Method and system for identifying origin and destination of passengers based on mobile phone signaling

Abstract

This invention discloses a method for identifying the origin and destination of air passengers based on mobile signaling. First, a mobile signaling dataset is acquired, consisting of mobile signaling data from all airports and surrounding cities within a province over a specific time period. Each user's mobile signaling data includes the user's signaling generation time, the user's IMSI number, and the corresponding CGI information. The latitude and longitude information of the base station serving the user is obtained based on the CGI information. The region corresponding to the mobile signaling data is determined based on this latitude and longitude information, and the CGI information in the mobile signaling data is replaced with this region and latitude and longitude information. The mobile signaling data is sorted according to the chronological order of the signaling generation times of all mobile signaling data in the dataset. Finally, the user's dwell time in different regions is determined based on the regions corresponding to all mobile signaling data and the sorting result.

Description

Technical Field

[0001] This invention belongs to the field of airport passenger flow statistics technology, and more specifically, relates to a method and system for identifying the origin and destination of passengers based on mobile phone signaling. Background Technology

[0002] Airport passenger flow statistics include airport throughput, origin of passengers, destination of arriving passengers, etc. Accurately grasping the distribution of passengers in the city is an important data foundation for studying airport service radius and related urban airport planning.

[0003] Existing passenger flow statistics methods can accurately determine passengers' departure and arrival points at the airport level, but they cannot determine passengers' origin before departure or their destination after arrival. Currently, the only way to obtain passenger origin before departure and destination after arrival is through manual surveys. However, manual surveys are time-consuming, labor-intensive, and have small sample sizes, and they cannot provide accurate, comprehensive, and broad statistical results.

[0004] With the development of information and communication technology in my country and the arrival of the big data era, mobile terminals and big data analysis have become important directions and development trends. Mobile signaling, as the information carrier of communication between mobile phones and base stations, has the characteristics of short sampling periods, long observation times, and large sample data, which can accurately reconstruct the spatiotemporal trajectory of users, providing a reliable data foundation for identifying the origin of passengers before departure and their destination after landing at the airport. However, existing methods for identifying the origin and destination of passengers based on mobile signaling still have certain shortcomings: First, because this method includes airport staff and on-site personnel, it affects the identification results; second, because this method does not exclude residents walking near the airport, it further reduces the accuracy of identification. Summary of the Invention

[0005] In view of the above-mentioned defects or improvement needs of the existing technology, the present invention provides a method and system for identifying the origin and destination of passengers based on mobile phone signaling. The purpose is to solve the technical problems of existing methods for identifying the origin and destination of passengers based on mobile phone signaling, which affect the identification results by including airport staff and on-site personnel, and the technical problems of further reducing the identification accuracy by not excluding residents walking near the airport.

[0006] To achieve the above objectives, according to one aspect of the present invention, a method for identifying the origin and destination of passengers based on mobile phone signaling is provided, comprising the following steps:

[0007] (1) Obtain a mobile signaling dataset consisting of mobile signaling data of all users in all airports and surrounding cities in a province within a certain time range. Each mobile signaling data of each user includes the signaling generation time of the user, the IMSI number of the user, and the CGI information corresponding to the mobile signaling data.

[0008] (2) For the mobile signaling data in the mobile signaling dataset of each user per day obtained in step (1), the latitude and longitude information of the base station serving the user is obtained according to the CGI information in the mobile signaling data, the region corresponding to the mobile signaling data is determined according to the latitude and longitude information, and the CGI information in the mobile signaling data is replaced with the region and latitude and longitude information to obtain the updated mobile signaling dataset.

[0009] (3) For each user obtained in step (1), the mobile signaling data updated in step (2) is sorted according to the order of the signaling generation time of all mobile signaling data in the updated mobile signaling dataset in step (2). The user's dwell time in different regions is determined according to the region and sorting result of all mobile signaling data obtained in step (2). The mobile signaling dataset is then filtered according to the dwell time to obtain the filtered mobile signaling dataset.

[0010] (4) For the mobile signaling dataset after filtering in step (3), establish a set of dwell points corresponding to the mobile signaling dataset based on the region, latitude and longitude information and start and end time of each mobile signaling data in the mobile signaling dataset;

[0011] (5) Construct all pairs of adjacent elements in the set of dwell points obtained in step (4) into departure-arrival pairs, and construct all departure-arrival pairs into a departure-arrival pair set according to the order of their corresponding start and end times. Obtain the user's movement speed as the speed corresponding to the departure-arrival pair based on the distance between the corresponding areas of each departure-arrival pair in the departure-arrival pair set and the time interval between the areas. Take the area corresponding to the departure area in the departure-arrival pair as the departure area, and take the area corresponding to the arrival area in the departure-arrival pair as the arrival area.

[0012] (6) For the set of departure-arrival pairs obtained in step (5), determine whether the departure area corresponding to the first departure-arrival pair is an airport, whether the corresponding arrival area is a street, and whether the start time corresponding to the departure area in the departure-arrival pair does not have the previous mobile signaling data before the time threshold in the multiple mobile signaling data sorted by the user on the same day in step (3). If so, mark the arrival area in the departure-arrival pair as the user's destination after the plane lands, and then the process ends; otherwise, proceed to step (7).

[0013] (7) For the set of departure-arrival pairs obtained in step (5), determine whether the departure area corresponding to the last departure-arrival pair is a street and the arrival area corresponding to it is an airport, and whether the termination time corresponding to the arrival area in the departure-arrival pair does not have a subsequent mobile signaling data after the time threshold in the multiple mobile signaling data sorted by the user on the same day in step (3). If so, mark the departure area in the departure-arrival pair as the user's departure point before the plane takes off; otherwise, the process ends.

[0014] Preferably, the time range is from 1 week to 1 month, and more preferably 1 week.

[0015] Preferably, each user corresponds to multiple mobile signaling data, and all mobile signaling data are arranged in chronological order of the time the mobile signaling is generated each day. The format of each mobile signaling data is <user's signaling generation time, user's IMSI number, CGI information of mobile signaling data>.

[0016] Preferably, the time threshold in steps (6) and (7) is in the range of 0 to 10 minutes, preferably 5 minutes.

[0017] According to another aspect of the present invention, a system for identifying the origin and destination of passengers based on mobile phone signaling is provided, comprising:

[0018] The first module is used to obtain a mobile signaling dataset consisting of mobile signaling data of all users in all airports and surrounding cities in a certain province within a certain time range. Each mobile signaling data of each user includes the signaling generation time of the user, the user's IMSI number, and the CGI information corresponding to the mobile signaling data.

[0019] The second module is used to obtain the latitude and longitude information of the base station serving the user based on the CGI information in the mobile signaling data of each user's daily mobile signaling dataset obtained by the first module, determine the area corresponding to the mobile signaling data based on the latitude and longitude information, and replace the CGI information in the mobile signaling data with the area and latitude and longitude information to obtain an updated mobile signaling dataset.

[0020] The third module is used to sort the mobile signaling data updated by the second module according to the order of the signaling generation time of all mobile signaling data in the mobile signaling dataset updated by the second module for each user obtained by the first module. It determines the user's dwell time in different regions according to the regions corresponding to all mobile signaling data obtained by the second module and the sorting results, and filters the mobile signaling dataset according to the dwell time to obtain the filtered mobile signaling dataset.

[0021] The fourth module is used to establish a set of dwell points corresponding to the mobile signaling dataset after the filtering in the third module, based on the region, latitude and longitude information and start and end time of each mobile signaling data in the dataset.

[0022] The fifth module is used to construct all pairs of adjacent elements in the set of dwell points obtained in the fourth module into departure-arrival pairs, and to construct all departure-arrival pairs into a set of departure-arrival pairs according to the order of their corresponding start and end times. The user's movement speed is obtained based on the distance between the corresponding areas of each departure-arrival pair in the set of departure-arrival pairs and the time interval between the areas, which is used as the speed corresponding to the departure pair. The area corresponding to the departure area in the departure-arrival pair is used as the departure area, and the area corresponding to the arrival area in the departure-arrival pair is used as the arrival area.

[0023] The sixth module, for the departure-arrival pair set obtained from the fifth module, determines whether the departure area corresponding to the first departure-arrival pair is an airport, whether the corresponding arrival area is a street, and whether the start time corresponding to the departure area in the departure-arrival pair does not have a previous mobile signaling data before the time threshold in the multiple mobile signaling data sorted by the user on the same day in the third module. If so, the arrival area in the departure-arrival pair is marked as the user's destination after the plane lands; otherwise, it proceeds to the seventh module.

[0024] The seventh module, for the departure-arrival pair set obtained from the fifth module, determines whether the departure area corresponding to the last departure-arrival pair is a street, whether the corresponding arrival area is an airport, and whether the termination time corresponding to the arrival area in the departure-arrival pair does not have a subsequent mobile signaling data after the time threshold in the multiple mobile signaling data sorted by the user on the same day in the third module. If so, the departure area in the departure-arrival pair is marked as the user's departure location before the plane takes off; otherwise, the process ends.

[0025] Overall, the above-described technical solutions conceived by this invention, compared with the prior art, can achieve the following beneficial effects: This invention, by employing steps (6) to (7), focuses on identifying users whose mobile phone signaling suddenly appears or disappears within the airport area. The mobile phone signaling data of airport staff and on-site personnel, as well as residents near the airport and people picking up passengers at the airport, are continuous in both time and space within the airport area. Therefore, it can solve the technical problem that existing methods for identifying the origin and destination of passengers based on mobile phone signaling do not exclude airport staff and on-site personnel, as well as residents walking near the airport, which affects the identification results. Attached Figure Description

[0026] Figure 1This is a flowchart of the present invention for identifying the origin and destination of passengers based on mobile phone signaling. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0028] This invention provides a method for identifying the origin and destination of passengers based on mobile phone signaling. The method is achieved through seven steps: extracting mobile phone signaling data of the city where the airport is located, associating base station information with airport and street area information, preprocessing mobile phone signaling data, identifying passenger dwelling points at the airport and streets, identifying arriving and departing passengers at the airport, connecting adjacent dwelling points to the destination and identifying the origin and destination of passengers.

[0029] This invention provides a method for identifying the origin and destination of air passengers based on mobile phone signaling. It first reads only mobile phone signaling data from the airport and surrounding cities, eliminating interference from signaling from other areas. Furthermore, it uses a time threshold to filter the data. Considering that users may generate signaling data outside the airport area as their plane is about to land, the method compares the first signaling data of the day with the start time of their arrival at the airport; data within a 5-minute difference is considered arrival, thus excluding airport staff and on-site personnel. The same principle applies to departures. This processing aligns with the characteristic that mobile phone signaling suddenly appears or disappears within the airport area during landing or takeoff, and also eliminates interference from residents walking near the airport, resulting in a more accurate identification result.

[0030] like Figure 1 As shown, this invention provides a method for identifying the origin and destination of passengers based on mobile phone signaling, including the following steps:

[0031] (1) Obtain a mobile signaling dataset consisting of mobile signaling data of all users in all airports and surrounding cities in a province within a certain time range. Each mobile signaling data of each user includes the signaling generation time of the user, the IMSI number of the user, and the Cell Global Identifier (CGI) information corresponding to the mobile signaling data.

[0032] Specifically, the time range is from 1 week to 1 month, preferably 1 week.

[0033] In this invention, each user corresponds to multiple mobile signaling data. All mobile signaling data are arranged in chronological order of the time when the mobile signaling is generated each day, and the format of each mobile signaling data is <user's signaling generation time, user's IMSI number, CGI information of mobile signaling data>.

[0034] For example, a mobile signaling dataset is, for instance:

[0035] IMSI 1 7:00 CGI Information 1

[0036] IMSI 1 7 o'clock 10 o'clock CGI information 2

[0037] IMSI 1 7:20 CGI Information 3

[0038] IMSI 1 7:30 CGI Information 4

[0039] IMSI 1 7:40 CGI Information 5

[0040] IMSI 1 7:50 CGI Information 6

[0041] IMSI 1 8:00 CGI Information 7

[0042] IMSI 1 8:10 CGI Information 8

[0043] IMSI 1 8:20 CGI Information 9

[0044] IMSI 1 8:30 CGI Information 10

[0045] IMSI 1 8:40 CGI Information 11

[0046] IMSI 1 8:50 CGI Information 12

[0047] IMSI 1 9:00 CGI Information 13

[0048] IMSI 1 9:10 CGI Information 14

[0049] (2) For the mobile signaling data in the mobile signaling dataset of each user per day obtained in step (1), the latitude and longitude information of the base station serving the user is obtained according to the CGI information in the mobile signaling data, the region corresponding to the mobile signaling data is determined according to the latitude and longitude information, and the CGI information in the mobile signaling data is replaced with the region and latitude and longitude information to obtain the updated mobile signaling dataset.

[0050] The advantage of steps (1) to (2) above is that the location information of the base station is replaced with a larger regional spatial attribute, which reduces the interference caused by the ping-pong effect of the base station within the region, thereby enabling more accurate identification of the camping point.

[0051] (3) For each user obtained in step (1), the mobile signaling data updated in step (2) is sorted according to the order of the signaling generation time of all mobile signaling data in the updated mobile signaling dataset in step (2). The user's dwell time in different regions is determined according to the region and sorting result of all mobile signaling data obtained in step (2). The mobile signaling dataset is then filtered according to the dwell time to obtain the filtered mobile signaling dataset.

[0052] Specifically, after completing this step, you will get an example like the one below (where LON represents longitude and LAT represents latitude):

[0053] IMSI 1 7:00 AM Airport 1LON1, LAT1

[0054] IMSI 1 7:00-10:00 Airport 1LON2, LAT2

[0055] IMSI 1 7:20 AM Airport 1LON3, LAT3

[0056] IMSI 1 7:30 AM Airport 1LON4, LAT4

[0057] IMSI 1 7:40 AM Airport 1LON5, LAT5

[0058] IMSI 1 7:50 AM Street 2LON6, LAT6

[0059] IMSI 1 8:00 Street 2LON7, LAT7

[0060] IMSI 1 8:10 AM Street 3LON8, LAT8

[0061] IMSI 1 8:20 AM Street 3LON9, LAT9

[0062] IMSI 1 8:30 AM Street 4LON10, LAT10

[0063] IMSI 1 8:40 AM Street 4LON11, LAT11

[0064] IMSI 1 8:50 AM Street 4LON12, LAT12

[0065] IMSI 1 9:00 AM Street 4LON13, LAT13

[0066] IMSI 1 9:10 AM Street 4LON14, LAT14

[0067] As can be seen from the above example, the user's stay time in Airport 1 is 40 minutes, in Street 2 is 10 minutes, in Street 3 is 10 minutes, and in Street 4 is 40 minutes. The filtering operation in this step involves deleting mobile signaling data from the mobile signaling dataset where the user's stay time in the airport area is less than a preset threshold (the preset threshold ranges from 5 to 15 minutes, preferably 10 minutes) and the stay time in the street area is less than a preset threshold (the preset threshold ranges from 20 to 40 minutes, preferably 30 minutes). In this example, the mobile signaling data corresponding to Street 2 and Street 3 are deleted, resulting in:

[0068] IMSI 1 7:00 AM Airport 1LON1, LAT1

[0069] IMSI 1 7:00-10:00 Airport 1LON2, LAT2

[0070] IMSI 1 7:20 AM Airport 1LON3, LAT3

[0071] IMSI 1 7:30 AM Airport 1LON4, LAT4

[0072] IMSI 1 7:40 AM Airport 1LON5, LAT5

[0073] IMSI 1 8:30 AM Street 4LON10, LAT10

[0074] IMSI 1 8:40 AM Street 4LON11, LAT11

[0075] IMSI 1 8:50 AM Street 4LON12, LAT12

[0076] IMSI 1 9:00 AM Street 4LON13, LAT13

[0077] IMSI 1 9:10 AM Street 4LON14, LAT14

[0078] The purpose of this step is to identify user dwell points in different areas using different dwell time thresholds.

[0079] The advantage of this step is that, considering users generally leave the airport relatively quickly after landing, their dwell time at the airport will be shorter. Therefore, setting different dwell time thresholds based on the user's location allows for a more accurate determination of the user's stopping points at the airport and on the streets.

[0080] (4) For the mobile signaling dataset after filtering in step (3), establish a set of dwell points corresponding to the mobile signaling dataset based on the region, latitude and longitude information and start and end time of each mobile signaling data in the mobile signaling dataset;

[0081] Specifically, for the example obtained in step (3), the set of lodging points established in this step is {(IMSI1, Airport 1, 7:00 to 7:40, LON1, LAT1, LON5, LAT5), (IMSI 1, Street 4, 8:30 to 9:10, LON10, LAT10, LON14, LAT14), ...};

[0082] The purpose of this step is to identify the time and location information of users entering and leaving the dwell point, so as to prepare data for the next step of identifying user occupation.

[0083] (5) Construct all pairs of adjacent elements in the set of dwell points obtained in step (4) into departure-arrival pairs, and construct all departure-arrival pairs into a departure-arrival pair set according to the order of their corresponding start and end times. Obtain the user's movement speed as the speed corresponding to the departure-arrival pair based on the distance between the corresponding areas of each departure-arrival pair in the departure-arrival pair set and the time interval between the areas. Take the area corresponding to the departure area in the departure-arrival pair as the departure area, and take the area corresponding to the arrival area in the departure-arrival pair as the arrival area.

[0084] Specifically, for the example above, the departure-arrival pair is {(IMSI 1, Airport 1, 7:00 to 7:40, LON1, LAT1, LON5, LAT5), (IMSI 1, Street 4, 8:30 to 9:10, LON10, LAT10, LON14, LAT14)}, where Airport 1 is the departure area and Street 4 is the arrival area;

[0085] In this step, for the aforementioned departure and arrival pairs, the user's movement speed from airport 1 to street 4 is equal to:

[0086] Distance from Airport 1 to Street 4 / Time interval between the user's journey from Airport 1 to Street 4

[0087] The distance from Airport 1 to Street 4 is obtained based on the latitude and longitude of Airport 1 and Street 4. The time interval between Airport 1 and Street 4 is from the end time of Airport 1 at 7:40 to the start time of Street 4 at 8:30, a total of 50 minutes.

[0088] (6) For the set of departure-arrival pairs obtained in step (5), determine whether the departure area corresponding to the first departure-arrival pair is an airport and whether the corresponding arrival area is a street. Also, if the start time of the departure area corresponding to the departure area in the departure-arrival pair is not before the time threshold (the value of the time threshold is 0 to 10 minutes, preferably 5 minutes) in the multiple mobile phone signaling data sorted by the user on the same day in step (3), then there is no previous mobile phone signaling data. If so, mark the arrival area in the departure-arrival pair as the user's destination after the plane lands, and then the process ends. Otherwise, proceed to step (7).

[0089] For example, in the example above, the departure area of ​​the first departure-arrival pair is (IMSI 1, Airport 1, 7:00 to 7:40, LON1, LAT1, LON5, LAT5), and its corresponding start time is 7:00. This start time is 5 minutes before the time threshold, that is, 6:55. In step (3), the previous mobile signaling data does not exist in the multiple mobile data sorted by the user on the same day.

[0090] (7) For the departure-arrival pair set obtained in step (5), determine whether the departure area corresponding to the last departure-arrival pair is a street and the corresponding arrival area is an airport, and whether the termination time corresponding to the arrival area in the departure-arrival pair does not have a subsequent mobile phone signaling data after the time threshold (the value range of the preset threshold is 0 to 10 minutes, preferably 5 minutes) among the multiple mobile phone signaling data sorted by the user on the same day in step (3). If so, mark the departure area in the departure-arrival pair as the user's departure location before the plane takes off; otherwise, the process ends.

[0091] The purpose of this step is to identify users who have taken air travel and to correlate their departure and arrival times at airports and on the streets, thereby identifying their initial point of origin before takeoff and their final destination after landing.

[0092] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0093] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying the origin and destination of air passengers based on mobile phone signaling, characterized in that, Includes the following steps: (1) Obtain a mobile signaling dataset consisting of mobile signaling data of all users in all airports and surrounding cities in a certain province within a certain time range. Each mobile signaling data of each user includes the signaling generation time of the user, the IMSI number of the user, and the CGI information corresponding to the mobile signaling data. (2) For the mobile signaling data in the mobile signaling dataset of each user per day obtained in step (1), the latitude and longitude information of the base station serving the user is obtained according to the CGI information in the mobile signaling data, the region corresponding to the mobile signaling data is determined according to the latitude and longitude information, and the CGI information in the mobile signaling data is replaced with the region and latitude and longitude information to obtain the updated mobile signaling dataset. (3) For each user obtained in step (1), the mobile signaling data updated in step (2) is sorted according to the order of the signaling generation time of all mobile signaling data in the updated mobile signaling dataset in step (2). The user's dwell time in different regions is determined according to the region and sorting result of all mobile signaling data obtained in step (2). The mobile signaling dataset is then filtered according to the dwell time to obtain the filtered mobile signaling dataset. (4) For the mobile signaling dataset after filtering in step (3), establish a set of dwell points corresponding to the mobile signaling dataset based on the region, latitude and longitude information and start and end time of each mobile signaling data in the mobile signaling dataset; (5) Construct all pairs of adjacent elements in the set of dwell points obtained in step (4) into departure-arrival pairs, and construct all departure-arrival pairs into a set of departure-arrival pairs according to the order of their corresponding start and end times. Obtain the user's movement speed as the speed corresponding to the departure-arrival pair based on the distance between the corresponding areas of each departure-arrival pair in the set of departure-arrival pairs and the time interval between the areas. Take the area corresponding to the departure area in the departure-arrival pair as the departure area, and take the area corresponding to the arrival area in the departure-arrival pair as the arrival area. (6) For the set of departure-arrival pairs obtained in step (5), determine whether the departure area corresponding to the first departure-arrival pair is an airport, whether the corresponding arrival area is a street, and whether the start time corresponding to the departure area in the departure-arrival pair does not have the previous mobile signaling data before the time threshold in the multiple mobile signaling data sorted by the user on the same day in step (3). If so, mark the arrival area in the departure-arrival pair as the user's destination after the plane lands, and then the process ends; otherwise, proceed to step (7). (7) For the set of departure-arrival pairs obtained in step (5), determine whether the departure area corresponding to the last departure-arrival pair is a street and the arrival area corresponding to it is an airport, and whether the termination time corresponding to the arrival area in the departure-arrival pair does not have a subsequent mobile signaling data after the time threshold in the multiple mobile signaling data sorted by the user in step (3). If so, mark the departure area in the departure-arrival pair as the user's departure point before the plane takes off; otherwise, the process ends.

2. The method for identifying the origin and destination of passengers based on mobile phone signaling according to claim 1, characterized in that, The timeframe is from one week to one month.

3. The method for identifying the origin and destination of passengers based on mobile phone signaling according to claim 2, characterized in that, Each user corresponds to multiple mobile signaling data entries. All mobile signaling data entries are arranged in chronological order of the time the mobile signaling was generated each day, and the format of each mobile signaling data entry is <user's signaling generation time, user's IMSI number, CGI information of mobile signaling data>.

4. The method for identifying the origin and destination of passengers based on mobile phone signaling according to any one of claims 1 to 3, characterized in that, The time threshold values ​​in steps (6) and (7) range from 0 to 10 minutes.

5. A system for identifying the origin and destination of air passengers based on mobile phone signaling, characterized in that, include: The first module is used to obtain a mobile signaling dataset consisting of mobile signaling data of all users in all airports and surrounding cities in a certain province within a certain time range. Each mobile signaling data of each user includes the signaling generation time of the user, the IMSI number of the user, and the CGI information corresponding to the mobile signaling data. The second module is used to obtain the latitude and longitude information of the base station serving the user based on the CGI information in the mobile signaling data of each user's daily mobile signaling dataset obtained by the first module, determine the area corresponding to the mobile signaling data based on the latitude and longitude information, and replace the CGI information in the mobile signaling data with the area and latitude and longitude information to obtain an updated mobile signaling dataset. The third module is used to sort the mobile signaling data updated by the second module according to the order of the signaling generation time of all mobile signaling data in the mobile signaling dataset updated by the second module for each user obtained by the first module. It determines the user's dwell time in different regions according to the regions corresponding to all mobile signaling data obtained by the second module and the sorting results, and filters the mobile signaling dataset according to the dwell time to obtain the filtered mobile signaling dataset. The fourth module is used to establish a set of dwell points corresponding to the mobile signaling dataset after the filtering in the third module, based on the region, latitude and longitude information and start and end time of each mobile signaling data in the dataset. The fifth module is used to construct all pairs of adjacent elements in the set of dwell points obtained in the fourth module into departure-arrival pairs, and to construct all departure-arrival pairs into a set of departure-arrival pairs according to the order of their corresponding start and end times. The user's movement speed is obtained based on the distance between the corresponding areas of each departure-arrival pair in the set of departure-arrival pairs and the time interval between the areas, which is used as the speed corresponding to the departure pair. The area corresponding to the departure area in the departure-arrival pair is used as the departure area, and the area corresponding to the arrival area in the departure-arrival pair is used as the arrival area. The sixth module is used to determine, for the departure-arrival pair set obtained from the fifth module, whether the departure area corresponding to the first departure-arrival pair is an airport, whether the corresponding arrival area is a street, and whether the start time corresponding to the departure area in the departure-arrival pair does not have a previous mobile signaling data before the time threshold in the multiple mobile signaling data sorted by the user on the same day in the third module. If so, the arrival area in the departure-arrival pair is marked as the user's destination after the plane lands, and then the process ends; otherwise, it proceeds to the seventh module. The seventh module, for the departure-arrival pair set obtained from the fifth module, determines whether the departure area corresponding to the last departure-arrival pair is a street, whether the corresponding arrival area is an airport, and whether the termination time corresponding to the arrival area in the departure-arrival pair does not have a subsequent mobile signaling data after the time threshold in the multiple mobile signaling data sorted by the user on the same day in the third module. If so, the departure area in the departure-arrival pair is marked as the user's departure location before the plane takes off; otherwise, the process ends.

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