Passenger flow determination method and apparatus, electronic device, and readable storage medium

Abstract

The application provides a passenger flow determination method and device, electronic equipment and readable storage medium, and relates to the field of passenger flow monitoring. The method comprises the following steps: acquiring at least one of a first passenger flow and a second passenger flow, the first passenger flow being a passenger flow in a first direction in a first sensing area at a first time determined based on a visual technology, the second passenger flow being a passenger flow in a second direction in the first sensing area at a second time determined based on the visual technology, the first direction and the second direction being directions of a visual device facing and facing away from the first sensing area respectively; determining passenger flows of N second sensing areas in the first direction at a third time according to the first passenger flow and time lengths of the N second sensing areas to the first sensing area, and determining passenger flows of M second sensing areas in the second direction at a fourth time according to the second passenger flow and time lengths of the first sensing area to the M second sensing areas. The application can take into account the cost of determining passenger flow information and passenger flow direction.

Description

Technical Field

[0001] This application relates to the field of passenger flow monitoring technology, and in particular to a passenger flow determination method, device, electronic device, and readable storage medium. Background Technology

[0002] Currently, passenger flow is typically monitored using either computer vision or wireless passive sensing technology. Computer vision technology determines passenger flow information, such as flow rate and direction, by collecting video data, while wireless passive sensing technology determines passenger flow information by collecting wireless signals. However, determining passenger flow information using computer vision technology requires significant computing power, while wireless passive sensing technology, although less expensive, cannot determine passenger flow direction. Therefore, existing technologies suffer from a trade-off between balancing the cost of determining passenger flow information and determining passenger flow direction. Summary of the Invention

[0003] This application provides a method, apparatus, electronic device, and readable storage medium for determining passenger flow, in order to solve the problem in the prior art that the cost of determining passenger flow information and the direction of passenger flow cannot be simultaneously considered.

[0004] To solve the above-mentioned technical problems, this application is implemented as follows;

[0005] In a first aspect, embodiments of this application provide a method for determining passenger flow, the method comprising:

[0006] When the first sensing area is determined to be an area jointly covered by the visual devices and WiFi nodes based on the pre-stored WiFi node topology map and visual device distribution map, at least one of the first passenger flow and the second passenger flow is obtained. The first passenger flow is the passenger flow in the first sensing area facing the first direction at a first time, determined based on visual technology. The second passenger flow is the passenger flow in the first sensing area facing the second direction at a second time, determined based on visual technology. The first direction and the second direction are directions relative to the visual device. The first direction is the direction facing the visual device, and the second direction is the direction away from the visual device.

[0007] If the first passenger flow is obtained and the first passenger flow is greater than 0, the passenger flow of the N second sensing areas towards the first sensing area at the third time is determined based on the first passenger flow and the time taken for the N second sensing areas to reach the first sensing area. The N second sensing areas are areas that are adjacent to the first sensing area, have passenger flow that can flow to the first sensing area, and are covered by WiFi nodes, as determined based on the WiFi node topology map.

[0008] If the second passenger flow is obtained and the second passenger flow is greater than 0, the passenger flow of the M second sensing areas at the fourth time point is determined based on the second passenger flow and the time taken for the first sensing area to reach the M second sensing areas. The M second sensing areas are areas that are adjacent to the first sensing area, whose passenger flow can come from the first sensing area, and which are covered by WiFi nodes, as determined based on the WiFi node topology map.

[0009] Secondly, embodiments of this application provide a passenger flow determination device, including:

[0010] The first acquisition module is used to acquire at least one of a first passenger flow and a second passenger flow when the first sensing area is determined to be an area jointly covered by the visual device and the WiFi node based on a pre-stored WiFi node topology map and a visual device distribution map. The first passenger flow is the passenger flow in the first sensing area facing a first direction at a first moment, as determined by visual technology, and the second passenger flow is the passenger flow in the first sensing area facing a second direction at a second moment, as determined by visual technology. The first direction and the second direction are directions relative to the visual device, the first direction is the direction facing the visual device, and the second direction is the direction away from the visual device.

[0011] The first determining module, upon acquiring the first passenger flow and finding that the first passenger flow is greater than 0, determines the passenger flow of the N second sensing areas toward the first direction at a third time based on the first passenger flow and the time taken for the N second sensing areas to reach the first sensing area. The N second sensing areas are areas that are adjacent to the first sensing area, have passenger flow that can flow toward the first sensing area, and are covered by WiFi nodes, as determined based on the WiFi node topology map.

[0012] The second determining module is used to determine the passenger flow of the M second sensing areas toward the second direction at a fourth time, based on the second passenger flow and the time taken for the first sensing area to reach the M second sensing areas, when the second passenger flow is obtained and the second passenger flow is greater than 0. The M second sensing areas are areas that are adjacent to the first sensing area, whose passenger flow can come from the first sensing area, and which are covered by WiFi nodes, as determined based on the WiFi node topology map.

[0013] Thirdly, embodiments of this application provide an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the passenger flow determination method as described in the first aspect.

[0014] Fourthly, embodiments of this application provide a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the passenger flow determination method as described in the first aspect.

[0015] In this embodiment, the passenger flow (first passenger flow) of the first sensing area towards the first direction at a first moment is determined based on visual technology, and / or the passenger flow (second passenger flow) of the first sensing area towards the second direction at a second moment is determined based on visual technology. Based on a pre-saved WiFi node topology map, it is known that the first passenger flow originates from N adjacent second sensing areas, and the passenger flow corresponding to the second passenger flow will eventually reach M adjacent second sensing areas. Based on the first passenger flow and the time taken for the N second sensing areas to reach the first sensing area, this embodiment can determine the passenger flow of the N second sensing areas towards the first direction at a third moment without needing to identify the passenger flow direction of the N second sensing areas using visual technology; based on the second passenger flow and the time taken for the first sensing area to reach the M second sensing areas, it can determine the passenger flow of the M second sensing areas towards the second direction at a fourth moment without needing to detect the passenger flow direction of the M second sensing areas using visual technology. Therefore, this embodiment can reduce the application of visual technology when determining passenger flow direction, thereby reducing the cost of passenger flow information determination while simultaneously determining passenger flow direction. Attached Figure Description

[0016] 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.

[0017] Figure 1 A flowchart illustrating a passenger flow determination method provided in this application embodiment;

[0018] Figure 2 An architecture diagram of a passenger flow calculation system provided in this application embodiment;

[0019] Figure 3 A WiFi node topology diagram provided in this application embodiment;

[0020] Figure 4 A schematic diagram of each sensing area provided in an embodiment of this application;

[0021] Figure 5 A method based on the embodiments of this application is provided. Figure 4 A defined WiFi node topology;

[0022] Figure 6 A structural diagram of a passenger flow determination device provided in an embodiment of this application;

[0023] Figure 7 This is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, not limited in number; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0026] For ease of understanding, the following explanation is provided regarding the relevant content of this application.

[0027] Currently, passenger flow monitoring technologies mainly include vision-based passenger flow monitoring and wireless passive sensing-based passenger flow monitoring. Vision-based passenger flow monitoring primarily uses image processing and computer vision technology to acquire passenger flow information and passenger flow direction. Wireless passive sensing-based passenger flow monitoring primarily acquires passenger flow by analyzing the propagation characteristics of wireless signals. However, vision-based passenger flow monitoring requires the deployment of smart cameras and consumes a large amount of computing power, resulting in high deployment and computing costs. It is also susceptible to interference from factors such as obstruction and lighting, leading to a decrease in the accuracy of passenger flow counting. While wireless passive sensing-based passenger flow monitoring is lower in cost and can be deployed on a large scale, it can only detect passenger flow and not the direction of passenger flow. Addressing the problem of the inability to simultaneously consider the cost and direction of passenger flow in the aforementioned related technologies, this application provides a passenger flow determination method, apparatus, electronic device, and readable storage medium.

[0028] The passenger flow determination method, apparatus, electronic device, and readable storage medium provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0029] See Figure 1 , Figure 1 This is a flowchart of a passenger flow determination method provided in an embodiment of this application, such as... Figure 1 As shown, the method includes the following steps:

[0030] Step 101: If the first sensing area is determined to be an area jointly covered by the visual devices and WiFi nodes based on the pre-stored WiFi node topology map and visual device distribution map, at least one of the first passenger flow and the second passenger flow is obtained. The first passenger flow is the passenger flow towards the first direction in the first sensing area at the first moment, determined based on visual technology. The second passenger flow is the passenger flow towards the second direction in the first sensing area at the second moment, determined based on visual technology. The first direction and the second direction are directions relative to the visual device. The first direction is the direction facing the visual device, and the second direction is the direction away from the visual device.

[0031] Step 102: When the first passenger flow is obtained and the first passenger flow is greater than 0, based on the first passenger flow and the time taken for the N second sensing areas to reach the first sensing area, determine the passenger flow of the N second sensing areas toward the first direction at the third time. The N second sensing areas are areas that are adjacent to the first sensing area, have passenger flow that can flow to the first sensing area, and are covered by WiFi nodes, as determined based on the WiFi node topology map.

[0032] Step 103: When the second passenger flow is obtained and the second passenger flow is greater than 0, based on the second passenger flow and the time taken for the first sensing area to reach the M second sensing areas, determine the passenger flow of the M second sensing areas toward the second direction at the fourth time. The M second sensing areas are areas that are adjacent to the first sensing area, whose passenger flow can come from the first sensing area, and which are covered by WiFi nodes, as determined based on the WIFI node topology map.

[0033] It should be noted that the passenger flow determination method provided in this application embodiment can be applied to a passenger flow determination device or an electronic device, etc. For better understanding, the following will specifically describe the technical solution provided in this application by taking the application of the method to a passenger flow determination device (hereinafter referred to as the device) as an example.

[0034] In step 101, a WiFi node topology map is pre-stored in the device. The WiFi node topology map is used to characterize the areas covered by each WiFi node, as well as the possible directions of passenger flow between the areas covered by each WiFi node. WiFi nodes can also be called WiFi access points (APs).

[0035] The visual device distribution map is also pre-stored in the device. The visual device distribution map is used to characterize the distribution of visual devices and the areas covered by the visual devices, such as cameras.

[0036] The first sensing area is the area jointly covered by visual devices and WIFI nodes, so that passenger flow information in the first sensing area can be determined based on wireless passive sensing technology and visual technology.

[0037] For ease of understanding, the following provides a passenger flow calculation system to illustrate how the embodiments of this application determine passenger flow information based on wireless passive sensing technology and vision technology.

[0038] See Figure 2 The passenger flow calculation system comprises four parts: a sensing device layer, an access layer, a basic algorithm layer, and a fusion computing layer. The device in this embodiment is applied to the fusion computing layer.

[0039] The sensing device layer includes vision devices and WiFi access points (APs). Vision devices typically need to support the RTSP protocol; there can be one or multiple vision devices. Multiple WiFi APs are typically required, and they usually need to have wireless probe functionality.

[0040] The access layer is used to access data collected by the sensing device layer. The access layer includes a video capture module (CV) and a WiFi uplink signal acquisition module. The CV capture module uses the RSTP protocol supported by the vision device to capture the video stream and then passes it to the basic algorithm layer for processing. The WiFi uplink signal acquisition module uses the wireless probe interface exposed by the WiFi AP (such as a commercial WiFi AP) to acquire the WiFi uplink signal of mobile terminals within the WiFi AP's coverage area and parses its characteristics (including timestamps, the MAC address of the reporting WiFi AP, the MAC address of the sensed WiFi device, and signal strength, etc.), transmitting this information to the basic algorithm layer for processing.

[0041] The basic algorithm layer includes a vision-based CV orientation detection module. This module uses computer vision algorithms to detect the orientation of people in video data. It outputs a detection timestamp, the IP address of the detection vision device, the virtual ID of the detected person, the pixel coordinates of the detected person, the orientation of the detected person, the confidence level of the orientation, and the overall confidence level of the image. The basic algorithm layer also includes a WiFi crowd counting module based on wireless passive sensing technology. This module uses wireless features and statistical models reported from the access layer to abstract the relationship between wireless uplink signal characteristics and the number of people, infers the number of people in the WiFi sensing area, and reports it to the fusion computing module. The WiFi crowd counting module ultimately outputs a detection timestamp, the number of people in the sensing area, the number of people in the sensing area, and the detection confidence level.

[0042] The fusion computing layer is the application layer of the passenger flow determination method provided in this application embodiment. The fusion computing layer can obtain passenger flow information from the basic algorithm layer. The basic algorithm layer does not need to actively determine passenger flow information based on visual technology and wireless passive sensing technology. Instead, it only calculates relevant passenger flow information based on the fusion computing layer's request (the fusion computing layer sends relevant instructions to the basic algorithm layer), thus saving settlement resources. For example, in this application embodiment, when the fusion computing layer needs to obtain the aforementioned first passenger flow and second passenger flow, the CV orientation detection module in the basic algorithm layer calculates and outputs the first and second passenger flow according to the request.

[0043] The first passenger flow is the passenger flow towards the first direction within the first perception area at a first moment, determined based on visual technology. The second passenger flow is the passenger flow towards the second direction within the first perception area at a second moment, determined based on visual technology. The first moment and the second moment may be equal or unequal. The first direction and the second direction are two directions relative to the visual device within the first perception area; the first direction is the direction facing the visual device, and the second direction is the direction away from the visual device. Figure 3 As shown, Figure 3 This is a WIFI node topology diagram provided in an embodiment of this application, where the y-region is the first sensing region and the first direction is... Figure 3 The middle arrow points in the direction of the y-region, and the second direction is... Figure 3 The arrow pointing from the y-region to other regions.

[0044] In this embodiment, it is assumed that the flow of people within the sensing area will maintain a constant speed and will not change its direction of travel.

[0045] Therefore, if the first passenger flow in the first sensing area at the first moment towards the first direction is not zero, the first passenger flow comes from the N second sensing areas adjacent to the first sensing area, where N is a positive integer, and the passenger flow direction of the N second sensing areas includes at least the direction towards the first sensing area. After determining the first passenger flow, based on the time taken for the N second sensing areas to reach the first sensing area, the passenger flow in the N second sensing areas towards the first direction at the third moment can be deduced in reverse, where the third moment can be equal to the first moment minus the time taken for the N second sensing areas to reach the first sensing area. When M is greater than 1, the average time taken for the N second sensing areas to reach the first sensing area can be determined as the total time taken for the N second sensing areas to reach the first sensing area.

[0046] If the second passenger flow in the second sensing area towards the second direction at the second time is not zero, the people corresponding to the second passenger flow will move towards the M second sensing areas adjacent to the first sensing area. The passenger flow direction of the M second sensing areas includes at least the direction from the first sensing area towards the M second sensing areas, where M is a positive integer. N and M may be equal or unequal. After determining the second passenger flow, based on the time it takes for the first sensing area to reach the M second sensing areas, the passenger flow towards the second direction in the M second sensing areas at the fourth time can be deduced in reverse, where the fourth time can be equal to the second time plus the time it takes for the first sensing area to reach the M second sensing areas. If M is greater than 1, the average of the time it takes for the first sensing area to reach the M second sensing areas can be determined as the total time it takes for the first sensing area to reach the M second sensing areas.

[0047] For ease of understanding, the following is combined with Figure 3 An example is provided on how to determine the direction of passenger flow in the second sensing area.

[0048] like Figure 3 As mentioned above, region y is the first sensing region, and region x is the second sensing region. The passenger flow direction in region x includes both the first and second directions. Assume that the passenger flow in region y towards the first direction at time t is W. x / y Given that the travel time from region x to region y is t1, and the passenger flow in region y towards the first direction at time t originates from region x, it can be determined that the passenger flow in region x towards the first direction at time (t-t1) is equal to W. x / y Assume that the passenger flow in region y towards the second direction at time t is W. y / x Given that the time taken to travel from region y to region x is t1, and that passenger flow in region y towards the second direction will move towards region x at time t, it can be determined that the passenger flow in region x in the second direction at time (t+t1) is equal to W. y / x .

[0049] The embodiments of this application can determine the passenger flow of N second sensing areas toward the first direction and the passenger flow of M second sensing areas toward the second direction without relying on visual technology to detect the passenger flow direction of M and N second sensing areas. It can be seen that the embodiments of this application can reduce the application of visual technology, thereby reducing the cost of passenger flow information determination while determining the passenger flow direction.

[0050] Optionally, the method further includes:

[0051] In the case where a first target sensing area exists in the N second sensing areas, the passenger flow of the first target sensing area determined by wireless passive sensing technology at the third time is obtained. The first target sensing area is a sensing area with a third direction, which is a passenger flow direction determined by the WiFi node topology map. The third direction is a direction that is different from the first direction relative to the first target sensing area.

[0052] Based on the passenger flow of the first target sensing area at the third time and the passenger flow of the first target sensing area toward the first direction at the third time, the passenger flow of the first target sensing area toward the third direction at the third time is determined.

[0053] The first target sensing area, which is the passenger flow direction determined based on the WiFi node topology map, also includes a third-direction sensing area. The third-direction is a direction other than the first direction that is different from the first target sensing area. It is known that the first direction is the direction of the visual device toward the first sensing area. The passenger flow in the third direction within the first target sensing area is the passenger flow in other directions outside the first sensing area within the first target sensing area.

[0054] In the presence of a first target sensing area, the passenger flow in the first target sensing area, determined based on wireless passive sensing technology, is obtained at a third time. The passenger flow in the first target sensing area at the third time is equal to the sum of the passenger flow in the first target sensing area towards the first direction and the passenger flow towards the third direction.

[0055] According to the above embodiment, the passenger flow of N second sensing areas towards the first direction at the third time has been determined. When N is 1, the N second sensing areas are the first target sensing area. When N is greater than 1, the passenger flow of the first target sensing area towards the first direction at the third time can be determined based on the following method.

[0056] Method 1: Determine using the following formula:

[0057]

[0058] In the formula, Wx / y W represents the passenger flow in the first target sensing area at the third moment, directed towards the first direction. N / y Let N be the passenger flow in the first direction at the third moment for the second sensing areas.

[0059] The formula above takes the average of the passenger flow of the N second sensing areas toward the first direction at the third time, and obtains the passenger flow of the first target sensing area toward the first direction at the third time.

[0060] Method 2: Determined using the following formula:

[0061] W x / y =W N / y ×W x (2)

[0062] In the formula, W x / y W represents the passenger flow in the first target sensing area at the third moment, directed towards the first direction. N / y Let W be the passenger flow in the N second sensing areas facing the first direction at the third time. x The weight of the passenger flow in the first target perception area towards the first direction at the third moment.

[0063] W x This can be calculated based on historical data of the sensing area. For example, based on historical passenger flow data, it can be determined that during the morning peak hours, 80% of the passenger flow in the first sensing area originates from the first target sensing area among N second sensing areas; during the evening peak hours, 10% of the passenger flow in the first sensing area originates from the first target sensing area; and outside of the morning and evening peak hours, 50% of the passenger flow in the first sensing area originates from the first target sensing area. If the first moment falls within the morning peak hours, W... x It is 80%.

[0064] The weight W is determined based on historical data of the sensing area using method 2. x This is conducive to improving W x / y The accuracy.

[0065] Given that the passenger flow of the first target sensing area at the third time has been obtained, and the passenger flow of the first target sensing area toward the first direction at the third time is known, the passenger flow of the first target sensing area toward the third direction at the third time can be calculated.

[0066] In this embodiment, by combining the passenger flow of the first target sensing area determined by wireless passive sensing technology, and by the relationship between the passenger flow of the first target sensing area at the third moment, the passenger flow of the first target sensing area toward the first direction at the third moment, and the passenger flow toward the third direction, it is possible to determine the passenger flow of the first target sensing area toward the third direction at the third moment without further using visual technology to detect passenger flow information. This is beneficial for saving computing resources and enriching passenger flow information.

[0067] To better understand the passenger flow in the first target perception area at the third time point, the following is combined with... Figure 4 and Figure 5 An example is provided to illustrate this.

[0068] See Figure 4 , Figure 4 This is a schematic diagram of the sensing area. Figure 4 The y-region is the first sensing area, and the CV (Vision Device) is a visual device installed in the y-region. The y-region is the area at the entrance / exit of the passageway. The x-region is also the second sensing area at the entrance / exit of the passageway. The z-region is the second sensing area at the subway entrance. The passenger flow direction at the entrance / exit of the passageway is unrestricted (passengers can enter or exit the subway), while the subway entrance only allows entry into the subway.

[0069] based on Figure 4 , determine and Figure 4 The corresponding WiFi node topology diagram is as follows: Figure 5 As shown, the passenger flow direction in region z does not include the direction towards region y (the first direction), and the passenger flow direction in region z includes the direction from region y towards region x (i.e., the direction away from the visual device in region y: the second direction). Therefore, region z does not belong to the aforementioned N second sensing regions, but to the aforementioned M second sensing regions. The passenger flow direction in region x includes a third direction other than the first direction (the direction towards region y), therefore region x is the first target sensing region in this embodiment. According to Figure 5 It can be seen that in addition to the direction of passenger flow towards area y, area x also includes the direction towards area z and the direction away from area y. Therefore, the third direction of area x includes: the direction from y to x and the direction from x to z.

[0070] Therefore:

[0071] W (x) (t)=W x / y (t)+W x / z (t)+W y / x (t ′ (3)

[0072] In the formula, t represents the third time point. ′W represents the time when people move from region y to region x at time t. (x) (t) represents the passenger flow in the first target sensing area determined based on wireless passive sensing technology at the third time point, W. x / y (t) represents the passenger flow in the first target perception area towards the first direction at the third time, W x / z (t)+W y / x (t ′ The first target perception area is the passenger flow towards the third party at the third moment.

[0073] In some embodiments, passenger flow in the x and y regions towards the outside of the passage can be ignored, therefore:

[0074] W(t) = W x / y (t)+W x / z (t)+W y / z (t)+W y / x (t) (4)

[0075] W(t) represents the total passenger flow in regions x and y at time t, determined using wireless probe technology. x / y (t) is known, W y / z (t)+W y / x (t) represents the passenger flow in the y-region at the third time point, determined by visual technology, towards the second direction. Therefore, W can be determined according to Formula 4. x / z (t), and then W x / z Substituting (t) into formula 3, we can determine W. y / x (t ′ ), based on t and t ′ The relationship between W y / x (t ′ Given that W is already determined, we can obtain it. y / x (t), and finally W can be obtained according to equation formula 4. y / z (t).

[0076] Therefore, in this embodiment, the passenger flow in region x and the passenger flow in region y can be obtained in any direction by using formulas 3 and 4.

[0077] Optionally, the method further includes:

[0078] In the case that there is a second target sensing area among the M second sensing areas, the passenger flow of the second target sensing area determined by the wireless passive sensing technology at the fourth time is obtained. The second target sensing area is the sensing area of ​​the passenger flow direction determined by the WiFi node topology map, which also includes the fourth direction. The fourth direction is a direction that is different from the second direction relative to the second target sensing area.

[0079] Based on the passenger flow of the second target sensing area at the fourth time and the passenger flow of the second target sensing area toward the second direction at the fourth time, the passenger flow of the second target sensing area toward the fourth direction at the fourth time is determined.

[0080] The fourth direction is the direction that is distinct from the second target perception area, such as... Figure 3 As shown, the y-region is the first sensing region, the x-region is the second target sensing region, the second direction is the direction from the y-region to the x-region, and the fourth direction includes the direction from the x-region to the y-region; as... Figure 5 As shown, the y region is the first sensing region, the x region is the second target sensing region, the second direction is the direction from the y region to the x region, and the fourth direction includes the direction from the x region to the y region and the direction from the x region to the z region.

[0081] According to the above embodiment, the passenger flow of M second sensing areas towards the second direction at the fourth time has been determined. When M is 1, the M second sensing areas are the second target sensing areas. When M is greater than 1, the passenger flow of the second target sensing areas towards the second direction at the fourth time can be determined based on the following method.

[0082] Method 1: Determine using the following formula:

[0083]

[0084] In the formula, W y / x W represents the passenger flow in the second target sensing area towards the second direction at time four. y / M Let M be the passenger flow in the second direction of the second sensing area at the fourth time.

[0085] The formula above takes the average of the passenger flow of the M second sensing areas toward the second direction at the fourth time, and obtains the passenger flow of the second target sensing area toward the second direction at the fourth time.

[0086] Method 2: Determined using the following formula:

[0087] W y / x =W y / M ×W X ′ (6)

[0088] In the formula, W y / x W represents the passenger flow in the second target sensing area towards the second direction at time four. y / M Let W be the passenger flow in the M second sensing areas towards the second direction at the fourth time. X ′The weight of the passenger flow in the second target perception area towards the second direction at the fourth moment.

[0089] W X ′ This can be calculated based on historical data of the sensing areas. For example, based on historical passenger flow data, it can be determined that during the morning peak, 20% of the passenger flow in the first sensing area will flow to the second target sensing area among M second sensing areas; during the evening peak, 60% of the passenger flow in the first sensing area will flow to the second target sensing area; and at other times, 50% of the passenger flow in the first sensing area will flow to the second target sensing area. If the second time point falls during the evening peak, then W... X ′ It is 60%.

[0090] The weight W is determined based on historical data of the sensing area using method 2. X ′ This is conducive to improving W y / x The accuracy.

[0091] In this embodiment, by combining the passenger flow of the second target sensing area determined by wireless passive sensing technology, and by the relationship between the passenger flow of the second target sensing area at the fourth moment, the passenger flow of the second target sensing area towards the second direction at the fourth moment, and the passenger flow towards the fourth direction, it is possible to determine the passenger flow of the second target sensing area towards the fourth direction at the fourth moment without further using visual technology to determine passenger flow information. This is beneficial for saving computing resources and enriching passenger flow information.

[0092] Optionally, if both the N second sensing regions and the M second sensing regions include a third target sensing region, and the third time and the fourth time are equal to the target time, the method further includes;

[0093] The first time is determined based on the target time and the time it takes for the third target sensing area to reach the first sensing area;

[0094] The second time is determined based on the target time and the time it takes for the first sensing area to reach the third target sensing area.

[0095] In this implementation, both the N second sensing areas and the M second sensing areas include a third target sensing area, thus the third target sensing area is the area where the passenger flow direction includes both the first and second directions. For example Figure 3 and Figure 4 The x region in the text.

[0096] In this embodiment of the application, when a third target sensing area is included, the third time and the fourth time are set to be equal to the target time, and the first time and the second time are deduced in reverse. Thus, based on the above embodiment, the passenger flow of the third target sensing area towards the first direction and the second direction at the same time (target time) can be determined, which is beneficial to enriching passenger flow information.

[0097] Optionally, if determining the passenger flow direction of the third target sensing area based on the WiFi node topology map further includes a fifth direction, the method further includes:

[0098] Obtain the passenger flow of the third target sensing area determined based on wireless passive sensing technology at the target time;

[0099] Based on the passenger flow of the third target sensing area at the target time, the passenger flow of the third target sensing area towards the first direction at the target time, and the passenger flow of the third target sensing area towards the second direction at the target time, the passenger flow of the third target sensing area towards the fifth direction at the target time is determined, wherein the fifth direction is a direction other than the first direction and the second direction relative to the third target sensing area.

[0100] The fifth direction is a direction that differs from the first and second directions relative to the third target perception area. That is, passenger flow in the third target perception area can flow towards the first perception area, originate from the first perception area, and also flow to other perception areas, for example... Figure 5 In the x region, for Figure 5 In the x region, the fifth direction is the direction from x to z. According to Formula 3, given the passenger flow of x region at the target time, the passenger flow of x region towards y region (first direction) at the target time, and the passenger flow of x region away from y region (second direction) at the target time, the passenger flow of x region towards z region (fifth direction) at the target time can be determined.

[0101] In this embodiment, by combining the passenger flow of the third target sensing area determined by wireless passive sensing technology, the passenger flow of the third target sensing area towards the fifth direction at the target time can be determined without further using visual technology to determine passenger flow information. This is beneficial for saving computing resources and enriching passenger flow information.

[0102] This application also provides a passenger flow determination device, see [link to relevant documentation]. Figure 6 , Figure 6 This is a structural diagram of a passenger flow determination device provided in an embodiment of this application. Figure 6 As shown, the device 200 includes:

[0103] The first acquisition module 201 is used to acquire at least one of a first passenger flow and a second passenger flow when the first sensing area is determined to be an area jointly covered by the visual device and the WiFi node based on a pre-stored WiFi node topology map and a visual device distribution map. The first passenger flow is the passenger flow in the first sensing area facing a first direction at a first moment, as determined by visual technology, and the second passenger flow is the passenger flow in the first sensing area facing a second direction at a second moment, as determined by visual technology. The first direction and the second direction are directions relative to the visual device, the first direction is the direction facing the visual device, and the second direction is the direction away from the visual device.

[0104] The first determining module 202, when the first passenger flow is obtained and the first passenger flow is greater than 0, determines the passenger flow of the N second sensing areas toward the first direction at a third time based on the first passenger flow and the time taken for the N second sensing areas to reach the first sensing area. The N second sensing areas are areas that are adjacent to the first sensing area, have passenger flow that can flow to the first sensing area, and are covered by WiFi nodes, as determined based on the WiFi node topology map.

[0105] The second determining module 203 is used to determine the passenger flow of the M second sensing areas toward the second direction at a fourth time, based on the second passenger flow and the time taken for the first sensing area to reach the M second sensing areas, when the second passenger flow is obtained and the second passenger flow is greater than 0. The M second sensing areas are areas that are adjacent to the first sensing area, whose passenger flow can come from the first sensing area, and which are covered by WiFi nodes, as determined based on the WiFi node topology map.

[0106] Optionally, the device 200 further includes:

[0107] The second acquisition module is used to acquire the passenger flow of the first target sensing area at the third time when the first target sensing area exists in the N second sensing areas. The first target sensing area is a sensing area with a passenger flow direction determined based on the WiFi node topology map and also includes a third direction. The third direction is a direction that is different from the first direction relative to the first target sensing area.

[0108] The third determining module is used to determine the passenger flow of the first target sensing area toward the third direction at the third time based on the passenger flow of the first target sensing area at the third time and the passenger flow of the first target sensing area toward the first direction at the third time.

[0109] Optionally, the device 200 further includes:

[0110] The third acquisition module is used to acquire the passenger flow of the second target sensing area at the fourth time when there is a second target sensing area in the M second sensing areas. The second target sensing area is a sensing area with a fourth direction, which is a passenger flow direction determined based on the WiFi node topology map. The fourth direction is a direction that is different from the second direction relative to the second target sensing area.

[0111] The fourth determining module is used to determine the passenger flow of the second target sensing area toward the fourth direction at the fourth time based on the passenger flow of the second target sensing area at the fourth time and the passenger flow of the second target sensing area toward the second direction at the fourth time.

[0112] Optionally, the device 200 further includes:

[0113] The fifth determining module is used to determine the first time based on the target time and the duration of the third target perception region reaching the first perception region, provided that the N second perception regions and the M second perception regions all include the third target perception region, and the third time and the fourth time are equal to the target time.

[0114] The sixth determining module is used to determine the second time based on the target time and the time it takes for the first sensing area to reach the third target sensing area.

[0115] Optionally, the device 200 further includes:

[0116] The fourth acquisition module is used to acquire the passenger flow of the third target sensing area at the target time, which is determined based on wireless passive sensing technology, when the passenger flow direction of the third target sensing area is determined based on the WiFi node topology map and includes a fifth direction.

[0117] The seventh determining module determines the passenger flow of the third target sensing area toward the fifth direction at the target time based on the passenger flow of the third target sensing area at the target time, the passenger flow of the third target sensing area toward the first direction at the target time, and the passenger flow of the third target sensing area toward the second direction at the target time. The fifth direction is a direction other than the first direction and the second direction relative to the third target sensing area.

[0118] It should be noted that the apparatus in this application embodiment can implement each process of the above-described passenger flow determination method embodiment and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0119] This application also provides an electronic device 300, see [link to previous document]. Figure 7 It includes at least one processor 301, a memory 302, and a computer program stored on the memory 302 and executable on the processor 301. The computer program is executed by at least one processor 301 to implement the various processes of the above-described passenger flow determination method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0120] This application also provides a computer-readable storage medium storing a computer program. This computer program is executed by a processor 301 to implement the various processes of the above-described passenger flow determination method embodiments, achieving the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium includes read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, etc.

[0121] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0122] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for determining passenger flow, characterized in that, The method includes: When the first sensing area is determined to be an area jointly covered by the visual devices and WiFi nodes based on the pre-stored WiFi node topology map and visual device distribution map, at least one of the first passenger flow and the second passenger flow is obtained. The first passenger flow is the passenger flow in the first sensing area facing the first direction at a first time, determined based on visual technology. The second passenger flow is the passenger flow in the first sensing area facing the second direction at a second time, determined based on visual technology. The first direction and the second direction are directions relative to the visual device. The first direction is the direction facing the visual device, and the second direction is the direction away from the visual device. If the first passenger flow is obtained and the first passenger flow is greater than 0, the passenger flow of the N second sensing areas towards the first sensing area at the third time is determined based on the first passenger flow and the time taken for the N second sensing areas to reach the first sensing area. The N second sensing areas are areas that are adjacent to the first sensing area, have passenger flow that can flow to the first sensing area, and are covered by WiFi nodes, as determined based on the WiFi node topology map. If the second passenger flow is obtained and the second passenger flow is greater than 0, the passenger flow of the M second sensing areas at the fourth time point is determined based on the second passenger flow and the time taken for the first sensing area to reach the M second sensing areas. The M second sensing areas are areas that are adjacent to the first sensing area, whose passenger flow can come from the first sensing area, and which are covered by WiFi nodes, as determined based on the WiFi node topology map.

2. The method according to claim 1, characterized in that, The method further includes: In the case where a first target sensing area exists in the N second sensing areas, the passenger flow of the first target sensing area determined by wireless passive sensing technology at the third time is obtained. The first target sensing area is a sensing area with a third direction, which is a passenger flow direction determined by the WiFi node topology map. The third direction is a direction that is different from the first direction relative to the first target sensing area. Based on the passenger flow of the first target sensing area at the third time and the passenger flow of the first target sensing area toward the first direction at the third time, the passenger flow of the first target sensing area toward the third direction at the third time is determined.

3. The method according to claim 1, characterized in that, The method further includes: In the case that there is a second target sensing area among the M second sensing areas, the passenger flow of the second target sensing area determined by the wireless passive sensing technology at the fourth time is obtained. The second target sensing area is the sensing area of ​​the passenger flow direction determined by the WiFi node topology map, which also includes the fourth direction. The fourth direction is a direction that is different from the second direction relative to the second target sensing area. Based on the passenger flow of the second target sensing area at the fourth time and the passenger flow of the second target sensing area toward the second direction at the fourth time, the passenger flow of the second target sensing area toward the fourth direction at the fourth time is determined.

4. The method according to claim 1, characterized in that, The method further includes the following steps when all N second sensing regions and M second sensing regions include a third target sensing region, and when the third time moment and the fourth time moment are equal to the target time moment: The first time is determined based on the target time and the time it takes for the third target sensing area to reach the first sensing area; The second time is determined based on the target time and the time it takes for the first sensing area to reach the third target sensing area.

5. The method according to claim 4, characterized in that, If the method further includes a fifth direction when determining the passenger flow direction of the third target sensing area based on the WiFi node topology map, the method also includes: Obtain the passenger flow of the third target sensing area determined based on wireless passive sensing technology at the target time; Based on the passenger flow of the third target sensing area at the target time, the passenger flow of the third target sensing area towards the first direction at the target time, and the passenger flow of the third target sensing area towards the second direction at the target time, the passenger flow of the third target sensing area towards the fifth direction at the target time is determined, wherein the fifth direction is a direction other than the first direction and the second direction relative to the third target sensing area.

6. A passenger flow determination device, characterized in that, include: The first acquisition module is used to acquire at least one of a first passenger flow and a second passenger flow when the first sensing area is determined to be an area jointly covered by the visual device and the WiFi node based on a pre-stored WiFi node topology map and a visual device distribution map. The first passenger flow is the passenger flow in the first sensing area facing a first direction at a first moment, as determined by visual technology, and the second passenger flow is the passenger flow in the first sensing area facing a second direction at a second moment, as determined by visual technology. The first direction and the second direction are directions relative to the visual device, the first direction is the direction facing the visual device, and the second direction is the direction away from the visual device. The first determining module is used to determine the passenger flow of the N second sensing areas toward the first direction at a third time, based on the first passenger flow and the time taken for the N second sensing areas to reach the first sensing area, when the first passenger flow is obtained and the first passenger flow is greater than 0. The N second sensing areas are areas that are adjacent to the first sensing area, have passenger flow that can flow to the first sensing area, and are covered by WiFi nodes, as determined based on the WiFi node topology map. The second determining module is used to determine the passenger flow of the M second sensing areas toward the second direction at a fourth time, based on the second passenger flow and the time taken for the first sensing area to reach the M second sensing areas, when the second passenger flow is obtained and the second passenger flow is greater than 0. The M second sensing areas are areas that are adjacent to the first sensing area, whose passenger flow can come from the first sensing area, and which are covered by WiFi nodes, as determined based on the WiFi node topology map.

7. The apparatus according to claim 6, characterized in that, Also includes: The second acquisition module is used to acquire the passenger flow of the first target sensing area at the third time when the first target sensing area exists in the N second sensing areas. The first target sensing area is a sensing area with a passenger flow direction determined based on the WiFi node topology map and also includes a third direction. The third direction is a direction that is different from the first direction relative to the first target sensing area. The third determining module is used to determine the passenger flow of the first target sensing area toward the third direction at the third time based on the passenger flow of the first target sensing area at the third time and the passenger flow of the first target sensing area toward the first direction at the third time.

8. The apparatus according to claim 6, characterized in that, Also includes: The third acquisition module is used to acquire the passenger flow of the second target sensing area at the fourth time when there is a second target sensing area in the M second sensing areas. The second target sensing area is a sensing area with a fourth direction, which is a passenger flow direction determined based on the WiFi node topology map. The fourth direction is a direction that is different from the second direction relative to the second target sensing area. The fourth determining module is used to determine the passenger flow of the second target sensing area toward the fourth direction at the fourth time based on the passenger flow of the second target sensing area at the fourth time and the passenger flow of the second target sensing area toward the second direction at the fourth time.

9. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the passenger flow determination method as described in any one of claims 1 to 5.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the passenger flow determination method as described in any one of claims 1 to 5.

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