A location-based service implementation method, data processing method and device

Abstract

This application discloses a location-based service implementation method, data processing method, and apparatus. It includes: when a first condition is met, a terminal acquires the cell signal of its current location; the terminal determines location information of its current location based on the cell signal; and the terminal executes a service matching the current location based on the location information.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a service implementation method, data processing method and apparatus based on location positioning. Background Art

[0002] With the rapid development of the internet, location-based services (LBS) are becoming increasingly widespread. Key technologies for LBS include indoor positioning and scene recognition. Indoor positioning refers to determining the coordinates of a terminal in an indoor environment, while scene recognition refers to determining the application scene to which the terminal belongs in an indoor environment (e.g., whether the terminal has just entered the indoor environment or is about to leave it). Scene recognition requires location positioning as its foundation.

[0003] Location positioning or scene recognition within subway stations is a typical application of location services. As a major urban transportation tool, subway stations are closely related to people's lives, and location services around subway stations can bring more convenience and a better user experience.

[0004] In subway stations or similar scenarios, how to better achieve scene recognition or location positioning, and thus provide better services to users and improve their experience, is a problem that needs to be solved. Summary of the Invention

[0005] This application provides a location-based service implementation method, a data processing method, and an apparatus.

[0006] In a first aspect, a location-based service implementation method is provided, comprising: when a first condition is met, a terminal acquires a cell signal of its current location; the terminal determines location information of its current location based on the cell signal; and the terminal executes a service matching the current location based on the location information.

[0007] Optionally, the location information may include location description information or location identifier. Unlike location coordinate information, location description information and location identifier can be predefined information used to distinguish locations; for example, the location information may be a subway station name or a subway station ID.

[0008] In the above implementation, on the one hand, since the terminal only performs location positioning when the first condition is met, invalid location positioning can be avoided, thereby reducing the power consumption of the terminal; on the other hand, the terminal executes services that match the current location based on the current location, which can improve the user experience. For example, when the current location is determined to be the entrance or exit of a subway station, the terminal can display the identification code for subway payment on the terminal screen to facilitate the user to use the identification code for payment.

[0009] In one possible implementation, the terminal determines the location information of the current location based on the cell signal, including: the terminal determines the location information corresponding to the cell signal of the current location based on the correspondence between cell signals and location information.

[0010] In one possible implementation, the correspondence between the cell signal and the location information includes the correspondence between the cell signal identifier and the location information; determining the location information corresponding to the cell signal at the current location includes: determining the location information corresponding to the identifier of the cell signal based on the identifier of the cell signal at the current location.

[0011] In one possible implementation, the correspondence between the cell signal and location information includes the correspondence between the cell signal identifier and strength and the location information; determining the location information corresponding to the cell signal at the current location includes: determining the location information corresponding to the cell signal identifier and strength based on the cell signal identifier and strength at the current location.

[0012] In one possible implementation, the location information includes subway station location information, which includes subway station signage information and subway station scene information. The subway station scene information includes subway station entrance signage, subway station exit signage, or subway station interior signage.

[0013] In one possible implementation, satisfying the first condition includes: the location positioning opportunity arrives and the location positioning initiation condition is met. In the above implementation, location positioning is only performed when the first condition is met, thereby avoiding invalid location positioning operations and saving terminal power consumption.

[0014] In one possible implementation, the arrival of the location positioning timing includes: the terminal turning on the screen and unlocking the screen; or, the terminal detecting continuous walking motion while the screen is on; or, the terminal detecting a change in the cell it is in while the screen is on; or, the terminal being in a screen-off state being periodically woken up.

[0015] In one possible implementation, satisfying the location positioning initiation condition includes at least one of the following:

[0016] The cell identifier contained in the cell signal received when the terminal is woken up is different from the cell identifier contained in the cell signal received before being woken up.

[0017] The cell identifiers contained in the cell signals received by the terminal are not included in the scene identification blocking list, which is used to store the identifiers of cells that do not require scene identification.

[0018] The terminal is in a non-vehicle-riding state.

[0019] In one possible implementation, the method further includes: if the terminal fails to locate itself based on the cell signal of the current location and the number of failures reaches a set threshold, then the cell identifier in the cell signal of the current location is added to the scene identification masking list.

[0020] In the above implementation, if location positioning fails when using the cell signal of the current location and the number of identification attempts reaches a set threshold, it indicates that location positioning can no longer be performed based on the cell signal. Therefore, the cell identifier in the cell signal can be added to the scene identification masking list to avoid subsequent invalid location positioning, thereby saving terminal power consumption.

[0021] In one possible implementation, the terminal performs a service matching the current location based on the location information, including: if the location indicated by the location information is the entrance or exit of a subway station, the terminal displays an identification code for subway payment on the screen.

[0022] In the above implementation method, if the identified location is a subway station entrance or exit, the terminal can automatically display the identification code for subway payment on the screen to facilitate the user's payment.

[0023] In one possible implementation, the terminal performs a service matching the current location based on the location information, including: if the location indicated by the location information is inside a subway station of a first subway station, the terminal obtains the predicted time information of the subway train arriving at the first subway station, and displays the predicted time information on the screen or broadcasts the predicted time information via voice.

[0024] In the above implementation, if the identified location is inside a subway station, the terminal can automatically obtain the predicted arrival time of the subway train at that station and broadcast it via voice or display it on the screen to help users understand the train's arrival time.

[0025] In one possible implementation, the terminal executes a service matching the current location based on the location information, including: if the scenario indicated by the location information is inside a subway station of the second subway station, and the movement state detected by the terminal is a riding state, then the terminal displays an arrival reminder on the screen or broadcasts the arrival reminder via voice, the arrival reminder being used to indicate arrival at the second subway station.

[0026] In the above implementation, if the identified location is inside a subway station and the terminal detects that the current movement state is a passenger state, the terminal can automatically provide an arrival reminder to facilitate the user's boarding.

[0027] In one possible implementation, the method further includes: the terminal detecting a first triggering event and initiating data acquisition in response to the first triggering event; the terminal recording the correspondence between cell signals and location information based on the received cell signals; and the terminal ending the data acquisition.

[0028] In the above implementation, the terminal collects data to obtain data for location positioning. This allows the data to be obtained based on user behavior habits, such as commuting habits or routes. When location positioning is performed based on the data collected by the terminal, it can meet the user's needs.

[0029] In one possible implementation, the first triggering event includes: the terminal obtaining entry permission through a first device set at the entrance of the subway station, thereby enabling data collection to be started when the terminal (user) enters the subway station, in order to collect cell signals in a specific area (such as the subway station).

[0030] In one possible implementation, the terminal terminates the data acquisition by: detecting a second trigger event; and responding to the second trigger event to terminate the data acquisition. This implementation allows for event-driven termination of the data acquisition process. Since the data acquisition process is started and terminated under event-driven conditions, it is possible to control data acquisition within a specific time and / or space, thereby saving terminal power consumption and enabling targeted data acquisition.

[0031] In one possible implementation, the second triggering event includes: the terminal obtaining exit permission through a second device installed at the subway station exit, thereby ending data collection upon exiting the station, allowing data collection to be performed within a certain space; or a first timer timing out, the first timer being started by the terminal in response to the first triggering event, thereby controlling the duration of data collection to avoid excessive power consumption of the terminal during the data collection process; or a second timer timing out, the second timer being started by the terminal sensing leaving the second area, thereby allowing data collection to continue for a period of time even after the terminal senses leaving the second area.

[0032] In one possible implementation, the correspondence between the cell signal and the location information is stored in a collection of data, which includes at least one data record; the method further includes: the terminal obtaining a location data set for location positioning based on the data records in the collection of data that meet the confidence requirements, the location data set including at least one data record, and each data record in the location data set storing the correspondence between the cell signal and the location information.

[0033] In the above implementation method, a location data set for location positioning is generated based on data records that meet the set confidence requirements, which can ensure the reliability of location positioning.

[0034] Secondly, a data processing method is provided, comprising: a terminal detecting a first triggering event, and initiating data acquisition in response to the first triggering event, wherein the first triggering event includes the terminal sensing entry into a first area; the terminal recording the correspondence between cell signals and location information based on received cell signals; and the terminal ending the data acquisition.

[0035] In the above implementation, on the one hand, the data acquisition process is started under event-driven conditions, so the data acquisition can be controlled to take place within a certain time and / or space, thereby saving terminal power consumption and allowing for targeted data acquisition; on the other hand, the acquired data is consistent with the user's behavioral habits and provides a data foundation and source for obtaining data for location positioning based on the acquired data (such as the correspondence between cell signals and location information).

[0036] In one possible implementation, the first triggering event includes: the terminal obtaining entry permission through a first device located at the entrance of the subway station.

[0037] In one possible implementation, the terminal terminates the data acquisition by: the terminal detecting a second trigger event; and the terminal terminating the data acquisition in response to the second trigger event.

[0038] In one possible implementation, the second triggering event includes: the terminal sensing leaving the second area; or a first timer timeout, the first timer being started by the terminal in response to the first triggering event; or a second timer timeout, the second timer being started when the terminal senses leaving the second area.

[0039] In one possible implementation, the terminal senses an event of leaving the second area by: the terminal obtaining exit permission through a second device located at the subway station exit.

[0040] In one possible implementation, the terminal records the correspondence between the received cell signal and location information, including: the terminal generating a first data record in response to the first triggering event, the first data record being used to store the correspondence between the cell signal received by the terminal and the location information of the terminal's current location; the terminal generating a second data record in response to receiving the cell signal, the second data record being used to store information about the cell signal received by the terminal; and the terminal generating a third data record in response to sensing leaving the second area, the third data record being used to store the correspondence between the cell signal received by the terminal and the location information of the terminal's current location.

[0041] In one possible implementation, the first data record is an entry data record, which includes: a community identifier and subway station location information; the second data record is an in-station data record, which includes: a community identifier; and the third data record is an exit data record, which includes: a community identifier and subway station location information.

[0042] Optionally, the inbound data record, the outbound data record, and the in-station data record may further include at least one of the following: a tracking area identifier, an operator identifier, and a country code, wherein the tracking area identifier, the operator identifier, and the country code are derived from the cell signal received by the terminal.

[0043] Optionally, the subway station location information in the entry data record, the exit data record, and the in-station data record may also include: the city name of the city where the subway station is located.

[0044] In one possible implementation, the inbound data record, the in-station data record, and / or the outbound data record may further include at least one of the following: acquisition time, number of acquisitions, signal strength, and motion state detected by the terminal.

[0045] In one possible implementation, the entry data record further includes evaluation information, which includes at least one of the following: successful verification count, failed verification count, and recall rate. The successful verification count is the number of times the terminal successfully verifies the location result when it senses entering the subway station; the failed verification count is the number of times the terminal fails to verify the location result when it senses entering the subway station; and the recall rate is determined based on the successful verification count and the failed verification count. And / or, the exit data record further includes evaluation information, which includes at least one of the following: successful verification count, failed verification count, and recall rate. The successful verification count is the number of times the terminal successfully verifies the location result when it senses leaving the subway station; the failed verification count is the number of times the terminal fails to verify the location result when it senses leaving the subway station; and the recall rate is determined based on the successful verification count and the failed verification count.

[0046] Optionally, the method further includes: when the terminal senses entry into a subway station, the terminal performs scene recognition based on the cell identifier contained in the received cell signal to obtain the identified subway station location information; if the subway station location information obtained based on scene recognition is the same as the subway station location information queried based on the POI returned by the first device at the entrance (such as the entrance gate), then the terminal updates the number of successful verifications in the entry data record, and updates the recall rate in the entry data record based on the number of failed verifications in the entry data record and the updated number of successful verifications; otherwise, the terminal updates the number of failed verifications in the entry data record, and updates the recall rate in the entry data record based on the number of successful verifications in the entry data record and the updated number of failed verifications.

[0047] Optionally, the method further includes: when the terminal senses leaving the subway station, the terminal performs scene recognition based on the cell identifier contained in the received cell signal to obtain the identified subway station location information; if the subway station location information obtained based on scene recognition is the same as the subway station location information queried based on the POI returned by the second device at the exit (such as the exit gate), then the terminal updates the number of successful verifications in the exit data record, and updates the recall rate in the exit data record based on the number of failed verifications in the exit data record and the updated number of successful verifications; otherwise, the terminal updates the number of failed verifications in the exit data record, and updates the recall rate in the exit data record based on the number of successful verifications in the exit data record and the updated number of failed verifications.

[0048] In one possible implementation, the method further includes: adding subway station location information to the station data records between the first and second station data records adjacent to the entry data record, arranged in chronological order of collection time, wherein the added subway station location information is the same as the subway station location information in the entry data record; wherein the second station data record is the first station data record in the entry data records arranged in chronological order of collection time whose movement state is "riding"; adding subway station location information to the station data records between the third and fourth station data records adjacent to the exit data record, arranged in chronological order of collection time, wherein the added subway station location information is the same as the subway station location information in the exit data record; wherein the fourth station data record is the first station data record in the entry data records arranged in chronological order of collection time whose movement state is "riding".

[0049] In one possible implementation, the method further includes: determining a first duration from the entry data record to the first passenger status data record in chronological order; adding the first duration to the dwell duration set corresponding to the entry subway station; determining an entry dwell duration threshold corresponding to the entry subway station based on the dwell duration in the updated dwell duration set corresponding to the entry subway station; if the first duration is greater than the entry dwell duration threshold, selecting the passenger data records within the entry dwell duration threshold starting from the collection time of the entry data record, and adding the subway station location information in the entry data record to the selected passenger data records; otherwise, adding the subway station location information in the entry data record to the time interval between the entry data record and the first passenger status data record. In the station data records; and / or, in chronological order from back to front, determine the second duration between the exit data record and the first travel status data record, add the second duration to the stay duration set corresponding to the exiting subway station, and determine the exit stay duration threshold corresponding to the exiting subway station based on the stay duration in the updated stay duration set corresponding to the exiting subway station; if the second duration is greater than the exit stay duration threshold, then, starting from the collection time of the exit data record, select the station data records within the exit stay duration threshold, and add the sticker location information in the exit data records to the selected station data records; otherwise, add the subway station location information in the exit data records to the station data records between the exit data record and the first travel status data record.

[0050] In one possible implementation, the correspondence between the cell signal and location information is stored in a collection of data, which includes at least one data record. The method further includes: the terminal obtaining a location data set for location positioning based on data records in the collection of data that meet confidence requirements, the location data set including at least one data record, the data records in the location data set being used to store the correspondence between the cell signal and location information.

[0051] In one possible implementation, the data records whose confidence level meets the requirement satisfy at least one of the following conditions:

[0052] Inbound data records with a recall rate greater than a set threshold;

[0053] Outbound data records with a recall rate greater than a set threshold;

[0054] The edge degree of the station data records that meet the requirements is represented by the ratio of the number of collections in the station data records to the maximum number of collections, where the maximum number of collections is the maximum number of collections among all station data records containing the same subway station location information.

[0055] The system collects incoming data records, in-station data records, and outgoing data records after a specified time; wherein the specified time is before the current time and the time elapsed since the current time is equal to the set time elapsed.

[0056] In one possible implementation, the data records in the location data set include: a cell identifier, subway station location information, and a first scene type identifier or a second scene type identifier, wherein the first scene type identifier is used to indicate that the scene corresponding to the data record is the entrance or exit of a subway station, and the second scene type identifier is used to indicate that the scene corresponding to the data record is inside a subway station.

[0057] Thirdly, a communication device is provided, comprising: one or more processors; wherein, when instructions of one or more computer programs are executed by the one or more processors, the communication device causes to perform the method as described in any one of the first aspects above, or the method as described in any one of the second aspects above.

[0058] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium comprising a computer program that, when executed on a computing device, causes the computing device to perform the method as described in any one of the first aspects above, or the method described in any one of the second aspects.

[0059] Fifthly, a chip is provided, the chip being coupled to a memory for reading and executing program instructions stored in the memory to implement the method as described in any one of the first aspects above, or the method as described in any one of the second aspects above.

[0060] In a sixth aspect, a computer program product is provided, which, when invoked by a computer, causes the computer to perform the method as described in any one of the first aspects above, or the method as described in any one of the second aspects above.

[0061] For the beneficial effects in aspects two through six above, please refer to the beneficial effects in aspect one; they will not be repeated here. Attached Figure Description

[0062] Figure 1 This is a schematic diagram of a scenario according to an embodiment of this application;

[0063] Figure 2 This is a schematic diagram of the terminal structure in the embodiments of this application;

[0064] Figure 3 This is a block diagram illustrating one implementation of an embodiment of this application;

[0065] Figure 4 , Figure 5 and Figure 6 These are schematic flowcharts of the data acquisition methods provided in the embodiments of this application;

[0066] Figure 7 This is a schematic diagram of the data collection process in the subway station application scenario in this application embodiment;

[0067] Figure 8 This is a schematic diagram illustrating one method of adding location information to a data record in an embodiment of this application;

[0068] Figure 9 This is a schematic diagram of a process for adding location information to a data record in an embodiment of this application;

[0069] Figure 10 This is a schematic diagram of a process for selecting data records that meet the confidence level requirements in an embodiment of this application;

[0070] Figure 11 This is a schematic diagram illustrating the collaborative generation of location data sets by the terminal and the network-side server in this embodiment of the application.

[0071] Figure 12 This is a schematic diagram of the location positioning process in an embodiment of this application;

[0072] Figure 13 This is a schematic diagram of a location positioning process in an embodiment of this application. Detailed Implementation

[0073] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings. It should be understood that the terms "first," "second," etc., in the embodiments, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as including a series of steps or units. Methods, systems, products, or devices are not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0074] The data processing method and location-based service implementation method provided in this application can be applied to subway stations. Subways are typically enclosed spaces with entrances and exits. Entrance turnstiles are installed at the entrances, and exit turnstiles are installed at the exits. These turnstiles can be used for subway fare payment processing. Multiple wireless communication network devices (such as base stations) are deployed within the subway station. It is understood that the subway station referred to here may include the underground or above-ground portion, or both. The underground portion of the subway station is typically an enclosed space where multiple base stations are deployed. The above-ground portion of the subway station is also typically an enclosed space, where base stations can be deployed. Terminals within this enclosed space can receive signals from base stations deployed within the enclosed space, and may also receive signals from base stations deployed outside the enclosed space.

[0075] In this embodiment, the terminal can receive signals sent by base stations in the subway station, collect data based on the received signals, obtain a collection data set, and further process the data (such as data mining) based on the collection data set to obtain a location data set for location positioning and / or scene recognition. Thus, the terminal can perform location positioning and / or scene recognition based on the location data set, and can further provide corresponding services to users based on the location positioning and / or scene recognition results.

[0076] In some embodiments of this application, location positioning and scene recognition have essentially the same meaning, with scene recognition being based on location positioning. Scene information can be understood as a type of location information. For example, subway station A is location information, and the entrance of subway station A or the subway station entrance can be understood as location information or scene information. In the subway station application scenario, the location information can refer to subway station location information, which includes subway station signage information and subway station scene information. The subway station scene information includes subway station entrance signs (used to indicate the subway station entrance), subway station exit signs (used to indicate the subway station exit), or subway station interior signs (used to indicate the subway station interior).

[0077] In this embodiment, the signal transmitted by the base station is referred to as a cell signal. The cell signal may include a cell identifier (such as cell ID, or CID for short), and may also include tracking area identifiers, country codes configured in the base station equipment, and other information. Understandably, the cell signal can also be referred to as a base station signal.

[0078] Understandably, the network equipment deployed in subway stations can also be other types of wireless communication network equipment, such as Bluetooth beacons (or Bluetooth base stations). Taking Bluetooth beacons as an example, terminals can receive signals transmitted by Bluetooth beacons (which can be called Bluetooth signals), and perform data collection and data mining to obtain a set of location data for location positioning and / or scene recognition. The signals transmitted by Bluetooth beacons may include information such as the Bluetooth beacon's identifier. Understandably, the signals transmitted by various network devices that may be deployed in the first area (such as base stations, Bluetooth beacons, etc.) can be collectively referred to as wireless signals.

[0079] It should be noted that the embodiments of this application can also be applied to scenarios similar to subway stations, such as places or areas with multiple base stations and entrances / exits. Entrance devices can be installed at the entrance, and exit devices at the exit. These entrance and exit devices can interact with terminals in a contactless manner, performing payment or other response operations when the terminal enters or leaves a subway station. For example, such scenarios may include exhibition halls, stadiums, etc. For ease of description, in some embodiments of this application, such areas or places are referred to as "first areas," while in other embodiments, "first areas" are specifically defined as subway stations.

[0080] Based on the above explanation of terminology, Figure 1This illustration illustrates a scenario according to an embodiment of the present application, which may include network devices and terminals. Taking a first area 10 as an example, the first area 10 may be an underground section or a partial area of ​​an underground section of a subway station. An entrance gate 11 is provided at the entrance of the first area 10, and an exit gate 12 is provided at the exit of the first area 10. Multiple network devices are deployed within the first area 10, such as... Figure 1 The network devices (13a to 13g) are included. Each network device can communicate with terminal 100 wirelessly.

[0081] Network devices (13a-13g), also known as wireless access network devices, are devices used to connect terminals to a wireless network. For example, a base station (e.g., an access point) can refer to a device in the access network that communicates with a wireless terminal via one or more cells over the air interface. Exemplarily, access network devices may include one or more access devices deployed in indoor environments (such as subway stations). For example, in a subway station scenario, network devices (13a-13g) may include dedicated micro base stations deployed inside the subway station, or they may include base stations, small stations, micro stations, etc., in future communication networks. This application embodiment is not limited to these categories.

[0082] Terminal 100 may be a mobile phone, tablet computer, or wearable device with wireless communication capabilities (such as a smartwatch or smart glasses). Exemplary embodiments of this terminal include, but are not limited to, carrying... Alternatively, it can be a device operating a different operating system. The aforementioned terminal can also be other portable devices, as long as the portable device can receive cell signals and generate data records.

[0083] In this embodiment, the terminal 100 within the first area 10 can generate a collection data set based on the cell signals received from network devices (13a-13e), and obtain a positioning data set for location positioning and / or scene recognition based on the generated collection data set. The terminal can perform location positioning and / or scene recognition within the first enclosed area 10 based on the positioning data set, and can further provide corresponding services to the user based on the location positioning results and / or scene recognition results. For a detailed description of the collection data set and the positioning data set, please refer to [link to relevant documentation]. Figure 3 .

[0084] For example, such as Figure 2The diagram shown illustrates a possible structure of terminal 100. Terminal 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, antenna 1, antenna 2, a mobile communication module 151, a wireless communication module 152, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, a headphone jack 170D, 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 gyroscope sensor 180A, an accelerometer sensor 180B, a fingerprint sensor 180H, a temperature sensor 180J, and a touch sensor 180K (of course, the terminal 100 may also include other sensors, such as pressure sensors, accelerometer sensors, gyroscope sensors, ambient light sensors, bone conduction sensors, etc., which are not shown in the figure).

[0085] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the terminal 100. In other embodiments of this application, the terminal 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0086] The processor 110 may include one or more processing units, such as an application processor (AP), modem, graphics processing unit (GPU), image signal processor (ISP), controller, memory, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU). Different processing units may be independent devices or integrated into one or more processors. The controller may serve as the central nervous system and command center of the terminal 100. The controller can generate operation control signals based on instruction opcodes and timing signals to control instruction fetching and execution.

[0087] Internal memory 121 can be used to store one or more computer programs, including instructions. Processor 110 executes various functional applications and data processing of terminal 100 by running the instructions stored in internal memory 121. Internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system, application code, etc. The data storage area may store statistical results of data transmission recorded during terminal 100 use, thresholds (used to determine whether the conditions for adjusting the timing duration of the RRC connection release timer are met), etc.

[0088] Furthermore, the internal memory 121 may include high-speed random access memory, and may also include non-volatile memory, such as one or more disk storage devices, flash memory devices, universal flash storage (UFS), etc. In some embodiments, the processor 110 may execute instructions stored in the internal memory 121 and / or instructions stored in memory disposed in the processor 110, causing the terminal 100 to perform the data processing method or scene recognition-based service implementation method provided in the embodiments of this application.

[0089] Of course, the code for the data processing method or location-based service method provided in this application embodiment, as well as information such as the collected data set and the location data set, can also be stored in external memory. In this case, the processor 110 can run the code stored in external memory for implementing the above-described methods of this application embodiment through the external memory interface 120.

[0090] The external memory interface 120 can be used to connect an external memory card (e.g., a Micro SD card) to expand the storage capacity of the terminal 100. The external memory card communicates with the processor 110 through the external memory interface 120 to perform data storage functions. For example, information such as the collection data set and location data set generated by the terminal can be stored in the external memory card.

[0091] The wireless communication function of terminal 100 can be implemented through antenna 1, antenna 2, mobile communication module 151, wireless communication module 152, modem processor, and baseband processor. Based on the above wireless communication function, the terminal can receive signals sent by network devices (such as cell signals sent by base stations), collect data according to the received signals, and obtain a collection of data sets.

[0092] Based on the detection data from the accelerometer 180B, the terminal 100 can determine the motion state. For example, the motion state may include a riding state and a non-riding state, and the non-riding state may further include a stationary state, a walking state, a running state, etc.

[0093] Optionally, the terminal 100 can also integrate a near field communication (NFC) chip, enabling the terminal to make subway ride payments through contactless operation based on the NFC chip.

[0094] For example, Figure 3 A block diagram illustrating one implementation of an embodiment of this application is shown. Figure 3 All the processing operations shown are performed by the same terminal.

[0095] like Figure 3 As shown, when the data acquisition start condition is met, the terminal initiates data acquisition. The data acquisition includes generating data records based on the cell signals received by the terminal, and these data records are stored in the acquired data set. Furthermore, the terminal can also terminate data acquisition to save power consumption. For example, when the data acquisition termination condition is met, the terminal terminates data acquisition.

[0096] For example, meeting the data collection initiation conditions may include the following: if a first triggering event occurs, the data collection initiation conditions are met, and the terminal initiates data collection in response to the first triggering event. The first triggering event includes the terminal sensing entry into a first area. Taking a subway station scenario as an example, the first triggering event is that the terminal obtains entry permission through a first device at the subway station entrance (such as an entrance gate), for example, by making contactless (or contactless) payment for subway rides.

[0097] For example, if subway payment is made using a barcode (such as a QR code), when the subway entrance gate scans the barcode displayed on its screen and identifies the payment account information within it, the gate sends a payment request containing that information to the payment server. The server completes the payment based on the account information, and since the payment account is associated with the terminal, it sends a first payment response to the terminal. Upon receiving this response, the terminal initiates data collection. In another example, if the barcode contains terminal identification information, the gate can send a first payment response to the terminal based on that information, and the terminal then initiates data collection upon receiving it.

[0098] For another example, if NFC is used for subway payment, when the entrance gate at the subway entrance senses the signal of the NFC chip in the terminal, it reads the payment account information in the NFC chip and writes the payment information to the payment account. The terminal can start data collection when it detects that the entrance gate is writing the payment information to the NFC chip.

[0099] For example, the data acquisition termination condition may include the following: if a second triggering event occurs, the data acquisition termination condition is met, and the terminal terminates data acquisition in response to the second triggering event.

[0100] For example, the second triggering event may include any of the following events:

[0101] Event 1: The terminal senses leaving the second area, such as leaving a subway station. If this event occurs, the condition for ending data collection is met, and the terminal ends data collection.

[0102] Taking a subway station scenario as an example, the second triggering event is that the terminal obtains exit permission through a second device at the subway station entrance (such as an exit gate), such as making contactless (or contactless) payment for the ride.

[0103] For example, if subway payment is made using a barcode (such as a QR code), when the exit gate at the subway exit scans the barcode displayed on its screen and identifies the payment account information within it, the exit gate sends a payment request containing that payment account information to the payment server. After the payment server completes the payment based on the payment account, and since the payment account is associated with the terminal, the server sends a second payment response to the terminal. Upon receiving this second payment response, the terminal ends data collection. In another example, if the barcode contains terminal identification information, the exit gate can send a second payment response to the terminal based on that identification information. Upon receiving this second payment response, the terminal ends data collection.

[0104] For another example, if NFC is used for subway payment, when the exit gate at the subway exit senses the signal of the NFC chip in the terminal, it reads the payment account information in the NFC chip and writes the exit payment information into the payment account. The terminal can end data collection when it detects that the entrance gate has written the exit payment information into the NFC chip.

[0105] Event 2: First timer times out. If this event occurs, the conditions for ending data acquisition are met, and the terminal ends data acquisition.

[0106] The first timer is an internal timer within the terminal, started and stopped by the terminal. It controls the duration of data collection within a specific area (e.g., a subway station), preventing excessive data collection time and thus avoiding excessive data storage and processing overhead, while also saving the terminal's power consumption.

[0107] For example, the first timer is started by the terminal in response to a first triggering event. Further, the first timer can be stopped when the terminal responds to a second triggering event. Taking a subway station application scenario as an example, the first timer can be started when the terminal makes an entry payment through the entrance gate at the subway station entrance; if the first timer has not expired when the terminal makes an exit payment through the entrance gate at the subway station exit, the terminal can stop the first timer.

[0108] For example, the duration of the first timer can be set according to the application scenario. For instance, when applying this embodiment of the application to a subway station scenario, the duration of the first timer can be set to 90 minutes.

[0109] Event 3: Second timer times out. If this event occurs, the conditions for ending data acquisition are met, and the terminal ends data acquisition.

[0110] The second timer is an internal timer within the terminal, started or stopped by the terminal. The second timer controls the duration of data acquisition after the terminal leaves the second area. This allows for the acquisition of cell signals from areas near the perimeter of the first area's entrance and exit, while also preventing excessive data acquisition time to avoid excessive data storage and processing overhead, and saving terminal power consumption.

[0111] For example, the second timer is activated when the terminal senses that it has left the second area. Taking a subway station application scenario as an example, the second timer can be activated when the terminal makes an exit payment through the exit gate of the subway station.

[0112] For example, the duration of the second timer can be set according to the application scenario. For instance, when this embodiment of the application is applied to a subway station scenario, the duration of the second timer can be set to 15 seconds.

[0113] In this embodiment, the terminal can obtain data such as cell signal information and location information through data acquisition. The terminal can store the acquired data as data records, which are stored in an acquired data set, also known as an acquired database. The terminal can store the acquired data records in the acquired data set in chronological order of acquisition time, thereby arranging the data records in the acquired data set in chronological order of acquisition time. Each data record in the acquired data set includes at least the acquired cell identifier, and may further include the acquisition time.

[0114] The data records collected at the entrance and exit of the first area also include location information. This location information may include location description information or location identifiers. Unlike location coordinate information, the location information in this embodiment can be predefined for location differentiation. For example, in a subway station scenario, the location information may be the subway station name or subway station ID, and may further include the city name where the subway station is located. The data record generated by the terminal in response to an entry payment event at a subway station entrance gate includes the name of the subway station where the entrance gate is located, and the data record generated by the terminal in response to an exit payment event at a subway station exit gate includes the name of the subway station where the exit gate is located.

[0115] Optionally, the data records in the collected dataset may also include information such as tracking area identifier, operator identifier, and country code. This information originates from the cell signals received by the terminal. The tracking area identifier identifies the tracking area to which the cell belongs, the operator identifier identifies the operator to which the corresponding cell base station belongs, and the country code identifies the country to which the cell base station belongs.

[0116] Optionally, the data records in the collected dataset may also include the corresponding motion states. The terminal can determine the motion state based on the detection data from sensors (such as accelerometers) installed in the terminal. Optionally, the motion state may include a riding state and a non-riding state, and the non-riding state may further include a stationary state, a walking state, a running state, etc.

[0117] Optionally, the data records in the collected dataset may also include the number of times the same cell signal was received. The number of times the same cell signal was received in the data records indicates the number of times the same cell signal was received.

[0118] Optionally, the data records in the collected dataset may also include evaluation information corresponding to the data records. This evaluation information is used to assess the confidence level or validity of the data records. The evaluation information can be obtained by verifying the collected data records based on the location positioning results when the terminal enters or exits the first area.

[0119] Optionally, the data records in the collected dataset may also include cell signal strength information, such as received signal strength indication (RSSI).

[0120] For a detailed explanation of the process of obtaining the collected data set through the data acquisition process, please refer to [link to relevant documentation]. Figure 4 .

[0121] like Figure 3As shown, after obtaining the collected data set, the terminal can perform data processing such as data mining on the collected data set to obtain a positioning data set, which is used for location positioning and / or scene recognition.

[0122] Optionally, the collected dataset can be subjected to the following two stages of data mining or data processing:

[0123] Phase 1: Based on the movement status and user's personal travel habit profile corresponding to the data records, add location information to the data records that do not contain location information; the user's personal travel habit profile refers to the length of time the user stays at each subway station (from entering the station to leaving the platform).

[0124] The second stage involves selecting data records that meet the confidence requirements and generating a location data set based on these records.

[0125] A location dataset is also called a location database. Each data record in a location dataset includes at least: cell identifier and location information.

[0126] Optionally, the location dataset may also include tracking area identifiers, operator identifiers, country codes, etc., which are derived from the corresponding data records in the collected dataset.

[0127] Optionally, the data records in the location dataset may also include a first scene type identifier or a second scene type identifier. The first scene type identifier indicates the entrance / exit of the first area, and the second scene type identifier indicates the internal area of ​​the first enclosed area. Taking a subway station application scenario as an example, the entry and exit data records contain the first scene type identifier. For example, if the first scene type identifier is 1, it indicates that the corresponding data record is an entry or exit data record, and the cellar identifier contained in this entry or exit data record corresponds to a cellar located at the subway station entrance / exit. For example, if a data record in the location dataset includes the subway station name S1 and the first scene type identifier, it indicates that the location indicated by this data record is the entrance / exit of subway station S1. The data records within the station contain the second scene type identifier. For example, if the second scene type identifier is 0, it indicates that the corresponding data record is an internal data record, and the cellar identifier contained in this internal data record corresponds to a cellar located inside the subway station. For example, if a data record in the location dataset includes the subway station name S1 and the second scene type identifier, it indicates that the location indicated by this data record is the internal area of ​​subway station S1 (such as the platform area).

[0128] Data mining and data processing are performed on the collected data set to generate a detailed description of the location data set, which can be found in the following sections.

[0129] like Figure 3 As shown, the terminal can perform location positioning and / or scene recognition based on the location data set. Furthermore, the terminal can also perform corresponding service processing operations based on the location positioning results and / or scene recognition results, that is, provide corresponding services to the user to improve the user experience. Specific implementation details can be found in the following sections.

[0130] Based on the above Figure 3 Taking the application of this embodiment in a subway station scenario as an example, in one implementation, when the terminal performs an entry payment operation through the subway station entrance gate, the terminal initiates a data collection process in response to the event. When the terminal performs an exit payment operation through the subway station exit gate, the terminal can terminate the data collection process in response to the event. In other words, the terminal's data collection process is based on sensing-driven data collection (SDDC), using relevant events perceived by the device in the subway station scenario as guidance to initiate and terminate the data collection process. This achieves targeted data collection based on user behavior in both time and space, concentrating data collection in the subway station scenario at both time and space levels, allowing for targeted data collection and improving data collection efficiency. Furthermore, compared to manual data collection, the data collection method provided in this embodiment improves data collection efficiency.

[0131] Taking a subway station scenario as an example, since the data records in the collected dataset are sorted in chronological order, the time sequence information of the user's entire subway ride is preserved, which provides a foundation for subsequent data processing to generate a location dataset for location positioning and / or scene recognition.

[0132] For example, Figure 4 This diagram illustrates a data acquisition method according to an embodiment of this application. Through this process, a terminal can initiate data acquisition when the data acquisition start condition is met, generate a collection of acquired data, and terminate data acquisition when the data acquisition end condition is met. The process is described using the second triggering event as an example of the terminal sensing leaving a second area (such as a subway station).

[0133] In this process, the first data record, the second data record, and the third data record represent data records generated based on different situations. Specifically, the data record generated when the terminal senses entering the first area is called the first data record (also known as the entry data record in a subway station scenario). The data record generated by the terminal within the first area based on the received cell signal is called the second data record (also known as the station-inside data record in a subway station scenario). The data record generated when the terminal senses leaving the second area is called the third data record (also known as the exit data record in a subway station scenario). The first, second, and third data records are stored in the collected data set.

[0134] like Figure 4 As shown, the process may include the following steps:

[0135] S410: The terminal responds to the first trigger event, starts data acquisition, and generates the first data record.

[0136] Since the first triggering event is the condition for starting data acquisition, when the first triggering event occurs, the terminal starts data acquisition and generates the first data record.

[0137] For example, the first data record includes the collection time, cell identifier, and location information. The collection time can be the time when the first triggering event occurs, or the time when the data record is generated; the cell identifier is the cell identifier contained in the cell signal received by the terminal at its current location when or before the first triggering event occurs; the location information indicates the terminal's current location, such as the location name or location ID. Optionally, the terminal can obtain the location information corresponding to the point of interest (POI) information carried in the payment response or other responses received when entering the first area.

[0138] Optionally, the first data record may also include information such as tracking area identifier, operator identifier, and country code, which are derived from the cell signal received by the terminal.

[0139] Optionally, the first data record may also include a motion state. For example, this motion state may be determined by the terminal when generating the first data record based on detection data from relevant sensors (such as an accelerometer) in the terminal. This application does not limit the method for detecting the motion state.

[0140] Optionally, the first data record may also include the number of collections. For example, after receiving a cell signal, the terminal can query the generated data records in the collection data set based on the information included in the cell signal (such as cell identifier, and further including tracking area identifier, operator identifier, country code, etc.). If no data record containing the same information is found, the number of collections in the currently generated first data record is set to 1. If a data record containing the same information is found and the number is N (N is an integer greater than or equal to 1), the number of collections in the currently generated first data record is set to N+1.

[0141] Optionally, the first data record may also include evaluation information. For example, the evaluation information may include at least one of the following: successful verification count, failed verification count, and recall rate. The successful verification count is the number of times the terminal successfully verifies its location when it senses entering the first area (e.g., a subway station); the failed verification count is the number of times the terminal fails to verify its location when it senses entering the first area (e.g., a subway station); and the recall rate is determined based on the successful verification count and the failed verification count.

[0142] For example, after receiving a cell signal, the terminal can perform location positioning and / or scene recognition based on the cell identifier contained in the cell signal. The identified location information is compared with the location information obtained from the Point of Interest (POI). If they match, the verification is successful, and the number of successful verifications in the currently generated first data record is incremented by one. Otherwise, the verification fails, and the number of failed verifications in the currently generated first data record is incremented by one. Further, the terminal calculates the recall rate based on the number of successful and failed verifications in the first data record and adds the calculated recall rate to the first data record.

[0143] Optionally, the recall rate can be calculated using the following formula:

[0144] R = TP / (TP + FN)

[0145] Where R represents recall, TP represents the number of successful verifications, and FN represents the number of failed verifications.

[0146] Optionally, the first data record may also include a first identifier, which is used to indicate entry into the first area. Taking a subway station application scenario as an example, the first identifier is an entry identifier, which is added to the first data record generated in response to the first trigger event by the terminal.

[0147] Optionally, the first data record may also include the cell signal strength. For example, the terminal may record the RSSI of the cell signal in the first data record.

[0148] S420: The terminal generates a second data record based on the received cell signal.

[0149] In one possible implementation, after the terminal starts the data acquisition process, when it detects a change in the cell it is in, such as when the terminal moves from the signal coverage area of ​​one cell to the signal coverage area of ​​another cell, and the cell identifier contained in the cell signal received by the terminal is different from the cell identifier contained in the cell signal received last time, the terminal generates a second data record based on the currently received cell signal.

[0150] In another possible implementation, after the terminal starts the data acquisition process, if it determines that the terminal is in motion (such as walking) since the last data record was generated and that the motion has lasted for a set period of time, the terminal can generate a second data record based on the currently received cell signal.

[0151] In another possible implementation, after the terminal starts the data acquisition process, if it determines that it is in a walking state based on the count of the terminal's step counter, and the number of steps in the walking state since the last data record is generated reaches a set threshold, then the terminal can generate a second data record based on the currently received cell signal.

[0152] For example, the second data record includes the acquisition time and the cell identifier. The acquisition time can be the time when the terminal receives the cell signal or the time when the data record is generated.

[0153] Optionally, the second data record may also include information such as tracking area identifier, operator identifier, and country code, which are derived from the cell signal received by the terminal.

[0154] Optionally, the second data record may also include motion status.

[0155] Optionally, the second data record may also include the number of data collections.

[0156] Optionally, the second data record may also include the cell signal strength.

[0157] Optionally, the second data record may also include a second identifier, which is used to indicate the area within the first region. Taking a subway station application scenario as an example, the second identifier is an internal station identifier, which the terminal adds to the second data record.

[0158] It should be noted that multiple second data records may be generated after data collection is initiated. For example, after data collection is initiated, the terminal may move within the first area, that is, it may move multiple times from the signal coverage area of ​​one base station to the signal coverage area of ​​another base station. Each time it moves from the signal coverage area of ​​one base station to the signal coverage area of ​​another base station, the terminal can generate a second data record based on the cell signal transmitted by the current base station.

[0159] S430: The terminal responds to the second trigger event, generates the third data record, and ends data acquisition.

[0160] In this embodiment of the application, the second triggering event is the event that the terminal senses leaving the second area. For example, the terminal makes a contactless payment for the subway through the exit gate at the subway station entrance. Since the second triggering event is the condition for ending data collection, the terminal ends data collection after generating the third data record when the second triggering event occurs.

[0161] For example, the third data record includes the collection time, cell identifier, and location information. The collection time can be the time when the second triggering event occurs, or the time when the data record is generated; the cell identifier is the cell identifier contained in the cell signal received by the terminal at its current location when or before the second triggering event occurs; the location information indicates the terminal's current location, such as the location name or location ID. Optionally, the terminal can obtain the location information corresponding to the POI information carried in the payment response or other responses received when leaving the second area.

[0162] Optionally, the third data record may also include information such as tracking area identifier, operator identifier, and country code, which are derived from the cell signal received by the terminal.

[0163] Optionally, the third data record may also include motion status.

[0164] Optionally, the third data record may also include the number of times data was collected.

[0165] Optionally, the third data record may also include evaluation information. For example, the evaluation information may include at least one of the following: successful verification count, failed verification count, and recall rate. The successful verification count is the number of times the terminal successfully verifies the location result when it senses leaving the first area (e.g., a subway station); the failed verification count is the number of times the terminal fails to verify the location result when it senses leaving the second area (e.g., a subway station); and the recall rate is determined based on the successful verification count and the failed verification count.

[0166] For example, after receiving a cell signal, the terminal can perform location positioning and / or scene recognition based on the cell identifier contained in the cell signal. The identified location information is compared with the location information obtained from the Point of Interest (POI). If they match, the verification is successful, and the number of successful verifications in the currently generated third data record is incremented by one. Otherwise, the verification fails, and the number of failed verifications in the currently generated third data record is incremented by one. Further, the terminal calculates the recall rate based on the number of successful and failed verifications in the third data record and adds the calculated recall rate to the third data record.

[0167] Optionally, the third data record may also include the cell signal strength. For example, the terminal may record the RSSI of the cell signal in the third data record.

[0168] Optionally, the third data record may also include a third identifier, which is used to indicate leaving the second area. Taking a subway station application scenario as an example, the third identifier is an exit identifier, which is added to the third data record generated by the terminal in response to the second trigger event.

[0169] For example, Figure 5 The diagram illustrates another data acquisition method provided in this application embodiment. Through this process, the terminal can start data acquisition when the data acquisition start conditions are met, generate a collection of acquired data through data acquisition, and end data acquisition when the data acquisition end conditions are met (such as when the first timer times out).

[0170] like Figure 5 As shown, the process may include the following steps:

[0171] S510: The terminal responds to the first trigger event, starts data acquisition, and generates the first data record.

[0172] S520: The terminal starts the first timer.

[0173] S530: The terminal determines whether the first timer has expired and whether the second trigger event has occurred. If the first timer has not expired and the second trigger event has not occurred, it proceeds to S540; if the first timer has expired, it proceeds to S550; if the second trigger event has occurred, it proceeds to S560.

[0174] S540: The terminal generates a second data record based on the received cell signal and returns it to S530.

[0175] S550: Terminal ends data acquisition.

[0176] S560: The terminal responds to the second trigger event, generates the third data record, and ends data acquisition.

[0177] Optionally, the terminal may stop the first timer after the second trigger event occurs or after the third data record is generated.

[0178] Figure 5 The method for generating the first, second, and third data records, and the content included in the data records, are related to... Figure 4 The relevant descriptions are the same.

[0179] Taking the application of the embodiments of this application to a subway station scenario as an example, based on Figure 5 In this implementation, after the terminal makes a payment at the subway station entrance gate, it starts data collection and starts a first timer. If the terminal does not make an exit payment at the subway station exit gate within a long period of time, the first timer expires, and the terminal ends data collection. This allows the terminal to control the data collection time to not exceed the duration of the first timer when it enters the subway station and stays in the station for a long time, thereby saving terminal power consumption.

[0180] For example, Figure 6 The diagram illustrates another data acquisition method provided in this application embodiment. Through this process, the terminal can start data acquisition when the data acquisition start conditions are met, generate a collection of acquired data through data acquisition, and end data acquisition when the data acquisition end conditions are met (such as the second timer timeout).

[0181] like Figure 6 As shown, the process may include the following steps:

[0182] S610: The terminal responds to the first trigger event, starts data acquisition, and generates the first data record.

[0183] S620: The terminal generates a second data record based on the received cell signal.

[0184] S630: The terminal responds to the second trigger event, generates a third data record, and starts a second timer.

[0185] S640: If the second timer times out, proceed to S650; otherwise, proceed to S660.

[0186] S650: Terminal ends data acquisition.

[0187] S660: The terminal generates a second data record based on the received cell signal and returns it to S640.

[0188] Figure 6 The method for generating the first, second, and third data records, and the content included in the data records, are related to... Figure 4 The relevant descriptions are the same.

[0189] Taking the application of the embodiments of this application to a subway station scenario as an example, based on Figure 6 In this implementation, after the terminal completes its exit payment at the subway station exit gate, it does not immediately stop data collection. Instead, it starts a second timer. During the operation of this second timer, the terminal continues data collection. When the second timer expires, the terminal stops data collection. This second timer allows the terminal to continue data collection for a period after exiting the station. On the one hand, it allows for the collection of cell signals in the vicinity of the subway exit gate, resulting in more comprehensive data records. On the other hand, it avoids excessively long data collection times, preventing excessive overhead and the generation of invalid data records, and also saves terminal power consumption.

[0190] In another possible implementation, a first timer can be started after the first triggering event occurs, and data acquisition ends when the first timer times out; if the first timer does not time out and a second triggering event occurs, the terminal stops the first timer and starts the second timer, and the terminal ends data acquisition when the second timer times out.

[0191] For example, Figure 7 Taking a subway station application scenario as an example, a data acquisition process is shown in an embodiment of this application.

[0192] When the terminal makes a contactless payment for subway rides through the entrance gate (such as by scanning a QR code or using NFC), it receives the payment information and initiates data collection.

[0193] The terminal generates an entry data record based on the received cell signal, obtains the corresponding subway station name based on the POI included in the received entry payment information, and adds the subway station name to the entry data record. Optionally, the entry data record may include: collection time, cell identifier, number of collections, subway station name, movement status, and evaluation information (such as the number of successful verifications, the number of failed verifications, and the recall rate). Further, the entry record may also include a tracking area identifier, operator identifier, and country code. Further, the entry record may also include an entry identifier (i.e., a first identifier). Further, the entry record may also include cell signal strength.

[0194] After the terminal generates the entry data record, it updates the scene status to the entry status and starts the first timer.

[0195] During the first timer's operation, as the terminal moves within the subway station, it may move multiple times from the signal coverage area of ​​one base station to the signal coverage area of ​​another. Each time it moves to a new base station's signal coverage area, the terminal generates an in-station data record based on the currently received cell signal. Optionally, this in-station data record may include: collection time, cell identifier, number of collections, and movement status. Further, the in-station record may also include a tracking area identifier, operator identifier, and country code. Further, the in-station record may also include an in-station identifier (i.e., a second identifier). Further, the in-station record may also include cell signal strength.

[0196] If the first timer times out, the terminal will stop data acquisition.

[0197] During the first timer's operation, when the terminal makes a contactless payment for subway rides through the exit gate (e.g., via QR code or NFC), it receives the exit payment information. The terminal generates an exit data record based on the received cell signal, obtains the corresponding subway station name from the POI included in the received exit payment information, and adds that subway station name to the exit data record. Optionally, the exit data record may include: collection time, cell identifier, number of collections, subway station name, movement status, and evaluation information (e.g., number of successful verifications, number of failed verifications, and recall rate). Furthermore, the entry record may also include a tracking area identifier, operator identifier, and country code. Furthermore, the entry record may also include an exit identifier (i.e., a third identifier). Furthermore, the exit record may also include cell signal strength.

[0198] After the terminal generates the outbound data record, it starts the second timer and updates the scene status to the outbound status.

[0199] During the second timer operation, the terminal generates in-station data records based on the received cell signals.

[0200] If the second timer times out, the terminal will stop data acquisition.

[0201] The data records generated by the terminal are stored in the first data set in the terminal. For a detailed implementation of the above data acquisition process, please refer to the foregoing embodiments.

[0202] For example, Table 1 shows an example of data records generated during a single ride.

[0203] Table 1: Data Records Collected

[0204]

[0205]

[0206] Among them, data record number 1 is the entry data record, data record number 13 is the exit data record, data records numbered 2-12 were collected inside the subway station, and data record number 14 was collected after exiting and paying at the exit gate. The "Time" field of each data record records the time when the terminal generated the entry data record; the "Cell Identifier" field records the cell identifier contained in the cell signal received by the terminal; the "Tracking Area Identifier" field records the tracking area identifier contained in the cell signal received by the terminal; the "Operator Identifier" field records the operator identifier contained in the cell signal received by the terminal; the "Country Code" field records the country code contained in the cell signal received during the communication; the "Subway Station Name" and "City Name" fields are obtained by the terminal based on the POI in the received entry payment information; the "Number of Collections" field records the number of times the terminal collected the same cell signal; the "Motion Status" field records the motion status detected by the terminal; and the "Recall Rate" field records the recall rate corresponding to the entry data record. In this example, the number of successful verifications for this inbound data field is 10, and the number of failed verifications is 0, therefore the recall rate is 1. The methods for determining the number of successful and failed verifications, as well as the method for generating the recall rate, can be found in the aforementioned embodiments. The "Record Number" field is optional and is used as an index for identifying record fields.

[0207] It should be noted that, in this example, the values ​​of information such as cell identifier, tracking area identifier, operator identifier, and country code in the data record are only exemplary descriptions used to illustrate the embodiments of this application and do not represent the values ​​in real scenarios.

[0208] based on Figure 7 The implementation method allows the user's terminal to collect data within the subway station from the moment the user enters until the user leaves the subway station, providing a data foundation and source for generating a timed dataset for location positioning and / or scene recognition in the subway station scenario.

[0209] The terminal can process the collected data set to obtain a location data set for location positioning and / or scene recognition. For example, the terminal can process the collected data set according to a set time or period to obtain the location data set. For instance, the terminal can process data records collected that day at a set time within a day (such as during the evening when terminal load is low). The following describes the method by which the terminal generates a location data set based on the collected data set, using a subway station application scenario as an example.

[0210] Optionally, the data mining operation performed by the terminal on the data records in the collected dataset may include a first-stage data mining and a second-stage data mining. Optionally, the data records after the first-stage data mining is completed can be stored in an intermediate dataset, and the second-stage data mining is performed based on the intermediate dataset. That is, the intermediate dataset can be obtained by performing the first-stage data mining on the collected dataset, and the location dataset can be obtained by performing the second-stage data mining on the intermediate dataset. Of course, the location dataset can also be obtained by directly performing both the first-stage and second-stage data mining on the collected dataset.

[0211] Optionally, the first stage of data mining may include: adding location information to data records that do not contain location information based on the motion state corresponding to the data records. Optionally, it may also include: adding a first scene type identifier to the inbound and outbound data records, and adding a second scene type identifier to the inbound data records.

[0212] The second stage of data mining may include: selecting data records that meet the confidence requirements based on the evaluation information and number of collections of the data records, and generating a location data set based on the selected data records that meet the confidence requirements.

[0213] The data mining process is described in detail below.

[0214] Optionally, before adding location information to the station data records that do not contain location information, the terminal can first segment the data records in the collected data set according to a single ride process to obtain the data records corresponding to a single ride process. A single ride process includes the process from entering the subway station to leaving the subway station. In one possible implementation, if the entry data records in the collected data set have an entry identifier and the exit data records have an exit identifier, the terminal can segment the data records according to the entry and exit identifiers. In another possible implementation, if the entry data records in the collected data set do not have an entry identifier and the exit data records do not have an exit identifier, the terminal can segment the data records based on the fact that both the entry and exit data records contain location information and the temporal sequence of the data records in the collected data set. Furthermore, if the data records in the collected dataset do not have entry, exit, or in-station identifiers, then after dividing the data records corresponding to a single ride, corresponding identifiers, such as entry, exit, or in-station identifiers, can be added to the data records corresponding to that single ride to facilitate subsequent data mining.

[0215] Furthermore, if the total duration of multiple consecutive station data records in the "riding" state is less than a set threshold, the motion state of these multiple "riding" station data records will be corrected to a non-riding state, such as a walking or stationary state.

[0216] For example, for data records corresponding to a single ride, location information can be added to station data records that do not currently contain location information, based on the corresponding movement states of these data records. For example, the process of adding location information to station data records corresponding to a single ride may include: adding subway station location information to the station data records between the first and second station data records adjacent to the entry data record, arranged in chronological order of collection time. The added subway station location information is the same as the subway station location information in the entry data record. Specifically, the second station data record is the first station data record in the entry data records arranged in chronological order of collection time whose movement state is "riding". Similarly, adding subway station location information to the station data records between the third and fourth station data records adjacent to the exit data record, arranged in chronological order of collection time. The added subway station location information is the same as the subway station location information in the exit data record. Specifically, the fourth station data record is the first station data record in the entry data records arranged in chronological order of collection time whose movement state is "riding".

[0217] Figure 8 A schematic diagram illustrates one method for adding location information to data records. For example... Figure 8 As shown, data record number 1 is the entry data record, and data record number 13 is the exit data record. These entry and exit data records, as well as the data records in between, constitute the data records for a single travel process. The "Metro station name" in the in-station data records numbered 2-12 is empty. When adding location information to the non-travel status data records numbered 2-12, the process can proceed by traversing downwards from the entry data records until the first travel status data record (i.e., data record number 6), and adding the same metro station name (S1) to data records numbered 2-5 based on the metro station name (S1) in that entry data record. Similarly, the process can proceed by traversing upwards from the exit data records until the first travel status data record (i.e., data record number 10), and adding the same metro station name (S3) to data records numbered 11-12 based on the metro station name (S3) in that exit data record.

[0218] It should be noted that the above is merely an example illustrating a method for adding location information to station data records that do not contain location information, and the embodiments of this application do not impose any limitations on this.

[0219] Taking the collected data records shown in Table 1 as an example, in the first stage of data mining, according to the motion state corresponding to each data record, the subway station name S1 and city A can be added to data records numbered 2-5, and the subway station name S3 and city A can be added to data records numbered 11-12, as shown in Table 2.

[0220] Table 2: Data records after the first stage of data mining:

[0221]

[0222] In other embodiments of this application, the terminal can add location information to the station data records in the collected dataset based on user behavior (such as the duration of stay in the subway station upon entry and exit) and movement status. For example, for data records corresponding to a single ride, the following processing operations are performed:

[0223] Operation 1: Determine the first duration (i.e., the dwell time within the subway station) between the entry data record and the first passenger status data record in chronological order. Add the first duration to the dwell time set corresponding to the entry subway station. Based on the dwell time in the updated dwell time set corresponding to the entry subway station, determine the entry dwell time threshold corresponding to the entry subway station. If the first duration is greater than the entry dwell time threshold, select the passenger data records within the entry dwell time threshold, starting from the collection time of the entry data record, and add the subway station location information in the entry data record to the selected passenger data records. Otherwise, add the subway station location information in the entry data record to the passenger data records between the entry data record and the first passenger status data record (excluding the passenger status data record).

[0224] Operation 2: Determine the second duration (i.e., the dwell time within the exiting subway station) between the exit data record and the first travel status data record, following the chronological order from back to front. Add the second duration to the dwell time set corresponding to the exiting subway station. Based on the dwell time in the updated dwell time set corresponding to the exiting subway station, determine the exit dwell time threshold corresponding to the exiting subway station. If the second duration is greater than the exit dwell time threshold, select the station data records within the exit dwell time threshold, starting from the collection time of the exit data record, and add the subway station location information from the exit data record to the selected station data records. Otherwise, add the subway station location information from the exit data record to the station data records between the exit data record and the first travel status data record (excluding the travel status data record).

[0225] In the above implementation, the stay duration set corresponding to a subway station includes historical information on the length of time the terminal stays in the subway station multiple times. A stay duration threshold is dynamically determined based on the stay duration in this set. Then, data records for which location information needs to be added are selected according to the relationship between the terminal's current stay duration in the subway station and the stay duration threshold. In this way, data records in the station that are compatible with the user's behavior habits can be selected for location addition, providing a data source for subsequent data mining to obtain data records for location positioning and / or scene recognition. This ensures that the final data records for location positioning and / or scene recognition are consistent with the user's behavior habits, thereby improving the reliability of location positioning and / or scene recognition.

[0226] Optionally, the method for determining the entry stay duration threshold corresponding to the entered subway station based on the updated stay duration set (hereinafter referred to as stay duration set 1) may include: if the number of stay durations in the updated stay duration set 1 is less than a set threshold, then the entry stay duration threshold is determined to be equal to the initial value; otherwise, the entry stay duration threshold is determined based on the stay durations in the stay duration set 1. For example, the stay durations in the stay duration set 1 can be sorted from smallest to largest, then divided into four equal parts, and the stay duration at the third dividing point can be determined as the entry stay duration threshold, thereby making the determined stay duration threshold match user behavior habits. Of course, this application embodiment may also use other algorithms to calculate the stay duration threshold based on the stay durations in the stay duration set 1, and this application embodiment does not limit this. The method for determining the exit stay duration threshold based on the updated stay duration set corresponding to the exit subway station is similar to the above method.

[0227] Optionally, when the number of stay durations in the set reaches the maximum limit, for each new stay duration added, the oldest stay duration added to the set can be deleted. For example, the maximum limit is 100.

[0228] Figure 9 A schematic diagram illustrating a process for adding location information to a data record is shown. Figure 9 As shown, the process may include the following steps:

[0229] S710: For the data records corresponding to a single ride, traverse downwards starting from the entry data record and upwards starting from the exit data record.

[0230] S730: When the first passenger status data record is encountered, proceed to S740.

[0231] S740: For the process of traversing downwards from the entry records, calculate the first duration from the entry data record to the currently traversed passenger status data record. This first duration is the dwell time within the entry subway station. Add this first duration to the dwell time set corresponding to the entry subway station, thereby updating the dwell time set. Using the same method, for the process of traversing upwards from the exit data records, determine the exit dwell time threshold corresponding to the exit subway station.

[0232] S750: Determine the entry stay time threshold for the entry subway station based on the stay time set corresponding to the entry subway station; determine the entry stay time threshold for the exit subway station based on the stay time set corresponding to the exit subway station.

[0233] S760: If the first duration (i.e., the length of stay in the subway station) is greater than the threshold for the length of stay in the subway station, then proceed to S761; otherwise, proceed to S762.

[0234] S761: Starting from the collection time of the entry data record, select the data records within the station downwards. The stay time corresponding to the selected data records within the station does not exceed the threshold of the entry stay time. Add the station name of the entering subway station to these selected data records within the station.

[0235] S762: Starting from the entry data record and moving down to the first passenger status data record, add the name of the entering subway station to the in-station data records within this range (excluding the passenger status data record).

[0236] For details on how this step is implemented, please refer to the aforementioned embodiments.

[0237] S770-772 describes a process for adding location information to corresponding data records within a station during the upward traversal of exit data records, based on the relationship between the dwell time within the exiting subway station and the corresponding exit dwell time threshold. The specific implementation method is similar to S760-762.

[0238] After completing the first stage of data mining, the second stage of data mining can be performed to obtain the location data set. During the second stage of data mining, data records with sufficient confidence can be selected from the collected data set (for cases where the first and second stages of data mining are performed based on the collected data set), or data records with sufficient confidence can be selected from an intermediate data set (for cases where the first stage of data mining is performed on the collected data set to obtain an intermediate data set, and then the second stage of data mining is performed on the intermediate data set to obtain the location data set). The location data set is then obtained based on the selected data records.

[0239] For example, a data record that meets the confidence requirement satisfies at least one of the following conditions:

[0240] Condition 1: The data record is an incoming data record.

[0241] In other words, incoming data records are considered to meet the confidence level requirements. Incoming data records can be identified based on their entry identifiers or by whether they contain evaluation information.

[0242] Condition 2: Inbound data records with a recall rate greater than the set threshold.

[0243] Incoming data records with a recall rate greater than a set threshold can be considered as data records that meet the confidence requirements. In this embodiment, the recall rate characterizes the credibility or validity of the data record. A higher recall rate indicates higher credibility of the data record. Therefore, in this embodiment, data records with higher confidence can be selected for subsequent location positioning and / or scene recognition, thereby ensuring the reliability of location positioning and / or scene recognition.

[0244] Condition 3: The data record is an outbound data record.

[0245] In other words, outbound data records are considered to meet the confidence level requirements. Outbound data records can be identified based on their outbound identifiers or by whether they contain evaluation information.

[0246] Condition 4: Outbound data records with a recall rate greater than the set threshold.

[0247] Condition 5: Data records within the station that meet the edge degree requirements.

[0248] The marginality is used to characterize the relative position of the cell indicated by the cell identifier to the center of the subway station. The marginality is represented by the ratio of the number of collections in the data records within the station to the maximum number of collections. The maximum number of collections is the maximum number of collections among all data records within the station that contain the same subway station location information.

[0249] For example, the marginality of a data record within a station can be determined to characterize whether the location of the corresponding neighborhood within the station belongs to the edge or center of the subway station. For example, the formula for calculating the marginality of a single data record within a station can be expressed as:

[0250] α = count / maxCnt

[0251] Where α is the edge degree of the data record in the station, count is the number of collections contained in the data record in the station, and maxCnt is the maximum number of collections. The maximum number of collections refers to the maximum number of collections among all data records containing the subway station in the collection data set or intermediate data set, based on the subway station indicated by the location information contained in the data record in the station.

[0252] The marginality value is greater than 0 and less than or equal to 1. The larger the marginality value, the more likely the corresponding data record's location is to be the center location within the subway station. In this embodiment, station data records with a marginality greater than a set threshold are considered to meet the confidence requirements.

[0253] The sixth condition: Data records collected after a specified time (including inbound data records, in-station data records, and outbound data records). The specified time is before the current time and the time elapsed since the current time is equal to the set duration. For example, data records obtained within the set duration starting from the current time are considered data records collected after the specified time. This set duration is configurable, for example, 180 days; that is, data records generated within the last 180 days are considered to meet this sixth condition. Since data records closer to the current time have higher reliability, selecting data records generated within a relatively recent period ensures the reliability of the data records, thereby guaranteeing the reliability of subsequent location positioning or scene recognition. Furthermore, aging out the data can save on terminal storage costs.

[0254] Seventh condition: Data records where the movement state is not a passenger state. In this embodiment of the application, the station data records where the movement state is a passenger state are generally collected when the terminal is located on the subway train. The collected cell signal may be a cell signal in the subway tunnel. In this embodiment of the application, these data records can be regarded as invalid data records.

[0255] The above conditions can be combined arbitrarily. For example, after excluding data records where the movement state is not a passenger state and data records whose collection time is before the specified time, the remaining data records can be selected to include inbound and outbound data records with a recall rate greater than a set threshold, as well as in-station data records with a marginality greater than a set threshold, in order to generate data records in the location data set.

[0256] For example, based on the data records after the first stage of data mining shown in Table 2, Table 3 shows the data records that meet the confidence requirements after the second stage of data mining.

[0257] As shown in Table 2, taking data records numbered 2 and 11 as examples, the marginality of data record number 2 is 7 / (10+7+5+6+5) = 0.2; the marginality of data record number 11 is 8 / (8+8+10+4) = 0.27. Since the marginalities of in-station data records numbered 2-5, 11-12, and 14 are all greater than the set threshold (which equals 0.1), and these in-station data records are all recently generated (e.g., all generated within the last 10 days), these in-station data records all meet the confidence requirements. Since the recall rates of inbound data record number 1 and outbound data record number 13 are both greater than the set threshold (which equals 0.9), and both are recently generated data records, the inbound data record number 1 and the outbound data record number 13 also meet the confidence requirements. The data records generated by the terminal based on these data records that meet the confidence requirements for location positioning and / or scene recognition are shown in Table 3.

[0258] Table 3: Data records that meet the confidence requirements after the second stage of data mining:

[0259]

[0260] For exit and entry data records, the scenario type field can be set to "1" to indicate that the corresponding data record corresponds to the scenario of the subway station entrance / exit. For in-station data records, the scenario type field can be set to "0" to indicate that the corresponding data record corresponds to the scenario of the subway station interior.

[0261] Figure 10 An exemplary embodiment illustrates a process for selecting data records from a collected data set to obtain a location data set based on the above-described conditions. As shown in the figure, this process may include: in step S801, clearing data records older than 6 months from the collected data set. Of course, 6 months is just an example; other time lengths can be used, depending on the terminal's storage capacity. Step S801 ensures that the remaining data records meet the sixth condition mentioned above. For each remaining data record, the following steps are performed:

[0262] S802: If the number of successful verifications for the current data record is greater than 0, or the number of failed verifications is greater than 0, proceed to S805. If the current data record has no set number of successful or failed verifications, proceed to S803.

[0263] In this embodiment, only inbound and outbound data records are set with a number of successful verifications and / or a number of failed verifications. If the number of successful verifications or the number of failed verifications is greater than 0, it indicates that the data has been verified at least once. Therefore, if the current data record is an inbound or outbound data record, the judgment result in S802 is yes, that is, condition 1 or condition 3 above is satisfied.

[0264] If the current data record is an internal data record, since there are no corresponding verification success counts and verification failure counts set in the internal data record, it is necessary to determine whether the current internal data record meets the fifth condition mentioned above based on the edge degree.

[0265] S803: Determine whether the number of data collections in the current data record is greater than or equal to 3. If yes, proceed to S804; otherwise, proceed to S806.

[0266] In this step, if the current data record contains fewer than 3 collection times, it indicates that the cell identifier in the current data record has been collected relatively infrequently, and it is very likely that the cell identifier is the cell identifier of an edge cell within the subway station. Therefore, proceed to S806. If the current data record contains more than or equal to 3 collection times, it is necessary to further proceed to S804 to determine whether the cell identifier in the current data record is the cell identifier of an edge cell within the subway station based on the edge degree.

[0267] It should be noted that this step only takes the judgment threshold of 3 collection times as an example, and the embodiments of this application do not limit this judgment threshold.

[0268] S804: Determine whether the edge degree corresponding to the current data record is greater than or equal to 0.1. If yes, proceed to S805; otherwise, proceed to S806.

[0269] In this step, if the marginality of the current data record is greater than or equal to 0.1, it indicates that the cell identifier in the current data record is likely to be the central cell within the subway station.

[0270] It should be noted that this step only takes the edge degree judgment threshold of 0.1 as an example, and the embodiments of this application do not limit the judgment threshold.

[0271] S805: Generate data records in the location data set based on the current data records.

[0272] S806: Add the cell identifier from the current data record to the list of cells outside the station.

[0273] Optionally, in this embodiment of the application, the terminal can also perform statistics or mining on user behavior based on the data records in the collected data set. For example, based on the data records in the collected data set, the user's commuting behavior can be determined. For instance, the user's work hours or time period, get off work hours or time period, commuting time, commuting route and other information can be determined based on the data records in the collected data set.

[0274] In some other embodiments of this application, after the terminal generates a collection data set, it can send the collection data set to a server on the network side. The server then performs data processing such as data mining on the collection data sets sent by the terminal and other terminals (e.g., performing first-stage data mining and second-stage data mining) to generate a location data set for location positioning and / or scene recognition. In other embodiments, after the terminal generates the collection data set, it can perform first-stage data mining on the collection data set to obtain an intermediate data set, and then send the intermediate data set to a server. The server then performs data processing such as data mining on the intermediate data sets sent by the terminal and other terminals (e.g., performing second-stage data mining) to generate a location data set for location positioning and / or scene recognition. Furthermore, the server can publish the location data set, enabling the terminal to obtain the location data set and perform location positioning and / or scene recognition based on it.

[0275] For example, Figure 11 This diagram illustrates the collaborative process between the terminal and the network-side server to generate location data sets. As shown, terminals 1 to N (where N is an integer greater than 1) are located in the same city. Terminals 1 to N each generate their own data sets and perform a first-stage data mining on their respective sets (e.g., segmenting data records corresponding to a single ride, adding location information to records that do not contain location information, etc., to obtain intermediate data sets). Terminals 1 to N then send their respective intermediate data sets to the network-side server. The implementation methods for generating the data sets and performing the first-stage data mining on the data sets by terminals 1 to N can be found in the aforementioned embodiments.

[0276] The server performs a second-stage data mining based on the intermediate data set sent by terminals 1 to N (such as selecting data records with confidence levels that meet the requirements based on evaluation information) to obtain a location data set for location positioning and scene recognition. The server then sends the location data set to terminals 1 to N respectively through the data publishing function.

[0277] For example, the server can merge intermediate data sets sent by various terminals. This includes merging data records from different terminals that share the same cell information (e.g., cell identifier, and further, tracking area identifier, operator identifier, country code, etc.) and location information. For instance, if M data records collected by terminals 1 to N contain the same cell identifier, location information (e.g., subway station name, city name), and operator identifier, these M records can be merged into one data record. Optionally, the number of collections in the merged data record is the sum of the number of collections in the M incoming data records, and edge detection can be performed based on the merged number of collections. Optionally, the time in the merged data record is the earliest time among the M data records, so that aging processing of the data records can be performed based on this time. Optionally, if M inbound data records are merged, the number of successful verifications in the merged inbound data record is the sum of the number of successful verifications in the M inbound data records, the number of failed verifications in the merged inbound data record is the sum of the number of failed verifications in the M inbound data records, and the recall rate in the merged inbound data record is calculated based on the number of successful verifications and the number of failed verifications in the merged data record.

[0278] The method by which the server performs a second-stage data mining on the merged dataset to obtain a second dataset is basically the same as the method by which the terminal performs a second-stage data mining to obtain a second dataset in the above embodiment.

[0279] By performing data mining and other data processing operations on the intermediate data sets sent from different terminals by the server, a location data set for location positioning and / or scene recognition can be generated. This allows the generated location data set to contain a wider and more comprehensive range of data records, that is, data records from more cells, thereby enabling better location positioning and / or scene recognition for the terminal.

[0280] Optionally, if the data records collected by terminals 1 to N cover multiple cities, the server can first store the data records belonging to the same city into the corresponding data set for that city, and then process the data sets corresponding to each city separately to obtain the location data sets for each city used for location positioning and / or scene recognition. When sending the location data sets to the terminals, the server can send the location data sets corresponding to the respective cities where the terminals are located.

[0281] The method described above, which uses the collaboration of terminals and servers to perform data mining and generate a set of location data for location positioning and / or scene recognition, can effectively utilize group data while retaining users' travel behavior habits on the terminal side. It can accurately mine community information within subway stations and further mine data in subdivided scenarios, such as community information at the entrance and exit of subway stations. It can also obtain community information in tunnels between subway platforms, thereby making the location positioning or scene recognition results more accurate.

[0282] For example, Figure 12 A schematic diagram of a location positioning process provided in an embodiment of this application is shown. As shown in the figure, the process may include:

[0283] S1010: If the first condition is met, proceed to S1020.

[0284] Optionally, in this embodiment of the application, the terminal may determine whether the first condition is met when the location positioning opportunity arrives. If the first condition is not met, the location positioning and / or scene recognition operation is not performed; otherwise, the location positioning and / or scene recognition operation is performed.

[0285] Optionally, satisfying the first condition may include: the location positioning opportunity arrives and the location positioning start condition is met, so that location positioning is only started when the location positioning opportunity arrives and the location positioning start condition is met, so as to reduce invalid location positioning operations and reduce terminal power consumption.

[0286] Optionally, the location positioning opportunity may be considered to have arrived when the terminal turns on the screen and unlocks the screen, or when the terminal detects a change in the cell it is in while the screen is on, or when walking motion is detected while the terminal is in the screen-on state, or when the terminal in the screen-off state is periodically woken up.

[0287] Optionally, the criteria for determining whether the location positioning activation conditions are met may include: whether the cell identifier contained in the cell signal received by the terminal is in the scene recognition mask list, the terminal's movement state, and whether the cell identifier contained in the cell signal received by the terminal is the same as the cell identifier contained in the cell signal received when the last location positioning opportunity occurred. For example, if the cell identifier contained in the cell signal received by the terminal is not in the scene recognition mask list, the terminal's movement state is not a passenger state, and the cell identifier contained in the cell signal received by the terminal is different from the cell identifier contained in the cell signal received when the last location positioning opportunity occurred, then location positioning and / or scene recognition can be activated.

[0288] For example, the situation in which the first condition is satisfied may include one of the following situations:

[0289] Scenario 1: When the terminal screen is turned on and unlocked, if the cell identifier contained in the cell signal received by the terminal is not in the scene recognition blocking list, and the terminal's current motion state is not in a vehicle-riding state, then the first condition is met. Optionally, the terminal can determine its motion state based on the detection data from relevant sensors (such as an accelerometer) set in the terminal.

[0290] Scenario 2: When the terminal is continuously on and is detected to be in a continuous walking state, if the cell identifier contained in the cell signal received by the terminal is not in the scene identification blocking list, then the first condition is met;

[0291] Scenario 3: When the terminal detects a change in the cell while the screen is on, if the cell identifier contained in the cell signal received by the terminal is not in the scene identification masking list, and the current motion state of the terminal is not in a vehicle state, then the first condition is met.

[0292] Scenario 4: When a terminal in a screen-off state is periodically woken up, if it detects that the cell it is in has changed, that is, the cell it is currently in is different from the cell it was in when it was last woken up, and the cell identifier contained in the cell signal received by the terminal is not in the scene recognition masking list, and the terminal's current motion state is not in a vehicle state, then the first condition is met.

[0293] It should be noted that the above are only examples of several situations that meet the first condition, and the embodiments of this application do not limit this.

[0294] When the location positioning opportunity arrives, determine whether to start location positioning and / or scene recognition. For example, if the cell identifier received by the terminal is in the scene recognition blocking list, it means that the current location belongs to a non-subway station area. In this case, there is no need to start location positioning and / or scene recognition in the subway station, so as to minimize the terminal power consumption while ensuring location positioning coverage.

[0295] The scene recognition masking list can include cell identifiers, including those for cells outside subway stations, such as those for residential and office areas. This scene recognition masking list can be pre-configured; for example, cell identifiers for areas outside subway stations can be pre-set in the scene recognition masking list. The cell identifiers in this scene recognition masking list can also be obtained by the terminal through self-learning.

[0296] For example, the process of the terminal obtaining the cell identifier of the area outside the subway station through self-learning and adding it to the scene recognition masking list may include: if the terminal fails to query the location data set based on the cell identifier contained in the received cell signal, and the cumulative number of failed queries based on the cell identifier reaches a set threshold (e.g., greater than or equal to 20 times), it indicates that the cell identifier may be the cell identifier of a cell outside the subway station, and then the cell identifier is added to the scene recognition masking list.

[0297] Optionally, all or part of the cell identifiers in the scene recognition masking list can be derived from a list of cells outside subway stations. This list contains cell identifiers from cells outside subway station areas collected by the terminal. When this list of cells outside subway stations is updated, the scene recognition masking list can be updated based on the updated list. Optionally, the list of cells outside subway stations can be cleaned up according to a set period. For example, cell identifiers that have not appeared in the past six months can be deleted according to a set period.

[0298] Optionally, the cell identifiers in the list of cells outside the subway station can be pre-configured, obtained using the method described in the aforementioned embodiments, or obtained through a self-learning method. For example, if the terminal fails to query the location data set based on the cell identifier contained in the received cell signal, and the cumulative number of failed queries based on the cell identifier reaches a set threshold, then the cell identifier is added to the list of cells outside the station.

[0299] S1020: The terminal obtains the cell signal of the current location and determines the location information of the current location based on the cell signal.

[0300] Optionally, the terminal can determine the location information corresponding to the cell signal at its current location based on the correspondence between cell signals and location information. Optionally, the correspondence between cell signals and location information includes the correspondence between the cell signal identifier and location information; the terminal can determine the location information corresponding to the identifier of the cell signal at its current location based on the identifier of the cell signal. Optionally, the correspondence between cell signals and location information includes the correspondence between the cell signal identifier and its strength and location information; the terminal can determine the location information corresponding to the identifier and strength of the cell signal at its current location based on the identifier and strength of the cell signal.

[0301] Optionally, the correspondence between cell signals and location information can be stored as a location data set. The terminal can query the location data set in the terminal according to the cell identifier in the cell signal to obtain the location information corresponding to the cell identifier. This location information is the location positioning result.

[0302] In this step, the terminal queries the location data set based on the cell identifier to obtain a data record containing the cell identifier. This data record includes location information and / or scene information corresponding to the cell identifier. The terminal then identifies the location information and / or scene information in this data record as the location positioning result or scene recognition result.

[0303] The location information may include subway station names, city names, etc. The scene information may include information such as a first scene type identifier or a second scene identifier.

[0304] The location data set may be generated by the terminal based on the collected data set, or it may be configured to the terminal by the network side. This application embodiment does not limit this.

[0305] Furthermore, following S1020, the above process may also include the following steps:

[0306] S1030: The terminal executes a service that matches the current location based on the determined location information.

[0307] In one possible implementation, taking a subway station application scenario as an example, when the terminal identifies that it is currently at the entrance or exit of a subway station, it automatically displays an identification code for subway payment on the terminal screen to facilitate user payment by scanning the code. For instance, if the data record containing the cell identifier retrieved by the terminal based on the cell identifier contained in the received cell signal also includes a first scenario type identifier, indicating that the location indicated by the data record is a subway station entrance or exit, then the terminal displays the identification code for subway payment on its screen.

[0308] Furthermore, if the terminal receives a payment response for entering the station, it can determine that the current scenario is entering the station. Therefore, it can obtain the arrival time information of the subway train at the station and display it on the terminal screen or announce it by voice so that users can understand the predicted arrival time of the subway train.

[0309] Furthermore, if the terminal receives the exit payment response information, it can determine that the current scenario is exiting the station. Therefore, after obtaining the location information (such as the subway station name) corresponding to the cell identifier based on the location data set, the terminal can obtain road traffic information, weather information, etc. for that location, and output the obtained information, such as displaying it on the terminal screen or broadcasting it via voice. The method for generating the list of cells outside the station can be found in the aforementioned embodiments.

[0310] In one possible implementation, taking a subway station application scenario as an example, when the terminal identifies that its current location is inside the subway station area, it outputs the predicted arrival time information of the subway train to facilitate the user's travel. For instance, if the data record containing the cell identifier retrieved by the terminal based on the cell information contained in the received cell signal also includes a second scenario type identifier, it indicates that the location indicated by the data record is inside the subway station area. Furthermore, if the terminal is not currently in a travel-related state, it can obtain and output the predicted arrival time information of the subway train at that subway station. For example, the arrival time of the subway train can be displayed on the terminal's screen or announced via voice.

[0311] In one possible implementation, taking a subway application scenario as an example, the terminal can provide arrival reminders. For instance, if the terminal queries a data record containing the cell identifier from the received cell signal, and this data record also includes a second scenario type identifier, it indicates that the location indicated by the data record is within the subway station area. Furthermore, if the terminal determines that it is currently in a boarding state, the terminal outputs a prompt message indicating that it has arrived at the subway station (i.e., the subway station name contained in the queried data record).

[0312] In one possible implementation, taking a subway application scenario as an example, after the terminal queries the location data set based on the cell identifier contained in the received cell signal to obtain the corresponding subway station name, it can also obtain push information associated with that subway station name and display the push information on the terminal's screen. Optionally, the push information may include, but is not limited to, commercial promotional information about the area surrounding the subway station.

[0313] Figure 13 An exemplary embodiment of this application illustrates a location positioning process. For example... Figure 13 As shown, the location positioning process can be initiated in the following situations:

[0314] Scenario 1: As shown in S1101-S1102, after the terminal turns on the screen and unlocks the screen, it obtains the cell identifier contained in the currently received cell signal. As shown in S1140-1150, the terminal determines whether the cell identifier is in the scene identification blocking list. If the cell identifier is not in the scene identification blocking list, it further determines whether the terminal's current motion state is a riding state, that is, whether the terminal is on a vehicle. If the terminal's current motion state is not a riding state, the subsequent location positioning process is started; otherwise, the location positioning process is not started.

[0315] Scenario 2: As shown in S1111-S1112, during the continuous screen-on period of the terminal, if the terminal's movement state is detected as continuous walking, the cell identifier contained in the currently received cell signal is obtained. As shown in S1140-1150, the terminal determines whether the cell identifier is in the scene identification masking list. If the cell identifier is not in the scene identification masking list, the terminal further determines whether the terminal's current movement state is in a vehicle state, that is, whether the terminal is on a vehicle. If the terminal's current movement state is not in a vehicle state, the subsequent location positioning process is started; otherwise, the location positioning process is not started.

[0316] Scenario 3: As shown in S1121-1122, if a change in the cell where the terminal is located is detected during the terminal's screen-on period, i.e., moving from the signal coverage area of ​​one cell to the signal coverage area of ​​another cell, the cell identifier contained in the currently received cell signal is obtained. As shown in S1140-S1150, the terminal determines whether the cell identifier is in the scene identification masking list. If the cell identifier is not in the scene identification masking list, the terminal further determines whether its current motion state is a riding state, i.e., whether the terminal is on a vehicle. If the terminal's current motion state is not a riding state, the subsequent location positioning process is started; otherwise, the location positioning process is not started.

[0317] Scenario 4: As shown in S1131-1133, when a terminal in a screen-off state is periodically woken up, it obtains the cell identifier contained in the currently received cell signal and determines whether the cell identifier is the same as the cell identifier contained in the cell signal received when it was last woken up; as shown in S1040-S1050, if they are different, it further determines whether the cell identifier is in the scene identification masking list. If the cell identifier is not in the scene identification masking list, it further determines whether the terminal's current motion state is a riding state, that is, whether the terminal is on a vehicle. If the terminal's current motion state is not a riding state, the subsequent location positioning process is started; otherwise, the location positioning process is not started.

[0318] In S1160, the terminal performs location positioning based on the second data set.

[0319] In S1170, the terminal determines whether the identified location or scene is within a subway station. If so, it proceeds to S1180; otherwise, it proceeds to S1190.

[0320] In this step, if the terminal finds a subway station name corresponding to the cell identifier in the second data set, it can be determined that the terminal is currently inside a subway station. If the terminal does not find a subway station name corresponding to the cell identifier in the second data set, it can be determined that the terminal is not currently inside a subway station.

[0321] S1180: The terminal updates the current scene status to "inside the subway station".

[0322] S1190: The terminal updates the current scene status to outside the subway station.

[0323] Furthermore, following S1190, the following steps may also be performed:

[0324] S1191: The terminal updates the number of failed queries corresponding to the cell identifier. If the number of failed queries reaches a set threshold, proceed to S1092.

[0325] S1192: The terminal adds the cell identifier to the external cell list. Further, the terminal can update the time corresponding to the cell identifier in the external cell list.

[0326] Furthermore, the above process may also include:

[0327] S1193: The terminal can update the scene identification blocking list based on the list of external cells. For example, it can add the cell identifiers from the list of external cells to the scene identification blocking list.

[0328] Furthermore, the terminal can age the cell identifiers in the external cell list according to a set period, for example, by deleting cell identifiers with earlier dates.

[0329] Taking a terminal containing the location data set shown in Table 3 as an example, when a user enters subway station S1 with the terminal and walks towards the entrance gate, the user turns on the terminal's screen and unlocks it. The cell identifier contained in the cell signal currently received by the terminal is 0001, and it is determined that cell identifier 0001 is not included in the scene identification blocking list. Furthermore, the terminal is currently not in a passenger state. Therefore, the terminal queries the second data set based on the cell identifier. The "scene type" field in the queried data record is set to "1", indicating that the current scene is a subway station entrance / exit scene. Thus, the terminal automatically displays the QR code for subway payment on the terminal's screen so that the user can make a payment. This eliminates the user's need to open the corresponding application and then open the subway payment QR code, thereby improving the user experience.

[0330] When a user enters the station gate and walks inside the subway station with the terminal, the terminal's screen remains on. The terminal detects a change in the cell signal and retrieves the cell identifier contained in the currently received cell signal. If the cell identifier is 0010, the terminal determines that this identifier is not included in the blocking list. Therefore, it queries the location data set based on this cell identifier. If the "Scene Type" field in the retrieved data record is "0", it indicates that the current scene is inside the subway station. The terminal obtains the subway train arrival information for subway station S1 at the current time from the network side and displays this information on the terminal's screen to help the user understand the subway train's arrival time, thereby improving the user experience.

[0331] When a user is riding a subway train with this terminal, the terminal's screen remains on and it detects a change in the cell. The cell identifier currently received in the cell signal is 1011. The terminal determines that this cell identifier is not included in the blocking list. Therefore, it queries the location data set based on this cell identifier. If the "Subway Station Name" field in the queried data record is S3 and the "Scene Type" field is "0", then a prompt message can be displayed on the terminal's screen (or output in other ways, such as voice output) to indicate that the user has arrived at subway station S3, so as to prevent the user from missing their stop.

[0332] When a user gets off at subway station S3 with this terminal, the terminal's screen lights up and unlocks. It then receives a cell signal containing a cell identifier of 1101. The terminal determines that this cell identifier is not included in the blocking list. Therefore, it queries the location data set based on this cell identifier. If the "subway station name" field in the queried data record is S3 and the "scene identifier" field is "1", the terminal will automatically display a QR code for subway payment on its screen so that the user can use the QR code to complete the payment.

[0333] This application also provides a computer-readable storage medium for storing a computer program. When the computer program is executed by a computer, the computer can implement the method provided in the above-described method embodiments.

[0334] This application also provides a computer program product for storing a computer program. When the computer program is executed by a computer, the computer can implement the method provided in the above-described method embodiments.

[0335] This application also provides a chip, including a processor coupled to a memory, for calling a program in the memory to enable the chip to implement the method provided in the above-described method embodiments.

[0336] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0337] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0338] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0339] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0340] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for implementing a location-based service, characterized in that, include: When the first condition is met, the terminal acquires the cell signal at its current location; The terminal determines its current location information based on the location data set and the cell signal; wherein, the location data set includes entry data records, in-station data records, and exit data records, the entry data records include cell identifiers, subway station location information, and a first scene type identifier for indicating the subway station entrance, the in-station data records include cell identifiers, subway station location information, and a second scene type identifier for indicating the subway station interior, and the exit data records include cell identifiers, subway station location information, and a first scene type identifier for indicating the subway station exit; The terminal executes a service matching the current location based on the location information; wherein, if the location information indicates the entrance or exit of a subway station, the terminal displays an identification code for subway payment on the screen; or, if the location information indicates the location inside a first subway station, the terminal displays the predicted arrival time of the subway train at the first subway station on the screen or announces the predicted arrival time via voice.

2. The method as described in claim 1, characterized in that, The terminal determines its current location information based on the cell signal, including: The terminal determines the location information corresponding to the cell signal of the current location based on the correspondence between cell signals and location information.

3. The method as described in claim 2, characterized in that, The correspondence between cell signals and location information includes the correspondence between cell signal identifiers and location information; The determination of location information corresponding to the cell signal at the current location includes: Based on the identifier of the cell signal at the current location, determine the location information corresponding to the identifier of the cell signal.

4. The method as described in claim 2, characterized in that, The correspondence between cell signals and location information includes the correspondence between cell signal identifiers and strengths and location information; The determination of location information corresponding to the cell signal at the current location includes: Based on the identifier and strength of the cell signal at the current location, determine the location information corresponding to the identifier and strength of the cell signal.

5. The method as described in claim 1, characterized in that, The first condition being met includes: The opportunity for location positioning has arrived and the conditions for initiating location positioning have been met.

6. The method as described in claim 5, characterized in that, The arrival of the location positioning opportunity includes: The terminal turns on its screen and unlocks it; or The terminal detects continuous walking motion while its screen is on; or The terminal detects a change in its cell while the screen is on; or The terminal, which is in a screen-off state, is periodically woken up.

7. The method as described in claim 5, characterized in that, The conditions for starting the location positioning process include at least one of the following: The cell identifier contained in the cell signal received when the terminal is woken up is different from the cell identifier contained in the cell signal received before being woken up. The cell identifiers contained in the cell signals received by the terminal are not included in the scene identification blocking list, which is used to store the identifiers of cells that do not require scene identification. The terminal is in a non-vehicle-riding state.

8. The method as described in claim 7, characterized in that, The method further includes: If the terminal fails to locate itself based on the cell signal at the current location, and the number of failures reaches a set threshold, then the cell identifier in the cell signal at the current location is added to the scene identification masking list.

9. The method as described in claim 1, characterized in that, The terminal executes a service matching the current location based on the location information, and further includes: If the location information indicates a scenario within the second subway station, and the movement state detected by the terminal is a passenger state, then the terminal displays an arrival reminder on the screen or broadcasts the arrival reminder via voice. The arrival reminder is used to indicate arrival at the second subway station.

10. The method according to any one of claims 1-9, characterized in that, The method further includes: The terminal detects a first trigger event and initiates data acquisition in response to the first trigger event; The terminal records the correspondence between cell signals and location information based on the received cell signals; The terminal terminates the data collection; The terminal obtains the location data set based on the recorded correspondence.

11. The method as described in claim 10, characterized in that, The first triggering event includes: The terminal obtains entry permission through a first device installed at the subway station entrance.

12. The method as described in claim 10, characterized in that, The terminal terminates the data collection, including: The terminal detects the second trigger event; The terminal responds to the second triggering event and ends the data acquisition.

13. The method as described in claim 12, characterized in that, The second triggering event includes: The terminal obtains exit permission through a second device installed at the subway station exit; or The first timer times out; the first timer is started by the terminal in response to the first triggering event; or The second timer times out. The second timer is activated when the terminal senses that it has left the second area.

14. The method according to any one of claims 10-13, characterized in that, The correspondence between the cell signal and the location information is stored in the collected data set, which includes at least one data record; The terminal obtains the location data set based on the recorded correspondence, including: The terminal obtains the location data set for location positioning based on the data records in the collected data set that meet the confidence requirements.

15. A data processing method, characterized in that, include: The terminal detects a first trigger event and initiates data acquisition in response to the first trigger event, wherein the first trigger event includes the terminal sensing that it has entered a first area; The terminal records the correspondence between cell signals and location information based on the received cell signals; The terminal terminates the data collection; A location data set is obtained based on the recorded correspondence. The location data set includes entry data records, in-station data records, and exit data records. The entry data records include a community identifier, subway station location information, and a first scene type identifier for indicating the subway station entrance. The in-station data records include a community identifier, subway station location information, and a second scene type identifier for indicating the subway station interior. The exit data records include a community identifier, subway station location information, and a first scene type identifier for indicating the subway station exit.

16. The method as described in claim 15, characterized in that, The first triggering event includes: The terminal obtains entry permission through a first device installed at the subway station entrance.

17. The method as described in claim 15, characterized in that, The terminal terminates the data collection, including: The terminal detects the second trigger event; The terminal responds to the second triggering event and ends the data acquisition.

18. The method as described in claim 17, characterized in that, The second triggering event includes: The terminal senses that it has left the second area; or The first timer times out; the first timer is started by the terminal in response to the first triggering event; or The second timer times out. The second timer is started when the terminal senses that it has left the second area.

19. The method as described in claim 18, characterized in that, The terminal senses an event of leaving the second area, including: The terminal obtains exit permission through a second device installed at the subway station exit.

20. The method as described in claim 15, characterized in that, The terminal records the correspondence between cell signals and location information based on the received cell signals, including: In response to the first triggering event, the terminal generates an entry data record, which includes a community identifier and subway station location information. The terminal generates an intra-station data record in response to receiving a cell signal, and the intra-station data record includes a cell identifier. The terminal generates an exit data record in response to sensing leaving the second area. The exit data record includes the community identifier and the subway station location information.

21. The method as described in claim 15, characterized in that, The inbound data record, the in-station data record, and / or the outbound data record also include at least one of the following: collection time, number of collections, signal strength, and motion state detected by the terminal.

22. The method according to any one of claims 15-21, characterized in that, The entry data record also includes evaluation information, which includes at least one of the following: successful verification count, failed verification count, and recall rate. The successful verification count is the number of times the terminal successfully verifies the location result when it senses entry into the subway station; the failed verification count is the number of times the terminal fails to verify the location result when it senses entry into the subway station; and the recall rate is determined based on the successful verification count and the failed verification count. The exit data record also includes evaluation information, which includes at least one of the following: number of successful verifications, number of failed verifications, and recall rate. The number of successful verifications is the number of times the terminal successfully verifies the location result when it senses that it has left the subway station. The number of failed verifications is the number of times the terminal fails to verify the location result when it senses that it has left the subway station. The recall rate is determined based on the number of successful verifications and the number of failed verifications.

23. The method according to any one of claims 20-22, characterized in that, The step of obtaining the location data set based on the recorded correspondence includes: According to the order of collection time from front to back, subway station location information is added to the station data records between the first station data record adjacent to the entry data record and the second station data record. The added subway station location information is the same as the subway station location information in the entry data record. The second station data record is the first station data record in the entry data records arranged in the order of collection time from front to back, where the movement state is the boarding state. According to the order of collection time from back to front, subway station location information is added to the station data records between the third station data record adjacent to the exit data record and the fourth station data record. The added subway station location information is the same as the subway station location information in the exit data record. The fourth station data record is the first station data record in the entry data records arranged in the order of collection time from back to front, where the movement state is the boarding state.

24. The method according to any one of claims 20-22, characterized in that, The step of obtaining the location data set based on the recorded correspondence includes: Following a chronological order, a first duration is determined between the entry data record and the first passenger status data record within the station. This first duration is added to the dwell duration set corresponding to the entering subway station. Based on the dwell duration set corresponding to the entering subway station, an entry dwell duration threshold is determined for the entering subway station. If the first duration is greater than the entry dwell duration threshold, then, starting from the collection time of the entry data record, station data records within the entry dwell duration threshold are selected, and the subway station location information from the entry data record is added to the selected station data records. Otherwise, the subway station location information from the entry data record is added to the station data records between the entry data record and the first passenger status data record; and / or Following a chronological order from back to front, a second duration is determined between the exit data record and the first passenger status data record. This second duration is added to the dwell duration set corresponding to the exiting subway station. Based on the dwell duration set corresponding to the exiting subway station, an exit dwell duration threshold is determined for the exiting subway station. If the second duration is greater than the exit dwell duration threshold, then, starting from the collection time of the exit data record, station data records within the exit dwell duration threshold are selected, and the subway station location information from the exit data record is added to the selected station data records. Otherwise, the subway station location information from the exit data record is added to the station data records between the exit data record and the first passenger status data record.

25. The method as described in claim 15, characterized in that, The correspondence between the cell signal and the location information is stored in the collected data set, which includes at least one data record; The step of obtaining the location data set based on the recorded correspondence includes: The terminal obtains the location data set for location positioning based on the data records in the collected data set that meet the confidence requirements.

26. The method as described in claim 25, characterized in that, The data records that meet the confidence requirements satisfy at least one of the following conditions: Inbound data records with a recall rate greater than a set threshold; Outbound data records with a recall rate greater than a set threshold; The edge degree of the station data records that meet the requirements is represented by the ratio of the number of collections in the station data records to the maximum number of collections, where the maximum number of collections is the maximum number of collections among all station data records containing the same subway station location information. The system collects incoming data records, in-station data records, and outgoing data records after a specified time; wherein the specified time is before the current time and the time elapsed since the current time is equal to the set time elapsed.

27. A communication device, characterized in that, include: One or more processors; wherein, when the instructions of one or more computer programs are executed by the one or more processors, the communication device causes to perform the method as described in any one of claims 1-14, or the method as described in any one of claims 15-26.

28. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a computer program that, when run on a computing device, causes the computing device to perform the method of any one of claims 1-14, or the method of any one of claims 15-26.

29. A chip, characterized in that, The chip is coupled to a memory for reading and executing program instructions stored in the memory to implement the method of any one of claims 1-14, or the method of any one of claims 15-26.

30. A computer program product, characterized in that, When the computer program product is invoked by a computer, it causes the computer to perform the method of any one of claims 1-14, or the method of any one of claims 15-26.

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