device 100 executes... Figure 9 The process is illustrated. For example, the triggering conditions for aircraft takeoff detection include: the electronic device 100 entering the airport's fence. For example, when the electronic device 100 obtains flight information, the triggering conditions for aircraft takeoff detection include: entering the fence of the departure airport in the flight information, and / or, the difference between the current time and the departure time in the flight information is less than or equal to a preset difference. Not limited to this, in another possible implementation, the electronic device 100 may also execute the aircraft takeoff detection algorithm in real time by default (i.e., execute...). Figure 9 (As shown in the flowchart), this application embodiment does not limit the triggering method for executing the aircraft takeoff detection algorithm.

[0260] Figure 9 The aircraft takeoff detection algorithm shown may include, but is not limited to, the following steps:

[0261] S201: Electronic device 100 acquires acceleration data and gyroscope data.

[0262] In one possible implementation, the electronic device 100 can acquire acceleration data in three axes (i.e., x-axis, y-axis, and z-axis) through a sensor module (e.g., an accelerometer), and the electronic device 100 can acquire gyroscope data in three axes (i.e., x-axis, y-axis, and z-axis) through a sensor module (e.g., a gyroscope sensor).

[0263] S202: Electronic device 100 performs data preprocessing on acceleration data and gyroscope data, wherein the data preprocessing includes one or more of the following: removing attitude change data, noise filtering, signal smoothing, normalization, and bias removal.

[0264] In one possible implementation, removing attitude change data during data preprocessing can be used to remove interference data (such as data on large acceleration changes or large orientation changes in a short period of time) from acceleration data and / or gyroscope data caused by rapid attitude changes (e.g., violent rotation, shaking). Methods for removing attitude change data include, but are not limited to, direct removal, interpolation substitution, and filtering noise reduction.

[0265] In one possible implementation, noise filtering during data preprocessing can be used to remove random interference or irrelevant information (i.e., noise) from acceleration and / or gyroscope data, retaining useful / true data. Noise filtering can be implemented in ways including, but not limited to, applying mean filtering, low-pass filtering, median filtering, wavelet denoising, etc.

[0266] In one possible implementation, signal smoothing during data preprocessing can be used to reduce local fluctuations or sharp changes in acceleration and / or gyroscope data, making it more "smooth" overall. Signal smoothing can be implemented in ways including, but not limited to, moving average filtering, moving average, low-pass filtering, median filtering, wavelet denoising, etc.

[0267] In one possible implementation, normalization in data preprocessing can be used to scale acceleration and / or gyroscope data to a uniform range, eliminating dimensional differences. Normalization implementations include, but are not limited to, minimum-maximum normalization, robust normalization, vector normalization, and feature-range normalization, etc.

[0268] In one possible implementation, bias removal during data preprocessing can be used to eliminate systematic biases (e.g., non-random offsets) in acceleration and / or gyroscope data. Implementations of bias removal include, but are not limited to, mean subtraction, high-pass filtering, moving average debiasing, median debiasing, etc.

[0269] For example, when executing the aircraft takeoff detection algorithm, S202 may be: the electronic device 100 first removes attitude change data from the acceleration data and gyroscope data, then performs noise filtering, and then performs normalization and bias removal.

[0270] Understandably, preprocessing the input data before executing the specific detection operations in the aircraft takeoff detection algorithm allows the data to better reflect changes in the aircraft's state, remove noise and interference, and make the data more stable, facilitating subsequent detection.

[0271] The data preprocessing shown in the embodiments of this application is for illustrative purposes only and should not be construed as limiting.

[0272] Understandably, during the execution of the aircraft takeoff detection algorithm, i.e. Figure 9 During the process shown, the electronic device 100 can acquire acceleration data and gyroscope data in real time, and perform data preprocessing on the acquired data, i.e., execute S201-S202 in real time. Subsequently, based on the acceleration data and gyroscope data obtained from the real-time execution of S201-S202, it executes the specific detection operations of the aircraft takeoff detection algorithm, such as executing... Figure 9 S203-S204, S205-S206.

[0273] S203: Electronic device 100 triggers gliding detection, wherein the acceleration modulus is determined based on acceleration data.

[0274] S204: Electronic device 100 determines whether the duration of acceleration magnitude within the threshold range 1 is greater than or equal to duration 1.

[0275] In one possible implementation, after the electronic device 100 initiates the aircraft takeoff detection algorithm, it performs taxiing detection in real time by default. In another possible implementation, after initiating the aircraft takeoff detection algorithm, the electronic device 100 triggers taxiing detection only when preset triggering conditions are met. For example, the triggering conditions for taxiing detection include: the real-time acquired acceleration data being greater than the standard gravitational acceleration (approximately 9.8 m / s²). 2 And it fluctuates to some extent.

[0276] In one possible implementation, when the electronic device 100 performs gliding detection, it can calculate the magnitude of the acceleration data obtained in real-time by executing S201-S202, thus obtaining the real-time acceleration magnitude. Furthermore, the electronic device 100 can determine whether the duration of the acceleration magnitude within a threshold range 1 is greater than or equal to duration 1 (i.e., executing S204), which can also be understood as determining whether the acceleration magnitude remains within the threshold range 1 within the real-time monitored time window of duration 1. For example, the electronic device 100 can determine whether the acceleration magnitude... Figure 8 Whether the duration within the indicated acceleration / skip zone (i.e., threshold range 1) is greater than or equal to duration 1 (e.g., ... Figure 8 30 seconds shown).

[0277] In one possible implementation, when the determination result of S204 is yes, that is, the duration of the acceleration magnitude within the threshold range is greater than or equal to the duration of 1, the electronic device 100 can determine that the aircraft has transitioned from a stationary state to a taxiing state and execute S205. When the determination result of S204 is no, that is, the duration of the acceleration magnitude within the threshold range is less than the duration of 1, the electronic device 100 can determine that the aircraft is still stationary, and therefore no aircraft takeoff scenario is detected (i.e., S208).

[0278] S205: Electronic device 100 detects a gliding state and triggers a climb detection, wherein the acceleration magnitude, gravitational acceleration, and acceleration variance are determined based on acceleration data and gyroscope data.

[0279] S206: Electronic device 100 determines whether the following conditions are met: the duration of acceleration magnitude within threshold range 2 is greater than or equal to duration 2, the duration of gravitational acceleration within threshold range 3 is greater than or equal to duration 3, and the duration of acceleration variance within threshold range 4 is greater than or equal to duration 4.

[0280] In one possible implementation, after detecting a glide state, the electronic device 100 triggers a climb detection. Optionally, the duration of the climb detection can be preset. During climb detection, the electronic device 100 can calculate the magnitude and variance of the acceleration data obtained in real-time execution S201-S202, obtaining the magnitude of the three-axis acceleration data (hereinafter referred to as acceleration magnitude) and the variance of the three-axis acceleration data (hereinafter referred to as acceleration variance). The acceleration variance characterizes the volatility / stability of acceleration changes. During climb detection, the electronic device 100 can also determine the acceleration component (hereinafter referred to as gravitational acceleration) in the direction of gravity (e.g., the z-axis) based on the acceleration data and gyroscope data obtained in real-time execution S201-S202.

[0281] In one possible implementation, for example, within a preset climb detection duration, the electronic device 100 can determine whether the climb conditions are met (i.e., execute S206). These climb conditions may include: the duration for which the acceleration magnitude is within a threshold range 2 is greater than or equal to duration 2; the duration for which the gravitational acceleration is within a threshold range 3 is greater than or equal to duration 3; and the duration for which the acceleration variance is within a threshold range 4 is greater than or equal to duration 4. Durations 2, 3, and 4 may be less than or equal to the preset climb detection duration. For example, threshold range 2 may be... Figure 8 The liftoff acceleration range shown has a threshold range of 3. Figure 8 The range of gravitational acceleration values ​​corresponding to the liftoff acceleration range shown.

[0282] In some examples, the climbing conditions can include not only the specific conditions for the acceleration magnitude, the specific conditions for gravitational acceleration, and the specific conditions for the variance of acceleration, but also the order in which these specific conditions are judged. For example, determining whether the climbing conditions are met can specifically include: first, judging whether the specific conditions for the acceleration magnitude (i.e., whether the duration of the acceleration magnitude within the threshold range 2 is greater than or equal to duration 2) and the specific conditions for gravitational acceleration (i.e., whether the duration of gravitational acceleration within the threshold range 3 is greater than or equal to duration 3); if the specific conditions for the acceleration magnitude and gravitational acceleration are met, then judging whether the specific conditions for the acceleration variance are met (i.e., whether the duration of the acceleration variance within the threshold range 4 is greater than or equal to duration 4); if the specific conditions for the acceleration variance are met, then the climbing conditions are determined to be met; otherwise, the climbing conditions are not met.

[0283] Not limited to Figure 9The climbing conditions shown in S206 can be further implemented in a specific way. The climbing conditions may include more or fewer conditions. For example, the climbing conditions may include one or more of the following: the duration of the acceleration magnitude within the threshold range 2 is greater than or equal to the duration 2, the duration of the gravitational acceleration within the threshold range 3 is greater than or equal to the duration 3, and the duration of the acceleration variance within the threshold range 4 is greater than or equal to the duration 4.

[0284] In one possible implementation, when the determination result of S206 is yes, that is, the climb condition is met, the electronic device 100 can determine that the aircraft has transitioned from the taxiing state to the climb state and execute S207. When the determination result of S206 is no, that is, the climb condition is not met, the electronic device 100 can determine that the aircraft is still in the taxiing state or has returned to a stationary state, and therefore no aircraft takeoff scenario is detected (i.e., S208).

[0285] S207: Electronic device 100 detected the climb state and, based on the taxiing state and climb state, detected the aircraft takeoff scenario.

[0286] In one possible implementation, the electronic device 100 first detects the taxiing state based on S203-S204, and then detects the climb state based on S205-S206, so that the electronic device 100 can determine that an aircraft takeoff scenario has been detected.

[0287] In one possible implementation, when electronic device 100 acquires flight information, after detecting an aircraft takeoff scenario, it can calculate the difference between the actual takeoff time and the time the takeoff scenario was detected (which can be referred to as takeoff delay) and record the takeoff delay. For example, the actual takeoff time is manually recorded by the user. This takeoff delay can be used to update the aircraft takeoff detection algorithm, thereby improving the accuracy of the aircraft takeoff detection algorithm.

[0288] S208: Electronic equipment 100 did not detect an aircraft takeoff scenario.

[0289] In one possible implementation, if electronic device 100 does not detect the taxiing state based on S203-S204, or if electronic device 100 detects the taxiing state based on S203-S204 but does not detect the climb state based on S205-S206, then electronic device 100 can determine that the aircraft takeoff scenario has not been detected. In this case, electronic device 100 can directly re-execute the process. Figure 9 The process shown may proceed as instructed, or the process may wait for subsequent triggers to execute. Figure 9 The process is shown below.

[0290] exist Figure 9The aircraft takeoff detection algorithm shown can accurately label the taxiing and climb states during takeoff by setting the value range and duration of acceleration features (such as acceleration magnitude, gravitational acceleration, and acceleration variance) that effectively reflect the aircraft's takeoff state. Furthermore, a state machine-based framework is constructed, using the aforementioned acceleration features as the basis for state transitions, achieving a high-accuracy and low-latency aircraft takeoff detection algorithm. The climb conditions used for climb detection can be multi-condition constraints based on various acceleration features. Therefore, it can effectively identify the key states (taxiing and climb states) during aircraft takeoff, further ensuring high accuracy and low latency in the detection results.

[0291] The following is an example of how electronic device 100 detects an aircraft cruise scenario.

[0292] Understandably, aircraft exhibit different levels of stability in speed and altitude during takeoff climb and cruise. During climb, the aircraft's acceleration fluctuates, and due to factors such as airflow and flight path, the aircraft needs to continuously change its velocity in the vertical / gravity direction (e.g., along the z-axis), thus typically experiencing multiple alternating periods of weightlessness and gravitational gain. During cruise, however, the aircraft's acceleration tends to stabilize, and its altitude and speed remain stable.

[0293] In some embodiments of this application, based on the aforementioned physical laws, the aircraft cruise detection algorithm can estimate the degree of change in the aircraft's speed and altitude using acceleration data. For example, the range of acceleration data (i.e., the difference between the maximum and minimum values ​​of the acceleration sequence within a time window) can be used to measure the volatility of the aircraft's acceleration, thereby detecting whether the aircraft has entered cruise mode. This achieves high accuracy (up to 95%) and low detection latency. An implementation example of the above-mentioned flight cruise detection algorithm can be found below. Figure 10 .

[0294] Figure 10 This is a flowchart illustrating an aircraft cruise detection algorithm provided in an embodiment of this application. Figure 10 The aircraft cruise detection algorithm shown can be applied to Figure 3 The electronic device 100 shown. Figure 10 The aircraft cruise detection algorithm shown can be applied to Figure 4 The electronic device 100 shown.

[0295] Figure 10 The aircraft cruise detection algorithm shown may include, but is not limited to, the following steps:

[0296] S301: After the electronic device 100 detects the aircraft takeoff scenario, it activates the aircraft cruise detection algorithm.

[0297] In one possible implementation, the electronic device 100 initiates an aircraft cruise detection algorithm when it detects an aircraft takeoff scenario. The electronic device 100 can record the runtime of the aircraft cruise algorithm, that is, the duration from when the electronic device 100 detects the aircraft takeoff scenario to the current time. For example, the electronic device 100 can... Figure 9 The aircraft takeoff detection algorithm shown detected an aircraft takeoff scenario.

[0298] S302: Electronic device 100 acquires acceleration data and gyroscope data.

[0299] S303: Electronic device 100 performs data preprocessing on acceleration data and gyroscope data, wherein the data preprocessing includes one or more of the following: removing attitude change data, noise filtering, signal smoothing, normalization, and bias removal.

[0300] Figure 10 S302-S303 and Figure 9 Similar to S201-S202, please refer to [link / reference needed]. Figure 9 Explanation of S201-S202.

[0301] Understandably, during the execution of the aircraft cruise detection algorithm, i.e. Figure 10 During the process shown, the electronic device 100 can acquire acceleration data and gyroscope data in real time, and perform data preprocessing on the acquired data, i.e., execute S302-S303 in real time. Subsequently, based on the acceleration data and gyroscope data obtained from the real-time execution of S302-S303, it executes the specific detection operations of the aircraft cruise detection algorithm, such as executing... Figure 10 S304, S306-S308.

[0302] In one possible implementation, after the electronic device 100 initiates the aircraft cruise detection algorithm, it can determine whether a preset waiting condition is met. This preset waiting condition may include: the aircraft is in a stable state, and / or the runtime of the aircraft cruise detection algorithm is greater than or equal to a preset time threshold. Examples of how the electronic device 100 determines whether the preset waiting condition is met can be found in S304 and S305 below.

[0303] S304: Electronic equipment 100 determines whether the aircraft is in a stable state based on acceleration data and gyroscope data.

[0304] In one possible implementation, the electronic device 100 can determine whether the aircraft is in a stable state based on the acceleration data and gyroscope data obtained in real time during S302-S303. For example, when the change in acceleration data is less than a certain value within a certain time period, and the change in gyroscope data is less than a certain value within a certain time period, the electronic device 100 determines that the aircraft is in a stable state. This application embodiment does not limit the specific implementation of S304.

[0305] In one possible implementation, when the determination result of S304 is yes, that is, when the aircraft is in a stable state, the electronic device 100 can continue to execute S305. When the determination result of S304 is no, that is, when the aircraft is not in a stable state, the electronic device 100 can re-execute S302-S304.

[0306] S305: Electronic device 100 determines whether the algorithm runtime is greater than or equal to a preset time threshold.

[0307] In one possible implementation, the electronic device 100 can determine whether the runtime of the aircraft cruise detection algorithm is greater than or equal to a preset time threshold, i.e., execute S305. When the determination result of S305 is yes, the electronic device 100 can start determining whether to enter the aircraft cruise state, i.e., execute S306-S308. When the determination result of S305 is no, the electronic device 100 can wait and continue to execute the determination of S305.

[0308] Not limited to Figure 10 As shown in the example, in other examples, when the result of S305 is negative, the electronic device 100 can also re-execute S302-S305.

[0309] S306: Electronic device 100 acquires the acceleration modulus value within time window 1.

[0310] In one possible implementation, after determining that the judgment result of S305 is yes, the electronic device 100 can continue to execute S302-S303 in real time and obtain processed acceleration data. Simultaneously, the electronic device 100 can determine in real time whether the processed acceleration data fills a preset time window 1. Time window 1 is a time window with a duration of 5 seconds, and can therefore be understood as a real-time determination of whether processed acceleration data for a duration of 5 seconds (time window 1) has been acquired. The starting time point of time window 1 is after executing S305. For example, when executing S306 for the first time, the starting time point of time window 1 in S306 is the time point when the electronic device 100 determines that the judgment result of S305 is yes. When the judgment result is no, i.e., the processed acceleration data does not fill time window 1, the electronic device 100 can continue to execute S302-S303 in real time and obtain processed acceleration data until the acquired processed acceleration data fills time window 1. When the above judgment result is yes, the electronic device 100 can determine whether the aircraft has entered the aircraft cruise state based on the processed acceleration data within the time window 1, such as calculating the magnitude of the acceleration data within the time window 1 and executing S307-S308.

[0311] In one possible implementation, the electronic device 100 can calculate the magnitude of the processed acceleration data within time window 1 and obtain the acceleration magnitude within time window 1. It is understood that there are multiple processed acceleration data within time window 1, which can be referred to as a sequence of acceleration data; therefore, there are also multiple acceleration magnitudes within time window 1, which can be referred to as a sequence of acceleration magnitudes.

[0312] S307: Range of acceleration modulus values ​​within time window 1 of electronic device 100.

[0313] In one possible implementation, the electronic device 100 can acquire the maximum and minimum values ​​of the sequence of acceleration modulus values ​​within time window 1, and calculate the difference between the maximum and minimum values, i.e., calculate the range of acceleration modulus values ​​within time window 1. The range of acceleration modulus values ​​within time window 1 can be used to measure the fluctuation of the aircraft's acceleration within time window 1, thereby assessing the aircraft's motion stability within time window 1.

[0314] S308: Electronic device 100 determines whether the range of acceleration magnitude values ​​within time window 1 is less than a preset range threshold.

[0315] In one possible implementation, when the judgment result of S308 is yes, that is, the range of acceleration modulus values ​​within time window 1 is less than a preset range threshold, the electronic device 100 can determine that the aircraft has entered a relatively stable cruise state, i.e., execute S309. When the judgment result of S308 is no, that is, the range of acceleration modulus values ​​within time window 1 is greater than or equal to the preset range threshold, the electronic device 100 can continue to obtain the range of acceleration modulus values ​​within the next time window 1, i.e., re-execute S306-S308. Here, the starting time point of the next time window 1 is after the execution of S308. For example, when S306 is executed for the second time, the starting time point of time window 1 in S306 is the time point when the electronic device 100 first executes S308 and determines that the judgment result of S308 is no.

[0316] S309: Electronic device 100 detected an aircraft cruise scenario.

[0317] In one possible implementation, when the judgment result of S308 is that the range of acceleration magnitude values ​​within time window 1 is less than the preset range threshold, it can be characterized that the fluctuation of the aircraft's acceleration within time window 1 is small / tends to be stable, that is, the aircraft's motion within time window 1 is relatively stable. Therefore, the electronic device 100 can determine that the aircraft has entered a relatively stable cruise state, that is, the aircraft cruise scenario has been detected.

[0318] Not limited to Figure 10 In the example shown, the execution order of S304 and S305 can be reversed in some other examples. That is, S305 is executed first, and S304 is executed if the result of S305 is yes, and S306-S308 are executed if the result of S304 is yes. In other examples, only S304 can be executed without executing S305, and in still other examples, only S305 can be executed without executing S304.

[0319] Not limited to Figure 10 The example shown is different from other examples where S304 may use only acceleration data or gyroscope data, and in other examples, S304 may use more sensor data.

[0320] exist Figure 10The aircraft cruise detection algorithm shown detects whether an aircraft is in a cruise scenario after detecting a takeoff scenario by using the range of acceleration modulus values ​​within a time window of duration 5 (1). This aligns with real-world scenarios and achieves high accuracy and low detection latency. Furthermore, before executing S306-S308 to detect the start of cruise, S304 and / or S305 can be executed first to further improve the accuracy of cruise detection. This is because an aircraft needs sufficient time to climb after takeoff before entering cruise, while the aircraft takeoff detection algorithm generally determines that a takeoff scenario has been detected once the climb begins. Figure 10 The aircraft cruise detection algorithm shown employs a heuristic time threshold. Specifically, in S305, S306-S308 will only begin to detect whether cruise has commenced after the aircraft has exceeded a preset time threshold since takeoff, avoiding detection errors caused by premature execution of S306-S308. Furthermore, in S304, preprocessed acceleration and / or gyroscope data are used to determine if the aircraft is stable. Only after stabilization will S306-S308 begin to detect whether cruise has commenced, effectively suppressing changes in aircraft attitude and reducing the impact of airflow disturbances.

[0321] Figure 10 The example given is that electronic device 100 detects an aircraft takeoff scenario and then initiates the aircraft cruise detection algorithm. However, this is not the only possible implementation. In another possible implementation, electronic device 100 can also initiate the aircraft cruise detection algorithm when preset triggering conditions for aircraft cruise detection are met. For example, the triggering conditions for aircraft cruise detection include the electronic device 100 being powered on. One example scenario is that the electronic device 100 is powered off before the aircraft takes off, therefore no aircraft takeoff scenario is detected. Then, the electronic device 100 is powered on, at which point it can initiate the aircraft cruise detection algorithm. This application does not limit the triggering method for executing the aircraft cruise detection algorithm.

[0322] The following is an example of how electronic device 100 detects an aircraft about to land.

[0323] In some embodiments of this application, the aircraft imminent landing detection algorithm can acquire important feature data (referred to as flight feature data) of the aircraft during flight based on sensor data. Then, a pre-trained landing prediction model can be used to detect whether the aircraft is in an imminent landing scenario based on the flight feature data, and when an imminent landing scenario is detected, the predicted imminent landing duration (i.e., the time elapsed between the detection of the imminent landing scenario and the aircraft's landing) is obtained, achieving high accuracy (reaching over 98%) and low detection latency. In the embodiments of this application, the time elapsed between the detected imminent landing scenario and the aircraft's landing completion is relatively short; therefore, the predicted imminent landing duration is also relatively short (e.g., less than 20 minutes). An implementation example of the above aircraft imminent landing detection algorithm can be found below. Figure 11 , Figure 12A and Figure 12B .

[0324] In one possible implementation, the electronic device 100 can trigger the execution of an aircraft imminent landing detection algorithm after detecting an aircraft takeoff scenario and / or an aircraft cruise scenario. Not limited to this, in another possible implementation, the electronic device 100 can also execute the aircraft imminent landing detection algorithm when preset triggering conditions for detecting an aircraft imminent landing are met. For example, the triggering conditions for detecting an aircraft imminent landing include: the electronic device 100 being powered on, and / or the electronic device 100 being offline for a duration greater than or equal to a preset offline duration. In this case, an example scenario is: the electronic device 100 is powered off before the aircraft takes off, therefore no aircraft takeoff or cruise scenario is detected; subsequently, after the aircraft begins landing, the electronic device 100 is powered on, at which point the electronic device 100 can begin executing the aircraft imminent landing detection algorithm. This application does not limit the triggering method for executing the aircraft imminent landing detection algorithm.

[0325] Figure 11 This is a schematic diagram of the architecture of an electronic device 100 provided in an embodiment of this application.

[0326] like Figure 11 As shown, the electronic device 100 may include a sensor module 1010, a data preprocessing module 1020, a feature extraction module 1030, a landing prediction module 1040, a post-processing calibration module 1050, and a network search and registration module 1060. Figure 11 The electronic device 100 shown can be used to execute an algorithm for detecting when an aircraft is about to land.

[0327] In one possible implementation, Figure 11 The electronic device 100 shown can correspond to Figure 3 The electronic device 100 shown, for example, Figure 11 The sensor module 1010 shown corresponds to Figure 3 The sensor module 180 shown is... Figure 11 The other modules shown correspond to Figure 3 The processor 110 shown includes a network search and registration module 1060 that corresponds to the modem within the processor 110, and data preprocessing module 1020, feature extraction module 1030, landing prediction module 1040, and post-processing calibration module 1050 that correspond to the access points (APs) within the processor 110. In one possible implementation, Figure 11 The electronic device 100 shown can correspond to Figure 4 The electronic device 100 shown, for example, Figure 11 The sensor module 1010 shown is composed of Figure 4 The kernel layer driver subsystem shown implements the driver. Figure 11 The other modules shown can correspond to the framework layer and the system service layer.

[0328] like Figure 11 As shown, sensor module 1010 can be used to acquire acceleration data and gyroscope data. For a specific implementation example, please refer to [link to example]. Figure 9 S201. Sensor module 1010 can input the acquired acceleration data and gyroscope data into data preprocessing module 1020.

[0329] like Figure 11 As shown, the data preprocessing module 1020 can be used to preprocess the input acceleration data and gyroscope data. The data preprocessing includes one or more of the following: removing attitude change data, noise filtering, signal smoothing, normalization, and bias removal. For specific implementation examples, please refer to [link to implementation details]. Figure 9 S202. The data preprocessing module 1020 can input the processed acceleration data and gyroscope data into the feature extraction module 1030. In one possible implementation, the data preprocessing module 1020 can also input the processed acceleration data and gyroscope data into the post-processing calibration module 1050.

[0330] like Figure 11As shown, the feature extraction module 1030 can be used to analyze and process the input processed acceleration data and gyroscope data to obtain flight feature data. The flight feature data may include, but is not limited to, one or more of the following: aircraft turning information, aircraft weightlessness information, data obtained by statistically analyzing and / or calculating acceleration data, data obtained by statistically analyzing and / or calculating gyroscope data, acceleration data, and gyroscope data. Aircraft turning information may include, but is not limited to, one or more of the following: number of aircraft turns, aircraft turning time, aircraft turning angle, etc. Aircraft weightlessness information may include, but is not limited to, one or more of the following: number of weightlessness events, weightlessness time, acceleration data during weightlessness, etc. The aforementioned statistical and / or calculations may include, but are not limited to, one or more of the following: calculating the mean, calculating the variance, calculating the components of a vector in a certain direction, calculating the cumulative amount over a period of time, calculating the change over a period of time, calculating the minimum value over a period of time, calculating the maximum value over a period of time, etc. An example of the feature extraction module 1030 obtaining aircraft turning information can be seen below. Figure 12A An example of how the feature extraction module 1030 acquires aircraft weightlessness information can be found below. Figure 12B The feature extraction module 1030 can input aircraft feature data into the landing prediction module 1040.

[0331] like Figure 11 As shown, the landing prediction module 1040 may include a pre-trained model for detecting whether the aircraft is in a landing scenario; therefore, the landing prediction module 1040 may also be referred to as the landing prediction model 1040. In one possible implementation, the landing prediction model 1040 is a decision tree regression model trained on a training set, which may include flight feature data from multiple aircraft landing scenarios. The landing prediction model 1040 may be trained by the electronic device 100 itself, or it may be downloaded by the electronic device 100 from other devices (e.g., cloud server 200). The training set may include flight feature data acquired by one or more electronic devices.

[0332] The landing prediction model 1040 can take flight feature data as input and obtain a corresponding output (which can be called the prediction result). The prediction result output by the landing prediction model 1040 can indicate whether the aircraft is in an imminent landing scenario. When it indicates that the aircraft is in an imminent landing scenario, the prediction result also includes the imminent landing duration t, which can be the time elapsed between the detection of the imminent landing scenario and the aircraft's landing. For example, the prediction result output by the landing prediction model 1040 indicates that the aircraft is in an imminent landing scenario and includes an imminent landing duration t = 15 minutes, which means that the aircraft will complete its landing 15 minutes after the current time, and also means that the electronic equipment 100 detected the imminent landing scenario 15 minutes before the aircraft landed.

[0333] For example, the landing prediction model 1040 is a decision tree regression model. The structure of the decision tree of the landing prediction model 1040 (including the root node and leaf nodes) can be determined during the training phase. The decision tree can include multi-level judgments, and a node in the decision tree can correspond to one or more judgment conditions. For example, the judgment conditions of a node on a certain path in this decision tree are as follows: the number of weightlessness events is greater than 3, the average turning angle of the aircraft is less than 45 degrees, and the cumulative change in acceleration is greater than 10 m / s². 2 The decision tree of landing prediction model 1040 can use a leaf node as the prediction endpoint (indicating an imminent landing scenario). The leaf node of the prediction endpoint can also be used to output the imminent landing duration. The range of the imminent landing duration output by the prediction endpoint can be determined based on the landing times corresponding to the training set, for example, approximately the average landing times corresponding to the training set. Optionally, during the training phase, a landing time window can be output based on the training set, and the landing times of subsequent time windows can be dynamically updated, thus forming a continuous landing time curve. The range of the imminent landing duration output by the prediction endpoint can be determined based on this curve. For example, if the training set includes 50 similar aircraft imminent landing events, and the average landing time corresponding to these 50 events is 120 seconds, then when the input to landing prediction model 1040 is flight feature data similar to these 50 events, the imminent landing duration output by the prediction endpoint of landing prediction model 1040 will be approximately 120 seconds.

[0334] When the trained landing prediction model 1040 predicts whether an aircraft is about to land, it can take a sequence of flight feature data arranged in chronological order (e.g., from morning to night) as input. Starting from the root node, the landing prediction model 1040 makes judgments layer by layer along the decision tree structure based on the aircraft feature data. If all the input flight feature data satisfies the conditions at each node of the decision tree of the landing prediction model 1040, it can reach the leaf node of the prediction endpoint. At this point, the landing prediction model 1040 outputs a prediction indicating that the aircraft is about to land, and this prediction result may also include the imminent landing duration. If the input flight feature data does not satisfy the conditions at any node, the landing prediction model 1040 will not output a prediction indicating that the aircraft is about to land.

[0335] In one possible implementation, the imminent landing duration output by the landing prediction model 1040 can be between a first time value and a second time value, where the first time value is less than the second time value. Specifically, the imminent landing duration output by the landing prediction model 1040 is relatively short, and the second time value can be less than the time from the start of descent to landing. The first and second time values ​​can be related to the training set of the landing prediction model 1040. For example, the first time value can be a time value that is less than the mean of the landing times corresponding to the training set but the difference is less than a certain threshold, and the second time value can be a time value that is greater than the mean of the landing times corresponding to the training set but the difference is less than a certain threshold.

[0336] When the prediction result output by the landing prediction model 1040 indicates that the aircraft is about to land, the prediction result can be input to the post-processing calibration module 1050. Otherwise, the sensor module 1010, data preprocessing module 1020, feature extraction module 1030 and landing prediction model 1030 can continuously execute the detection algorithm for the aircraft about to land. Figure 11 Taking the prediction result output by the landing prediction model 1040 as an example, which indicates that the aircraft is about to land and the aircraft will land after a duration of t1 (t1 is a positive number), the landing prediction model 1040 can input the prediction result into the post-processing calibration module 1050.

[0337] like Figure 11 As shown, the post-processing calibration module 1050 can be used to correct the prediction results output by the landing prediction model 1040. In one possible implementation, the post-processing calibration module 1050 can correct the prediction results output by the landing prediction model 1040 based on the processed acceleration data and gyroscope data input by the data preprocessing module 1020.

[0338] In one possible implementation, while the electronic device 100 executes the aircraft imminent landing detection algorithm, the landing prediction module 1040 and the post-processing calibration module 1050 can remain operational, for example, running in parallel after the aircraft's cruise phase. The acceleration and gyroscope data used by the landing prediction model 1040 to detect whether the aircraft is in an imminent landing scenario can be acquired during time period 1, which can be the algorithm execution period before the landing prediction model 1040 outputs a prediction indicating that the aircraft is in an imminent landing scenario. The acceleration and gyroscope data used by the post-processing calibration module 1050 to correct the prediction result output by the landing prediction model 1040 can be acquired during time period 2, which can be the algorithm execution period before the post-processing calibration module 1050 makes corrections. Time period 2 can include time period 1, optionally, and time periods following time period 1.

[0339] Understandably, in the period before landing, due to the low altitude, the aircraft is affected by factors such as unstable low-altitude airflow, low speed, and decreased acceleration, resulting in frequent lateral shaking. Based on this physical law, the post-processing calibration module 1050 can compensate for and correct the prediction results of the landing prediction model 1040 based on aircraft shaking detection. In one possible implementation, the post-processing calibration module 1050 can obtain the aircraft shaking situation within time period 2 based on the processed acceleration data and gyroscope data (collected during time period 2) input by the data preprocessing module 1020. When the post-processing calibration module 1050 receives the prediction results sent by the landing prediction model 1040 (in a scenario where the aircraft is about to land and will land after time period t1), it can correct the prediction results sent by the landing prediction model 1040 based on the aircraft shaking situation within time period 2. Optionally, the post-processing calibration module 1050 can correct the prediction result indicating that the aircraft will land after time period t1 to that the aircraft will land after time period t2, where t2 is a positive number. The post-processing calibration module 1050 can output the prediction results of the corrected landing prediction model 1040 (in the scenario where the aircraft is about to land and the aircraft lands after time t2) to the search network module 1060.

[0340] In some examples, the post-processing calibration module 1050, based on the aircraft jitter acquired during time period 2, identifies that the aircraft does not exhibit frequent left-right jitter during time period 3 within time period 2, but does exhibit frequent left-right jitter during time period 4 following time period 3. Time period 3 refers to the period before and after the landing prediction model 1040 outputs its prediction result, which can be represented as the time interval before landing within (t1-a, t1+b), where a and b are positive numbers, and a is less than t1. Time period 4 can be represented as the time interval before landing within (c, d), where c is less than (t1-a), and c and d are positive numbers. Based on the above identification results, the post-processing calibration module 1050 can correct the imminent landing time t1 in the above prediction result to t2, where t2 is less than t1, and t2 can take a value within (c, d).

[0341] Not limited to this, in other examples, the post-processing calibration module 1050 identifies that there is no frequent left and right shaking behavior in time period 2 based on the obtained aircraft shaking situation in time period 2. Therefore, the post-processing calibration module 1050 can determine that it is not in the scenario of the aircraft about to land, and at this time the detection algorithm of the aircraft about to land can be re-executed.

[0342] like Figure 11 As shown, the network search and monitoring module 1060 can receive the prediction results from the corrected landing prediction model 1040. If the corrected prediction results indicate that the aircraft is about to land, the network search and monitoring module 1060 can trigger the scanning of the country code and the network search, for example, by executing... Figure 6 S105-S107, and then set up the network based on the network search results, for example, execute Figure 6 S107.

[0343] exist Figure 11 The aircraft imminent landing detection algorithm shown can train a landing prediction model 1040 using a large amount of real aircraft feature data from imminent landing scenarios. This model is then used to detect whether the aircraft is in an imminent landing scenario and the duration of the impending landing. The flight feature data used is not limited to acceleration and gyroscope data; it incorporates data that effectively reflects important characteristics of the aircraft's flight process (such as weightlessness and turning information), achieving high accuracy and low detection latency. Furthermore, a post-processing calibration module 1050 based on aircraft jitter detection can compensate for and correct the prediction results of the landing prediction model 1040, further improving detection accuracy, achieving a detection accuracy rate of over 98%.

[0344] The following examples illustrate some ways to obtain flight feature data for input into landing prediction models.

[0345] Figure 12A This is a flowchart illustrating the process of acquiring aircraft turning information according to an embodiment of this application. For example... Figure 12A The acquisition process shown is Figure 11 The feature extraction module 1030 shown is used for this purpose. Figure 12A The acquisition process shown may include, but is not limited to, the following steps:

[0346] S401: Electronic device 100 obtains the change in heading angle within time window 2 based on the processed gyroscope data.

[0347] In one possible implementation, the electronic device 100 can acquire gyroscope data in real time through the sensor module, and perform data preprocessing on the gyroscope data to obtain processed gyroscope data. For a specific implementation example, please refer to [link to relevant documentation]. Figure 11 Description of sensor module 1010 and data preprocessing module 1020. Electronic device 100 can determine whether the aircraft is turning using time window 2 (i.e., a time window with a duration of 6). Therefore, electronic device 100 can acquire processed gyroscope data within time window 2, calculate the component / projection of the gyroscope data (three axes) in the direction of gravity (which can be simply referred to as gravity gyroscope data), and integrate the gravity gyroscope data to obtain the change in heading angle within time window 2.

[0348] S402: Electronic device 100 determines whether the change in heading angle within time window 2 is greater than or equal to angle threshold 1.

[0349] In one possible implementation, when the determination result of S402 is yes, that is, the change in heading angle within time window 2 is greater than or equal to the angle threshold 1, the electronic device 100 can determine that the aircraft has turned within time window 2, and thus execute S403. When the determination result of S402 is no, that is, the change in heading angle within time window 2 is less than the angle threshold 1, the electronic device 100 can re-determine whether the aircraft has turned based on the next time window 2, that is, re-acquire the gyroscope data within the next time window 2 and re-execute S401-S402.

[0350] S403: Electronic device 100 determines that the aircraft is turning and obtains the aircraft turning information.

[0351] In one possible implementation, the electronic device 100 can acquire and record the aircraft turning information corresponding to any determined aircraft turn. The aircraft turning information may include, but is not limited to, one or more of the following: number of aircraft turns, aircraft turning time, aircraft turning angle, etc. Among them, the aircraft turning angle includes, for example, but is not limited to: the turning angle of the aircraft in the three axes, the turning angle of the aircraft in the direction of gravity, and the turning angle of the aircraft in the horizontal direction.

[0352] In one possible implementation, after S403, the electronic device 100 can re-determine whether the aircraft has turned based on the next time window 2, that is, re-acquire the processed gyroscope data within the next time window 2 and re-execute S401-S402. The electronic device 100 can acquire aircraft turning information corresponding to multiple time windows 2 (e.g., non-overlapping in time) as flight characteristic data.

[0353] Not limited to Figure 12A In the example shown, in other examples, the electronic device 100 can also determine whether the cumulative amount of gyroscope data (three axes) within the time window 2 (i.e., the amount of angle change within the time window 2) is greater than or equal to the angle threshold 2. When the result of this determination is yes, and the result of S402 is yes, the electronic device 100 determines that the aircraft is turning. The embodiments of this application do not limit the specific determination method for aircraft turning.

[0354] Figure 12B This is a flowchart illustrating the process of acquiring aircraft weightlessness information according to an embodiment of this application. For example... Figure 12B The acquisition process shown is Figure 11 The feature extraction module 1030 shown is used for this purpose. Figure 12B The acquisition process shown may include, but is not limited to, the following steps:

[0355] S501: Electronic device 100 obtains the gravitational acceleration and acceleration magnitude within time window 3 based on the processed acceleration data and gyroscope data.

[0356] In one possible implementation, the electronic device 100 can acquire acceleration data and gyroscope data in real time through the sensor module, and perform data preprocessing on the acceleration data and gyroscope data to obtain processed acceleration data and gyroscope data. For a specific implementation example, please refer to [link to implementation details]. Figure 11 Description of sensor module 1010 and data preprocessing module 1020. Electronic device 100 can determine whether the aircraft is experiencing weightlessness using time window 3 (i.e., a time window with a duration set to duration 7). Therefore, electronic device 100 can acquire processed acceleration data and gyroscope data within time window 3, and calculate the component / projection of the acceleration data (three axes) in the direction of gravity (i.e., gravitational acceleration) based on the acceleration data and gyroscope data, and calculate the magnitude of the acceleration data (i.e., acceleration magnitude) based on the acceleration data.

[0357] S502: Electronic device 100 determines whether the following conditions are met: the gravitational acceleration within time window 3 is less than the weightlessness threshold 1, and the acceleration magnitude within time window 3 is less than the weightlessness threshold 2.

[0358] In one possible implementation, when the judgment result of S502 is yes, that is, the gravitational acceleration within time window 3 is less than the weightlessness threshold 1, and the acceleration magnitude within time window 3 is less than the weightlessness threshold 2, the electronic device 100 can determine that aircraft weightlessness has occurred within time window 3, and thus execute S503. When the judgment result of S502 is no, that is, the gravitational acceleration within time window 3 is greater than or equal to the weightlessness threshold 1, and / or, the acceleration magnitude within time window 3 is greater than or equal to the weightlessness threshold 2, the electronic device 100 can re-determine whether the aircraft has experienced weightlessness based on the next time window 3, that is, re-acquire the acceleration data and gyroscope data within the next time window 3 and re-execute S501-S502.

[0359] S503: Electronic device 100 determines aircraft weightlessness and acquires aircraft weightlessness information.

[0360] In one possible implementation, the electronic device 100 can acquire and record the aircraft weightlessness information corresponding to any instance of determining aircraft weightlessness. The aircraft weightlessness information may include, but is not limited to, one or more of the following: number of weightlessness events, weightlessness duration, and acceleration data during weightlessness. The acceleration data during weightlessness may include, for example, but is not limited to: triaxial acceleration data, the component / projection of the triaxial acceleration data in the direction of gravity (i.e., gravitational acceleration), and the component / projection of the triaxial acceleration data in the horizontal direction (which may be referred to as horizontal acceleration).

[0361] Not limited to Figure 12B In the example shown, in other examples, S502 may also be to determine whether the following conditions are met: the gravitational acceleration within time window 3 is less than the weightlessness threshold 1, and / or the acceleration magnitude within time window 3 is less than the weightlessness threshold 2.

[0362] The following is an example of how electronic device 100 detects an aircraft landing scenario.

[0363] In some embodiments of this application, the aircraft landing detection algorithm can detect the aircraft landing scenario by detecting the aircraft's overweight state and grounding state during the landing phase, achieving high accuracy, for example, an accuracy rate of over 98%, and for example, the time delay between detecting the aircraft landing scenario and the actual landing time is less than 5 seconds. Optionally, the aircraft overweight state can be detected by gravitational acceleration. Optionally, the aircraft grounding state can be detected by one or more sensor feature data. Implementation examples of the above aircraft landing detection algorithm can be found below. Figure 13 .

[0364] Figure 13 This is a flowchart illustrating an aircraft landing detection algorithm provided in an embodiment of this application. Figure 13 The aircraft landing detection algorithm shown can be applied to Figure 3 The electronic device 100 shown. Figure 13 The aircraft landing detection algorithm shown can be applied to Figure 4 The electronic device 100 shown.

[0365] In one possible implementation, the electronic device 100 can trigger the execution of an aircraft landing detection algorithm after detecting one or more of the following scenarios: aircraft takeoff, aircraft cruise, and aircraft imminent landing. For example, the electronic device 100 executes the aircraft imminent landing detection algorithm after detecting an aircraft imminent landing scenario. Not limited to this, in another possible implementation, the electronic device 100 can also execute the aircraft landing detection algorithm when preset triggering conditions for aircraft landing detection are met. For example, the triggering conditions for aircraft landing detection include: the electronic device 100 is powered on, and / or the electronic device 100 is not connected to the network. In this case, an example scenario is: the electronic device 100 is powered off before the aircraft takes off, therefore no aircraft takeoff, aircraft cruise, or aircraft imminent landing scenario is detected; subsequently, when the aircraft is about to land, the electronic device 100 is powered on, at which point the electronic device 100 can begin executing the aircraft landing detection algorithm. This application does not limit the triggering method for executing the aircraft landing detection algorithm.

[0366] Figure 13 The aircraft landing detection algorithm shown may include, but is not limited to, the following steps:

[0367] S601: Electronic device 100 acquires acceleration data and gyroscope data.

[0368] S602: Electronic device 100 performs data preprocessing on acceleration data and gyroscope data, wherein the data preprocessing includes one or more of the following: removing attitude change data, noise filtering, signal smoothing, normalization, and bias removal.

[0369] Figure 13 S601-S602 and Figure 9 Similar to S201-S202, please refer to [link / reference needed]. Figure 9 Explanation of S201-S202.

[0370] Understandably, during the execution of the aircraft landing detection algorithm, i.e. Figure 13 During the process shown, the electronic device 100 can acquire acceleration data and gyroscope data in real time, and perform data preprocessing on the acquired data, i.e., execute S601-S602 in real time. Subsequently, based on the acceleration data and gyroscope data obtained from the real-time execution of S601-S602, the specific detection operations of the aircraft landing detection algorithm are executed, such as executing... Figure 13 S603-S604, S605-S606.

[0371] S603: Electronic device 100 triggers overload detection, wherein the gravitational acceleration is determined based on acceleration data and gyroscope data.

[0372] S604: Electronic device 100 determines whether the gravitational acceleration is greater than or equal to the overweight threshold.

[0373] In one possible implementation, when the electronic device 100 performs overload detection, it can determine the acceleration component (i.e., gravitational acceleration) in the direction of gravity (e.g., the z-axis) based on the acceleration data and gyroscope data obtained in real time during S601-S602, i.e., execute S603. Furthermore, the electronic device 100 can determine whether the determined gravitational acceleration is greater than or equal to a preset overload threshold, i.e., execute S604. Optionally, in S604, the electronic device 100 can determine whether the duration for which the gravitational acceleration is greater than or equal to the overload threshold is greater than or equal to a duration of 8.

[0374] In one possible implementation, when the determination result of S604 is yes, that is, when the gravitational acceleration is greater than or equal to the overweight threshold, the electronic device 100 can determine that the aircraft overweight state has been detected and execute S605. When the determination result of S604 is no, that is, when the gravitational acceleration is less than the overweight threshold, the electronic device 100 can determine that no aircraft landing scenario has been detected (i.e., S608).

[0375] S605: Electronic device 100 detects an overweight state in the aircraft and triggers a grounding detection, wherein the variance of the horizontal acceleration and the magnitude of the acceleration are determined based on acceleration data and gyroscope data.

[0376] S606: Electronic device 100 determines whether the following conditions are met: the variance of horizontal acceleration is greater than or equal to the grounding threshold, and the magnitude of acceleration magnitude meets the preset magnitude condition.

[0377] In one possible implementation, after the electronic device 100 detects an overweight state in the aircraft, it triggers a grounding detection. Optionally, the duration of the grounding detection can be preset. During the grounding detection, the electronic device 100 can execute steps S601-S602 in real time and obtain acceleration data within time window 4 (duration 9), and calculate the acceleration magnitude within time window 4. Furthermore, the electronic device 100 can execute steps S601-S602 in real time and obtain acceleration data and gyroscope data within time window 5 (duration 10), and determine the acceleration components (i.e., horizontal acceleration) in the horizontal direction (e.g., the x-axis and y-axis) based on the acceleration data and gyroscope data within time window 5, then calculate the variance of the horizontal acceleration within time window 5. Durations 9 and 10 are less than or equal to the preset landing detection duration.

[0378] In one possible implementation, for example, within a preset landing detection duration, the electronic device 100 can determine whether the grounding condition is met (i.e., execute S606). This grounding condition may include: the magnitude of the acceleration modulus within time window 4 satisfies a preset modulus condition, and the variance of the horizontal acceleration within time window 5 is greater than or equal to a grounding threshold. The preset modulus condition may include, but is not limited to, the sum of the maximum and minimum acceleration modulus values ​​within time window 4 falling within a first value range (e.g., the first value range is a value R, where R is a positive number), and / or the difference between the maximum and minimum acceleration modulus values ​​within time window 4 falling within a second value range (e.g., the second value range is a value T).

[0379] Among them, time window 4 and time window 5 can be the same or different. For example, if the preset time window 4 is before or after time window 5, it can be understood that when judging whether the grounding condition is met, the specific conditions of acceleration magnitude and the specific conditions of horizontal acceleration variance can be judged in sequence.

[0380] Not limited to Figure 13 The grounding conditions shown in S606 can be further implemented with more or fewer conditions. For example, the grounding conditions may include: the magnitude of the acceleration modulus within time window 4 meets a preset modulus condition, or the variance of the horizontal acceleration within time window 5 is greater than or equal to a grounding threshold.

[0381] In one possible implementation, when the determination result of S606 is yes, i.e., the grounding condition is met, the electronic device 100 can determine that the aircraft has transitioned from an overweight state to an grounded state and execute S607. When the determination result of S606 is no, i.e., the grounding condition is not met, the electronic device 100 can determine that the aircraft grounding state has not been detected, and therefore the aircraft landing scenario has not been detected (i.e., S608).

[0382] S607: Electronic device 100 detected the aircraft's grounding status and detected the aircraft landing scenario based on the aircraft's overweight status and grounding status.

[0383] In one possible implementation, the electronic device 100 first detects the aircraft's overweight state based on S603-S604, and then detects the aircraft's grounding state based on S605-S606, so that the electronic device 100 can determine that an aircraft landing scenario has been detected.

[0384] S608: Electronic equipment 100 did not detect an aircraft landing scenario.

[0385] In one possible implementation, if electronic device 100 does not detect an aircraft overweight condition based on S603-S604, or if electronic device 100 initially detects an aircraft overweight condition based on S603-S604 but does not detect an aircraft landing condition based on S605-S606, then electronic device 100 can determine that an aircraft landing scenario has not been detected. In this case, electronic device 100 can directly re-execute the process. Figure 13 The process is shown below.

[0386] Not limited to Figure 13 As shown in the example, in other examples, electronic device 100 can also trigger overweight detection and grounding detection simultaneously. If both aircraft overweight and aircraft grounding conditions are detected, an aircraft landing scenario is detected.

[0387] exist Figure 13The aircraft landing detection algorithm shown first determines whether the aircraft is in an overweight state. If the result is yes, it then determines whether the aircraft is in a landing state. Furthermore, the landing conditions used for landing detection can be multi-condition constraints based on various acceleration characteristics. For example, the variance of horizontal acceleration must be greater than or equal to a landing threshold, and the magnitude of the acceleration magnitude must meet a preset magnitude condition. Specifically, if the variance of horizontal acceleration is greater than or equal to the landing threshold, the aircraft is not in a steady state and is highly likely in a landing scenario. The magnitude of the acceleration magnitude during aircraft landing follows a specific pattern; the magnitude meeting the preset magnitude condition indicates that the aircraft conforms to this specific pattern and is highly likely to be in a landing scenario. Therefore, this algorithm can effectively identify the key states during aircraft landing (overweight state and landing state), achieving a high-accuracy and low-latency aircraft landing detection algorithm.

[0388] In the aircraft scene detection algorithm described above, after acquiring sensor data through the sensor module, the electronic device 100 first performs data preprocessing on the sensor data, and then obtains relevant judgment data (such as gravitational acceleration, acceleration magnitude, horizontal acceleration, acceleration variance, range of acceleration magnitude, etc.) based on the processed sensor data. Subsequently, the algorithm performs specific judgments based on the relevant judgment data. However, this is not a limitation. In some examples, the electronic device 100 may also perform data preprocessing on the relevant judgment data. In other examples, the electronic device 100 may only perform data preprocessing on the relevant judgment data without preprocessing the sensor data. This application embodiment does not limit this.

[0389] The detection algorithm for the above aircraft scene is for illustrative purposes only and should not be construed as limiting. For example, the relevant judgment data used to perform the specific judgment of the algorithm may be more or less, the judgment conditions of the algorithm may be more or less, the judgment conditions of the algorithm may be changed, and optionally replaced with judgment conditions with the same effect, etc.

[0390] Understandably, electronic device 100 will periodically search for a network when there is no cellular network (e.g., it is powered on but not connected to a cellular network, or the cellular network is disconnected). In the scenario of air travel, electronic device 100 carried by a user in high altitude does not have a cellular network. Therefore, when electronic device 100 is powered on and airplane mode is not activated, electronic device 100 will periodically search for a network (this can be called a second network search method). See below for a specific example. Figure 14 This will increase the power consumption of electronic devices 100, affecting the user experience.

[0391] Figure 14 An exemplary diagram illustrates a web search process.

[0392] like Figure 14 As shown, after takeoff, electronic devices 100% lose network connectivity. At this point, you can use the second network search method to search for a network until you successfully establish a connection. For example... Figure 14 The second search method shown includes: first, searching historical frequency points multiple times; if no results are found, then searching historical frequency points and preferred frequency bands multiple times; if no results are found, then searching historical frequency points and the entire frequency band. Figure 14 The following explanation uses searching historical frequency points and the entire frequency band after an aircraft lands as an example. The preferred frequency band can be a band preset by the electronic device 100, such as a band with good network quality. Understandably, since there is no cellular network when the aircraft is flying at high altitudes, therefore... Figure 14 During the flight of the aircraft shown, the electronic device 100 will fail to search for historical frequency bands and preferred frequency bands according to the second search network method, resulting in unnecessary power consumption of the electronic device 100.

[0393] In some embodiments of this application, the electronic device 100 can use a first network search method to search for networks during aircraft flight, and a second network search method to search for networks after the aircraft flight (which can be understood as resuming normal network search). In one case, the network search frequency 1 in the first network search method is less than the network search frequency 2 in the second network search method; in another case, the network search frequency 1 in the first network search method is 0, that is, the first network search method is no network search. In other words, compared to before adjusting the network search method, the electronic device 100 can reduce the network search frequency or stop searching for networks during aircraft flight, thereby saving the power consumption of the electronic device 100 (e.g., saving more than 30% of power consumption) and improving the user experience.

[0394] In one possible implementation, the electronic device 100 (e.g., powered on but not in flight mode) can use a first network search method after detecting an aircraft takeoff scenario and before detecting an aircraft about to land scenario. After detecting an aircraft about to land scenario, the electronic device 100 can revert to a second network search method, which can be understood as resuming normal network search. See below for specific examples. Figure 15A and Figure 15B .

[0395] Figure 15A and Figure 15B These are schematic diagrams illustrating some of the web search processes provided in the embodiments of this application.

[0396] like Figure 15AAs shown, after the aircraft takes off, electronic device 100 loses network connection. Since electronic device 100 detects the aircraft takeoff scenario, it begins searching for a network using a first network search method. Then, detecting the aircraft's impending landing, electronic device 100 can resume searching for a network using a second network search method. The network search frequency 1 in the first network search method is less than the network search frequency 2 in the second network search method.

[0397] For example, Figure 14 The electronic equipment 100 uses a second search method during flight after takeoff. Figure 15A In the process, electronic device 100 uses the first network search method after detecting an aircraft takeoff scenario and before detecting an aircraft about to land scenario. Assume... Figure 15A The frequency points / bands searched in the first network search method shown are... Figure 14 The frequency points / bands searched in the second network search method shown are similar. Figure 15A The first network search method shown includes first searching historical frequency points, and if no results are found, then searching historical frequency points again and searching for preferred frequency bands. Therefore, Figure 15A The frequency of searching historical points in the first search method shown can be higher than... Figure 14 The second search method shown has a low frequency of searching historical points. Figure 15A The frequency of searching historical frequency points and preferred frequency bands in the first search method shown can be higher than that of searching for historical frequency points and preferred frequency bands. Figure 14 The second search method shown has a low frequency of searching historical frequency points and preferred frequency bands.

[0398] Figure 14 The electronic device 100 uses a second search network method before the aircraft lands (including the period from the moment the aircraft is about to land to the moment it lands). Figure 15A In the middle, after electronic device 100 detects that the aircraft is about to land, it uses the second search network method. Assuming... Figure 15A The second search method shown includes the search target frequency. In one case, Figure 15A The frequency point / band searched in the second network search method shown is... Figure 14 The frequency points / bands searched in the second search method shown are similar; therefore, the target frequencies include historical frequency points, preferred frequency bands, and the entire frequency band. Figure 15A The second search method shown can search for historical frequency points / preferred frequency bands / full frequency bands with frequencies that are compatible with... Figure 14 The second search method shown searches for the same frequencies in historical frequency points / preferred frequency bands / full frequency bands. However, it is not limited to this; in another case, the target frequency band includes... Figure 6 The frequencies / bands used by the search network in S105-S107 shown (such as the frequencies / bands of candidate airports corresponding to the first country code) are therefore... Figure 15AIn the second search method shown, the frequency of the target frequency band can be the same as... Figure 14 The second search method shown has the same frequency for searching historical frequency points / preferred frequency bands / full frequency bands.

[0399] like Figure 15B As shown, after the aircraft takes off, electronic device 100 loses network connection. Because electronic device 100 detects the aircraft takeoff scenario, it does not perform a network search. Then, electronic device 100 detects the aircraft is about to land, therefore, it can resume network searching using the second method. Figure 15B For instructions on using the second search method after the Chinese electronic equipment 100 detects an impending aircraft landing, please refer to [link to documentation]. Figure 15A Instructions for using the second search method.

[0400] In another possible implementation, the electronic device 100 (e.g., powered on but not in flight mode) can use a first network search method after detecting aircraft takeoff and cruise scenarios but before detecting an imminent landing scenario. After detecting an imminent landing scenario, the electronic device 100 can revert to a second network search method, which can be understood as resuming normal network search. See below for specific examples. Figure 16A and Figure 16B .

[0401] Figure 16A and Figure 16B This is a schematic diagram of some other web searching processes provided in the embodiments of this application.

[0402] like Figure 16A As shown, after the aircraft takes off, electronic device 100 loses network connection. At this time, electronic device 100 detects the aircraft takeoff scenario and can search for a network using the second network search method. Then, electronic device 100 detects the aircraft cruising scenario, and therefore, electronic device 100 will start searching for a network using the first network search method. Then, electronic device 100 detects the aircraft is about to land, and therefore, electronic device 100 can resume searching for a network using the second network search method. The network search frequency 1 in the first network search method is less than the network search frequency 2 in the second network search method. Figure 16A For instructions on using the second search method after the Chinese electronic device 100 detects an aircraft takeoff scenario and before it detects an aircraft cruise scenario, please refer to [link to documentation]. Figure 14 Instructions for using the second search method. Figure 16A For instructions on how the China Electronics System 100 uses the first search method after detecting an aircraft cruising scenario, please refer to [link to documentation]. Figure 15A Instructions for using the first search network method after the electronic device 100 detects an aircraft takeoff scenario. Figure 16AFor instructions on using the second search method after the Chinese electronic equipment 100 detects an impending aircraft landing, please refer to [link to documentation]. Figure 15A Instructions for using the second search method.

[0403] like Figure 16B As shown, after the aircraft takes off, electronic device 100 loses network connection. At this time, electronic device 100 detects the aircraft takeoff scenario and can perform a network search using the second network search method. Then, electronic device 100 detects the aircraft cruising scenario, therefore, electronic device 100 does not perform a network search. Then, electronic device 100 detects the aircraft is about to land, therefore, electronic device 100 can resume using the second network search method. Figure 16B For instructions on using the second search method after the Chinese electronic device 100 detects an aircraft takeoff scenario and before it detects an aircraft cruise scenario, please refer to [link to documentation]. Figure 14 Instructions for using the second search method. Figure 16B For instructions on using the second search method after the Chinese electronic equipment 100 detects an impending aircraft landing, please refer to [link to documentation]. Figure 15A Instructions for using the second search method.

[0404] Not limited to the above-described embodiments, in another possible implementation, the electronic device 100 (e.g., powered on but not in flight mode) can use a first network search method after detecting an aircraft cruise scenario but before detecting an aircraft landing scenario. After detecting an aircraft landing scenario, the electronic device 100 reverts to using a second network search method. For example, if the electronic device 100 is powered off before takeoff and no aircraft takeoff scenario is detected, and after takeoff the electronic device 100 is powered on by the user (e.g., the flight mode of the electronic device 100 is also off), the electronic device 100 can detect both the aircraft cruise scenario and the aircraft landing scenario.

[0405] In another possible implementation, the electronic device 100 (e.g., powered on but not in flight mode) can use a first network search method after detecting an aircraft takeoff scenario and / or an aircraft cruise scenario, but before detecting an aircraft landing scenario. After detecting an aircraft landing scenario, the electronic device 100 reverts to using a second network search method. For example, if the electronic device 100 is powered off by the user after the aircraft cruise phase and before the aircraft is about to land, it cannot detect the aircraft about to land scenario. If the electronic device 100 is powered on by the user after the aircraft is about to land phase, it can detect the aircraft landing scenario.

[0406] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can implement the steps performed by the electronic device 100 in the above-described method embodiments.

[0407] This application also provides a computer program product, including a computing program, which, when run on a computer, enables the computer to perform the steps executed by the electronic device 100 in the above-described method embodiments.

[0408] This application also provides a chip system, which includes a processing circuit interface circuit. The interface circuit receives code instructions and transmits them to the processing circuit. The processing circuit executes the code instructions to enable the chip system to perform the steps executed by the electronic device 100 in any method embodiment of this application. The chip system can be a single chip or a chip module composed of multiple chips.

[0409] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A network access method applied to electronic devices, characterized in that, The method includes: The system anticipates that the aircraft will land after the first hour, and then scans the country code. If a first country code is detected, a search is performed based on the search parameters of the candidate airports corresponding to the first country code, and first search information is obtained, wherein the candidate airports include one or more airports; Access to the first network is based on the information obtained from the first search network.

2. The method as described in claim 1, characterized in that, The method further includes: The sensor module collects the first acceleration data and the first gyroscope data; Flight characteristic data is determined based on the first acceleration data and the first gyroscope data, wherein the flight characteristic data includes one or more of the following: aircraft turning information, aircraft weightlessness information, data obtained by statistically analyzing and / or calculating the first acceleration data, and data obtained by statistically analyzing and / or calculating the first gyroscope data; The flight characteristic data is input into the landing prediction model, and the prediction results of the landing prediction model are obtained; The prediction that the aircraft will scan the country code upon landing after the first time interval includes: If the landing prediction model indicates that the aircraft will land after the first duration, scan the country code.

3. The method as described in claim 2, characterized in that, After inputting the flight characteristic data into the landing prediction model and obtaining the prediction result of the landing prediction model, the method further includes: The aircraft vibration is obtained based on the second acceleration data and the second gyroscope data; The prediction results of the landing prediction model are corrected based on the aircraft shaking conditions. If the landing prediction model indicates that the aircraft will land after the first duration, scanning the country code includes: If the corrected landing prediction model indicates that the aircraft will land after the first duration, scan the country code.

4. The method according to any one of claims 1-3, characterized in that, The scanning of the country code includes: Scan the country code in the preset frequency band.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: Before the predicted landing time of the aircraft, the first flight information is obtained, which includes the first destination and the first landing airport; Determine the second country code of the first destination and the search parameters of the candidate airports corresponding to the second country code, wherein the candidate airports corresponding to the second country code include the first landing airport; If a first country code is detected, a network search is performed based on the network search parameters of the candidate airports corresponding to the first country code, including: If the first country code and the second country code are the same, a network search is performed based on the network search parameters of the first landing airport; If the search based on the search parameters of the first landing airport fails, a search based on the search parameters of the first candidate airport is performed. The first candidate airport includes one or more other candidate airports besides the first landing airport among the candidate airports corresponding to the second country code.

6. The method as described in claim 5, characterized in that, If a first country code is detected, a network search is performed based on the network search parameters of the candidate airports corresponding to the first country code, including: If the first country code and the second country code are different, obtain the search parameters of the candidate airport corresponding to the first country code, and perform a search based on the search parameters of the candidate airport corresponding to the first country code.

7. The method according to any one of claims 1-6, characterized in that, If a first country code is detected, a network search is performed based on the network search parameters of the candidate airports corresponding to the first country code, including: If the first country code and the first search parameters corresponding to the first country code are detected, a search is performed based on the first search parameters, and a search is also performed based on the search parameters of the candidate airports corresponding to the first country code.

8. The method according to any one of claims 1-7, characterized in that, The prediction that the aircraft will scan the country code upon landing after the first time interval includes: With the flight mode of the electronic device enabled, it is predicted that the aircraft will land after the first duration, and the country code is scanned. If a first country code is detected, a network search is performed based on the network search parameters of the candidate airports corresponding to the first country code, and first network search information is obtained, wherein the candidate airports include one or more airports; accessing the first network based on the first network search information includes: In response to turning off the flight mode of the electronic device, if the first country code is detected, a network search is performed based on the network search parameters of the candidate airport corresponding to the first country code, and the first network search information is obtained. Then, the device accesses the first network based on the first network search information.

9. The method according to any one of claims 1-8, characterized in that, Before performing a network search based on the search parameters of the candidate airports corresponding to the first country code and obtaining the first network search information, if a first country code is scanned, the method further includes: If the first country code is detected, a network search is performed based on the first country code, and the second network search information is obtained; If a first country code is detected, a network search is performed based on the network search parameters of the candidate airports corresponding to the first country code, including: If the first country code is detected, a network search is performed based on the network search parameters of the candidate airports corresponding to the first country code, and the network in the second network search information is also searched.

10. The method according to any one of claims 1-9, characterized in that, The method further includes: Before the predicted landing time of the aircraft is reached, the electronic device receives a search list sent by the cloud server. The search list includes one or more country codes and search parameters for candidate airports corresponding to each of the one or more country codes. The search parameters include one or more of the following: Public Land Mobile Network (PLMN), Radio Access Technology (RAT), frequency band or frequency point. The search parameters for the candidate airports corresponding to the first country code are obtained by the electronic device from the search list.

11. The method according to any one of claims 1-10, characterized in that, The method further includes: After accessing the first network based on the first network search information, the network information of the first network is sent to the cloud server. The network information of the first network includes one or more of the following: the first country code corresponding to the first network, the PLMN corresponding to the first network, the PLMN registration information corresponding to the first network, the standard of the first network, the frequency band of the first network, the frequency point of the first network, the cell identifier corresponding to the first network, the location information of the electronic device accessing the first network, and the service experience information of the electronic device using the first network.

12. The method according to any one of claims 1-11, characterized in that, The method, which predicts that the aircraft will land after the first time interval, before scanning the country code, further includes: An aircraft takeoff scenario was detected, and / or an aircraft cruise scenario was detected; In response to the detected aircraft takeoff scenario and / or aircraft cruise scenario, the aircraft landing time is predicted.

13. The method according to any one of claims 1-12, characterized in that, The method further includes: After the predicted landing of the aircraft after the first time period, the landing scene of the aircraft was detected; The access to the first network based on the first search information includes: After detecting an aircraft landing scenario, the system accesses the first network based on the first search network information.

14. The method as described in claim 12, characterized in that, The detected aircraft takeoff scenario includes: Third acceleration data is acquired through the sensor module; Detect whether the aircraft is in a taxiing state based on the third acceleration data; If the aircraft is detected to be in the taxiing state, the system will determine whether the aircraft is in the climbing state based on the fourth acceleration data and the third gyroscope data. If the aircraft is detected to be in a climb state, then the aircraft takeoff scenario is detected.

15. The method as described in claim 14, characterized in that, The step of detecting whether the aircraft is in a taxiing state based on the third acceleration data includes: Determine whether the duration of the magnitude of the third acceleration data within the first threshold range is greater than or equal to the second duration; If the duration of the magnitude of the third acceleration data within the first threshold range is greater than or equal to the second duration, the aircraft is detected to be in the taxiing state. The step of detecting whether the aircraft is in a climb state based on the fourth acceleration data and the third gyroscope data includes: Based on the fourth acceleration data and the third gyroscope data, it is determined whether the preset climbing conditions are met. The climbing conditions include one or more of the following: the duration of the magnitude of the fourth acceleration data within a second threshold range is greater than or equal to a third duration; the duration of the first gravitational acceleration within a third threshold range is greater than or equal to a fourth duration; and the duration of the variance of the fourth acceleration data within a fourth threshold range is greater than or equal to a fifth duration. The first gravitational acceleration is determined based on the fourth acceleration data and the third gyroscope data, and the first gravitational acceleration is the component of the fourth acceleration data in the direction of gravity. If the climb conditions are met, the aircraft is detected to be in a climb state.

16. The method as described in claim 12, characterized in that, The detected aircraft cruise scenario includes: After detecting the aircraft takeoff scenario, it is determined whether the preset waiting conditions are met, wherein the waiting conditions include: the aircraft is in a stable state, and / or the time elapsed after the aircraft takeoff scenario is detected is greater than or equal to the sixth time period. If the waiting conditions are met, the fifth acceleration data is collected through the sensor module within the first time window, and the range of the magnitude of the fifth acceleration data is determined. Determine whether the range of the magnitude of the fifth acceleration data is less than a preset range threshold; If the range of the magnitude of the fifth acceleration data is less than the preset range threshold, the aircraft cruise scenario is detected.

17. The method as described in claim 13, characterized in that, The detected aircraft landing scenario includes: The sensor module collects sixth acceleration data and fourth gyroscope data; The system detects whether the aircraft is in a state of g-force during landing based on the sixth acceleration data and the fourth gyroscope data. If an overweight state is detected during the aircraft's landing, the aircraft is checked for grounding based on the seventh acceleration data and the fifth gyroscope data. If the aircraft is detected to be in a grounding state, the aircraft landing scenario is detected.

18. The method as described in claim 17, characterized in that, The step of detecting whether the aircraft is in a state of g-force during landing based on the sixth acceleration data and the fourth gyroscope data includes: The second gravitational acceleration is determined based on the sixth acceleration data and the fourth gyroscope data, wherein the second gravitational acceleration is the component of the sixth acceleration data in the direction of gravity; Determine whether the second gravitational acceleration is greater than or equal to a preset overgravity threshold; If the second gravitational acceleration is greater than or equal to the overweight threshold, an overweight state is detected during the aircraft's landing. The process of detecting whether the aircraft is in a grounding state based on the seventh acceleration data and the fifth gyroscope data includes: Based on the seventh acceleration data and the fifth gyroscope data, it is determined whether a preset grounding condition is met. The grounding condition includes: the variance of the first horizontal acceleration is greater than or equal to a preset grounding threshold, and / or, the magnitude of the seventh acceleration data satisfies a preset magnitude condition. The first horizontal acceleration is determined based on the seventh acceleration data and the fifth gyroscope data, and the first horizontal acceleration is the horizontal component of the seventh acceleration data. The preset magnitude condition includes: the sum of the maximum and minimum magnitudes of the seventh acceleration data is within a first value range, and / or, the difference between the maximum and minimum magnitudes of the seventh acceleration data is within a second value range. If the grounding conditions are met, the aircraft is detected to be in the grounding state.

19. The method according to any one of claims 1-18, characterized in that, The method further includes: After detecting an aircraft takeoff scenario, before predicting that the aircraft will land a certain time later, a first search method is used; after predicting that the aircraft will land a certain time later, a second search method is used; or... After detecting an aircraft takeoff scenario and an aircraft cruise scenario, before predicting that the aircraft will land after a first period of time, a first search network method is used; after predicting that the aircraft will land after a first period of time, a second search network method is used. Wherein, the search frequency in the first search method is less than the search frequency in the second search method, or the first search method is no search and the second search method is search.

20. An electronic device, characterized in that, It includes a transceiver, a processor, and a memory, the memory being used to store a computer program, and the processor calling the computer program to perform the steps of the method as described in any one of claims 1-19.

21. A computer storage medium, characterized in that, The computer storage medium stores a computer program, which, when executed by a processor, implements the method as described in any one of claims 1-19.

22. A computer program product, characterized in that, When the computer program product is run on a processor, it is used to implement the method as described in any one of claims 1-19.

23. A chip system, characterized in that, The method includes a processing circuit and an interface circuit, wherein the interface circuit is used to receive code instructions and transmit them to the processing circuit, and the processing circuit is used to execute the code instructions to perform the method as described in any one of claims 1-19.

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