Method and device for determining entry mode and electronic equipment

Abstract

The invention discloses an entry mode determination method and device and electronic equipment. The method comprises: obtaining a network element group table corresponding to a plurality of traffic modes, the network element group table comprising at least one of the following: a base station cell number, a cell name and a scene name corresponding to the traffic mode; base station cells occupied by foreign entry tourists in a preset entry time period are determined from mobile depth data packet detection (DPI), a tourist entry time trajectory table is obtained, and the tourist entry time trajectory table at least comprises the base station cells occupied by the foreign entry tourists and geographical location information corresponding to the base station cells occupied by the foreign entry tourists; and according to the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table, determining the traffic mode used by the foreign entry tourists during entry. According to the invention, the technical problem of misjudgment of an entry mode caused by incomplete base station network element group information of a traffic scene in related technologies is solved.

Description

Technical Field

[0001] The present application relates to the field of data processing, and more specifically, to a method, device, and electronic device for determining an entry mode. Background Art

[0002] Departments such as the Transportation Bureau, Tourism Bureau, and Statistics Bureau closely monitor a city's out-of-town tourist data and their inbound transportation methods. Common inbound transportation methods include airplanes, high-speed trains, railways, highways, national and provincial roads, and shipping. Operators typically use base station network element group information for various transportation scenarios provided by wireless network maintenance departments. They then use DPI signaling data to determine whether visitors occupied base stations within these network element groups upon entry. For example, if a tourist arriving at an airport by plane occupies a base station cell within the airport, they are considered to have entered by plane. However, due to incomplete base station network element group information, this approach can lead to misjudgment of entry methods.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] The embodiments of the present application provide a method, device and electronic device for determining an entry mode, so as to at least solve the technical problem in the related art that the base station network element group information of the traffic scene is incomplete, resulting in misjudgment of the entry mode.

[0005] According to one aspect of an embodiment of the present application, a method for determining an entry mode is provided, comprising: obtaining a network element group table corresponding to multiple transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a scene name corresponding to the transportation mode; determining the base station cells occupied by out-of-town inbound tourists within a preset entry time period from mobile deep data packet inspection (DPI), and obtaining a tourist entry time trajectory table, wherein the tourist entry time trajectory table includes at least the base station cells occupied by out-of-town inbound tourists and geographical location information corresponding to the base station cells occupied by out-of-town inbound tourists; determining the transportation mode used by out-of-town inbound tourists upon entry based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

[0006] Optionally, out-of-town inbound tourists are determined in the following manner: determining from the mobile DPI the mobile phone users whose access time to the base station in the local area during the first time period is greater than or equal to the first time period and who have not accessed the base station in the local area during the second time period, to obtain the first out-of-town inbound tourist, wherein the first time period is after the second time period; determining the boundary users, the users who have recently started their phones and the newly developed mobile phone users from the first out-of-town inbound tourists, wherein the boundary users are all the base station cells connected in the mobile DPI during the first time period and are located within the first preset range of the city boundary, the users who have recently started their phones and the newly developed mobile phone users are the base station cells that appear in the mobile DPI for the first time during the first time period and are not located within the second preset range of the city boundary, and the base station cells that appear in the mobile DPI during the first time period do not include base station cells in the airport scene, and the first preset range is smaller than the second preset range; deleting the boundary users, the users who have recently started their phones and the newly developed mobile phone users from the first out-of-town inbound tourists, to obtain the out-of-town inbound tourists.

[0007] Optionally, based on the geographic location information in the tourist entry time trajectory table and the geographic location information corresponding to each cell name in the network element group table, the transportation mode used by the out-of-town inbound tourists when entering the country is determined, including: based on the geographic location information in the tourist entry time trajectory table and the geographic location information corresponding to each cell name in the network element group table, determining the distance from each base station cell occupied by the out-of-town inbound tourists to each base station cell in the network element group table corresponding to each transportation mode, to obtain a distance set; determining the minimum value in each distance set as the minimum distance from each base station cell occupied by the out-of-town inbound tourists to the network element group table corresponding to each transportation mode; determining the average value of the minimum distances from all base station cells occupied by the out-of-town inbound tourists to the network element group table corresponding to each transportation mode; and determining the transportation mode corresponding to the minimum value in the average value as the transportation mode used by the out-of-town inbound tourists when entering the country.

[0008] Optionally, determining the distance from each base station cell occupied by inbound tourists from outside the province to each base station cell in the network element group table corresponding to each mode of transportation includes: obtaining first geographic location information corresponding to the base station cell occupied by inbound tourists from outside the province, wherein the first geographic location information includes first longitude information and first latitude information of the base station cell occupied by inbound tourists from outside the province; obtaining second geographic location information corresponding to each base station in the network element group table corresponding to each mode of transportation, wherein the second geographic location information includes second longitude information and second latitude information of each base station in the network element group table corresponding to each mode of transportation; determining the distance from the base station cell occupied by inbound tourists to each base station cell in the network element group table corresponding to each mode of transportation based on the first geographic location information and the second geographic location information, wherein, when the base station cells in the network element group table corresponding to each mode of transportation meet the first condition, the first method is used to determine the distance from the base station cell occupied by inbound tourists to the base station cells in the network element group table corresponding to each mode of transportation; and when the base station cells in the network element group table corresponding to each mode of transportation do not meet the first condition, the second method is used to determine the distance from the base station cell occupied by inbound tourists to the base station cells in the network element group table corresponding to each mode of transportation.

[0009] Optionally, a first method is used to determine the distance between the base station cell occupied by inbound tourists from outside the province and the base station cell in the network element group table corresponding to each mode of transportation, including: determining the longitude difference between the first longitude information and the second longitude information; determining the latitude difference between the first latitude information and the second latitude information; determining the base station cell in the network element group table whose longitude difference is greater than the first value, or whose latitude difference is greater than the second value as the target base station cell; and determining the distance between the target base station cell and the base station cell occupied by inbound tourists from outside the province as a fixed distance.

[0010] Optionally, a second method is used to determine the distance between the base station cell occupied by inbound tourists from other places and the base station cell in the network element group table corresponding to each mode of transportation, including: converting the first geographic location information into first arc information, wherein the first arc information includes first sub-arc information corresponding to the first longitude information and second sub-arc information corresponding to the first latitude information; converting the second geographic location information into second arc information, wherein the second arc information includes third sub-arc information corresponding to the second longitude information and fourth sub-arc information corresponding to the second latitude information; and determining the distance between the base station cell occupied by inbound tourists from other places and the base station cell in the network element group table corresponding to each mode of transportation based on the first arc information and the second arc information.

[0011] Optionally, the method also includes: obtaining the highway indoor network element group and the high-speed rail indoor network element group in the network element group table; screening target users whose inbound tourists use railways and highways as their means of transportation; when the target users occupy the highway indoor network element group and the high-speed rail indoor network element group, determining the occupancy status of the base station cells occupied by the target users within a preset entry time period and the number of times the occupied base station cells appear; obtaining the target base station cells whose number of occurrences of the occupied base station cells is greater than the preset number and which are not in the original network element group table, and adding the target base station cells to the corresponding network element group table.

[0012] Optionally, the method also includes: obtaining the airport polygon area corresponding to the airport scene in the map; expanding the airport polygon area outward by a preset distance to obtain an airport buffer zone; deleting the base station cells in the network element group table corresponding to other scenes in the airport buffer zone from the corresponding network element group table, wherein the other scenes are scenes other than the airport scene among the scenes corresponding to multiple modes of transportation.

[0013] According to another aspect of an embodiment of the present application, a device for determining an entry mode is also provided, including: an acquisition module, used to obtain a network element group table corresponding to multiple transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name and a scene name corresponding to the transportation mode; a first determination module, used to determine the base station cell occupied by out-of-town inbound tourists within a preset entry time period from mobile deep data packet inspection DPI, and obtain a tourist entry time trajectory table, wherein the tourist entry time trajectory table includes at least the base station cell occupied by out-of-town inbound tourists and the geographical location information corresponding to the base station cell occupied by out-of-town inbound tourists; a second determination module, used to determine the transportation mode used by out-of-town inbound tourists when entering the country based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

[0014] According to another aspect of the embodiments of the present application, an electronic device is also provided, including: a memory for storing program instructions; a processor, connected to the memory, for executing program instructions to implement the following functions: obtaining a network element group table corresponding to multiple transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a transportation mode name corresponding to the transportation mode; determining the base station cells occupied by out-of-town inbound tourists within a preset entry time period from mobile deep data packet inspection (DPI), and obtaining a tourist entry time trajectory table, wherein the tourist entry time trajectory table includes at least the base station cells occupied by out-of-town inbound tourists and the geographical location information corresponding to the base station cells occupied by out-of-town inbound tourists; determining the transportation mode used by out-of-town inbound tourists when entering the country based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

[0015] According to another aspect of the embodiments of the present application, a non-volatile storage medium is further provided, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned method for determining the entry mode by running the computer program.

[0016] According to another aspect of the embodiments of the present application, a computer program product is provided, including computer instructions, which implement the above-mentioned method for determining the entry mode when executed by a processor.

[0017] In an embodiment of the present application, by obtaining a network element group table corresponding to multiple modes of transportation, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a scene name corresponding to the mode of transportation; determining the base station cell occupied by out-of-town inbound tourists within a preset entry time period from mobile deep data packet inspection DPI, and obtaining a tourist entry time trajectory table, wherein the tourist entry time trajectory table at least includes the base station cells occupied by out-of-town inbound tourists and the geographical location information corresponding to the base station cells occupied by out-of-town inbound tourists; based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table, the mode of transportation used by out-of-town inbound tourists when entering the country is determined, thereby achieving the purpose of finely judging the specific mode of transportation used by out-of-town inbound tourists to enter the country, thereby achieving the technical effect of improving the accuracy of judging the tourist entry mode, and further solving the technical problem in the related technology that the base station network element group information of the traffic scene is incomplete, resulting in misjudgment of the entry mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 This is a schematic diagram showing the physical space overlap of base station coverage;

[0020] Figure 2 is a hardware structure block diagram of a computer terminal for implementing a method for determining an entry mode according to an embodiment of the present application;

[0021] Figure 3 is a flow chart of a method for determining an entry mode according to an embodiment of the present application;

[0022] Figure 4 This is an example of a calculated network element group table for airport, high-speed rail, waterway, expressway, and national highway scenarios;

[0023] Figure 5This is a schematic diagram of the distances from the base station cells in the tourist entry time trajectory table to the base station cells in the highway network element group table according to an embodiment of the present application;

[0024] Figure 6 This is a schematic diagram of a long-distance base station directly assigned a value of 10 km according to an embodiment of the present application;

[0025] Figure 7 is a schematic diagram of an airport buffer zone according to an embodiment of the present application;

[0026] Figure 8 This is a structural diagram of a device for determining an entry method according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] The information collected in the embodiments of the present application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or reject the automated decision results; if the user chooses to reject, the expert decision-making process will be entered.

[0030] First, some nouns or terms that appear in the process of explaining the embodiments of this application are subject to the following explanations:

[0031] Base station network element group: In wireless communications, base stations with the same attributes are grouped together. For example, all base stations covering a university form a network element group, or all base stations covering an airport form a network element group.

[0032] Indoor base station: It is a base station system designed specifically to solve the problem of wireless signal coverage inside buildings. It uses distributed antennas to evenly cover the signal to all areas indoors.

[0033] Buffer: Commonly used in spatial analysis and spatial queries within Geographic Information Systems (GIS), it expands or contracts the boundaries of geometric objects within a given distance. It applies a buffer to geometric objects, generating a new geometric object based on the original geometric object. This new object is the union of all points in the original object whose distance to the original object does not exceed the specified distance. For example, for a MultiPoint object, applying a buffer operation generates a polygon object, which is the union of all points in the original multipoint object to the specified buffer distance.

[0034] ST_Within: A function provided by GIS geography that checks whether a geometric object is completely inside another geometric object.

[0035] The entry identification method in the related art has the following problems:

[0036] 1. Base station network element group data integrity defects: There are data missing in the base station network element group information of the existing traffic scene, and the base station cell changes caused by base station expansion / optimization are difficult to synchronize and update in time, resulting in misjudgment of entry mode. Figure 1 As shown: The red area is the designated high-speed rail base station network element group range, but the base station cell actually occupied by a high-speed rail user may be outside this range.

[0037] 2. Spatial coverage overlap: There is physical overlap between base station coverage along high-speed rail lines, highways, and airport transportation hubs (see below). Figure 1 As shown in the figure, a base station serves both a high-speed rail station and a highway), resulting in a single user being repeatedly counted in multiple transportation modes.

[0038] 3. Multimodal switching interference: During their actual travels, tourists may experience successive transitions between multiple modes of transportation (e.g., transferring from high-speed rail to highways), and mobile networks have inter-regional switching mechanisms (e.g., when landing, the plane first connects to a highway base station near the airport and then switches to the airport base station), resulting in multiple determinations of entry methods.

[0039] 4. Misidentification of border users: Permanent users in administrative boundary areas are mistakenly identified as inbound tourists due to base station signal drift.

[0040] In order to solve the problem of misjudgment of entry mode in related technologies, the embodiment of the present application provides a method for determining the entry mode, which can be run on Figure 2 Among the computer terminals shown, the computer terminal will be described below.

[0041] The method for determining the entry mode provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 2 FIG1 shows a hardware structure block diagram of a computer terminal for implementing a method for determining an entry mode. Figure 2 As shown, the computer terminal 10 may include one or more (illustrated by 102a, 102b, ..., 102n in the figure) processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission module 106 for communication functions connected via a wired and / or wireless network. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, and a BUS bus. It will be understood by those skilled in the art that Figure 2 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 2 More or fewer components than shown, or with Figure 2 Different configurations shown.

[0042] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry." The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 10. As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0043] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method for determining the entry method in the embodiments of the present application. The processor executes the software programs and modules stored in the memory 104 to perform various functional applications and data processing, thereby implementing the above-mentioned method for determining the entry method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0044] The transmission module 106 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of the computer terminal 10. In one embodiment, the transmission module 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission module 106 may be a radio frequency (RF) module, which is configured to communicate with the Internet wirelessly.

[0045] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 .

[0046] It should be noted that, in some optional embodiments, the above Figure 2 The computer terminal shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of hardware elements and software elements. Figure 2 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the computer terminal described above.

[0047] In the above-mentioned operating environment, an embodiment of the present application provides an embodiment of a method for determining an entry mode. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0048] Figure 3 is a flow chart of a method for determining an entry mode according to an embodiment of the present application, such as Figure 3As shown, the method includes the following steps:

[0049] Step S302: Acquire a network element group table corresponding to a plurality of transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a scene name corresponding to the transportation mode.

[0050] In step S302, the network element group table is a data set used to describe all relevant base station information in a specific transportation scenario. The aforementioned multiple transportation modes refer to various means of transportation that passengers can use to enter the country, such as airplanes, high-speed trains, highways, national roads, and Yangtze River shipping. The purpose of the network element group table is to organize the base station information corresponding to these transportation modes for subsequent analysis and processing. The network element group table can be determined by the following methods:

[0051] For example, in an airport scenario, when you enter the name of an airport in the map search box, the boundaries of the airport will be displayed on the map, and the boundary data can be obtained through the API interface provided by the map.

[0052] For expressways and national highways, for example, if you enter "Third Ring Expressway - Road" in the map, you will see the road on the map (this does not apply to the high-speed rail and shipping scenarios mentioned above). This road data consists of individual line segments and polylines, which are stacked along the expressway. The above search operation actually sends an HTTP request to the map server through the browser, which then returns the map data for "Inner Ring Expressway - Road." The returned map data can be obtained from the browser's debug panel. This map data is in JSON format. The profile_geo section of the place_info node represents the road data, which can be retrieved using a crawler. The obtained road data represents the line segments and polylines displayed on the map, separated by semicolons, with each semicolon representing a line segment or polyline. Multiple numbers within a line segment or polyline are separated by commas, with each pair representing a point. For example, the first number 11865628.26 represents the longitude of the point, and 3497439.15 represents the latitude. The following 11865531.23 and 3497397.43 represent the longitude and latitude of another point, which together form a line segment. These coordinates must be converted to longitude and latitude (WGS84 coordinate system), with each line segment and polyline saved as a record. By forming these line segments and polylines into a MultiLineString object and buffering this MultiLineString object, a narrow polygon along the road is formed. The buffer size set during buffering determines the width of this narrow polygon.

[0053] Map software can also display scenes such as high-speed rail, railways, and Yangtze River shipping, but the previously described method won't work for obtaining road data. Instead, manually draw the corresponding path in the map software to create a LineString object. Then, use a buffering operation on the LineString object to create a narrow polygon along the road. Similarly, the buffer size set during the buffering process will determine the width of this narrow polygon.

[0054] To create a network element group table for scenarios such as airports, high-speed railways, waterways, highways, and national highways, this can be done based on the longitude and latitude data (longitude, latitude) of each base station cell in the base station's engineering parameter data and the corresponding polygons for airports, high-speed railways, waterways, highways, and national highways. The traditional method uses the spatial query function provided by mapping software to filter out base station cells within the polygons, but this method relies on manual work and cannot be automated. During the construction, maintenance, and optimization of wireless network base stations, information such as base station numbers and cell numbers will change, making automated updates impossible.

[0055] In some embodiments of the present application, the spatial data function provided by the GIS geographic information system can be used to convert the longitude and latitude of the base station cell into a point object - Point, and convert the airport, high-speed rail and highway into a polygon object - Polygon. Then, use SQL query (ST_Within or ST_Contains) to find the points within a specific polygon. For example: select the engineering parameter table.base station number, engineering parameter table.cell number, engineering parameter table.cell name, scene circle.scene name from the engineering parameter table left join scene circle on ST_Contains (scene circle.polygons, engineering parameter table.base station cell longitude and latitude) where scene circle.scene name = 'airport'. If this query operation is performed on all base station cells in the entire network, it will consume more computing resources. In order to save computing resources, you can first take the maximum longitude and latitude (longitude_max, latitude_max) and minimum longitude and latitude (longitude_min, latitude_min) of the polygon boundary to generate the upper left and lower right corners of a rectangle. Taking an airport as an example, first determine the airport's longitude_max, latitude_max, longitude_min, and latitude_min. Then, by comparing the longitude and latitude of the existing base station cells, determine whether they meet the following conditions: longitude between longitude_min and longitude_max, and latitude between latitude_min and latitude_max. This quickly filters out all base stations outside the rectangle. Only base station cells within the rectangle are evaluated, quickly establishing a network element table for the airport scenario.

[0056] The same method can be used to implement other network element group tables. Figure 4 The following table shows the calculated network element group tables for airport, high-speed rail, waterway, expressway, and national highway scenarios. Using the above method, the network element group information for each scenario can be automatically updated every day.

[0057] Step S304: Determine the base station cells occupied by inbound tourists from outside the province during a preset entry time period from the mobile deep data packet inspection (DPI), and obtain a tourist entry time trajectory table, wherein the tourist entry time trajectory table includes at least the base station cells occupied by inbound tourists from outside the province and the geographical location information corresponding to the base station cells occupied by inbound tourists from outside the province.

[0058] In the above step S304, DPI can be used to monitor and analyze the communication data between the user device (such as a mobile phone) and the network base station, including but not limited to the user's location information, the connected base station information, the data transmission type, etc. In an embodiment of the present application, the DPI data can provide information on the base station cells occupied by foreign inbound tourists during a preset entry time period (referring to the initial period of time when tourists just enter a city or region, such as within 30 minutes after entry). According to the information of the base station cells, a tourist entry time trajectory table can be obtained. Among them, if the number of base station cells occupied in the first 30 minutes is less than 10, the time limit is expanded, and 10 different base station cells are taken in the DPI data to form a tourist entry time trajectory table (or called a tourist entry 30-minute base station). The following table is an example of a base station cell for a tourist's entry for 30 minutes.

[0059]

[0060]

[0061] Step S306: Determine the mode of transportation used by the inbound tourists at the time of entry based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

[0062] In the above step S306, the tourist entry time trajectory table records the detailed information of all base station cells occupied by foreign inbound tourists within a preset entry time period (for example, the first 30 minutes), including but not limited to the base station cell number, the geographical location information of the base station cell (i.e., longitude and latitude coordinates), and the specific time when foreign inbound tourists occupied these base stations. The network element group table is a database that organizes all base station information within the coverage area of a specific transportation scenario (such as airports, high-speed railways, highways, etc.), including the name, number and geographical location information (i.e., longitude and latitude coordinates) of the base station cells. Based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table, the mode of transportation used by foreign inbound tourists when entering the country can be determined.

[0063] Through steps S302 to S306 above, the goal of finely determining the specific mode of transportation used by inbound tourists from other places is achieved, thereby achieving the technical effect of improving the accuracy of determining the tourist's entry method. This further solves the technical problem in related technologies of incomplete base station network element group information in traffic scenarios, which leads to misjudgment of entry methods. This is explained below.

[0064] In step S304 of the above-mentioned method for determining the entry mode, out-of-town inbound tourists are determined in the following manner: determining from the mobile DPI a mobile phone user whose access time to the base station in the local area during a first time period is greater than or equal to the first time period and who has not accessed the base station in the local area during a second time period, thereby obtaining a first out-of-town inbound tourist, wherein the first time period is located after the second time period; determining from the first out-of-town inbound tourist boundary users, recently powered-on users, and newly developed mobile phone users, wherein the boundary users are all base station cells connected in the mobile DPI during the first time period and are located within a first preset range of the city boundary, the recently powered-on users and the newly developed mobile phone users are base station cells that appear in the mobile DPI for the first time during the first time period and are not located within a second preset range of the city boundary, and the base station cells that appear in the mobile DPI during the first time period do not include base station cells in the airport scene, and the first preset range is smaller than the second preset range; deleting the boundary users, recently powered-on users, and newly developed mobile phone users from the first out-of-town inbound tourists, thereby obtaining an out-of-town inbound tourist.

[0065] In some embodiments of the present application, the base station cells that a mobile phone user passes through can be counted in the mobile DPI data, and by formulating certain rules, it can be determined whether a user is a foreign tourist. For example, in the mobile DPI, the mobile phone users who have accessed the base station in the local area for 3 hours or more (i.e., the above-mentioned first time period) on the same day (i.e., the above-mentioned first time period) and have not accessed the base station in the local area in the previous period (e.g., the previous 7 days, i.e., the above-mentioned second time period) are counted. The obtained mobile phone users are the above-mentioned first foreign inbound tourists. However, this method may include some border users, users who have recently turned on their phones, and newly developed mobile phone users, so it is necessary to delete border users, users who have recently turned on their phones, and newly developed mobile phone users.

[0066] When determining a border user, a buffer operation is first performed based on the city boundary to form a 3-kilometer range of the city boundary (i.e., the first preset range mentioned above). Then, a determination is made as to whether all base station cells connected to the user's mobile phone in the mobile DPI data on that day are within the 3-kilometer range of the city boundary. If so, the user is determined to be a border user.

[0067] After analysis, it was found that if a real foreign tourist enters the country normally through highways, high-speed railways, shipping, and national highways, then the base station cell that appears in his DPI for the first time will generally be located within the 20-kilometer area of the border (that is, the second preset range mentioned above). If a tourist enters the country by plane, then the base station cell that appears in the DPI of that day will include the base station cell of the airport scene. Specifically, according to the boundary of the city, a range of 20 kilometers of the city boundary is formed through buffer operation. Determine whether the base station cell that appears in the DPI of the user for the first time that day is located within 20 kilometers of the city boundary or the base station cell that appears in the DPI of the user on that day includes the base station cell of the airport scene. If neither is satisfied, that is, the base station cell that appears in the DPI of the user for the first time that day is not located within 20 kilometers of the city boundary, and the base station cell that appears in the DPI of the user on that day does not include the base station cell of the airport scene, then this type of user is a recently started user and a newly developed user.

[0068] The boundary users, the users who recently turned on their phones, and the newly developed mobile phone users determined above are deleted from the first group of out-of-town inbound tourists to obtain out-of-town inbound tourists.

[0069] In step S306 of the above-mentioned method for determining the entry mode, the transportation mode used by the out-of-town inbound tourists when entering the country is determined based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table, including: determining the distance from each base station cell occupied by the out-of-town inbound tourists to each base station cell in the network element group table corresponding to each transportation mode based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table, to obtain a distance set; determining the minimum value in each distance set as the minimum distance from each base station cell occupied by the out-of-town inbound tourists to the network element group table corresponding to each transportation mode; determining the average value of the minimum distances from all base station cells occupied by the out-of-town inbound tourists to the network element group table corresponding to each transportation mode; and determining the transportation mode corresponding to the minimum value in the average value as the transportation mode used by the out-of-town inbound tourists when entering the country.

[0070] In some embodiments of the present application, in order to calculate the minimum distance between the base station cells in the tourist entry time trajectory table and the network element group table corresponding to each transportation mode, it is necessary to calculate the distance between the base station cells in the tourist entry time trajectory table and all the base station cells in the network element group table corresponding to all transportation modes, for example Figure 5As shown, the red circle indicates a base station cell in the tourist entry time trajectory table. We need to calculate the distances from this base station cell to each base station cell in the highway network element group table. These distances are set as d1, d2, d3, d4, and so on, representing the distance set described above. We then find the minimum value among d1, d2, d3, d4, and so on, and use this as the minimum distance from this base station cell in the tourist entry time trajectory table to the highway network element group table. For example, the resulting distance set is shown in the following table:

[0071]

[0072] The minimum value of these distances is 45.2 kilometers, so the minimum distance from cell 10142102_1024 to the highway network element group table is 45.2 kilometers. For each of the other cell sites in the tourist arrival time trajectory table, we also need to calculate their distances to the highway network element group table and the network element group tables corresponding to other transportation modes. We also need to calculate the minimum distance from each cell site occupied by inbound tourists to the network element group table corresponding to each transportation mode.

[0073] The minimum distances from each base station cell (i.e., each base station cell occupied by out-of-town inbound tourists) to the network element group table corresponding to each mode of transportation are averaged to obtain the minimum average distance from the base station to each mode of transportation during the 30-minute period of entry. The mode of transportation corresponding to the minimum value is used as the mode of transportation used by out-of-town inbound tourists upon entry. As shown in the table below, the minimum average distances for the five scenarios are: 9665.18 meters, 800.61 meters, 1.21 meters, 8681.75 meters, and 5568.14 meters. The minimum average distance for the high-speed rail scenario is only 1.21 meters, so high-speed rail will be the inbound transportation mode for this tourist.

[0074]

[0075]

[0076] If we use the statistical method introduced above to determine the entry transportation methods of all foreign tourists, we will get the following table.

[0077]

[0078] In the table above, the minimum average distance between the base station cells occupied by the first two visitors in the first 30 minutes and the highway cell group (table) is 0, while the distances to other cell groups are relatively large, indicating that these two visitors entered via the highway. As previously mentioned in the technical bottleneck of traditional methods, the physical overlap between base station coverage along high-speed rail lines and highways is a problem. Using this method, the minimum average distance in the high-speed rail scenario is smaller than the minimum average distance to the highway scenario, effectively determining the actual mode of exit.

[0079] The same approach can be used to determine the specific high-speed rail or highway that a tourist passed through when entering the country. For example, a network element group is created for each highway line, and then the minimum average distance from the base station to each highway 30 minutes after the tourist entered the country is determined. The results are shown in the following table:

[0080]

[0081]

[0082] Based on the minimum average distance, we can determine that tourists entered through the Yurong Expressway. After identifying each tourist's inbound transportation method, the daily inbound tourist transportation methods in the city are shown in the following table:

[0083] date airplane highway high-speed rail channel national highway 20250217 15337 87493 72794 631 16745 20250218 14454 104423 66853 505 17708 20250219 13957 85876 63732 642 15910 20250220 15143 75408 68591 594 14753 20250221 17148 101352 97036 2042 47526 20250222 16775 95784 92939 1270 32882 20250223 15214 76750 74978 1435 23624 20250224 13121 64697 57884 676 13846 20250225 13068 65920 50106 770 14075 20250226 13121 66297 51136 812 15365

[0084] It can be seen that the main means of transportation for foreign tourists to enter the city are highways and high-speed railways, followed by national highways and airplanes.

[0085] In the above steps, determining the distance between each base station cell occupied by non-local inbound tourists and each base station cell in the network element group table corresponding to each transportation mode includes: obtaining first geographic location information corresponding to the base station cell occupied by non-local inbound tourists, wherein the first geographic location information includes first longitude information and first latitude information of the base station cell occupied by non-local inbound tourists; obtaining second geographic location information corresponding to each base station in the network element group table corresponding to each transportation mode, wherein the second geographic location information includes second longitude information and second latitude information of each base station in the network element group table corresponding to each transportation mode; and determining the distance between the base station cell occupied by non-local inbound tourists and each base station cell in the network element group table corresponding to each transportation mode based on the first geographic location information and the second geographic location information, wherein, if the base station cells in the network element group table corresponding to each transportation mode meet the first condition, the distance between the base station cell occupied by non-local inbound tourists and the base station cells in the network element group table corresponding to each transportation mode is determined using the first method; and if the base station cells in the network element group table corresponding to each transportation mode do not meet the first condition, the distance between the base station cell occupied by non-local inbound tourists and the base station cells in the network element group table corresponding to each transportation mode is determined using the second method.

[0086] In the above steps, a first method is used to determine the distance between the base station cell occupied by inbound tourists from outside the province and the base station cell in the network element group table corresponding to each mode of transportation, including: determining the longitude difference between the first longitude information and the second longitude information; determining the latitude difference between the first latitude information and the second latitude information; determining the base station cell in the network element group table whose longitude difference is greater than the first value, or whose latitude difference is greater than the second value as the target base station cell; and determining the distance between the target base station cell and the base station cell occupied by inbound tourists from outside the province as a fixed distance.

[0087] In some embodiments of the present application, due to the large number of base stations in the network element group table corresponding to each mode of transportation, the amount of calculation is very large. In order to more quickly calculate the minimum distance from the base station cell in the tourist entry time trajectory table to the network element group table corresponding to each mode of transportation, for base stations with a relatively long distance from the base station cell to the base stations in each network element group table, there is no need to calculate the specific distance value d, and a relatively large distance value d can be directly assigned (for example, d = 10 kilometers). Through the Haversine formula (explained below), it can be found that if the longitudes of two base station cells differ by 0.102942 degrees, the distance d differs by 10 kilometers; when the latitudes of the two base station cells differ by 0.089832 degrees, the distance d differs by 10 kilometers, so a preliminary screening can be performed first through the longitude and latitude data of the base station cell, as follows Figure 6For example, the longitude and latitude of cell M in the tourist arrival time trajectory table are (107.05456, 29.56442206). A longitude difference of 0.102942 degrees or a latitude difference of 0.089832 degrees from this latitude and longitude value will form a red square. Cells outside the square are at least 10 kilometers away from cell M and are directly assigned a distance d = 10 kilometers. Cells within the square are calculated using the Haversine formula. This method eliminates the need for spherical distance calculations for many distant base stations, saving computing resources and preventing any impact on subsequent results.

[0088] For example, the following table shows the distance values from the base station cells in a tourist's entry time trajectory table to the network element group tables corresponding to all transportation modes. There are 12 base stations, and if the minimum distance from these base stations to the network element group tables corresponding to the transportation modes is 10,000 meters, based on the above description, it can be inferred that the minimum distance from this base station cell to the network element group table corresponding to the transportation mode exceeds 10 kilometers.

[0089]

[0090] In the above table, the distance is 0, which means that the base station cell in the tourist’s current tourist entry time trajectory table belongs to the high-speed rail or highway network element group.

[0091] In the above steps, the second method is used to determine the distance between the base station cell occupied by inbound tourists from other places and the base station cell in the network element group table corresponding to each transportation mode, including: converting the first geographic location information into first arc information, wherein the first arc information includes first sub-arc information corresponding to the first longitude information and second sub-arc information corresponding to the first latitude information; converting the second geographic location information into second arc information, wherein the second arc information includes third sub-arc information corresponding to the second longitude information and fourth sub-arc information corresponding to the second latitude information; and determining the distance between the base station cell occupied by inbound tourists from other places and the base station cell in the network element group table corresponding to each transportation mode based on the first arc information and the second arc information.

[0092] In some embodiments of the present application, assuming that the longitude and latitude of the base station cell in the tourist entry time trajectory table are Lon1 (first longitude information) and Lat1 (first latitude information), and the longitude and latitude of a base station in the network element group table in the highway scenario are Lon2 (second longitude information) and Lat2 (second latitude information), to calculate the spherical distance between these two points, the Haversine formula can be used:

[0093]

[0094] Where d is the spherical distance between the two points, r is the radius of the sphere, λ1 and λ2 are the radians converted from the longitudes Lon1 and Lon2, i.e., the first and third sub-radians mentioned above, respectively; φ1 and φ2 are the radians converted from the latitudes Lat1 and Lat2, i.e., the second and fourth sub-radians mentioned above, respectively; Δλ = λ2 - λ1, and Δφ = φ2 - φ1.

[0095] The detailed steps are as follows:

[0096] 1. Convert longitude and latitude to radians: Lon1, Lon2, Lat1, Lat2 to radians.

[0097]

[0098] 2. Calculate the latitude difference and longitude difference: Δλ = λ2 - λ1, Δφ = φ2 - φ1.

[0099] 3. Apply Haversine function:

[0100] but

[0101] 4. Calculate the central angle:

[0102] 5. Calculate the distance: d = r·c.

[0103] In the above-mentioned method for determining the entry mode, the method also includes: obtaining the highway indoor network element group and the high-speed rail indoor network element group in the network element group table; screening target users whose means of transportation used by foreign inbound tourists are railways and highways; when the target user occupies the highway indoor network element group and the high-speed rail indoor network element group, determining the occupancy status of the base station cell occupied by the target user within the preset entry time period and the number of times the occupied base station cell appears; obtaining the target base station cell whose number of occurrences of the occupied base station cell is greater than the preset number and is not in the original network element group table, and adding the target base station cell to the corresponding network element group table.

[0104] In some embodiments of the present application, a polygon is first obtained by BUFFERing the map of scenes such as high-speed rail, waterways, highways, and national highways. Then, the base station cell is selected using this polygon. The size of the BUFFER value will determine the width of the narrow polygon. The size of the buffer value at this BUFFER cannot be accurately set, which will cause the network element group of scenes such as high-speed rail, waterways, highways, and national highways to be not necessarily accurate. If they are not added to the high-speed rail network element group, the calculated minimum average distance will not reach 0. The network element group table information can be improved by the following methods:

[0105] First, collect the indoor distributed base stations in the waiting halls and exits of high-speed railway stations, the indoor distributed base stations in tunnels on high-speed railway lines, the indoor distributed base stations in tunnels on highway lines, the indoor distributed base stations at highway toll stations, and the indoor distributed base stations in highway service areas, as shown in the following table, to form the highway indoor distributed network element group and the high-speed railway indoor distributed network element group.

[0106]

[0107] The base station signal can only be received by mobile phones on high-speed trains and highways. Only real high-speed train users and highway users will use the above-mentioned indoor base stations.

[0108] Based on the previously identified transportation methods of inbound tourists, after filtering out railway and highway users, the team further determines whether these inbound tourists also occupy these highway and high-speed rail indoor network element groups. If so, the user is considered a correct high-speed rail or highway user. The team then analyzes the base station cells they occupy within this time period (30 minutes after arrival) and counts the number of occurrences of each cell. If a cell appears frequently (for example, more than 50 times per day, the preset number) and is not in the original network element group, the target cell is added to the corresponding network element group table. This method is highly suitable for improving the cell groups of airports, high-speed rail stations, and highways.

[0109] In the above-mentioned method for determining the entry mode, the method also includes: obtaining the airport polygon area corresponding to the airport scene in the map; expanding the airport polygon area outward by a preset distance to obtain an airport buffer zone; deleting the base station cells in the network element group table corresponding to other scenes in the airport buffer zone from the corresponding network element group table, wherein the other scenes are scenes other than the airport scene among the scenes corresponding to multiple transportation modes.

[0110] In some embodiments of the present application, if a tourist enters by plane and flies at low altitude during landing (without entering the airport polygon), he will receive ground base station signals. If these base station cells happen to belong to the high-speed rail or highway polygon, then the tourist's entry method may be counted as high-speed rail or highway, which will affect the accuracy of the statistical results. To solve this problem, it is necessary to perform a buffer operation on the airport polygon. When buffering, the buffer zone is set to a larger size (for example, 10 kilometers, the preset distance mentioned above) to form an airport buffer zone. As follows Figure 7 As shown in the figure, all base station cells in the network element group tables for all scenarios within the airport buffer, such as expressways, high-speed railways, and national highways (i.e., the other scenarios mentioned above), have been removed from the corresponding scenario network element groups. In other words, the base station cells in the high-speed railway and expressway network element groups circled in purple in the figure have been removed from the high-speed railway and expressway network element groups because they would interfere with the judgment of the transportation mode of flight.

[0111] The above method improves the recognition accuracy of inbound traffic modes by improving network element group information, eliminating border users, and only taking base stations within 30 minutes of entry, and realizes automatic program update and improvement of traffic scene network element group information.

[0112] Figure 8 is a structural diagram of a device for determining an entry mode according to an embodiment of the present application, such as Figure 8 As shown, the device includes:

[0113] An acquisition module 50 is configured to acquire a network element group table corresponding to a plurality of transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a scene name corresponding to the transportation mode;

[0114] A first determining module 52 is configured to determine, from mobile deep data packet inspection (DPI), base station cells occupied by inbound tourists from outside the province during a preset entry time period, and obtain a tourist entry time trajectory table, wherein the tourist entry time trajectory table includes at least base station cells occupied by inbound tourists from outside the province and geographic location information corresponding to the base station cells occupied by the inbound tourists from outside the province;

[0115] The second determining module 54 is configured to determine the mode of transportation used by the inbound tourists at the time of entry based on the geographical location information in the tourists' entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

[0116] It should be noted that Figure 8 The entry mode determination device shown is used to perform Figure 3 The method for determining the entry method shown in the figure, therefore the relevant explanations in the above-mentioned method for determining the entry method are also applicable to the device for determining the entry method, and will not be repeated here.

[0117] An embodiment of the present application also provides an electronic device, which includes a memory and a processor, wherein the memory is used to store program instructions; the processor is connected to the memory and is used to execute program instructions to implement the following functions: obtaining a network element group table corresponding to multiple transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a transportation mode name corresponding to the transportation mode; determining the base station cells occupied by out-of-town inbound tourists within a preset entry time period from mobile deep data packet inspection (DPI), and obtaining a tourist entry time trajectory table, wherein the tourist entry time trajectory table includes at least the base station cells occupied by out-of-town inbound tourists and the geographical location information corresponding to the base station cells occupied by out-of-town inbound tourists; determining the transportation mode used by out-of-town inbound tourists when entering the country based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

[0118] It should be noted that the above electronic equipment is used to perform Figure 3The method for determining the entry method shown in the figure, therefore the relevant explanations in the above method for determining the entry method also apply to the electronic device and will not be repeated here.

[0119] An embodiment of the present application also provides a non-volatile storage medium, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned method for determining the entry mode by running the computer program.

[0120] An embodiment of the present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the method for determining the entry mode in each embodiment of the present application.

[0121] An embodiment of the present application also provides a computer program, which, when executed by a processor, implements the steps of the method for determining the entry mode in each embodiment of the present application.

[0122] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0123] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0124] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0125] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0126] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0127] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0128] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining an entry mode, characterized in that: include: Acquire a network element group table corresponding to a plurality of transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a scene name corresponding to the transportation mode; Determine the base station cells occupied by inbound tourists from outside the province during a preset entry time period from mobile deep data packet inspection (DPI), and obtain a tourist entry time trajectory table, wherein the tourist entry time trajectory table includes at least the base station cells occupied by the inbound tourists from outside the province and the geographical location information corresponding to the base station cells occupied by the inbound tourists from outside the province; The mode of transportation used by the out-of-town inbound tourists upon entry is determined based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

2. The method according to claim 1, characterized in that The inbound tourists from other places are determined in the following ways: Determine from the mobile DPI that a mobile phone user who has accessed a base station in the local area for a time period greater than or equal to the first time period in a first time period and has not accessed the base station in the local area in a second time period, thereby obtaining a first non-local inbound tourist, wherein the first time period is after the second time period; Determine boundary users, recently powered-on users, and newly developed mobile phone users from the first inbound tourists, wherein the boundary users are all base station cells connected in the mobile DPI during the first time period and are located within a first preset range of the city boundary; the recently powered-on users and the newly developed mobile phone users are base station cells that appear in the mobile DPI for the first time during the first time period and are not located within a second preset range of the city boundary, and the base station cells that appear in the mobile DPI during the first time period do not include base station cells in airport scenes, and the first preset range is smaller than the second preset range; The border users, the users who recently turned on their phones, and the newly developed mobile phone users are deleted from the first group of out-of-town inbound tourists to obtain the out-of-town inbound tourists.

3. The method according to claim 1, characterized in that Determining the mode of transportation used by the out-of-town inbound tourists upon entry based on the geographic location information in the tourist entry time trajectory table and the geographic location information corresponding to each cell name in the network element group table includes: Determine the distance between each base station cell occupied by the out-of-town inbound tourist and each base station cell in the network element group table corresponding to each transportation mode based on the geographic location information in the tourist entry time trajectory table and the geographic location information corresponding to each cell name in the network element group table, and obtain a distance set; Determine the minimum value in each distance set as the minimum distance between each base station cell occupied by the out-of-town inbound tourists and the network element group table corresponding to each transportation mode; Determine the average value of the minimum distances from all base station cells occupied by the inbound tourists to the network element group table corresponding to each mode of transportation; The mode of transportation corresponding to the minimum value among the average values is determined as the mode of transportation used by the foreign inbound tourists when entering the country.

4. The method according to claim 3, characterized in that Determining the distance between each base station cell occupied by the out-of-town inbound tourists and each base station cell in the network element group table corresponding to each transportation mode includes: Acquire first geographic location information corresponding to the base station cell occupied by the inbound tourist from outside the province, wherein the first geographic location information includes first longitude information and first latitude information of the base station cell occupied by the inbound tourist from outside the province; Obtaining second geographical location information corresponding to each base station in the network element group table corresponding to each transportation mode, wherein the second geographical location information includes second longitude information and second latitude information of each base station in the network element group table corresponding to each transportation mode; Based on the first geographic location information and the second geographic location information, determine the distance between the base station cell occupied by the out-of-town inbound tourists and each base station cell in the network element group table corresponding to each transportation mode, wherein, when the base station cell in the network element group table corresponding to each transportation mode meets the first condition, the first method is adopted to determine the distance between the base station cell occupied by the out-of-town inbound tourists and the base station cell in the network element group table corresponding to each transportation mode; when the base station cell in the network element group table corresponding to each transportation mode does not meet the first condition, the second method is adopted to determine the distance between the base station cell occupied by the out-of-town inbound tourists and the base station cell in the network element group table corresponding to each transportation mode.

5. The method according to claim 4, characterized in that The first method is used to determine the distance between the base station cell occupied by the out-of-town inbound tourists and the base station cell in the network element group table corresponding to each transportation mode, including: determining a longitude difference between the first longitude information and the second longitude information; determining a latitude difference between the first latitude information and the second latitude information; Determine the base station cell in the network element group table whose longitude difference is greater than the first value, or whose latitude difference is greater than the second value, as the target base station cell; The distance between the target base station cell and the base station cell occupied by the foreign inbound tourists is determined as a fixed distance.

6. The method according to claim 4, characterized in that The second method is used to determine the distance between the base station cell occupied by the out-of-town inbound tourists and the base station cell in the network element group table corresponding to each transportation mode, including: Converting the first geographic location information into first arc information, wherein the first arc information includes first sub-arc information corresponding to the first longitude information and second sub-arc information corresponding to the first latitude information; Converting the second geographic location information into second arc information, wherein the second arc information includes third sub-arc information corresponding to the second longitude information and fourth sub-arc information corresponding to the second latitude information; The distance between the base station cell occupied by the foreign inbound tourists and the base station cell in the network element group table corresponding to each transportation mode is determined based on the first arc information and the second arc information.

7. The method according to claim 1, characterized in that The method further comprises: Obtaining the highway indoor network element group and the high-speed rail indoor network element group in the network element group table; Screening the target users of the transportation modes used by the inbound tourists from other places as railways and highways; In the case where the target user occupies the highway indoor network element group and the high-speed railway indoor network element group, determining the occupancy status of the base station cell occupied by the target user during the preset entry time period and the number of times the occupied base station cell appears; A target base station cell is obtained, the target base station cell of which the number of times the occupied base station cell appears is greater than a preset number and is not in the original network element group table, and the target base station cell is added to the corresponding network element group table.

8. The method according to claim 1, characterized in that The method further comprises: Get the airport polygon area corresponding to the airport scene in the map; Expanding the airport polygonal area outward by a preset distance to obtain an airport buffer zone; The base station cells in the network element group table corresponding to other scenarios in the airport buffer zone are deleted from the corresponding network element group table, wherein the other scenarios are scenarios corresponding to the multiple transportation modes except the airport scenario.

9. A device for determining an entry mode, characterized in that: include: An acquisition module is configured to acquire a network element group table corresponding to a plurality of transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a scene name corresponding to the transportation mode; A first determination module is configured to determine, from mobile deep data packet inspection (DPI), base station cells occupied by inbound tourists from other places within a preset entry time period, and obtain a tourist entry time trajectory table, wherein the tourist entry time trajectory table includes at least the base station cells occupied by the inbound tourists from other places and geographical location information corresponding to the base station cells occupied by the inbound tourists from other places; The second determining module is used to determine the mode of transportation used by the out-of-town inbound tourists when entering the country based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

10. An electronic device, characterized in that: include: a memory for storing program instructions; A processor, connected to the memory, is used to execute program instructions that implement the following functions: obtaining a network element group table corresponding to multiple transportation modes, wherein the network element group table includes at least one of the following: a base station cell number, a cell name, and a transportation mode name corresponding to the transportation mode; determining the base station cell occupied by out-of-town inbound tourists within a preset entry time period from mobile deep data packet inspection (DPI), and obtaining a tourist entry time trajectory table, wherein the tourist entry time trajectory table at least includes the base station cell occupied by the out-of-town inbound tourists and the geographical location information corresponding to the base station cell occupied by the out-of-town inbound tourists; determining the transportation mode used by the out-of-town inbound tourists when entering the country based on the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table.

11. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the method for determining the entry mode according to any one of claims 1 to 8 by running the computer program.

12. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the method for determining the entry mode described in any one of claims 1 to 8 is implemented.

Images