Passenger flow counting method and device

Abstract

The embodiment of the application discloses a kind of passenger flow statistics method and device, the method comprises: obtaining at least one wireless probe device in passenger flow statistics scene The wireless probe request set collected, each wireless probe request carries the positioning related information and MAC address of request sending device, after calculating the position data of request sending device for sending each wireless probe request according to the positioning related information carried by each wireless probe request, redundant position data is filtered from the calculated position data using a predetermined data filtering method, redundant position data is the position data repeatedly calculated for the request sending device sending random MAC address, determine the passenger flow in scene according to the number of remaining position data.The technical scheme provided by the application can avoid the interference of random MAC address and improve the accuracy of passenger flow statistics result.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method and apparatus for passenger flow statistics. Background Technology

[0002] In recent years, with the popularization of wireless smart terminals (smartphones, tablets, etc.), the market has seen the emergence of wireless smart terminal WiFi (Wi-Fi Fidelity) technology for passenger flow statistics. This technology is mainly used in public places such as shopping malls or subways with high passenger flow. By counting passenger flow, staff in public places can prevent emergencies caused by large passenger flow, conduct emergency plan drills in advance, and orderly arrange security personnel to evacuate passengers when passenger flow is high.

[0003] This method, implemented via WiFi, requires the wireless smart terminal to connect to a WiFi hotspot so that the WiFi detection device can obtain the real MAC address (Media Access Control Address) of the wireless smart terminal in the WiFi environment. The MAC address is the hardware address of the wireless smart terminal, and the real MAC address is real and unique. The number of real MAC addresses is counted to achieve the counting of passenger flow.

[0004] However, to improve terminal security and prevent tracking and privacy leaks, smart terminal manufacturers have introduced MAC address randomization functionality into their devices. When a smart terminal has Wi-Fi enabled but is not connected to any Wi-Fi hotspot, it broadcasts a large number of random MAC addresses. These random MAC addresses lack any discernible pattern, leading to data redundancy and inaccuracy when using MAC addresses to count customer traffic. Therefore, a technical solution is needed to address the inaccurate customer traffic statistics caused by random MAC addresses. Summary of the Invention

[0005] To overcome the problems existing in related technologies, this application provides a passenger flow statistics method and apparatus to accurately count passenger flow.

[0006] According to a first aspect of the embodiments of this application, a method for counting passenger flow is provided, including:

[0007] Obtain a set of wireless probe requests collected by at least one wireless probe device in a passenger flow statistics scenario. Each wireless probe request carries the location-related information and MAC address of the requesting device.

[0008] Based on the location-related information carried in each wireless probe request, calculate the location data of the requesting device that sent each wireless probe request;

[0009] A preset data filtering method is used to filter out redundant location data from the calculated location data. The redundant location data is the location data that is repeatedly calculated by the request sending device for sending a random MAC address.

[0010] The number of remaining location data after removing the redundant location data is used to calculate the passenger flow in the scene.

[0011] In some embodiments, the passenger flow statistics scenario is divided into at least one area; each wireless detection request also carries a request reporting time; the step of using a preset data filtering method to filter out redundant location data from the calculated location data includes:

[0012] By identifying the request reporting time carried in each wireless detection request, the target information of the location data corresponding to the same request reporting time in each area is determined. The target information includes at least one of the following: number and spacing; the spacing is the spacing between the locations corresponding to the location data.

[0013] Based on the target information, redundant location data corresponding to the same request reporting time are determined in each region.

[0014] In some embodiments, the target information includes the number, where the number is M and M is a positive integer; determining the redundant location data corresponding to the same request reporting time in each region based on the target information includes:

[0015] For each region, determine whether M is greater than N1, where N1 is a positive integer;

[0016] If M is greater than N1, then the M-N1 location data corresponding to the same request reporting time in the region are determined as redundant location data corresponding to the same request reporting time in the region.

[0017] In some embodiments, the target information includes the number and the spacing, where the number is M, and M is a positive integer; determining the redundant location data corresponding to the same request reporting time in each region based on the target information includes:

[0018] For each region, determine whether M is greater than N2, where N2 is a positive integer;

[0019] If M is greater than N2, then determine whether the distance between the position corresponding to any one of the M position data and the position corresponding to other position data is less than a preset distance;

[0020] If the distance is less than the preset interval, the other location data will be identified as redundant location data corresponding to the same request reporting time within the region.

[0021] In some embodiments, at least some of the requests in the wireless detection request set carry different request reporting times, and the step of counting the passenger flow in the scenario based on the number of remaining location data after removing the redundant location data includes:

[0022] The remaining location data is obtained by removing redundant location data corresponding to each request reporting time within each region from the calculated location data;

[0023] Based on the remaining location data, the passenger flow in the scene is calculated.

[0024] In some embodiments, the step of calculating the passenger flow in the scene based on the number of remaining location data after removing the redundant location data includes:

[0025] The number of remaining location data is determined as the passenger flow.

[0026] In some embodiments, the target information includes the number, and the information for determining the location data corresponding to the same request reporting time in each region includes any one of the following:

[0027] When a location data point is located on the boundary of multiple adjacent regions, determine whether there is a target adjacent region. If there is a location data point with the same request reporting time as the location data point, then increase the number of location data points with the same request reporting time in the target region by one.

[0028] When a location data point is located on the boundary of multiple adjacent regions, it is determined whether a target location data point exists. The target location data point corresponds to the same request reporting time as the location data point and the location distance meets a preset condition. If the target location data point exists, the number of location data points corresponding to the same request reporting time within the region where the target location data point is located is increased by one.

[0029] In some embodiments, the method further includes any one of the following:

[0030] The passenger flow statistics scenario is divided into multiple areas according to the preset grid size;

[0031] The passenger flow statistics scenario is divided into multiple areas according to the grid size set according to the current time;

[0032] The area where the location data cluster in the passenger flow statistics scenario is located is defined as the area of ​​the passenger flow statistics scenario.

[0033] According to a second aspect of the embodiments of this application, a passenger flow counting device is provided, comprising:

[0034] The collection acquisition module is used to acquire a set of wireless detection requests collected by at least one wireless probe device in the passenger flow statistics scenario. Each wireless detection request carries the location-related information and MAC address of the requesting device.

[0035] The data calculation module is used to calculate the location data of the requesting device that sends each wireless detection request based on the location-related information carried in each wireless detection request.

[0036] The data filtering module is used to filter out redundant location data from the calculated location data using a preset data filtering method. The redundant location data is location data that is repeatedly calculated by the request sending device that sends a random MAC address.

[0037] The passenger flow statistics module is used to count the passenger flow in the scene based on the number of remaining location data after removing the redundant location data.

[0038] In some embodiments, the passenger flow statistics scenario is divided into at least one area; each wireless detection request also carries a request reporting time; the data filtering module includes:

[0039] The information determination submodule is used to determine the target information of the location data corresponding to the same request reporting time in each area by identifying the request reporting time carried by each wireless detection request. The target information includes at least one of the following: number and spacing; the spacing is the spacing between the locations corresponding to the location data.

[0040] The data determination submodule is used to determine redundant location data corresponding to the same request reporting time in each region based on the target information.

[0041] In some embodiments, the target information includes the number, where the number is M and M is a positive integer; the data determination submodule includes:

[0042] The first number determination unit is used to determine, for each region, whether M is greater than N1, where N1 is a positive integer;

[0043] The first data determination unit is used to determine the M-N1 location data corresponding to the same request reporting time in the region as redundant location data corresponding to the same request reporting time in the region when M is greater than N1.

[0044] In some embodiments, the target information includes the number and the spacing, where the number is M, and M is a positive integer; the data determination submodule includes:

[0045] The second number determination unit is used to determine, for each region, whether M is greater than N2, where N2 is a positive integer;

[0046] The second data determination unit is used to determine whether the distance between the position corresponding to any one of the M position data and the position corresponding to other position data is less than a preset distance when M is greater than N2.

[0047] The third data determination unit is used to determine the other location data as redundant location data corresponding to the same request reporting time within the region when the spacing is less than the preset spacing.

[0048] In some embodiments, at least some of the requests in the wireless detection request set carry different request reporting times, and the passenger flow statistics module includes:

[0049] The data acquisition submodule is used to remove redundant location data corresponding to each request reporting time in each region from the calculated location data to obtain the remaining location data;

[0050] The passenger flow statistics submodule is used to count the passenger flow in the scene based on the remaining location data.

[0051] In some embodiments, the passenger flow statistics module is used to determine the number of remaining location data as the passenger flow.

[0052] In some embodiments, the target information includes the number, and the information determining submodule includes any one of the following:

[0053] The third number determination unit is used to determine whether there is a target adjacent area when a location data is located on the boundary of multiple adjacent areas. If there is a location data with the same request reporting time as the location data, the number of location data with the same request reporting time in the target area is increased by one.

[0054] The fourth number determination unit is used to determine whether there is target location data when a location data is located on the boundary of multiple adjacent areas. The target location data corresponds to the same request reporting time as the location data and the location distance meets a preset condition. If it exists, the number of location data corresponding to the same request reporting time in the area where the target location data is located is increased by one.

[0055] In some embodiments, the device further includes any one of the following:

[0056] The first area division module is used to divide the passenger flow statistics scenario into multiple areas according to a preset grid size;

[0057] The second area division module is used to divide the passenger flow statistics scenario into multiple areas according to the grid size set corresponding to the current time;

[0058] The third region division module is used to divide the area where the location data cluster in the passenger flow statistics scenario is located into the regions of the passenger flow statistics scenario.

[0059] According to a third aspect of the embodiments of this application, a passenger flow counting device is provided, comprising:

[0060] processor;

[0061] Memory used to store processor-executable instructions;

[0062] The processor is configured as follows:

[0063] Obtain a set of wireless probe requests collected by at least one wireless probe device in a passenger flow statistics scenario. Each wireless probe request carries the location-related information and MAC address of the requesting device.

[0064] Based on the location-related information carried in each wireless probe request, calculate the location data of the requesting device that sent each wireless probe request;

[0065] A preset data filtering method is used to filter out redundant location data from the calculated location data. The redundant location data is the location data that is repeatedly calculated by the request sending device for sending a random MAC address.

[0066] The number of remaining location data after removing the redundant location data is used to calculate the passenger flow in the scene.

[0067] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the above-described method.

[0068] According to the embodiments of this application, a set of wireless detection requests collected by at least one wireless probe device in a passenger flow statistics scenario is obtained. Each wireless detection request carries location-related information and a MAC address of the requesting device. After calculating the location data of the requesting device that sent each wireless detection request based on the location-related information carried by each wireless detection request, a preset data filtering method is used to filter out redundant location data from the calculated location data. Redundant location data refers to location data that is repeatedly calculated for requesting devices that send random MAC addresses. Based on the number of remaining location data, the passenger flow in the scenario is determined. The technical solution provided by this application can avoid interference from random MAC addresses and improve the accuracy of passenger flow statistics results.

[0069] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0070] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0071] Figure 1 This is a flowchart of a passenger flow statistics method according to an embodiment of this application;

[0072] Figure 2 This is a flowchart of a passenger flow statistics method according to another embodiment of this application;

[0073] Figure 3 This is a flowchart of a passenger flow statistics method according to another embodiment of this application;

[0074] Figure 4 This is a block diagram of a passenger flow counting device according to an embodiment of this application;

[0075] Figure 5 This is a block diagram of a passenger flow counting device according to another embodiment of this application;

[0076] Figure 6 This is a block diagram of a passenger flow counting device according to another embodiment of this application;

[0077] Figure 7 This is a block diagram of a passenger flow counting device according to another embodiment of this application. Detailed Implementation

[0078] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0079] Example 1

[0080] Figure 1 This is a flowchart of a passenger flow statistics method according to an embodiment of this application. Figure 1 As shown, this passenger flow statistics method includes the following steps:

[0081] Step 101: Obtain the set of wireless probe requests collected by at least one wireless probe device in the passenger flow statistics scenario.

[0082] In some embodiments, the passenger flow statistics scenario can be a public place, such as a shopping mall, subway station, or train station.

[0083] The request-sending device is equipped with a wireless function module. After the wireless function is enabled, it sends a wireless detection request. The request-sending device can be a smart terminal, such as a mobile phone or tablet. The wireless function module can be a WiFi module or a module using other wireless technologies. The request-sending device can send wireless detection requests periodically or randomly.

[0084] Wireless probe devices are used to collect wireless probe requests. These devices can be WiFi probes (also known as APs, Access Points, or Wi-Fi technology) or probes using other wireless technologies. A certain number of wireless probe devices can be deployed within a visitor flow statistics scenario, depending on factors such as the size of the scene and the required positioning accuracy. For example, WiFi probes can be installed on the ceiling of an indoor location, and to improve positioning accuracy, one WiFi probe can be installed every 10 meters.

[0085] The wireless detection request set can be a collection of wireless detection requests collected at a specific moment, or a collection of wireless detection requests collected within a preset duration. For example, if the preset duration is 5 seconds, the wireless detection request set is the collection of wireless detection requests collected within those 5 seconds. The preset duration can be set according to different scenarios. The wireless detection request set can include one, two, or more wireless detection requests.

[0086] Step 102: Calculate the location data of the requesting device that sent each wireless detection request based on the location-related information carried in each wireless detection request.

[0087] When a smart device with WiFi capability enables WiFi, it sends a WiFi probe request to a nearby WiFi probe device to search for available WiFi networks. Upon receiving the request, the WiFi probe device broadcasts the detected packet data to a designated port, which then receives the packet data. The received packet data is parsed, and the parsed data includes: the MAC address of the WiFi probe device, the MAC address of the smart device, the reporting time of the WiFi probe request, signal strength, and packet length.

[0088] When a smart terminal has WiFi enabled and is connected to a WiFi hotspot, the WiFi probe request carries the smart terminal's real MAC address. When a smart terminal has WiFi enabled but is not connected to any WiFi hotspot, the smart terminal may broadcast a large number of WiFi probe requests. These WiFi probe requests may carry random MAC addresses, and simultaneous WiFi probe requests will carry the same request reporting time.

[0089] The signal strength carried in a WiFi detection request can be used as location-related information for a smart terminal to calculate its location data. For example, the location data of a smart terminal can be obtained by calculating the signal strength carried in a WiFi detection request and using a multi-point centroid positioning method.

[0090] Step 103: Using a preset data filtering method, redundant location data is filtered out from the calculated location data. Redundant location data refers to location data that is repeatedly calculated by the request sending device for sending a random MAC address.

[0091] When a smart device has its WiFi function enabled but is not connected to any WiFi hotspot, it may broadcast numerous WiFi probe requests. These requests may carry a large number of random MAC addresses. A smart device broadcasting multiple WiFi probe requests from the same location may carry the same or different random MAC addresses. Due to varying distances between the same smart device and multiple WiFi probe devices, and different levels of obstruction between them, even if the smart device sends multiple WiFi probe requests from the same location, the signal strength of the WiFi probe requests collected by different WiFi probe devices will vary. This leads to different location data calculated for the same smart device, resulting in multiple location data calculations for the same smart device.

[0092] The design concept of this application is to count passenger flow based on the number of location data of smart terminals. When multiple location data are calculated for a smart terminal located at a certain location, redundant location data that are repeatedly calculated for that smart terminal needs to be removed to optimize the number of location data of smart terminals and improve the accuracy of passenger flow statistics.

[0093] In some embodiments, when a smart terminal has WiFi enabled but is not connected to any WiFi hotspot, it broadcasts multiple WiFi detection requests to the outside world at the same location and time at the same time, and the multiple WiFi detection requests carry the same request reporting time.

[0094] For multiple WiFi detection requests sent by a smart terminal at the same location and time, multiple location data of the smart terminal may be calculated based on the different distances between the smart terminal and the multiple WiFi detection devices, as well as the different occlusion between the smart terminal and the multiple WiFi detection devices. However, the distances between the multiple location data are usually relatively close.

[0095] In this embodiment, the passenger flow statistics scenario can be divided into at least one area. Step 103 can be implemented in the following way: Step (1) By identifying the request reporting time carried by each wireless detection request, determine the target information of the location data corresponding to the same request reporting time in each area. The target information includes at least one of the following: number and spacing; wherein, the spacing is the spacing between the locations corresponding to the location data. Step (2) Based on the target information of the location data corresponding to the same request reporting time in each area, determine the redundant location data corresponding to the same request reporting time in each area.

[0096] If the set of wireless probe requests collected in step 101 is a set collected within a certain time period, and several wireless probe requests in the set carry different request reporting times, then the above steps need to be performed for each request reporting time in each area.

[0097] In some embodiments, when a location data point is located on the boundary of multiple adjacent regions, the information for determining the location data corresponding to the same request reporting time in each region in step (1) can be implemented in any of the following ways:

[0098] Method 1: Determine if there is a target adjacent area. If there is a location data with the same request reporting time corresponding to a location data in the target adjacent area, then increase the number of location data with the same request reporting time in the target area by one.

[0099] Method 2: When a location data point is located on the boundary of multiple adjacent regions, determine if a target location data point exists. This target location data point must correspond to the same request reporting time as the given location data point, and the location distance must meet a preset condition. If such a target location data point exists, increase the number of location data points with the same request reporting time within the region containing the target location data point by one. There are various preset conditions, such as minimum location distance or location distance less than a preset value.

[0100] To simplify calculations, location data located on the region boundary can be randomly assigned to an adjacent region, or location data located on the region boundary can be deleted.

[0101] In some embodiments, the method may further include a step of dividing the passenger flow statistics scenario into regions. This can be understood as dividing the passenger flow statistics scenario plane into regions.

[0102] There are multiple methods for dividing the passenger flow statistics scenario. For example, the passenger flow statistics scenario can be divided into multiple regions according to a preset grid size, or the passenger flow statistics scenario can be divided into multiple regions according to a grid size set corresponding to the current time, or the region where the location data cluster in the passenger flow statistics scenario is located can be divided into regions of the passenger flow statistics scenario.

[0103] For example, the passenger flow statistics scenario can be divided into a 1m×1m grid area, or a 6m×6m grid area. Alternatively, when multiple location data are concentrated, such as when the number of location data points in a certain area reaches a preset number, the area containing the location data cluster in the passenger flow statistics scenario is defined as the area of ​​the passenger flow statistics scenario.

[0104] Step 104: Calculate the passenger flow in the scene based on the number of remaining location data after removing redundant location data.

[0105] The remaining location data is the location data remaining after removing redundant location data from the calculated location data.

[0106] In some embodiments, the number of remaining location data can be determined as the number of visitors in the scene.

[0107] By removing redundant location data, the number of remaining location data points allows for accurate calculation of passenger flow within the scene. Furthermore, it enables the determination of appropriate passenger flow management methods tailored to the passenger flow.

[0108] According to the embodiments of this application, a set of wireless detection requests collected by at least one wireless probe device in a passenger flow statistics scenario is obtained. Each wireless detection request carries location-related information and a MAC address of the requesting device. After calculating the location data of the requesting device that sent each wireless detection request based on the location-related information carried by each wireless detection request, a preset data filtering method is used to filter out redundant location data from the calculated location data. Redundant location data refers to location data that is repeatedly calculated for requesting devices that send random MAC addresses. The passenger flow in the scenario is determined based on the number of remaining location data. Using the technical solution provided by this application can avoid interference from random MAC addresses and improve the accuracy of passenger flow statistics results.

[0109] Example 2

[0110] Figure 2 This is a flowchart of a passenger flow statistics method according to another embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0111] Step 201: Obtain the set of wireless probe requests collected by at least one wireless probe device in the passenger flow statistics scenario.

[0112] Step 202: Calculate the location data of the requesting device that sent each wireless detection request based on the location-related information carried in each wireless detection request.

[0113] Step 203: By identifying the request reporting time carried in each wireless probe request, determine the number M of location data corresponding to the same request reporting time in each area. M is a positive integer.

[0114] Step 204: For each region, determine whether M is greater than N1. N1 is a positive integer.

[0115] Step 205: If M is greater than N1, then the M-N1 location data corresponding to the same request reporting time in the region are determined as redundant location data corresponding to the same request reporting time in the region.

[0116] In some embodiments, although multiple wireless detection requests are sent by the same smart terminal at the same time and location, multiple location data of the smart terminal may be calculated. However, in reality, the smart terminal does not change its location and its location data is only one. Therefore, N1 can be set to 1.

[0117] The passenger flow statistics scenario is divided into multiple grid areas according to a preset grid size. Each grid area is small, and only one person can be accommodated in one grid area. For example, the scenario is divided into 1m×1m grid areas. If the number M of location data corresponding to the same request reporting time in a given 1m×1m grid area is greater than 1, then the M-1 location data corresponding to the same request reporting time in that grid area are considered redundant location data.

[0118] Since this application only needs to count the number of redundant location data within the region, M-1 location data can be randomly selected from M data as redundant location data.

[0119] Step 206: Remove redundant location data corresponding to each request reporting time in each region from the calculated location data to obtain the remaining location data.

[0120] Step 207: Based on the remaining location data, calculate the passenger flow in the scene.

[0121] According to the embodiments of this application, based on the number of location data corresponding to the same request reporting time in each area, redundant location data corresponding to the same request reporting time in each area are filtered out. The redundant location data corresponding to each request reporting time in each area are removed from the calculated location data to obtain the remaining location data. The passenger flow is accurately determined based on the remaining location data.

[0122] Example 3

[0123] Figure 3 This is a flowchart of a passenger flow statistics method according to another embodiment of this application. Figure 3 As shown, the method includes the following steps:

[0124] Step 301: Obtain the set of wireless probe requests collected by at least one wireless probe device in the passenger flow statistics scenario.

[0125] Step 302: Calculate the location data of the requesting device that sent each wireless detection request based on the location-related information carried in each wireless detection request.

[0126] Step 303: By identifying the request reporting time carried in each wireless detection request, determine the number M of location data corresponding to the same request reporting time in each area. M is a positive integer.

[0127] Step 304: For each region, determine whether M is greater than N2. N2 is a positive integer.

[0128] Step 305: If M is greater than N2, determine whether the distance between the position corresponding to any one of the M position data in the region and the position corresponding to other position data is less than the preset distance.

[0129] For example, if the number of location data points M corresponding to a request reporting time within a region is 3, and these 3 location data points are location data 1, location data 2, and location data 3, it can be determined whether the distance between location data 1 and location data 2 is less than a preset distance, and also whether the distance between location data 1 and location data 3 is less than a preset distance. Similarly, it can be determined whether the distance between location data 2 and location data 1 is less than a preset distance, and also whether the distance between location data 2 and location data 3 is less than a preset distance.

[0130] Step 306: If the spacing is less than the preset spacing, then other location data are identified as redundant location data corresponding to the same request reporting time within the region.

[0131] In some embodiments, although multiple wireless detection requests are sent by the same smart terminal at the same time and location, multiple location data of the smart terminal may be calculated. However, in reality, the smart terminal has not moved its location and its location data is only one. Therefore, N2 can be set to 1.

[0132] For multiple WiFi probe requests (carrying random MAC addresses) sent by a smart terminal at the same time and location, multiple location data of the smart terminal may be calculated, but usually the distance between the multiple location data is relatively close.

[0133] The scene is divided into multiple grid areas according to a preset grid size. Each grid area is relatively large and can accommodate multiple people. For example, the scene can be divided into 6m × 6m grid areas.

[0134] Based on this, after determining that the number M of location data corresponding to the same request reporting time in a region is greater than 1, it is determined whether the distance between the location corresponding to any location data corresponding to the same request reporting time in the region and the location corresponding to other location data is less than a preset distance. If it is less than the preset distance, it is considered that these M nearby location data are all calculated for the same smart terminal that sent the random MAC address, and the location data is redundant. M-1 of the M nearby location data are determined as redundant location data.

[0135] Step 307: Remove redundant location data corresponding to each request reporting time in each region from the calculated location data to obtain the remaining location data.

[0136] Step 308: Based on the remaining location data, calculate the passenger flow in the scene.

[0137] According to the embodiments of this application, based on the number and spacing of location data corresponding to the same request reporting time in each area, redundant location data corresponding to the same request reporting time in each area are filtered out. The redundant location data corresponding to each request reporting time in each area are removed from the calculated location data to obtain the remaining location data. The passenger flow is accurately determined based on the remaining location data.

[0138] Example 4

[0139] Figure 4 This is a block diagram of a passenger flow counting device according to an embodiment of this application. Figure 4 As shown, the device includes:

[0140] The set acquisition module 401 is used to acquire a set of wireless detection requests collected by at least one wireless probe device in the passenger flow statistics scenario. Each wireless detection request carries the location-related information and MAC address of the request sending device.

[0141] The data calculation module 402 is used to calculate the location data of the requesting device that sends each wireless detection request based on the location-related information carried in each wireless detection request.

[0142] Data filtering module 403 is used to filter out redundant location data from the calculated location data using a preset data filtering method. The redundant location data is location data that is repeatedly calculated by the request sending device for sending a random MAC address.

[0143] The passenger flow statistics module 404 is used to count the passenger flow in the scene based on the number of remaining location data after removing the redundant location data.

[0144] In some embodiments, the passenger flow statistics scenario is divided into at least one area; each wireless detection request also carries a request reporting time; the data filtering module 403 includes:

[0145] The information determination submodule is used to determine the target information of the location data corresponding to the same request reporting time in each area by identifying the request reporting time carried by each wireless detection request. The target information includes at least one of the following: number and spacing; the spacing is the spacing between the locations corresponding to the location data.

[0146] The data determination submodule is used to determine redundant location data corresponding to the same request reporting time in each region based on the target information.

[0147] In some embodiments, at least some of the requests in the wireless detection request set carry different request reporting times, and the passenger flow statistics module 404 includes:

[0148] The data acquisition submodule is used to remove redundant location data corresponding to each request reporting time in each region from the calculated location data to obtain the remaining location data;

[0149] The passenger flow statistics submodule is used to count the passenger flow in the scene based on the remaining location data.

[0150] In some embodiments, the passenger flow statistics module 404 is used to determine the number of remaining location data as the passenger flow.

[0151] In some embodiments, the target information includes the number, and the information determining submodule includes any one of the following:

[0152] The third number determination unit is used to determine whether there is a target adjacent area when a location data is located on the boundary of multiple adjacent areas. If there is a location data with the same request reporting time as the location data, the number of location data with the same request reporting time in the target area is increased by one.

[0153] The fourth number determination unit is used to determine whether there is target location data when a location data is located on the boundary of multiple adjacent areas. The target location data corresponds to the same request reporting time as the location data and the data interval meets a preset condition. If it exists, the number of location data corresponding to the same request reporting time in the area where the target location data is located is increased by one.

[0154] In some embodiments, the device further includes any one of the following:

[0155] The first area division module is used to divide the passenger flow statistics scenario into multiple areas according to a preset grid size;

[0156] The second area division module is used to divide the passenger flow statistics scenario into multiple areas according to the grid size set corresponding to the current time;

[0157] The third region division module is used to divide the area where the location data cluster in the passenger flow statistics scenario is located into the region of the scenario.

[0158] According to the embodiments of this application, in this embodiment, a set of wireless detection requests collected by at least one wireless probe device in a passenger flow statistics scenario is obtained. Each wireless detection request carries location-related information and a MAC address of the requesting device. After calculating the location data of the requesting device that sent each wireless detection request based on the location-related information carried by each wireless detection request, a preset data filtering method is used to filter out redundant location data from the calculated location data. Redundant location data refers to location data that is repeatedly calculated for requesting devices that send random MAC addresses. Based on the number of remaining location data, the passenger flow in the scenario is determined. Using the technical solution provided by this application can avoid interference from random MAC addresses and improve the accuracy of passenger flow statistics results.

[0159] Example 5

[0160] Figure 5 This is a block diagram of a passenger flow counting device according to another embodiment of this application. Figure 5 As shown, the device includes:

[0161] The set acquisition module 401 is used to acquire a set of wireless detection requests collected by at least one wireless probe device in the passenger flow statistics scenario. Each wireless detection request carries the location-related information and MAC address of the request sending device.

[0162] The data calculation module 402 is used to calculate the location data of the requesting device that sends each wireless detection request based on the location-related information carried in each wireless detection request.

[0163] Data filtering module 403 is used to filter out redundant location data from the calculated location data using a preset data filtering method. The redundant location data is location data that is repeatedly calculated by the request sending device for sending a random MAC address.

[0164] The passenger flow statistics module 404 is used to count the passenger flow in the scene based on the number of remaining location data after removing the redundant location data;

[0165] The scenario is divided into at least one area; each wireless detection request also carries a request reporting time; the data filtering module 403 includes:

[0166] The information determination submodule 4031 is used to determine the target information of the location data corresponding to the same request reporting time in each area by identifying the request reporting time carried by each wireless detection request, wherein the target information includes the number;

[0167] The data determination submodule 4032 is used to determine redundant location data corresponding to the same request reporting time in each region based on the target information.

[0168] The number is M, where M is a positive integer; the data determination submodule 4032 includes:

[0169] The first number determination unit 40321 is used to determine whether M is greater than N1 for each region, where N1 is a positive integer;

[0170] The first data determination unit 40322 is used to determine the M-N1 location data corresponding to the same request reporting time in the region as redundant location data corresponding to the same request reporting time in the region when M is greater than N1.

[0171] At least some of the requests in the wireless detection request set carry different request reporting times. The passenger flow statistics module 404 includes:

[0172] The data acquisition submodule 4041 is used to remove redundant location data corresponding to each request reporting time in each region from the calculated location data to obtain the remaining location data;

[0173] The passenger flow statistics submodule 4042 is used to count the passenger flow in the scene based on the remaining location data.

[0174] According to the embodiments of this application, based on the number of location data corresponding to the same request reporting time in each area, redundant location data corresponding to the same request reporting time in each area are filtered out. The redundant location data corresponding to each request reporting time in each area are removed from the calculated location data to obtain the remaining location data. The passenger flow is accurately determined based on the remaining location data.

[0175] Example 6

[0176] Figure 6 This is a block diagram of a passenger flow counting device according to another embodiment of this application. Figure 6 As shown, the device includes:

[0177] The set acquisition module 401 is used to acquire a set of wireless detection requests collected by at least one wireless probe device in the passenger flow statistics scenario. Each wireless detection request carries the location-related information and MAC address of the request sending device.

[0178] The data calculation module 402 is used to calculate the location data of the requesting device that sends each wireless detection request based on the location-related information carried in each wireless detection request.

[0179] Data filtering module 403 is used to filter out redundant location data from the calculated location data using a preset data filtering method. The redundant location data is location data that is repeatedly calculated by the request sending device for sending a random MAC address.

[0180] The passenger flow statistics module 404 is used to count the passenger flow in the scene based on the number of remaining location data after removing the redundant location data;

[0181] The passenger flow statistics scenario is divided into at least one area; each wireless detection request also carries the request reporting time; the data filtering module 403 includes:

[0182] The information determination submodule 4031 is used to determine the target information of the location data corresponding to the same request reporting time in each area by identifying the request reporting time carried by each wireless detection request. The target information includes the number and spacing.

[0183] The data determination submodule 4032 is used to determine redundant location data corresponding to the same request reporting time in each region based on the target information.

[0184] The number is M, where M is a positive integer; the data determination submodule 6032 includes:

[0185] The second number determination unit 40323 is used to determine whether M is greater than N2 for each region, where N2 is a positive integer;

[0186] The second data determination unit 40324 is used to determine whether the distance between the position corresponding to any one of the M position data and the position corresponding to other position data is less than a preset distance when M is greater than N2.

[0187] The third data determination unit 40325 is used to determine the other location data as redundant location data corresponding to the same request reporting time within the region when the spacing is less than the preset spacing;

[0188] At least some of the requests in the wireless detection request set carry different request reporting times. The passenger flow statistics module 404 includes:

[0189] The data acquisition submodule 4041 is used to remove redundant location data corresponding to each request reporting time in each region from the calculated location data to obtain the remaining location data;

[0190] The passenger flow statistics submodule 4042 is used to count the passenger flow in the scene based on the remaining location data.

[0191] According to the embodiments of this application, based on the number and spacing of location data corresponding to the same request reporting time in each area, redundant location data corresponding to the same request reporting time in each area are filtered out. The redundant location data corresponding to each request reporting time in each area are removed from the calculated location data to obtain the remaining location data. The passenger flow is accurately determined based on the remaining location data.

[0192] Since the mobile terminal embodiment is basically the same as the foregoing Figures 1-3 The method embodiments shown are provided below. Therefore, for any details not covered in the description of this embodiment, please refer to the relevant descriptions in the foregoing embodiments. They will not be repeated here.

[0193] Figure 7 This is a block diagram of a passenger flow counting device according to another embodiment of this application. Figure 7 The passenger flow counting device 700 shown includes at least one processor 701, a memory 702, at least one network interface 704, and other user interfaces 703. The various components in the passenger flow counting device 700 are coupled together via a bus system 705. It is understood that the bus system 705 is used to implement communication between these components. In addition to a data bus, the bus system 705 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 7 The general labeled all buses as Bus System 705.

[0194] The user interface 703 may include a display, keyboard, or clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0195] It is understood that the memory 702 in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 702 of the systems and methods described in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0196] In some implementations, memory 702 stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating system 7021 and application program 5022.

[0197] The operating system 7021 includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 7022 includes various applications, such as a media player and a browser, used to implement various application functions. The program implementing the method of this application embodiment can be included in the application program 7022.

[0198] In this embodiment, by calling the program or instructions stored in memory 702, specifically the program or instructions stored in application program 7022, processor 701 is used to acquire a set of wireless detection requests collected by at least one wireless probe device in the passenger flow statistics scenario. Each wireless detection request carries location-related information and MAC address of the request sending device. Based on the location-related information carried by each wireless detection request, the location data of the request sending device that sent each wireless detection request is calculated. A preset data filtering method is used to filter out redundant location data from the calculated location data. The redundant location data is the location data that is repeatedly calculated for the request sending device that sent the random MAC address. Based on the number of remaining location data after removing the redundant location data, the passenger flow in the scenario is counted.

[0199] The methods disclosed in the embodiments of this application can be applied to or implemented by processor 701. Processor 701 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 701 or by instructions in the form of software. The processor 701 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 702. Processor 701 reads the information in memory 702 and, in conjunction with its hardware, completes the steps of the above method.

[0200] It is understood that the embodiments described in this application can be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in this application, or combinations thereof.

[0201] For software implementation, the techniques described in the embodiments of this application can be implemented by modules (e.g., procedures, functions, etc.) that perform the functions described in the embodiments of this application. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or externally.

[0202] Optionally, the processor 701 is further configured to divide the scene into at least one area; each wireless detection request also carries a request reporting time; the step of using a preset data filtering method to filter out redundant location data from the calculated location data includes:

[0203] By identifying the request reporting time carried in each wireless detection request, the target information of the location data corresponding to the same request reporting time in each area is determined. The target information includes at least one of the following: number and spacing; the spacing is the spacing between the locations corresponding to the location data.

[0204] Based on the target information, redundant location data corresponding to the same request reporting time are determined in each region.

[0205] Optionally, the processor 701 is further configured to include the number in the target information, wherein the number is M, and M is a positive integer; the step of determining redundant location data corresponding to the same request reporting time in each region based on the target information includes:

[0206] For each region, determine whether M is greater than N1, where N1 is a positive integer;

[0207] If M is greater than N1, then the M-N1 location data corresponding to the same request reporting time in the region are determined as redundant location data corresponding to the same request reporting time in the region.

[0208] Optionally, the processor 701 is further configured to include the number and the spacing in the target information, wherein the number is M, and M is a positive integer; the step of determining redundant location data corresponding to the same request reporting time in each region based on the target information includes:

[0209] For each region, determine whether M is greater than N2, where N2 is a positive integer;

[0210] If M is greater than N2, then determine whether the distance between the position corresponding to any one of the M position data and the position corresponding to other position data is less than a preset distance;

[0211] If the spacing is less than the preset spacing, then the other location data are determined as redundant location data corresponding to the same request reporting time within the region.

[0212] Optionally, the processor 701 is further configured to handle requests in the wireless detection request set that carry different reporting times, and the step of calculating passenger flow in the scenario based on the number of remaining location data after removing the redundant location data includes:

[0213] The remaining location data is obtained by removing redundant location data corresponding to each request reporting time within each region from the calculated location data;

[0214] Based on the remaining location data, the passenger flow in the scene is calculated.

[0215] Optionally, the processor 701 is further configured to handle requests in the wireless detection request set that carry different reporting times, and the step of calculating passenger flow in the scenario based on the number of remaining location data after removing the redundant location data includes:

[0216] The number of remaining location data is determined as the passenger flow.

[0217] Optionally, the processor 701 is further configured to include the number in the target information, and the information for determining the location data corresponding to the same request reporting time in each region includes any one of the following:

[0218] When a location data point is located on the boundary of multiple adjacent regions, determine whether there is a target adjacent region. If there is a location data point with the same request reporting time as the location data point, then increase the number of location data points with the same request reporting time in the target region by one.

[0219] When a location data point is located on the boundary of multiple adjacent regions, it is determined whether a target location data point exists. The target location data point corresponds to the same request reporting time as the location data point and the location distance meets a preset condition. If the target location data point exists, the number of location data points corresponding to the same request reporting time within the region where the target location data point is located is increased by one.

[0220] Optionally, the processor 701 is also used in the method to further include any of the following:

[0221] The passenger flow statistics scenario is divided into multiple areas according to the preset grid size;

[0222] The passenger flow statistics scenario is divided into multiple areas according to the grid size set according to the current time;

[0223] The area where the location data cluster in the passenger flow statistics scenario is located is defined as the area of ​​the passenger flow statistics scenario.

[0224] The passenger flow counting device 700 can realize the various processes implemented by the mobile terminal in the aforementioned embodiments, and will not be repeated here to avoid repetition.

[0225] According to the embodiments of this application, a set of wireless detection requests collected by at least one wireless probe device in a passenger flow statistics scenario is obtained. Each wireless detection request carries location-related information and a MAC address of the requesting device. After calculating the location data of the requesting device that sent each wireless detection request based on the location-related information carried by each wireless detection request, a preset data filtering method is used to filter out redundant location data from the calculated location data. Redundant location data refers to location data that is repeatedly calculated for requesting devices that send random MAC addresses. The passenger flow in the scenario is determined based on the number of remaining location data. Using the technical solution of this application can avoid interference from random MAC addresses and improve the accuracy of passenger flow statistics results.

[0226] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software 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 this application.

[0227] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0228] In the embodiments provided in this application, 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 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 system, 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 apparatuses or units may be electrical, mechanical, or other forms.

[0229] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0230] In addition, the functional units in the various embodiments of this application 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.

[0231] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. 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.

[0232] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art 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 counting passenger flow, characterized in that, The method includes: Obtain a set of wireless probe requests collected by at least one wireless probe device in a passenger flow statistics scenario. Each wireless probe request carries the location-related information and MAC address of the requesting device. Based on the location-related information carried in each wireless probe request, calculate the location data of the requesting device that sent each wireless probe request; A preset data filtering method is used to filter out redundant location data from the calculated location data. The redundant location data is the location data that is repeatedly calculated by the request sending device for sending a random MAC address. Based on the number of remaining location data after removing the redundant location data, the passenger flow in the scene is calculated. The passenger flow statistics scenario is divided into at least one area; each wireless detection request also carries the request reporting time; the step of using a preset data filtering method to filter out redundant location data from the calculated location data includes: By identifying the request reporting time carried in each wireless detection request, the target information of the location data corresponding to the same request reporting time in each area is determined. The target information includes at least one of the following: number and spacing; the spacing is the spacing between the locations corresponding to the location data. Based on the target information, determine the redundant location data corresponding to the same request reporting time in each region; The target information includes the number, where the number is M, and M is a positive integer; determining the redundant location data corresponding to the same request reporting time in each region based on the target information includes: For each region, determine whether M is greater than N1, where N1 is a positive integer; If M is greater than N1, then the M-N1 location data corresponding to the same request reporting time in the region are determined as redundant location data corresponding to the same request reporting time in the region.

2. The method according to claim 1, characterized in that, The target information includes the number and the spacing, where the number is M, and M is a positive integer; determining the redundant location data corresponding to the same request reporting time within each region based on the target information includes: For each region, determine whether M is greater than N2, where N2 is a positive integer; If M is greater than N2, then determine whether the distance between the position corresponding to any one of the M position data and the position corresponding to other position data is less than a preset distance; If the distance is less than the preset interval, the other location data will be identified as redundant location data corresponding to the same request reporting time within the region.

3. The method according to claim 2, characterized in that, At least some of the requests in the wireless detection request set carry different request reporting times. The step of calculating the passenger flow in the scenario based on the number of remaining location data after removing the redundant location data includes: The remaining location data is obtained by removing redundant location data corresponding to each request reporting time within each region from the calculated location data; Based on the remaining location data, the passenger flow in the scene is calculated.

4. The method according to claim 2, characterized in that, The target information includes the number, and the information for determining the location data corresponding to the same request reporting time in each region includes any one of the following: When a location data point is located on the boundary of multiple adjacent regions, determine whether there is a target adjacent region. If there is a location data point with the same request reporting time as the location data point, then increase the number of location data points with the same request reporting time in the target adjacent region by one. When a location data point is located on the boundary of multiple adjacent regions, it is determined whether a target location data point exists. The target location data point corresponds to the same request reporting time as the location data point and the location distance meets a preset condition. If the target location data point exists, the number of location data points corresponding to the same request reporting time within the region where the target location data point is located is increased by one.

5. The method according to claim 2, characterized in that, The method further includes any one of the following: The passenger flow statistics scenario is divided into multiple areas according to the preset grid size; The passenger flow statistics scenario is divided into multiple areas according to the grid size set according to the current time; The area where the location data cluster in the passenger flow statistics scenario is located is defined as the area of ​​the passenger flow statistics scenario.

6. A passenger flow counting device, characterized in that, The device includes: processor; Memory used to store processor-executable instructions; The processor is configured as follows: Obtain a set of wireless probe requests collected by at least one wireless probe device in a passenger flow statistics scenario. Each wireless probe request carries the location-related information and MAC address of the requesting device. Based on the location-related information carried in each wireless probe request, calculate the location data of the requesting device that sent each wireless probe request; A preset data filtering method is used to filter out redundant location data from the calculated location data. The redundant location data is the location data that is repeatedly calculated by the request sending device for sending a random MAC address. Based on the number of remaining location data after removing the redundant location data, the passenger flow in the scene is calculated. The passenger flow statistics scenario is divided into at least one area; each wireless detection request also carries the request reporting time; the step of using a preset data filtering method to filter out redundant location data from the calculated location data includes: By identifying the request reporting time carried in each wireless detection request, the target information of the location data corresponding to the same request reporting time in each area is determined. The target information includes at least one of the following: number and spacing; the spacing is the spacing between the locations corresponding to the location data. Based on the target information, determine the redundant location data corresponding to the same request reporting time in each region; The target information includes the number, where the number is M, and M is a positive integer; determining the redundant location data corresponding to the same request reporting time in each region based on the target information includes: For each region, determine whether M is greater than N1, where N1 is a positive integer; If M is greater than N1, then the M-N1 location data corresponding to the same request reporting time in the region are determined as redundant location data corresponding to the same request reporting time in the region.

7. A computer-readable storage medium having a computer program stored thereon for performing a passenger flow statistics method as described in any one of claims 1-5, characterized in that, The computer program is implemented when it is executed by a processor.

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