A people flow monitoring method and device, electronic equipment and storage medium

Abstract

The application provides a kind of passenger flow monitoring method, device, electronic equipment and storage medium, it is related to data analysis technical field, for monitoring the passenger flow tide distribution situation of subway station.The method comprises: obtaining the signaling data of M users located in target area, the signaling data of each user includes the information of base station accessed by user in first time period, the information of base station includes the identification and access time point of the base station, M is positive integer;According to the signaling data of M users, identify N subway users from M users;Subway user is the user using subway in first time period, N is positive integer less than or equal to M;According to the signaling data of N subway users, and the identification of base station associated with target subway station in target area, determine the passenger flow information of target subway station, passenger flow information is used to indicate the number of the subway users of subway station in each time point in first time period.

Description

Technical Field

[0001] This application relates to the field of data analysis technology, and in particular to a method, device, electronic device and storage medium for monitoring pedestrian flow. Background Technology

[0002] With the vigorous advancement of subway construction, more and more subway lines are operating in various places, and the mileage is getting longer and longer. The subway has become the first choice for citizens' travel, which has also put pressure on the traditional subway operation mode.

[0003] Currently, monitoring the tidal distribution of passenger flow at subway stations can serve as a foundation for improving subway operations. Subway users can also adjust their travel times and routes based on this data, avoiding congestion and safety hazards at subway stations. Therefore, how to monitor passenger flow at subway stations is a pressing issue that needs to be addressed. Summary of the Invention

[0004] This invention provides a method, device, electronic equipment, and storage medium for monitoring passenger flow, used to monitor the tidal distribution of passenger flow at subway stations. The technical solution of this invention is as follows:

[0005] In a first aspect, the present invention provides a method for monitoring pedestrian traffic, the method comprising:

[0006] Obtain signaling data for M users located in the target area. The signaling data for each user includes information about the base stations the user has accessed during the first time period. The base station information includes the base station identifier and the access time. M is a positive integer.

[0007] Based on the signaling data of M users, identify N subway users from the M users; subway users are users who have used the subway in the first time period, and N is a positive integer less than or equal to M;

[0008] Based on the signaling data of N subway users and the identifiers of the base stations associated with the target subway station in the target area, the passenger flow information of the target subway station is determined. The passenger flow information is used to indicate the number of subway users at each time point within the first time period.

[0009] The technical solution provided by this invention offers at least the following advantages: First, based on the signaling data of M users, N subway users who used the subway during the first time period are identified from among the M users. This avoids analyzing the signaling data of some non-subway users, improving the accuracy of subsequent monitoring results. Then, based on the signaling data of the N subway users and the identifiers of the base stations associated with the target subway station within the target area, the number of subway users at various time points around the target subway station is counted over a period of time, enabling the monitoring of the tidal distribution of passenger flow at the target subway station.

[0010] In one possible implementation, for each of the M users, based on the user's signaling data, it is determined whether the user meets preset conditions; if the preset conditions are met, the user is identified as a subway user; wherein the preset conditions include at least one of the following:

[0011] The number of times a user has accessed the first base station within the first time period is greater than or equal to the first preset value;

[0012] The number of times a user has continuously accessed the first base station within the first time period is greater than or equal to the second preset value;

[0013] The time interval between the first and second base stations that the user has continuously accessed within the first time period is less than a third preset value;

[0014] The first base station is a base station that is associated with a subway station, and the second base station is a base station that is not associated with a subway station.

[0015] Based on this possible implementation method, among a large number of travelers, subway users whose mode of travel is subway can be identified according to their signaling data, while some non-subway users can be excluded, thereby improving the accuracy of subsequent monitoring of passenger flow at subway stations.

[0016] In another possible implementation, for each of the N subway users, if the subway user's signaling data contains the identifier of the base station associated with the target subway station in the target area, the subway user's travel time, travel distance, and travel speed are determined based on the subway user's signaling data; if the subway user's travel time, travel distance, and travel speed meet preset rules, the subway user is associated with the target subway station in the target area; and based on the signaling data of the subway user associated with the target subway station, the passenger flow information of the target subway station is determined.

[0017] Based on this possible implementation method, for each of the N subway users, the subway user is associated with the target subway station in the target area through time and geographical dimensions, thereby determining the passenger flow information of the target subway station.

[0018] In another possible implementation, based on the signaling data of N subway users, P first subway users and Q second subway users are determined. The first time period includes a first sub-time period and a second sub-time period. The first subway users are the subway users who access the associated base station of the first subway station in the first sub-time period. The second subway users are the subway users who access the associated base station of the second subway station in the second sub-time period. The second sub-time period is the next sub-time period adjacent to the first sub-time period. P is a positive integer less than or equal to N, and Q is a positive integer less than or equal to N.

[0019] The subway users who overlap among the P first subway users and Q second subway users are defined as third subway users. The third subway user is a subway user who accesses the associated base station of the first subway station in the first sub-time period and accesses the associated base station of the second subway station in the second sub-time period.

[0020] The number of third-tier subway users is used as the number of subway users who moved from the first subway station to the second subway station during the first sub-time period.

[0021] Based on this possible implementation method, the tidal changes in passenger flow at subway stations in time and direction can be determined by identifying overlapping subway users in the associated base stations of different subway stations at adjacent times.

[0022] In a second aspect, the present invention provides a pedestrian flow monitoring device, the device comprising:

[0023] The acquisition module is used to acquire signaling data of M users located in the target area. The signaling data of each user includes information about the base stations that the user has accessed in the first time period. The base station information includes the base station identifier and the access time point. M is a positive integer.

[0024] The processing module is used to identify N subway users from M users based on the signaling data of M users; subway users are users who have used the subway in the first time period, and N is a positive integer less than or equal to M.

[0025] The processing module is also used to determine the passenger flow information of the target subway station based on the signaling data of N subway users and the identifier of the base station associated with the target subway station in the target area. The passenger flow information is used to indicate the number of subway users at each time point in the first time period.

[0026] In one possible implementation, the processing module is specifically used to: for each of the M users, determine whether the user meets the preset conditions based on the user's signaling data; if the preset conditions are met, determine that the user is a subway user;

[0027] The preset conditions include at least one of the following:

[0028] The number of times a user has accessed the first base station within the first time period is greater than or equal to the first preset value;

[0029] The number of times a user has continuously accessed the first base station within the first time period is greater than or equal to the second preset value;

[0030] The time interval between the first and second base stations that the user has continuously accessed within the first time period is less than a third preset value;

[0031] The first base station is a base station that is associated with a subway station, and the second base station is a base station that is not associated with a subway station.

[0032] In another possible implementation, the processing module is specifically used to: for each of the N subway users, if the subway user's signaling data contains the identifier of the base station associated with the target subway station in the target area, determine the subway user's travel time, travel distance, and travel speed based on the subway user's signaling data; and if the subway user's travel time, travel distance, and travel speed meet the preset rules, associate the subway user with the target subway station in the target area.

[0033] Based on the signaling data of subway users associated with the target subway station, determine the passenger flow information of the target subway station.

[0034] In another possible implementation, the processing module is further configured to determine P first subway users and Q second subway users based on the signaling data of N subway users. The first time period includes a first sub-time period and a second sub-time period. The first subway users are subway users who access the associated base station of the first subway station in the first sub-time period. The second subway users are subway users who access the associated base station of the second subway station in the second sub-time period. The second sub-time period is the next sub-time period adjacent to the first sub-time period. P is a positive integer less than or equal to N, and Q is a positive integer less than or equal to N.

[0035] The subway users who overlap among the P first subway users and Q second subway users are defined as third subway users. The third subway user is a subway user who accesses the associated base station of the first subway station in the first sub-time period and accesses the associated base station of the second subway station in the second sub-time period.

[0036] The number of third-tier subway users is used as the number of subway users who moved from the first subway station to the second subway station during the first time period.

[0037] Thirdly, the present invention also provides an electronic device comprising: a processor and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions, causing the electronic device to perform a pedestrian flow monitoring method as described in the first aspect and any possible implementation thereof.

[0038] Fourthly, the present invention also provides a computer-readable storage medium storing computer instructions that, when executed on an electronic device, cause the electronic device to perform a pedestrian flow monitoring method as described in the first aspect and any possible implementation thereof. Attached Figure Description

[0039] Figure 1This is a schematic diagram of the structure of a people flow monitoring system provided in an embodiment of the present invention;

[0040] Figure 2 A flowchart of a people flow monitoring method provided in an embodiment of the present invention Figure 1 ;

[0041] Figure 3 This is a schematic diagram of a user's travel trajectory provided in an embodiment of the present invention;

[0042] Figure 4 This is a location map of the jurisdiction area of ​​a subway station provided in an embodiment of the present invention;

[0043] Figure 5 This is a diagram showing the tidal distribution of passenger flow at a subway station, provided as an embodiment of the present invention.

[0044] Figure 6 A flowchart of a people flow monitoring method provided in an embodiment of the present invention Figure 2 ;

[0045] Figure 7 This is a diagram showing the passenger flow distribution of a subway line's downline during a certain time period, provided as an embodiment of the present invention.

[0046] Figure 8 This is a schematic diagram of the structure of a people flow monitoring device provided in an embodiment of the present invention;

[0047] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] It should be noted that in this invention, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0050] Currently, existing 4G networks employ a hybrid networking architecture combining Time Division Long Term Evolution (TDD-LTE) and Frequency Division Long Term Evolution (FDD-LTE), and the resulting signaling data is also based on this TDD-FDD converged networking approach. Specifically, TDD-FDD mobile signaling is generated when a mobile user makes a call, sends a text message, or moves their location; the signaling trajectory of the same user is captured and recorded by the communication base station. After declassification, anonymization, and sampling, this data can be used for research on resident behavior preferences, mobile trajectory analysis, and urban spatial layout.

[0051] Signaling data typically has a spatial resolution at the base station level, while its temporal resolution can be accurate to milliseconds. Signaling data fields include time and spatial location attributes, as well as call and message records. By correlating this information, users' travel trajectories can be inferred, making it a valuable data source for studying urban residents' behavior and spatial distribution.

[0052] In view of this, the present invention provides a method for monitoring passenger flow, which acquires signaling data of M users located in a target area. The signaling data of each user includes information about the base stations that the user has accessed during a first time period. The base station information includes the base station identifier and the access time. Based on the signaling data of the M users, N subway users are identified from the M users. Based on the signaling data of the N subway users and the identifiers of the base stations associated with the target subway station in the target area, the number of subway users at each time point of the target subway station during the first time period is determined.

[0053] For example, Figure 1 A schematic diagram of a pedestrian flow monitoring system is provided, such as... Figure 1 As shown, based on the signaling events generated by the interaction of signaling data (from TD-LTE and FDD-LTE networks) between the user's terminal device and the operator's base station, and according to the dwell segmentation logic, a set of mobile signal data (including time and location information) of all base stations for a user during a trip is obtained; by sorting these mobile signal data sets in chronological order, the user's travel trajectory can be obtained.

[0054] A user's travel trajectory includes multiple base station interaction points (jvp). Each time a terminal device interacts with a base station, a jvp point is generated at that point. Multiple jvp points, arranged chronologically, constitute a user's travel trajectory. For example, a user's travel trajectory may contain five jvp points.

[0055] The information at the base station interaction point includes the identification code of the terminal device interacting with the device, the current time and geographical location of the terminal device, and the signal base station number providing the signal to the terminal device. The current geographical location of the terminal device can be stored as a GeoHash7 string.

[0056] The method for monitoring pedestrian flow provided by the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0057] Figure 2 The flow chart of the pedestrian flow monitoring method provided in the embodiments of the present invention Figure 1 .like Figure 2 As shown, the method includes the following steps:

[0058] S101. Obtain signaling data for M users located in the target area.

[0059] The signaling data for each of the M users includes information about the base stations the user accessed during the first time period. The base station information includes the base station identifier and the access time, where M is a positive integer. The first time period can be the subway's operating hours on a weekday, for example, Monday from 7:00 AM to 7:40 PM.

[0060] In some embodiments, the base stations accessed by the user during the first time period include base stations that are not associated with subway stations and base stations that are associated with subway stations.

[0061] In some embodiments, the base stations that a user accesses during the first time period can also be referred to as JVP points. A JVP point can be a base station associated with a subway station or a base station not associated with a subway station.

[0062] S102. Based on the signaling data of M users, identify N subway users from among the M users.

[0063] Among them, subway users are users who have used the subway during the first time period, and N is a positive integer less than or equal to M.

[0064] In some embodiments, for each of the M users, it is determined whether the user meets the preset conditions based on the user's signaling data; if the preset conditions are met, the user is determined to be a subway user.

[0065] The preset conditions include at least one of the following: the number of first base stations accessed by the user within the first time period is greater than or equal to a first preset value; the number of first base stations accessed by the user consecutively within the first time period is greater than or equal to a second preset value; the time interval between the first base station and the second base station accessed by the user consecutively within the first time period is less than a third preset value; the first base station is a base station associated with a subway station, and the second base station is a base station not associated with a subway station.

[0066] For example, suppose the first preset value is 3, the second preset value is 2, and the third preset value is 5 minutes. Figure 3 This is a user's travel trajectory map provided in an embodiment of the present invention. Figure 3 (1) represents the user's travel trajectory in the first time period. Figure 3 (2) in the figure represents the travel trajectory of user 2 in the first time period. Figure 3 (3) in the figure represents the travel trajectory of user 3 in the first time period. Figure 3 The dark triangles in the image represent base stations that are associated with subway stations. From... Figure 3 As can be seen from (1), the number of times User 1 accessed the first base station during the first time period was 4, which is greater than the first preset value, so User 1 is a subway user. From Figure 3 From (2) we can see that the number of times user 2 continuously accessed the first base station during the first time period was 2, which is equal to the second preset value, so user 2 is a subway user. From Figure 3 As can be seen from (3) in the first time period, the time interval between the first base station and the second base station that user 3 accessed in the first time period was greater than 5 minutes, so user 3 is a subway user.

[0067] For example, continue to refer to Figure 3 , Figure 3 (4) The user's travel mode is a combination of ground light rail (including elevated subway) and underground railway. Since the signal base station is an outdoor base station, it is large in scale and inconvenient to mark, so it is impossible to judge subway travel by signaling method alone. It is understandable that when users take the subway, the situation where each subway station can generate a VP point is a very ideal situation. In reality, most stations cannot be marked, but multiple indoor subway stations can be marked in a subway trip. The proportion of (1) and (2) in subway travel data is about 50-60%. When the signal quality of TD-LTE and FDD-LTE is poor, the situation of (3) will occur, which accounts for about 20-30% in subway travel data. The indoor and outdoor mixed base station in scenario (4), and the indoor signaling is insufficient, accounts for about 10-15% in subway travel data.

[0068] By summarizing the cases in (1), (2), and (3), we can obtain the vast majority of scenarios for users traveling by indoor subway. When the user's mode of transportation is... Figure 3 In case (4), it can be determined whether the user is a subway user for the target line based on whether the user's itinerary includes subway stations. For example, the user's mode of transportation is... Figure 3 In (4), if the user's VP point includes a subway station on Line 4, then the user is determined to be a subway user on Line 4.

[0069] S103. Based on the signaling data of N subway users and the identifiers of the base stations associated with the target subway station in the target area, determine the passenger flow information of the target subway station.

[0070] Among them, passenger flow information is used to indicate the number of subway users at each time point within the first time period.

[0071] In some embodiments, for each of the N subway users, if the signaling data of the subway user contains the identifier of the base station associated with the target subway station in the target area, the travel time, travel distance, and travel speed of the subway user are determined based on the signaling data of the subway user; if the travel time, travel distance, and travel speed of the subway user meet the preset rules, the subway user is associated with the target subway station in the target area; and the passenger flow information of the target subway station is determined based on the signaling data of the subway user associated with the target subway station.

[0072] In some embodiments, the number of subway users at each time point within a first time period is determined based on signaling data of subway users associated with the target subway station, thereby obtaining passenger flow information for the target subway station.

[0073] In some embodiments, a predetermined range surrounding a base station associated with a target subway station is defined as the jurisdiction area of ​​that base station. This jurisdiction area is then coded geographically. When a subway user enters this jurisdiction area, the user's terminal device interacts with the base station to generate signaling data containing the geographical code. Thus, when the subway user's signaling data contains the geographical code, it is possible to determine geographically that the subway user is located at the target subway station within the target area.

[0074] In some embodiments, the jurisdiction area is encoded using the GeoHash method. GeoHash is a method for encoding geographic coordinates, mapping two-dimensional coordinates to a string. Each string represents a specific rectangle, where all coordinates share the same string. Examples include wx4g04e and wx4g04s.

[0075] For example, such as Figure 4 As shown, a base station associated with a certain subway station is used as the center, and its jurisdiction area is represented by a 3x3 GeoHash7 grid. Assume the preset rules are: travel time greater than 5 minutes and less than 159 minutes, travel distance greater than 1 kilometer, and travel speed between 25 km / h and 85 km / h. If subway user A's signaling data contains GeoHash7, then based on subway user A's signaling data, subway user A's travel time is determined to be 50 minutes, travel distance to be 1.5 kilometers, and travel speed to be 60 km / h. It can be seen that subway user A's travel time, travel distance, and travel speed meet the preset rules, therefore subway user A is associated with the target subway station within the target area.

[0076] In some embodiments, the travel distance of a metro user is the sum of the straight-line distances between adjacent metro stations during the user's journey.

[0077] For example, since the distance between two adjacent subway stations is relatively short, the difference in distance on the Earth's sphere can be simplified to a two-dimensional planar straight-line distance. Thus, the straight-line distance between two subway stations satisfies the following formula:

[0078]

[0079]

[0080] Where R is the Earth's radius, which can be taken as an average of 6,371,393 m, and D(x, y) is the distance between two points in meters. dist (x, y) represents the straight-line distance between the subway stations. λ1 represents the latitude and longitude of point x. λ2 represents the latitude and longitude of point y, C1 is a constant with a value of 0.09849126401096386, C2 is a constant with a value of 0.5871718746897914, C3 is a constant with a value of 0.03339217569498998, and C4 is a constant with a value of 0.9953804128609185.

[0081] In some embodiments, the travel speed of a subway user is determined based on the subway user's travel distance and travel time.

[0082] For example, the travel speed of subway users satisfies the following formula:

[0083]

[0084] Where v represents the travel speed of subway users. This represents the travel distance for subway users. t1 is the start time of the subway user's trip, and t2 is the end time of the subway user's trip.

[0085] In some examples, the following principles are generally followed when planning urban rail transit lines:

[0086] (1) For road sections that pass through the city center or urban area (0-15km from the city center), a small station spacing of 1-1.5km is generally adopted to cover as many blocks as possible. The maximum speed is usually 70-80km / h, and the travel speed is generally 30-40km / h.

[0087] (2) Suburban sections (>15km) adopt a large station spacing of 1.5-5km (a few lines can reach 6-10km) to shorten the speed of entering the city from the suburbs. The maximum speed is usually 100-120km / h, and the travel speed is generally above 45km / h.

[0088] In some embodiments, the signaling data of subway users associated with the target subway station is sliced ​​according to a preset slicing rule, and the number of subway users at each time point within the first time period of the target subway station is obtained based on the sliced ​​signaling data.

[0089] For example, the signaling data of subway users associated with the target subway station is sliced ​​into 2-minute intervals, with the slicing rule being rounded down. For instance, based on the signaling data of subway users associated with the target subway station from 11:00 to 11:02, the number of subway users at the target subway station at 11:00 is obtained.

[0090] For example, Figure 5 A map showing the tidal distribution of passenger flow at a certain subway station was provided. Figure 5 It can be seen that the subway station experienced peak passenger flow from 7:00 to 9:40; the passenger flow was relatively low from 9:40 to 17:40; and the passenger flow was relatively high from 17:40 to 18:00.

[0091] It is understandable that the total number of users identified using signaling data may differ from the actual total number of users. On one hand, the number of mobile phones a user has is not fixed, and some users have multiple phones, or their phones support dual SIM dual standby; children and the elderly may not have mobile phones. On the other hand, whether it's TD-LTE or FDD-LTE communication networks, the mobile signaling collection system itself may miss data. Furthermore, people's mobile phone usage habits and varying needs, such as infrequent phone calls or prolonged periods of phone shutdown, mean that mobile phone data cannot accurately reflect the travel characteristics of the overall population.

[0092] In some embodiments, a two-layer amplification model is employed to amplify the acquired user signaling data. The first layer of amplification involves amplifying the signaling data of users within the target area, which may be recorded by multiple operators, from a single operator to a sample of all operators. The second layer of amplification involves amplifying the signaling data from multiple operators within the target area to the overall urban subway travel population, including elderly people, children, and other individuals without 4G mobile phones. Although the signaling data represents a large-scale sample of the overall population, it is still necessary to amplify it to reflect the travel characteristics of the entire urban population.

[0093] This expands the user's signaling data to reflect reality, avoiding the situation where the results of the previous passenger flow travel characteristic analysis are accurate but deviate from the actual travel characteristics in the final result display.

[0094] Based on this, according to the signaling data of N subway users and the identifiers of the base stations associated with the target subway station in the target area, the number of subway users at various time points around the target subway station is counted over a period of time, so as to realize the monitoring of the tidal distribution of passenger flow at the target subway station.

[0095] Figure 6 The flow chart of the pedestrian flow monitoring method provided in the embodiments of the present invention Figure 2 .like Figure 6 As shown, the method includes the following steps:

[0096] S201. Based on the signaling data of N subway users, determine P first subway users and Q second subway users.

[0097] The first time period includes a first sub-time period and a second sub-time period. The first subway user is the subway user who accesses the base station associated with the first subway station in the first sub-time period. The second subway user is the subway user who accesses the base station associated with the second subway station in the second sub-time period. The second sub-time period is the next sub-time period adjacent to the first sub-time period. P is a positive integer less than or equal to N, and Q is a positive integer less than or equal to N.

[0098] S202. The subway users who overlap among the P first subway users and Q second subway users are designated as third subway users.

[0099] Among them, the third subway user is a subway user who accesses the base station associated with the first subway station in the first sub-time period and accesses the base station associated with the second subway station in the second sub-time period.

[0100] S203. The number of third subway users is used as the number of subway users who moved from the first subway station to the second subway station during the first sub-time period.

[0101] For example, based on signaling data from 500 subway users, 200 first subway users and 300 second subway users are identified. The first subway users are those who accessed the base station associated with subway station A during the cumulative time segment of 10:00, and the second subway users are those who accessed the base station associated with subway station B between 10:05 and 11:06. There are 50 overlapping subway users between the first and second subway users, meaning the number of third subway users is 50. Therefore, the number of subway users moving from subway station A to subway station B at 10:00 is 50.

[0102] For example, Figure 7 This is a diagram showing the passenger flow distribution on the southbound lane of a subway line during a certain time period, provided as an embodiment of the present invention. Figure 7 As shown, during this period, the passenger flow on this line was high from Beijing South Railway Station to Majiabao. From Anheqiao North to Tiangongyuan, the passenger flow first increased, then decreased slightly in the middle section, and then remained at a peak in the latter half, showing an overall trend of moving from north to south.

[0103] Based on this, by identifying overlapping subway users in the associated base stations of different subway stations at adjacent times, the tidal changes in passenger flow at subway stations in terms of time and direction can be determined, thereby providing a basis for improving the operation of subway stations.

[0104] It is understood that the above method can be implemented by a people flow monitoring device. To achieve the above functions, the people flow monitoring device includes hardware structures or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, the embodiments of the present invention can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of the present invention.

[0105] In this embodiment of the invention, the aforementioned pedestrian flow monitoring device and the like can be divided into functional modules according to the above method examples. For example, each function can be divided into its own functional modules. The integrated modules can be implemented in hardware or as software functional modules. It should be noted that the module division in this embodiment of the invention is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0106] When dividing each function into modules according to its corresponding function. Figure 8 A possible structural schematic diagram of the pedestrian flow monitoring device involved in the above embodiments is shown. For example... Figure 8 As shown, the pedestrian flow monitoring device 30 includes an acquisition module 31 and a processing module 32.

[0107] The acquisition module 31 is used to acquire signaling data of M users located in the target area. The signaling data of each user includes information about the base stations that the user has accessed in the first time period. The base station information includes the base station identifier and the access time point. M is a positive integer.

[0108] Processing module 32 is used to identify N subway users from M users based on the signaling data of M users; subway users are users who have used the subway in the first time period, and N is a positive integer less than or equal to M;

[0109] The processing module 32 is also used to determine the passenger flow information of the target subway station based on the signaling data of N subway users and the identifier of the base station associated with the target subway station in the target area. The passenger flow information is used to indicate the number of subway users at each time point in the first time period.

[0110] In some embodiments, the processing module 32 is specifically used to: for each of the M users, determine whether the user meets the preset conditions based on the user's signaling data; if the preset conditions are met, determine that the user is a subway user;

[0111] The preset conditions include at least one of the following:

[0112] The number of times a user has accessed the first base station within the first time period is greater than or equal to the first preset value;

[0113] The number of times a user has continuously accessed the first base station within the first time period is greater than or equal to the second preset value.

[0114] The time interval between the first and second base stations that the user has continuously accessed within the first time period is less than a third preset value;

[0115] The first base station is a base station that is associated with a subway station, and the second base station is a base station that is not associated with a subway station.

[0116] In some embodiments, the processing module 32 is specifically used to: for each of the N subway users, if the signaling data of the subway user contains the identifier of the base station associated with the target subway station in the target area, determine the travel time, travel distance and travel speed of the subway user based on the signaling data of the subway user; and if the travel time, travel distance and travel speed of the subway user meet the preset rules, associate the subway user with the target subway station in the target area.

[0117] Based on the signaling data of subway users associated with the target subway station, determine the passenger flow information of the target subway station.

[0118] In some embodiments, the processing module 32 is further configured to determine P first subway users and Q second subway users based on the signaling data of N subway users. The first time period includes a first sub-time period and a second sub-time period. The first subway user is a subway user who accesses the associated base station of the first subway station during the first sub-time period. The second subway user is a subway user who accesses the associated base station of the second subway station during the second sub-time period. The second sub-time period is the next sub-time period adjacent to the first sub-time period. P is a positive integer less than or equal to N, and Q is a positive integer less than or equal to N.

[0119] The subway users who overlap among the P first subway users and Q second subway users are defined as third subway users. The third subway user is a subway user who accesses the associated base station of the first subway station in the first sub-time period and accesses the associated base station of the second subway station in the second sub-time period.

[0120] The number of third-tier subway users is used as the number of subway users who moved from the first subway station to the second subway station during the first time period.

[0121] Of course, the pedestrian flow monitoring device 30 includes, but is not limited to, the unit modules listed above. Furthermore, the specific functions that the aforementioned functional units can achieve include, but are not limited to, the functions corresponding to the method steps in the above examples. For detailed descriptions of other modules of the pedestrian flow monitoring device 30, please refer to the detailed descriptions of their corresponding method steps; these will not be repeated here in this embodiment of the invention.

[0122] When using integrated units, Figure 9 A possible structural diagram of the electronic device involved in the above embodiments is shown. The electronic device 400 may include a processor 401 and a memory 402. The memory 402 is used to store executable instructions of the processor 401. The processor 401 is configured to execute the instructions, causing the electronic device to perform various functions or steps in the above method embodiments.

[0123] Specifically, the processor 401 is used to control and manage the operation of the electronic device. The memory 402 is used to store the program code and data of the electronic device, such as the people flow monitoring method, preset weights, preset value ranges, etc.

[0124] Furthermore, the electronic device 400 may also include a communication module. The communication module is used to support communication between the electronic device and other network entities to achieve functions such as data interaction. For example, the communication module supports communication between the electronic device and a backend server to achieve data interaction.

[0125] The processor 401 may include one or more processing cores, such as a quad-core processor or a penta-core processor. The processor 401 may include an attached processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural network processing unit (NPU).

[0126] The memory 402 may include one or more computer-readable storage media, which may be non-transitory. The memory 402 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 402 are used to store at least one instruction, which is executed by the processor 401 to implement the pedestrian flow monitoring method provided in the embodiments of the present invention.

[0127] This invention also provides a computer-readable storage medium including computer instructions that, when executed on the electronic device, cause the electronic device to perform the various functions or steps described in the method embodiments. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, or optical data storage device, etc.

[0128] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0129] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0130] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0131] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0132] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, in essence, 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. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0133] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for monitoring pedestrian flow, characterized in that, The method includes: Obtain signaling data for M users located in the target area. The signaling data for each user includes information about the base stations the user has accessed during a first time period. The information about the base stations includes the identifier of the base station and the access time point. M is a positive integer. Based on the signaling data of the M users, N subway users are identified from the M users; the subway users are users who have used the subway during the first time period, and N is a positive integer less than or equal to M; Based on the signaling data of the N subway users and the identifier of the base station associated with the target subway station in the target area, the passenger flow information of the target subway station is determined. The passenger flow information is used to indicate the number of subway users at each time point within the first time period. The step of identifying N subway users from the M users based on the signaling data of the M users within the first time period includes: For each of the M users, based on the user's signaling data, determine whether the user meets the preset conditions; if the preset conditions are met, determine that the user is the subway user; The preset conditions include at least one of the following: The number of times the user accessed the first base station within the first time period is greater than or equal to a first preset value. The number of times the user has continuously accessed the first base station during the first time period is greater than or equal to a second preset value; The time interval between the first base station and the second base station that the user has continuously accessed during the first time period is less than a third preset value; The first base station is a base station that is associated with a subway station, and the second base station is a base station that is not associated with a subway station. Furthermore, determining the passenger flow information of the target subway station based on the signaling data of the N subway users within the first time period and the identifiers of the base stations associated with the target subway station within the target area includes: For each of the N subway users, if the signaling data of the subway user contains the identifier of the base station associated with the target subway station in the target area, the travel time, travel distance, and travel speed of the subway user are determined according to the signaling data of the subway user; if the travel time, travel distance, and travel speed of the subway user meet the preset rules, the subway user is associated with the target subway station in the target area. Based on the signaling data of subway users associated with the target subway station, the passenger flow information of the target subway station is determined.

2. The method according to claim 1, characterized in that, The method further includes: Based on the signaling data of the N subway users, P first subway users and Q second subway users are determined. The first time period includes a first sub-time period and a second sub-time period. The first subway users are subway users who access the associated base station of the first subway station during the first sub-time period. The second subway users are subway users who access the associated base station of the second subway station during the second sub-time period. The second sub-time period is the next sub-time period adjacent to the first sub-time period. P is a positive integer less than or equal to N, and Q is a positive integer less than or equal to N. The subway users who overlap with the P first subway users and the Q second subway users are designated as third subway users. The third subway users are those who access the first subway station associated base station in the first sub-time period and access the second subway station associated base station in the second sub-time period. The number of the third subway users is taken as the number of subway users who moved from the first subway station to the second subway station during the first sub-time period.

3. A pedestrian flow monitoring device, characterized in that, The device includes: The acquisition module is used to acquire signaling data of M users located in the target area. The signaling data of each user includes information about the base stations that the user has accessed during a first time period. The information of the base stations includes the identifier of the base station and the access time point. M is a positive integer. The processing module is used to identify N subway users from the M users based on the signaling data of the M users; the subway users are users who have used the subway during the first time period, and N is a positive integer less than or equal to M; The processing module is further configured to determine the passenger flow information of the target subway station based on the signaling data of the N subway users and the identifier of the base station associated with the target subway station in the target area. The passenger flow information is used to indicate the number of subway users at each time point within the first time period. The processing module is specifically used for: For each of the M users, based on the user's signaling data, determine whether the user meets the preset conditions; if the preset conditions are met, determine that the user is the subway user; The preset conditions include at least one of the following: The number of times the user accessed the first base station within the first time period is greater than or equal to a first preset value. The number of times the user has continuously accessed the first base station during the first time period is greater than or equal to a second preset value; The time interval between the first base station and the second base station that the user has continuously accessed during the first time period is less than a third preset value; The first base station is a base station that is associated with a subway station, and the second base station is a base station that is not associated with a subway station. The processing module is specifically used for: For each of the N subway users, if the signaling data of the subway user contains the identifier of the base station associated with the target subway station in the target area, the travel time, travel distance, and travel speed of the subway user are determined according to the signaling data of the subway user; if the travel time, travel distance, and travel speed of the subway user meet the preset rules, the subway user is associated with the target subway station in the target area. Based on the signaling data of subway users associated with the target subway station, the passenger flow information of the target subway station is determined.

4. The apparatus according to claim 3, characterized in that, The processing module is further configured to determine P first subway users and Q second subway users based on the signaling data of the N subway users. The first time period includes a first sub-time period and a second sub-time period. The first subway users are subway users who access the associated base station of the first subway station during the first sub-time period. The second subway users are subway users who access the associated base station of the second subway station during the second sub-time period. The second sub-time period is the next sub-time period adjacent to the first sub-time period. P is a positive integer less than or equal to N, and Q is a positive integer less than or equal to N. The subway users who overlap with the P first subway users and the Q second subway users are designated as third subway users. The third subway users are those who access the first subway station associated base station in the first sub-time period and access the second subway station associated base station in the second sub-time period. The number of the third subway users is taken as the number of subway users who moved from the first subway station to the second subway station during the first sub-time period.

5. An electronic device, characterized in that, The electronic device includes: a processor and a memory for storing instructions executable by the processor; The processor is configured to execute the instructions, causing the electronic device to perform the pedestrian flow monitoring method as described in claim 1 or 2.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed on an electronic device, cause the electronic device to perform the pedestrian flow monitoring method as described in claim 1 or 2.

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