A passenger flow audience analysis method, system and storage medium for pushing information

Abstract

The present invention provides a method, system and storage medium for analyzing a passenger flow audience for pushing information, and relates to the technical field of audience analysis, comprising: step S1, using a camera to shoot at a fork in a shopping mall; step S2, analyzing passenger flow videos and passenger flow forks, and establishing a passenger flow daily table, a passenger flow weekly table and a passenger flow monthly table based on the analysis results; step S3, establishing an analysis line graph based on the passenger flow daily table, the passenger flow weekly table and the passenger flow monthly table; step S4, setting an audience for pushing information based on the analysis line graph; the present invention is used to solve the problem that there is a lack of targeted and effective improvement methods in the analysis of passenger flow audiences in the prior art, resulting in a lack of strong data support for passenger flow audience analysis when pushing information, and the most effective information cannot be pushed to target users quickly and accurately.

Description

Technical Field

[0001] The present invention relates to the technical field of audience analysis, and in particular to a passenger flow audience analysis method, system and storage medium for pushing information. Background Art

[0002] Information push, also known as web broadcasting, is a new technology that reduces information overload by regularly delivering information that users need on the Internet through certain technical standards or protocols. Push technology reduces the time spent on searching on the Internet by automatically delivering information to users; audience analysis enables marketers to gain key insights into consumer groups across the entire available market with the help of real-time data extracted from various online resources.

[0003] The improvement of the existing customer flow audience method for pushing information is usually to analyze the push results based on user evaluation and then further push them. For example, a Chinese patent with application publication number CN109034912A discloses an information push system for e-commerce operations with audience screening. The solution can independently evaluate the actual push situation through self-learning. The entire closed-loop system does not require human intervention. It only needs to be pre-configured to push information to the corresponding audience, thereby reducing operating costs. At the same time, other improvements in the customer flow audience method for pushing information are usually to improve the accuracy of pushed information and optimize the way of pushing information. There is a lack of targeted and effective improvement methods in the analysis of customer flow audiences, which will lead to a lack of strong customer flow audience analysis basis when pushing information, and the most effective information cannot be pushed to the target users quickly and accurately. In view of this, it is necessary to improve the existing customer flow audience analysis for pushing information. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a passenger flow audience analysis method, system and storage medium for pushing information, which is used to solve the problem that the prior art lacks targeted and effective improvement methods in the analysis of passenger flow audience, resulting in a lack of strong data support for passenger flow audience analysis when pushing information, and the inability to quickly and accurately push the most effective information to target users.

[0005] In order to achieve the above-mentioned object, in a first aspect, the present invention provides a method for analyzing a customer flow audience for pushing information, comprising:

[0006] Step S1, using a camera to shoot at a fork in the shopping mall, recording the shot video as a passenger flow video, and recording the fork in the road shot by the camera as a passenger flow fork;

[0007] Step S2, analyzing the passenger flow video and passenger flow intersections, and establishing a daily passenger flow table, a weekly passenger flow table, and a monthly passenger flow table based on the analysis results;

[0008] Step S3, establishing an analysis line graph based on the daily passenger flow table, the weekly passenger flow table, and the monthly passenger flow table;

[0009] Step S4, setting the audience for push information based on the analysis line graph.

[0010] Furthermore, the step S2 includes the following sub-steps:

[0011] Step S201, obtaining the intersection information of the fork road photographed by the camera, wherein the intersection information includes an entrance and an exit and commodity area 1 to commodity area N;

[0012] Step S202, for any one of the commodity areas 1 to N, obtain the commodity type with the largest number in the commodity area, and record it as the representative commodity of the commodity area;

[0013] Step S203, based on product area 1 to product area N, using step S202 to obtain representative products 1 to representative products N;

[0014] Step S204, obtaining the business hours of the shopping mall, and dividing the shooting time period of the camera into a closed time period, a normal time period, and a busy time period based on the business hours of the shopping mall;

[0015] The closed period is the non-business hours of the mall, the opening time of the mall is recorded as time A, and the closing time of the mall is recorded as time B;

[0016] The normal time period is from time A to the first business hour, from the second business hour to the third business hour, and from the fourth business hour to time B;

[0017] The busy period is from the first business hour to the second business hour and from the third business hour to the fourth business hour;

[0018] Record all normal periods and busy periods between time A and time B as a group of periods;

[0019] Step S205, when the camera is in the closed period, analyze the passenger flow videos of the latest group of time periods, and establish a passenger flow daily table based on the analysis results;

[0020] Step S206, whenever a passenger flow daily table of the first table quantity is established, the latest established passenger flow daily table of the first table quantity is obtained and a passenger flow weekly table is established;

[0021] Step S207, whenever a weekly passenger flow table of the second table quantity is established, the latest weekly passenger flow table of the second table quantity is obtained and a monthly passenger flow table is established.

[0022] Furthermore, the step S205 includes the following sub-steps:

[0023] Step S2051, recording the passenger flow video of the normal period in a group of passenger flow videos of a period as a normal passenger flow video;

[0024] The passenger flow videos in the busy period among the passenger flow videos in a group of time periods are recorded as busy passenger flow videos;

[0025] Step S2052, obtaining the number of customers entering each product area from product area 1 to product area N in the normal customer flow video, and recording the value of the number of customers divided by the time of the first period as the normal unit customer flow of the product area;

[0026] Get normal unit passenger flow 1 to normal unit passenger flow N;

[0027] Step S2053, obtaining the number of customers entering each of the commodity areas from commodity area 1 to commodity area N in the busy customer flow video, and recording the value of the number of customers divided by the time of the second period as the busy unit customer flow of the commodity area;

[0028] Get the busy unit passenger flow 1 to the busy unit passenger flow N;

[0029] Step S2054, using a weight algorithm to calculate the weight value of each commodity area, and record it as daily weight value 1 to daily weight value N;

[0030] The weight algorithm is L1=α1×L2+α2×L3, where L1 is the weight value, L2 is the normal unit passenger flow, L3 is the busy unit passenger flow, α1 is the first weight coefficient, α2 is the second weight coefficient, and α1 and α2 are both positive numbers;

[0031] Step S2055, create a table of T1 rows × Y1 columns, recorded as the daily passenger flow table, where the top row of the daily passenger flow table records the names of commodity areas 1 to N, and the leftmost column of the daily passenger flow table is time. Fill in the corresponding daily weight value in the cell corresponding to the commodity area and time, where the unit of time is day.

[0032] Furthermore, the step S206 includes the following sub-steps:

[0033] Step S2061, obtaining the passenger flow daily tables of the first table number, obtaining the commodity area corresponding to the maximum weight value and the commodity area corresponding to the minimum weight value in each passenger flow daily table, and recording them as the large weight area and the small weight area respectively;

[0034] Step S2062, create a table of T2 rows × Y1 columns, recorded as the passenger flow weekly table, wherein the top row of the passenger flow weekly table records the names of commodity areas 1 to N, the leftmost column of the passenger flow weekly table is the week number, and the large-weight area and small-weight area corresponding to the commodity area are filled in the cell corresponding to the commodity area and the week number, wherein the week number is the working week corresponding to the data in the passenger flow weekly table.

[0035] Furthermore, the step S207 includes the following sub-steps:

[0036] Step S2071, obtaining the second table number of weekly passenger flow tables, obtaining the total number of times each commodity area is recorded as a large-weight area and the total number of times a small-weight area is recorded in all weekly passenger flow tables, and recording them as the large-weight number and the small-weight number;

[0037] Step S2072, create a table of T3 rows × Y1 columns, recorded as the monthly passenger flow table, wherein the top row of the monthly passenger flow table records the names of commodity areas 1 to N, and the leftmost column of the monthly passenger flow table is the large weight and the small weight. The large weight number corresponding to the commodity area is filled in the cell corresponding to the commodity area and the large weight, and the small weight number is filled in the cell corresponding to the commodity area and the small weight.

[0038] Furthermore, the step S3 includes the following sub-steps:

[0039] Step S301, establishing an analysis line graph based on the passenger flow monthly table, wherein the analysis line graph is placed in a three-dimensional rectangular coordinate system;

[0040] Step S302, establish a three-dimensional rectangular coordinate system, mark the area formed by the x-axis and the z-axis of the three-dimensional rectangular coordinate system as the main coordinate system, in which the unit of the x-axis is the name of the commodity area, and the unit of the z-axis is the quantity;

[0041] Step S303, punctuate in the principal coordinate system based on the high-weighted number of times corresponding to each commodity area in the monthly passenger flow table, connect the punctuation points and record the resulting polyline as the high-weighted polyline;

[0042] Based on the small-weighted number of times corresponding to each commodity area in the monthly passenger flow table, punctuate the punctuation points in the principal coordinate system, connect the punctuation points and record the resulting polyline as the small-weight polyline;

[0043] Step S304, record the area formed by the x-axis and the y-axis of the three-dimensional rectangular coordinate system as a secondary coordinate system, in which the unit of the y-axis is the weight value;

[0044] Obtain the sum of the daily weight values ​​in all daily passenger flow tables corresponding to the monthly passenger flow table for each commodity area, record it as the total weight value, mark the punctuation points corresponding to each commodity area and the total weight value in the secondary coordinate system, connect the punctuation points and record the resulting polyline as the total weight polyline.

[0045] Furthermore, the step S4 includes the following sub-steps:

[0046] Step S401, obtaining a large weight polyline and a small weight polyline, for any product area from product area 1 to product area N, when the large weight number of the product area is greater than or equal to the first weight number, the product area is recorded as a region with a wide audience;

[0047] Step S402, when the small weight number of the commodity area is less than or equal to the second weight number, the commodity area is recorded as a better audience area;

[0048] Step S403, obtaining a total weight polyline, for any product area from product area 1 to product area N, when the total weight value of the product area is greater than or equal to the standard weight, the product area is recorded as a stable audience area;

[0049] Step S404, record the commodity areas other than the areas with a wider audience, the areas with a better audience, and the areas with a stable audience as areas with a mediocre audience.

[0050] Furthermore, the step S4 further includes the following sub-steps:

[0051] Step S405, when the product area is recorded as both a relatively large audience area and a stable audience area, the product area is recorded as a good area;

[0052] Step S406, customers who go to excellent areas are recorded as preferred customers, and customers who go to areas other than excellent areas are recorded as non-preferred customers. When pushing information, relevant products in mediocre areas with good audiences are pushed to preferred customers, and relevant products in excellent areas and areas with good audiences are pushed to non-preferred customers.

[0053] In a second aspect, the present invention provides a passenger flow audience analysis system for pushing information, including a shooting analysis module, a picture building module and a chart analysis module, wherein the shooting analysis module and the picture building module are communicatively connected with the chart analysis module;

[0054] The shooting and analysis module uses a camera to shoot at a fork in the shopping mall, records the shot video as a passenger flow video, and records the fork in the road shot by the camera as a passenger flow fork; and analyzes the passenger flow video and the passenger flow fork, and establishes a passenger flow daily table, a passenger flow weekly table, and a passenger flow monthly table based on the analysis results;

[0055] The graph building module builds an analysis line graph based on the daily passenger flow table, the weekly passenger flow table, and the monthly passenger flow table;

[0056] The chart analysis module sets the audience for push information based on analyzing the line chart.

[0057] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in the method described above are executed.

[0058] Beneficial effects of the present invention: The present invention uses a camera to shoot at a fork in the shopping mall, records the shot video as a customer flow video, and records the fork shot by the camera as a customer flow fork. This has the advantage that using a camera to shoot customers at the fork can intuitively obtain the direction chosen by the customer after entering the shopping mall, which is conducive to analyzing the customer's preferences;

[0059] The present invention also establishes daily, weekly and monthly passenger flow tables based on the analysis results of passenger flow videos and passenger flow intersections; and establishes analysis line graphs based on the daily, weekly and monthly passenger flow tables; finally, the audience for pushing information is set based on the analysis line graph. The advantage of this is that by establishing daily, weekly and monthly passenger flow tables, it is helpful to analyze the choices of customers for product areas in the supermarket in a short period of time and a long period of time. From the analysis results, it is possible to more accurately obtain excellent areas with a wider audience range and mediocre areas with a relatively mediocre audience in the mall, so that the most effective information can be delivered to customers when pushing information.

[0060] Advantages of additional aspects of the present invention will be given in part in the description of the following specific embodiments, and in part will become apparent from the following description, or will be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0062] Figure 1 A flowchart of the steps of the method for analyzing the passenger flow audience for pushing information of the present invention;

[0063] Figure 2 It is a principle block diagram of the passenger flow audience analysis system for pushing information of the present invention;

[0064] Figure 3 It is a schematic diagram of the analysis line graph of the present invention. DETAILED DESCRIPTION

[0065] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0066] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0067] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0068] Example 1

[0069] See also Figure 1 As shown, the present invention provides a passenger flow audience analysis method for pushing information, which is used to solve the problem that there is a lack of targeted and effective improvement methods in the analysis of passenger flow audiences in the prior art, resulting in a lack of strong data support for passenger flow audience analysis when pushing information, and the most effective information cannot be pushed to target users quickly and accurately;

[0070] Specifically, the passenger flow audience analysis method for pushing information includes the following steps:

[0071] Step S1, using a camera to shoot at a fork in the shopping mall, recording the shot video as a passenger flow video, and recording the fork in the road shot by the camera as a passenger flow fork;

[0072] In the specific implementation process, the passenger flow intersection is selected as an intersection that can only be entered and exited in one direction. For any commodity area except the entrance and exit, it is impossible to enter and exit in any way other than the passenger flow intersection, ensuring that customers entering the commodity area will only touch the commodities in the commodity area;

[0073] Step S2, analyzing the passenger flow video and passenger flow intersections, and establishing a daily passenger flow table, a weekly passenger flow table, and a monthly passenger flow table based on the analysis results;

[0074] Step S2 includes the following sub-steps:

[0075] Step S201, obtaining the intersection information of the fork road captured by the camera, the intersection information including the entrance and exit and commodity area 1 to commodity area N;

[0076] Step S202, for any one of the commodity areas 1 to N, obtain the commodity type with the largest number in the commodity area, and record it as the representative commodity of the commodity area;

[0077] Step S203, based on product area 1 to product area N, using step S202 to obtain representative products 1 to representative products N;

[0078] Step S204, obtaining the business hours of the shopping mall, and dividing the shooting time period of the camera into a closed time period, a normal time period, and a busy time period based on the business hours of the shopping mall;

[0079] In the specific implementation process, the customer flow in the mall during normal hours and busy hours is quite different, so they need to be analyzed separately. The camera is turned on all day and the closing time is not within the analysis range, so the closing time needs to be separated separately;

[0080] The closed period is the non-business hours of the mall. The opening time of the mall is recorded as time A, and the closing time of the mall is recorded as time B;

[0081] Normal periods are from time A to the first business hour, from the second business hour to the third business hour, and from the fourth business hour to time B;

[0082] Peak hours are from the first business hour to the second business hour and from the third business hour to the fourth business hour;

[0083] In the specific implementation process, the first business hour is set at 11 a.m., the second business hour is set at 2 p.m., the third business hour is set at 5 p.m., and the fourth business hour is set at 8 p.m.;

[0084] Record all normal periods and busy periods between time A and time B as a group of periods;

[0085] Step S205, when the camera is in the closed period, analyze the passenger flow videos of the latest group of time periods, and establish a passenger flow daily table based on the analysis results;

[0086] Step S205 includes the following sub-steps:

[0087] Step S2051, recording the passenger flow video of the normal period in a group of passenger flow videos of a period as a normal passenger flow video;

[0088] The passenger flow videos in the busy period among the passenger flow videos in a group of time periods are recorded as busy passenger flow videos;

[0089] Step S2052, obtaining the number of customers entering each product area from product area 1 to product area N in the normal customer flow video, and recording the value of the number of customers divided by the time of the first period as the normal unit customer flow of the product area;

[0090] In the specific implementation process, the first period time is set to 7. By obtaining the normal unit passenger flow, the passenger flow data of each commodity area in the mall during the normal period can be unified, which is conducive to subsequent analysis;

[0091] Get normal unit passenger flow 1 to normal unit passenger flow N;

[0092] Step S2053, obtaining the number of customers entering each of the commodity areas from commodity area 1 to commodity area N in the busy customer flow video, and recording the value of the number of customers divided by the time of the second period as the busy unit customer flow of the commodity area;

[0093] In the specific implementation process, the second period time is set to 6;

[0094] Get the busy unit passenger flow 1 to the busy unit passenger flow N;

[0095] Step S2054, using a weight algorithm to calculate the weight value of each commodity area, and record it as daily weight value 1 to daily weight value N;

[0096] The weight algorithm is L1=α1×L2+α2×L3, where L1 is the weight value, L2 is the normal unit passenger flow, L3 is the busy unit passenger flow, α1 is the first weight coefficient, α2 is the second weight coefficient, α1 and α2 are both positive numbers, α1+α2=1;

[0097] In the specific implementation process, α1 is set to 0.6, α2 is set to 0.4, and it is detected that the normal unit passenger flow is 1000 and the busy unit passenger flow is 2000. Then the weight value obtained by calculation is 1400;

[0098] Step S2055, refer to Table 1, create a table of T1 rows × Y1 columns, record it as the passenger flow daily table, where the top row of the passenger flow daily table records the names of commodity areas 1 to N, the leftmost column of the passenger flow daily table is time, fill in the corresponding daily weight value in the cell corresponding to the commodity area and time, where the unit of time is day, and Y1 is set to N+1;

[0099] Table 1 Daily passenger flow table

[0100] Name of product area 1 ...... Name of product area N time Daily weight value Daily weight value Daily weight value

[0101] Step S206, whenever a passenger flow daily table of the first table quantity is established, the latest established passenger flow daily table of the first table quantity is obtained and a passenger flow weekly table is established;

[0102] In the specific implementation process, the number of the first table is set to 7;

[0103] Step S206 includes the following sub-steps:

[0104] Step S2061, obtaining the passenger flow daily tables of the first table number, obtaining the commodity area corresponding to the maximum weight value and the commodity area corresponding to the minimum weight value in each passenger flow daily table, and recording them as the large weight area and the small weight area respectively;

[0105] Step S2062, refer to Table 2, create a table of T2 rows × Y1 columns, recorded as a passenger flow weekly table, wherein the top row of the passenger flow weekly table records the names of commodity areas 1 to N, the leftmost column of the passenger flow weekly table is the week number, and the large-weight area and small-weight area corresponding to the commodity area are filled in the cell corresponding to the commodity area and the week number, wherein the week number is the working week corresponding to the data in the passenger flow weekly table;

[0106] Table 2 Passenger flow weekly table

[0107]

[0108] Step S207, whenever a weekly passenger flow table of the second table quantity is established, the latest weekly passenger flow table of the second table quantity is obtained and a monthly passenger flow table is established;

[0109] In the specific implementation process, the number of the second table is set to 4;

[0110] Step S207 includes the following sub-steps:

[0111] Step S2071, obtaining the second table number of weekly passenger flow tables, obtaining the total number of times each commodity area is recorded as a large-weight area and the total number of times a small-weight area is recorded in all weekly passenger flow tables, and recording them as the large-weight number and the small-weight number;

[0112] Step S2072, refer to Table 3, create a table of T3 rows × Y1 columns, recorded as the monthly passenger flow table, wherein the top row of the monthly passenger flow table records the names of commodity areas 1 to N, and the leftmost column of the monthly passenger flow table is the large weight and the small weight. The large weight number corresponding to the commodity area is filled in the cell corresponding to the commodity area and the large weight, and the small weight number corresponding to the commodity area is filled in the cell corresponding to the commodity area and the small weight;

[0113] Table 3 Passenger flow monthly table

[0114] Name of product area 1 ...... Name of product area N Large weights Number of times of great weight Number of times of great weight Number of times of great weight Small weights Small weight times Small weight times Small weight times

[0115] Step S3, establishing an analysis line graph based on the daily passenger flow table, the weekly passenger flow table, and the monthly passenger flow table;

[0116] Step S3 includes the following sub-steps:

[0117] Step S301, establishing an analysis line graph based on the monthly passenger flow table, and placing the analysis line graph in a three-dimensional rectangular coordinate system;

[0118] Step S302, see Figure 3 As shown, V1 is a large-weight polyline, V2 is a small-weight polyline, and V3 is a total-weight polyline. A three-dimensional rectangular coordinate system is established, and the area formed by the x-axis and the z-axis of the three-dimensional rectangular coordinate system is marked as the main coordinate system. In the main coordinate system, the unit of the x-axis is the name of the commodity area, and the unit of the z-axis is the quantity.

[0119] Step S303, punctuate in the principal coordinate system based on the high-weighted number of times corresponding to each commodity area in the monthly passenger flow table, connect the punctuation points and record the resulting polyline as the high-weighted polyline;

[0120] Based on the small-weighted number of times corresponding to each commodity area in the monthly passenger flow table, punctuate the punctuation points in the principal coordinate system, connect the punctuation points and record the resulting polyline as the small-weight polyline;

[0121] Step S304, record the area formed by the x-axis and the y-axis of the three-dimensional rectangular coordinate system as a secondary coordinate system, in which the unit of the y-axis is the weight value;

[0122] Obtain the sum of the daily weight values ​​in all the daily passenger flow tables corresponding to the monthly passenger flow table of each commodity area, record it as the total weight value, mark the punctuation points corresponding to each commodity area and the total weight value in the secondary coordinate system, connect the punctuation points and record the resulting polyline as the total weight polyline;

[0123] Step S4, setting the audience for push information based on the analysis line graph;

[0124] Step S4 includes the following sub-steps: Step S401, obtaining a large weight polyline and a small weight polyline, for any product area from product area 1 to product area N, when the large weight number of the product area is greater than or equal to the first weight number, the product area is recorded as a region with a wide audience;

[0125] Step S402, when the small weight number of the commodity area is less than or equal to the second weight number, the commodity area is recorded as a better audience area;

[0126] In the specific implementation process, the first weight number is set to 2, the second weight number is set to 0, and the standard weight is determined according to the specific situation of the supermarket customer flow, preferably 1500;

[0127] Step S403, obtaining a total weight polyline, for any product area from product area 1 to product area N, when the total weight value of the product area is greater than or equal to the standard weight, the product area is recorded as a stable audience area;

[0128] Step S404, recording the commodity areas other than the areas with a wide audience, the areas with a good audience, and the areas with a stable audience as areas with a mediocre audience;

[0129] Step S405, when the product area is recorded as both a relatively large audience area and a stable audience area, the product area is recorded as a good area;

[0130] Step S406, customers who go to the excellent area are recorded as preferred customers, and customers who go to areas other than the excellent area are recorded as non-preferred customers. When pushing information, relevant products in the mediocre area of ​​the audience are pushed to the preferred customers, and relevant products in the excellent area and the area with good audience are pushed to the non-preferred customers;

[0131] In the specific implementation process, pushing relevant products in areas with mediocre audiences to preferred customers is to increase the customer flow of preferred customers in areas with mediocre audiences, so that preferred customers can discover more types of products. Pushing relevant products in excellent areas and areas with better audiences to non-preferred users is to show non-preferred customers products with a wider audience in the supermarket, which is conducive to increasing the customer flow of the supermarket.

[0132] Example 2

[0133] See also Figure 2 As shown, a passenger flow audience analysis system for pushing information includes a shooting analysis module, a picture building module and a chart analysis module, and the shooting analysis module and the picture building module are communicatively connected with the chart analysis module;

[0134] The shooting and analysis module uses a camera to shoot at the fork in the shopping mall, records the shot video as the passenger flow video, and records the fork in the road shot by the camera as the passenger flow fork; and analyzes the passenger flow video and the passenger flow fork, and establishes a passenger flow daily table, a passenger flow weekly table, and a passenger flow monthly table based on the analysis results;

[0135] In the specific implementation process, the passenger flow intersection is selected as an intersection that can only be entered and exited in one direction. For any commodity area except the entrance and exit, it is impossible to enter and exit in any way other than the passenger flow intersection, ensuring that customers entering the commodity area will only touch the commodities in the commodity area;

[0136] The shooting analysis module is configured with shooting analysis strategies, which include:

[0137] Obtain the intersection information of the fork road captured by the camera, the intersection information includes the entrance and exit and commodity area 1 to commodity area N;

[0138] For any product area from product area 1 to product area N, obtain the product type with the largest number in the product area and record it as the representative product of the product area;

[0139] Obtain representative products 1 to representative products N based on product area 1 to product area N;

[0140] Obtain the business hours of the shopping mall, and divide the camera's shooting time period into closed hours, normal hours, and busy hours based on the shopping mall's business hours;

[0141] In the specific implementation process, the customer flow in the mall during normal hours and busy hours is quite different, so they need to be analyzed separately. The camera is turned on all day and the closing time is not within the analysis range, so the closing time needs to be separated separately;

[0142] The closed period is the non-business hours of the mall. The opening time of the mall is recorded as time A, and the closing time of the mall is recorded as time B;

[0143] Normal periods are from time A to the first business hour, from the second business hour to the third business hour, and from the fourth business hour to time B;

[0144] Peak hours are from the first business hour to the second business hour and from the third business hour to the fourth business hour;

[0145] In the specific implementation process, the first business hour is set at 11 a.m., the second business hour is set at 2 p.m., the third business hour is set at 5 p.m., and the fourth business hour is set at 8 p.m.;

[0146] Record all normal periods and busy periods between time A and time B as a group of periods;

[0147] When the camera is closed, analyze the passenger flow videos of the latest set of time periods and create a passenger flow table based on the analysis results;

[0148] The passenger flow videos in the normal period among the passenger flow videos in a group of time periods are recorded as normal passenger flow videos;

[0149] The passenger flow videos in the busy period among the passenger flow videos in a group of time periods are recorded as busy passenger flow videos;

[0150] Obtain the number of customers entering each product area from product area 1 to product area N in the normal customer flow video, and record the value of the number of customers divided by the time of the first period as the normal unit customer flow of the product area;

[0151] In the specific implementation process, the first period time is set to 7. By obtaining the normal unit passenger flow, the passenger flow data of each commodity area in the mall during the normal period can be unified, which is conducive to subsequent analysis;

[0152] Get normal unit passenger flow 1 to normal unit passenger flow N;

[0153] Obtain the number of customers entering each product area from product area 1 to product area N in the busy customer flow video, and record the value of the number of customers divided by the time of the second period as the busy unit customer flow of the product area;

[0154] In the specific implementation process, the second period time is set to 6;

[0155] Get the busy unit passenger flow 1 to the busy unit passenger flow N;

[0156] Use the weight algorithm to calculate the weight value of each commodity area and record it as daily weight value 1 to daily weight value N;

[0157] The weight algorithm is L1=α1×L2+α2×L3, where L1 is the weight value, L2 is the normal unit passenger flow, L3 is the busy unit passenger flow, α1 is the first weight coefficient, α2 is the second weight coefficient, and α1 and α2 are both positive numbers;

[0158] In the specific implementation process, α1 is set to 0.6, α2 is set to 0.4, and it is detected that the normal unit passenger flow is 1000 and the busy unit passenger flow is 2000. Then the weight value obtained by calculation is 1400;

[0159] The shooting analysis module is also configured with a table creation strategy, which includes:

[0160] Please refer to Table 1, and establish a table of T1 rows × Y1 columns, which is recorded as the passenger flow daily table. The top row of the passenger flow daily table records the names of commodity areas 1 to N. The leftmost column of the passenger flow daily table is time. Fill in the corresponding daily weight value in the cell corresponding to the commodity area and time. The unit of time is day, and Y1 is set to N+1.

[0161] Table 1 Daily passenger flow table

[0162] Name of product area 1 ...... Name of product area N time Daily weight value Daily weight value Daily weight value

[0163] Whenever a passenger flow daily table with the first number of tables is established, the passenger flow daily table with the latest number of tables established is obtained and a passenger flow weekly table is established;

[0164] In the specific implementation process, the number of the first table is set to 7;

[0165] Obtain the passenger flow daily table of the first table number, obtain the commodity area corresponding to the maximum weight value and the commodity area corresponding to the minimum weight value in each passenger flow daily table, and record them as the large weight area and the small weight area respectively;

[0166] Please refer to Table 2, establish a table of T2 rows × Y1 columns, recorded as the passenger flow weekly table, where the top row of the passenger flow weekly table records the names of commodity areas 1 to N, and the leftmost column of the passenger flow weekly table is the week number. Fill in the large-weight area and small-weight area corresponding to the commodity area in the cell corresponding to the commodity area and the week number, where the week number is the working week corresponding to the data in the passenger flow weekly table;

[0167] Table 2 Passenger flow weekly table

[0168]

[0169] Whenever a weekly passenger flow table of the second table quantity is established, the latest weekly passenger flow table of the second table quantity is obtained and a monthly passenger flow table is established;

[0170] In the specific implementation process, the number of the second table is set to 4;

[0171] Obtain the weekly passenger flow table of the second table, and obtain the total number of times each commodity area is recorded as a large-weight area and the total number of times a small-weight area is recorded in all weekly passenger flow tables, and record them as the large-weight number and the small-weight number;

[0172] Please refer to Table 3, and establish a table of T3 rows × Y1 columns, which is recorded as the passenger flow monthly table. The top row of the passenger flow monthly table records the names of commodity areas 1 to N. The leftmost column of the passenger flow monthly table is the large weight and the small weight. The large weight number corresponding to the commodity area is filled in the box corresponding to the commodity area and the large weight, and the small weight number corresponding to the commodity area is filled in the box corresponding to the commodity area and the small weight.

[0173] Table 3 Passenger flow monthly table

[0174] Name of product area 1 ...... Name of product area N Large weights Number of times of great weight Number of times of great weight Number of times of great weight Small weights Small weight times Small weight times Small weight times

[0175] The graph building module builds analytical line graphs based on the daily passenger flow table, weekly passenger flow table, and monthly passenger flow table;

[0176] The graph building module is configured with a graph building strategy, which includes:

[0177] See also Figure 3 As shown, V1 is a large-weight polyline, V2 is a small-weight polyline, and V3 is a total-weight polyline. A three-dimensional rectangular coordinate system is established, and the area formed by the x-axis and the z-axis of the three-dimensional rectangular coordinate system is marked as the main coordinate system. In the main coordinate system, the unit of the x-axis is the name of the commodity area, and the unit of the z-axis is the quantity.

[0178] Based on the high-weighted number of times corresponding to each commodity area in the monthly passenger flow table, punctuate the points in the principal coordinate system, connect the points and record the resulting polyline as the high-weight polyline;

[0179] Based on the small-weighted number of times corresponding to each commodity area in the monthly passenger flow table, punctuate the punctuation points in the principal coordinate system, connect the punctuation points and record the resulting polyline as the small-weight polyline;

[0180] The area formed by the x-axis and the y-axis of the three-dimensional rectangular coordinate system is recorded as the secondary coordinate system, and in the secondary coordinate system, the unit of the y-axis is the weight value;

[0181] Obtain the sum of the daily weight values ​​in all the daily passenger flow tables corresponding to the monthly passenger flow table of each commodity area, record it as the total weight value, mark the punctuation points corresponding to each commodity area and the total weight value in the secondary coordinate system, connect the punctuation points and record the resulting polyline as the total weight polyline;

[0182] The chart analysis module sets the audience for push information based on the analysis of the line chart.

[0183] The chart analysis module is configured with chart analysis strategies, which include:

[0184] Obtain a large-weight polyline and a small-weight polyline. For any product area from product area 1 to product area N, when the large-weight number of the product area is greater than or equal to the first-weight number, the product area is recorded as a region with a wide audience.

[0185] When the number of times of small weight in a product area is less than or equal to the number of times of second weight, the product area is recorded as a better audience area;

[0186] In the specific implementation process, the first weight number is set to 2, the second weight number is set to 0, and the standard weight is determined according to the specific situation of the supermarket customer flow, preferably 1500;

[0187] Obtain the total weight polyline. For any product area from product area 1 to product area N, when the total weight value of the product area is greater than or equal to the standard weight, the product area is recorded as a stable audience area.

[0188] The product areas outside the areas with a wide audience, areas with a good audience, and areas with a stable audience are recorded as areas with a mediocre audience;

[0189] When a product area is recorded as both a wide audience area and a stable audience area, the product area is recorded as a good area;

[0190] Customers who go to excellent areas are recorded as preferred customers, and customers who go to areas other than excellent areas are recorded as non-preferred customers. When pushing information, relevant products in mediocre areas are pushed to preferred customers, and relevant products in excellent areas and areas with good audiences are pushed to non-preferred customers.

[0191] In the specific implementation process, pushing relevant products in areas with mediocre audiences to preferred customers is to increase the customer flow of preferred customers in areas with mediocre audiences, so that preferred customers can discover more types of products. Pushing relevant products in excellent areas and areas with better audiences to non-preferred users is to show non-preferred customers products with a wider audience in the supermarket, which is conducive to increasing the customer flow of the supermarket.

[0192] Example 3

[0193] The present application provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method are executed. Through the above technical solution, when the computer program is executed by the processor, the method in any optional implementation of the above embodiment is executed to achieve the following functions: by using a camera to shoot at a fork in the shopping mall, and then based on the analysis results of the passenger flow video and the passenger flow fork, a passenger flow daily table, a passenger flow weekly table, and a passenger flow monthly table are established; and based on the passenger flow daily table, the passenger flow weekly table, and the passenger flow monthly table, an analysis line graph is established; finally, the audience for push information is set based on the analysis line graph.

[0194] It should be understood by those skilled in the art that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Wherein, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0195] The above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for analyzing the flow of customers for pushing information, characterized in that: include: Step S1, using a camera to shoot at a fork in the shopping mall, recording the shot video as a passenger flow video, and recording the fork in the road shot by the camera as a passenger flow fork; Step S2, analyzing the passenger flow video and passenger flow intersections, and establishing a daily passenger flow table, a weekly passenger flow table, and a monthly passenger flow table based on the analysis results; Step S3, establishing an analysis line graph based on the daily passenger flow table, the weekly passenger flow table, and the monthly passenger flow table; Step S4, setting the audience for push information based on the analysis line graph; The step S2 includes the following sub-steps: Step S201, obtaining the intersection information of the fork road photographed by the camera, wherein the intersection information includes an entrance and an exit and commodity area 1 to commodity area N; Step S202, for any one of the commodity areas 1 to N, obtain the commodity type with the largest number in the commodity area, and record it as the representative commodity of the commodity area; Step S203, based on product area 1 to product area N, using step S202 to obtain representative products 1 to representative products N; Step S204, obtaining the business hours of the shopping mall, and dividing the shooting time period of the camera into a closed time period, a normal time period, and a busy time period based on the business hours of the shopping mall; The closed period is the non-business hours of the mall, the opening time of the mall is recorded as time A, and the closing time of the mall is recorded as time B; The normal time period is from time A to the first business hour, from the second business hour to the third business hour, and from the fourth business hour to time B; The busy period is from the first business hour to the second business hour and from the third business hour to the fourth business hour; Record all normal periods and busy periods between time A and time B as a group of periods; Step S205, when the camera is in the closed period, analyze the passenger flow videos of the latest group of time periods, and establish a passenger flow daily table based on the analysis results; Step S206, whenever a passenger flow daily table of the first table quantity is established, the latest established passenger flow daily table of the first table quantity is obtained and a passenger flow weekly table is established; Step S207, whenever a weekly passenger flow table of the second table quantity is established, the latest weekly passenger flow table of the second table quantity is obtained and a monthly passenger flow table is established; The step S205 includes the following sub-steps: Step S2051, recording the passenger flow video of the normal period in a group of passenger flow videos of a period as a normal passenger flow video; The passenger flow videos in the busy period among the passenger flow videos in a group of time periods are recorded as busy passenger flow videos; Step S2052, obtaining the number of customers entering each product area from product area 1 to product area N in the normal customer flow video, and recording the value of the number of customers divided by the time of the first period as the normal unit customer flow of the product area; Get normal unit passenger flow 1 to normal unit passenger flow N; Step S2053, obtaining the number of customers entering each of the commodity areas from commodity area 1 to commodity area N in the busy customer flow video, and recording the value of the number of customers divided by the time of the second period as the busy unit customer flow of the commodity area; Get the busy unit passenger flow 1 to the busy unit passenger flow N; Step S2054, using a weight algorithm to calculate the weight value of each commodity area, and record it as daily weight value 1 to daily weight value N; The weight algorithm is L1=α1×L2+α2×L3, where L1 is the weight value, L2 is the normal unit passenger flow, L3 is the busy unit passenger flow, α1 is the first weight coefficient, α2 is the second weight coefficient, and α1 and α2 are both positive numbers; Step S2055, create a table of T1 rows × Y1 columns, recorded as a passenger flow daily table, wherein the top row of the passenger flow daily table records the names of commodity areas 1 to N, and the leftmost column of the passenger flow daily table is time. The corresponding daily weight value is filled in the cell corresponding to the commodity area and time, wherein the unit of time is day; The step S206 includes the following sub-steps: Step S2061, obtaining the passenger flow daily tables of the first table number, obtaining the commodity area corresponding to the maximum weight value and the commodity area corresponding to the minimum weight value in each passenger flow daily table, and recording them as the large weight area and the small weight area respectively; Step S2062, create a table of T2 rows × Y1 columns, recorded as a passenger flow weekly table, wherein the top row of the passenger flow weekly table records the names of commodity areas 1 to N, the leftmost column of the passenger flow weekly table is the week number, and the large-weight area and small-weight area corresponding to the commodity area are filled in the cell corresponding to the commodity area and the week number, wherein the week number is the working week corresponding to the data in the passenger flow weekly table; The step S207 includes the following sub-steps: Step S2071, obtaining the second table number of weekly passenger flow tables, obtaining the total number of times each commodity area is recorded as a large-weight area and the total number of times a small-weight area is recorded in all weekly passenger flow tables, and recording them as the large-weight number and the small-weight number; Step S2072, create a table of T3 rows × Y1 columns, recorded as the monthly passenger flow table, wherein the top row of the monthly passenger flow table records the names of commodity areas 1 to N, and the leftmost column of the monthly passenger flow table is the large weight and the small weight. The large weight number corresponding to the commodity area is filled in the cell corresponding to the commodity area and the large weight, and the small weight number is filled in the cell corresponding to the commodity area and the small weight. The step S3 includes the following sub-steps: Step S301, establishing an analysis line graph based on the passenger flow monthly table, wherein the analysis line graph is placed in a three-dimensional rectangular coordinate system; Step S302, establish a three-dimensional rectangular coordinate system, mark the area formed by the x-axis and the z-axis of the three-dimensional rectangular coordinate system as the main coordinate system, in which the unit of the x-axis is the name of the commodity area, and the unit of the z-axis is the quantity; Step S303, punctuate in the principal coordinate system based on the high-weighted number of times corresponding to each commodity area in the monthly passenger flow table, connect the punctuation points and record the resulting polyline as the high-weighted polyline; Based on the small-weighted number of times corresponding to each commodity area in the monthly passenger flow table, punctuate the punctuation points in the principal coordinate system, connect the punctuation points and record the resulting polyline as the small-weight polyline; Step S304, record the area formed by the x-axis and the y-axis of the three-dimensional rectangular coordinate system as a secondary coordinate system, in which the unit of the y-axis is the weight value; Obtain the sum of the daily weight values ​​in all the daily passenger flow tables corresponding to the monthly passenger flow table of each commodity area, record it as the total weight value, mark the punctuation points corresponding to each commodity area and the total weight value in the secondary coordinate system, connect the punctuation points and record the resulting polyline as the total weight polyline; The step S4 includes the following sub-steps: Step S401, obtaining a large weight polyline and a small weight polyline, for any product area from product area 1 to product area N, when the large weight number of the product area is greater than or equal to the first weight number, the product area is recorded as a region with a wide audience; Step S402, when the small weight number of the commodity area is less than or equal to the second weight number, the commodity area is recorded as a better audience area; Step S403, obtaining a total weight polyline, for any product area from product area 1 to product area N, when the total weight value of the product area is greater than or equal to the standard weight, the product area is recorded as a stable audience area; Step S404, record the commodity areas other than the areas with a wider audience, the areas with a better audience, and the areas with a stable audience as areas with a mediocre audience.

2. The method for analyzing the passenger flow audience for pushing information according to claim 1, characterized in that: The step S4 also includes the following sub-steps: Step S405, when the product area is recorded as both a relatively large audience area and a stable audience area, the product area is recorded as a good area; Step S406, customers who go to excellent areas are recorded as preferred customers, and customers who go to areas other than excellent areas are recorded as non-preferred customers. When pushing information, relevant products in mediocre areas with good audiences are pushed to preferred customers, and relevant products in excellent areas and areas with good audiences are pushed to non-preferred customers.

3. A system applicable to a method for analyzing passenger flow audience for pushing information as claimed in claim 1 or 2, characterized in that: It includes a shooting analysis module, a picture building module and a chart analysis module, wherein the shooting analysis module and the picture building module are communicatively connected with the chart analysis module; The shooting and analysis module uses a camera to shoot at a fork in the shopping mall, records the shot video as a passenger flow video, and records the fork in the road shot by the camera as a passenger flow fork; and analyzes the passenger flow video and the passenger flow fork, and establishes a passenger flow daily table, a passenger flow weekly table, and a passenger flow monthly table based on the analysis results; The graph building module builds an analysis line graph based on the daily passenger flow table, the weekly passenger flow table, and the monthly passenger flow table; The chart analysis module sets the audience for push information based on analyzing the line chart.

4. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method according to claim 1 or 2 are executed.

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