Advertisement placement location evaluation device, advertisement placement location evaluation method, and advertisement placement location evaluation program

Abstract

To provide an advertisement display place evaluation device, an advertisement display place evaluation method and an advertisement display place evaluation program which can acquire information related to evaluation of advertising effectiveness of an advertisement display place.SOLUTION: An advertisement display place evaluation device comprises evaluation means (control unit 11) which determines evaluation about the advertisement display place according to a prescribed reference, by using estimated viewers number information which is information related to an estimation value of the number of viewers who view an advertisement display place.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an advertising display location evaluation device, an advertising display location evaluation method, and an advertising display location evaluation program.

Background Art

[0002] Inside the premises of facilities such as railway stations, it is assumed that there are significant differences in the flow of people, that is, how many people pass through which locations within the facility, depending on the characteristics of the facility (type of facility, scale of the facility, etc.) and various conditions such as the time zone. However, in order to provide appropriate services to users according to the flow of people or to take measures against accidents caused by excessive congestion, it is necessary to grasp the situation of the flow of people within the facility.

[0003] Therefore, a system for estimating the flow of people inside the premises of facilities such as railway stations is known (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Inside the premises of facilities such as railway stations, there are usually many display locations for posting advertisements. However, the promotional effect obtained when posting an advertisement at such an advertisement display location depends on the number of people who see each display location and is assumed to be different for each display location. [[ID=四十]] In this regard, in the conventional system, it only estimates the flow of people inside the premises of facilities such as railway stations, and for each advertisement display location provided within the facility, information related to the evaluation of its promotional effect cannot be obtained.

[0006] The object of the present invention is to provide an advertising location evaluation device, an advertising location evaluation method, and an advertising location evaluation program that enable the acquisition of information related to the evaluation of the advertising effectiveness of advertising locations. [Means for solving the problem]

[0007] To solve the above problems, the invention described in claim 1 relates to an advertising location evaluation device, Regarding the location where the advertisement is displayed, an estimation means estimates the number of people who will see the advertisement based on the ticket usage history information and obtains estimated viewer count information. An evaluation means that uses the estimated number of viewers information to determine the effectiveness of the advertising campaign according to the number of viewers in the estimated number of viewers information, Equipped with 、 The estimation means divides the number of people aggregated from the ticket usage history information into platforms and passages where use is estimated, and uses the direction of movement in a passage when moving from a specific platform to a specific ticket gate or from a specific ticket gate to a specific platform using a specific passage as the direction of movement information in that passage, and estimates the number of people who see the advertisement display location based on the relationship between the direction of movement information and the orientation of the advertisement surface. It is characterized by the following.

[0008] The invention described in claim 2 is an advertising location evaluation device described in claim 1, The aforementioned estimated number of viewers is information that estimates the number of viewers for each time period. The evaluation means is characterized by determining an evaluation for each time period for the advertising display location.

[0009] The invention described in claim 3 is an advertising location evaluation device according to claim 1 or 2, The aforementioned estimated number of viewers is information obtained by estimating the number of viewers for each attribute of the viewers. The evaluation means is characterized by determining an evaluation for each of the attributes of the target viewers for each advertising display location.

[0011] Claim 4 The invention described in the claim 1 In the advertising location evaluation device described above, The aforementioned advertising display locations are provided near the passageway, facing in a direction opposite to the direction of pedestrian movement in the passageway. The estimation means estimates the number of people moving in the direction opposite to the direction in which the advertising display location faces the passage as the number of viewers.

[0012] Claim 5 The invention according to claim 1 In the advertising display location evaluation device according to claim The advertising display location is provided near the passage so as to face a direction orthogonal to the direction of movement of people in the passage. The estimation means estimates the number of people moving in the direction orthogonal to the direction in which the advertising display location faces the passage as the number of viewers.

[0013] Claim 6 The invention according to claim 1 In the advertising display location evaluation device according to claim The advertising display location is provided near the passage so as to face a direction orthogonal to the direction of movement of people in the passage. The estimation means estimates the number obtained by multiplying the number of people moving in the direction orthogonal to the direction in which the advertising display location faces the passage by a predetermined coefficient as the number of viewers.

[0014] Claim 7 The invention according to claim is in the advertising display location evaluation device according to any one of claims 1 to 6 The evaluation means determines a score for each advertising display location based on an estimated value of the number of viewers who see the advertising display location. Based on an estimated value of the number of viewers who see the advertising display location 、 The evaluation means determines a score for each advertising display location.

[0015] Claim 8 The invention according to claim is in the advertising display location evaluation device according to any one of claims 1 to 7 Based on an estimated value of the number of viewers who see the advertising display location 、 The evaluation means determines a rank for each advertising display location.

[0016] The invention according to claim 9 is an advertisement display location evaluation method in an advertisement display location evaluation device, comprising: an estimation step of estimating the number of viewers who see the advertisement display location based on the ticket usage history information for the advertisement display location and obtaining estimated viewer number information; an evaluation step of determining an evaluation of the advertising effect according to the number of viewers in the estimated viewer number information using the estimated viewer number information; and fruit, The estimation step involves dividing the number of people aggregated from the ticket usage history information into platforms and passages where usage is estimated, determining the direction of movement in a passage when moving from a specific platform to a specific ticket gate or from a specific ticket gate to a specific platform using a specific passage, and estimating the number of people who see the advertisement based on the relationship between the direction of movement information and the orientation of the advertisement surface. characterized by this.

[0017] The invention according to claim 10 is an advertisement display location evaluation program, causing a computer to function as an estimation means for estimating the number of viewers who see the advertisement display location based on the ticket usage history information for the advertisement display location and obtaining estimated viewer number information, and an evaluation means for determining an evaluation of the advertising effect according to the number of viewers in the estimated viewer number information using the estimated viewer number information; and 、 The estimation means divides the number of people aggregated from the ticket usage history information into platforms and passages where use is estimated, and uses the direction of movement in a passage when moving from a specific platform to a specific ticket gate or from a specific ticket gate to a specific platform using a specific passage as the direction of movement information in that passage, and estimates the number of people who see the advertisement display location based on the relationship between the direction of movement information and the orientation of the advertisement surface. characterized by this.

Advantages of the Invention

[0018] According to the present invention, it is possible to provide an advertisement display location evaluation device, an advertisement display location evaluation method, and an advertisement display location evaluation program capable of acquiring information related to the evaluation of the advertising effect of an advertisement display location.

Brief Description of the Drawings

[0019] [Figure 1] It is a block diagram showing the configuration of a station concourse pedestrian flow estimation system according to an embodiment. [Figure 2] It is a flowchart showing the flow of operations during the estimation of the pedestrian flow of a station concourse pedestrian flow estimation system according to an embodiment. [Figure 3]This is a flowchart showing the workflow when evaluating the advertising value of the station pedestrian flow estimation system according to the embodiment. [Figure 4] This figure shows an example of aggregated result information generated when estimating pedestrian flow in a train station according to the embodiment. [Figure 5] This figure shows an example of rounding processing performed when estimating pedestrian flow in a station premises pedestrian flow estimation system according to the embodiment, where (a) is the data before processing and (b) is the data after processing. [Figure 6] This figure shows an example of the division of passenger flow by platform used during the estimation of passenger flow within a station according to the embodiment, where (a) is the data before processing and (b) is the data after processing. [Figure 7] This figure shows an example of the division of traffic by usage route performed when estimating traffic flow in a station premises pedestrian flow estimation system according to the embodiment, where (a) is the data before processing and (b) is the data after processing. [Figure 8] This figure shows an example of aggregated information after adding movement direction, which is generated when estimating pedestrian flow in a station premises according to the embodiment. [Figure 9] This figure shows an example of a pedestrian flow information display screen generated during pedestrian flow estimation by the pedestrian flow estimation system within a station according to the embodiment. [Figure 10] This figure shows the pedestrian flow information display screen related to Modification 4. [Modes for carrying out the invention]

[0020] The following describes an embodiment of the present invention, a station pedestrian flow estimation system 100, based on Figures 1 to 10. However, the technical scope of the present invention is not limited to the illustrated examples.

[0021] [Explanation of the Structure] The station premises pedestrian flow estimation system 100 is a system for estimating pedestrian flow within a station and, based on the estimation results, evaluating the advertising value of advertising locations within the station. As shown in Figure 1, it is composed of a data analysis server 1, a ticket usage history information management server 2, and an operation terminal 3, and these devices are connected via a communication network N.

[0022] Furthermore, each of the above-mentioned servers does not necessarily need to be provided separately; a single device may perform the functions of all of these servers. Conversely, each of the above servers does not necessarily have to be implemented by a single device; multiple devices connected via a communication network N may be used to realize the functions of each server.

[0023] [1 Data Analysis Server] The data analysis server 1 is, for example, a computer owned by a company that manages and operates the station pedestrian flow estimation system 100. As described later, it estimates pedestrian flow within the station based on information obtained from the ticket usage history information management server 2, and evaluates the advertising value of each advertising location within the station. As shown in Figure 1, the data analysis server 1 is configured to include, for example, a control unit 11, a storage unit 12, and a communication unit 13.

[0024] [(1) Control Unit] The control unit 11 is the part that controls the operation of the data analysis server 1, and is configured with, for example, a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), etc., and comprehensively controls each part of the data analysis server 1 through cooperation between the program data stored in the storage unit 12 and the CPU.

[0025] [(2) Storage section] The memory unit 12 is the part that stores various information necessary for the operation of the data analysis server 1. For example, it is composed of an HDD (Hard Disk Drive), semiconductor memory, etc., and stores data necessary for the operation of the data analysis server 1, which will be described in the operation description below, in a readable and writable format by the control unit 11. Furthermore, the memory unit 12 stores a program that includes various commands to the control unit 11 for operating the data analysis server 1. The operation of the data analysis server 1, as described in the operation explanation below, will be performed according to the program stored in the memory unit 12. Furthermore, the memory unit 12 stores route-specific usage ratio information D3 and aisle-specific usage ratio information D4. The contents of this information will be described in the operation description below.

[0026] [(3) Communications Department] The communication unit 13 is the part used for communication between the data analysis server 1, the ticket usage history information management server 2, and the operation terminal 3. For example, it is a communication interface having a communication IC (Integrated Circuit) and a communication connector, and under the control of the control unit 11, it performs data communication via the communication network N using a predetermined communication protocol.

[0027] [2. Ticket Usage History Information Management Server] The ticket usage history information management server 2 is, for example, a computer owned by a company that manages and operates the station pedestrian flow estimation system 100. It acquires and stores ticket usage history information D1, which is information related to the history of ticket usage by station users, and then transmits it to the data analysis server 1.

[0028] As shown in Figure 1, the ticket usage history information management server 2 is configured similarly to the data analysis server 1, for example, by including a control unit 21, a storage unit 22, and a communication unit 23.

[0029] The configurations of the control unit 21 and the communication unit 23 are identical to those of the control unit 11 and the communication unit 13 in the data analysis server 1. The storage unit 22, like the storage unit 12 in the data analysis server 1, is composed of, for example, an HDD, semiconductor memory, etc., and stores the ticket usage history information D1.

[0030] Ticket usage history information D1 is information relating to the usage history of IC cards as tickets at the ticket gates of each railway station that can be used to estimate passenger flow by this system. The ticket usage history information D1 includes, for example, entry / exit information D1-1, which is information relating to whether the usage history corresponds to entry or exit; ticket gate used information D1-2, which is information relating to the ticket gate used (entered or exited); date of use information D1-3, which is information relating to the date of use; time of use information D1-4, which is information relating to the time of use (for example, in one-hour increments such as 9 o'clock hour, 10 o'clock hour, etc.); entry station information D1-5, which is information relating to the entry station; exit station information D1-6, which is information relating to the exit station; and attribute information D1-7, which is information relating to the attributes of the user related to the usage history.

[0031] Furthermore, attribute information D1-7 includes, for example, gender information D1-7-1, which is information relating to the user's gender, and age information D1-7-2, which is information relating to the user's age group (e.g., teens, twenties). Furthermore, the attributes that can be included in attribute information D1-7 are not limited to these two; other attributes may also be included. While it is preferable to include both gender information D1-7-1 and age information D1-7-2, it is also possible to include only either gender information D1-7-1 or age information D1-7-2, or to omit both and consist only of other attributes. Other types of information that can be included in attribute information D1-7, besides gender information D1-7-1 and age information D1-7-2, include, for example, payment information and authentication information. As for payment information, for example, by using the electronic money function or individual identification number included in the IC card used as a train ticket, information related to the time of payment, the amount paid, the store where the payment was made, and the mode of transportation used (bus, taxi, etc.) can be obtained and stored. Furthermore, as authentication information, it would be sufficient to acquire information related to the authentication history at building entrances, etc., and store information related to the location and time of authentication.

[0032] In the ticket usage history information management server 2, for example, user attribute information D2, which is information that links identification information such as an ID set for each IC card with information related to the user's attributes of the IC card (attribute information D1-7), is stored in the storage unit 22 in advance. Whenever an IC card is used as a ticket at a ticket gate installed at a station, the server receives and acquires entry / exit information D1-1, ticket gate information D1-2, date of use information D1-3, time of use information D1-4, entry station information D1-5, and exit station information D1-6 related to the usage history, along with the identification information of the IC card used, via the communication unit 23. By linking the acquired information with the attribute information D1-7 related to the user of the IC card, ticket usage history information D1 is generated and stored in the storage unit 22.

[0033] As a result, each time an IC card is used as a ticket at a ticket gate installed at a station, ticket usage history information D1 will be accumulated in the storage unit 22 of the ticket usage history information management server 2.

[0034] [3 Operating Terminal] Operating terminal 3 is an information device such as a PC (Personal Computer) used by companies and other organizations that use this system to estimate pedestrian flow within station premises. As described later, it is used for inputting preconditions for pedestrian flow estimation, such as the target station and target day, and for viewing information related to the estimation results. As shown in Figure 1, the operating terminal 3, like the data analysis server 1, for example, comprises a control unit 31, a storage unit 32, and a communication unit 33, and further comprises a display unit 34 and an operation unit 35.

[0035] The display unit 34 includes a display such as an LCD (Liquid Crystal Display) and displays an image on the display screen based on the display control signal output from the control unit 31.

[0036] The operation unit 35 includes, for example, a keyboard having character input keys, numeric input keys, and other keys associated with various functions, and receives operation input from the user of the operation terminal 3 and outputs an operation signal corresponding to the operation input to the control unit 31. The operation unit 35 may be, for example, a touch panel formed integrally with the display unit 34, and is not particularly limited as long as it can receive operation input from the user of the operation terminal 3.

[0037] [4 Communication Networks] The communication network N is, for example, the internet, a telephone network, a mobile phone network, a wireless LAN network, etc., and connects the various devices that make up the station pedestrian flow estimation system 100, as shown in Figure 1. The communication network N is not particularly limited as long as it is capable of connecting the devices that make up the station pedestrian flow estimation system 100 as described above, and of sending and receiving data between them.

[0038] [2. Explanation of Operation] Next, the operation of the station pedestrian flow estimation system 100 according to this embodiment will be described. The operation of the station pedestrian flow estimation system 100 consists of two main steps: estimating pedestrian flow (step S1) and evaluating advertising value (step S2).

[0039] [Step 1: Estimating pedestrian flow] First, we will explain the operation of this system when estimating pedestrian flow within the station based on the ticket usage history information D1, following the flowchart in Figure 2.

[0040] When using this system to estimate pedestrian flow within a station, first, the company or organization using the system inputs information related to the analysis conditions, including information about the target station and target date, using the operation unit 35 of the operation terminal 3. The input information is then transmitted from the communication unit 33 to the data analysis server 1 via the communication network N (step S1-1).

[0041] The data analysis server 1, which receives information transmitted from the operation terminal 3 via the communication unit 13, retrieves all of the ticket usage history information D1 stored in the storage unit 22 from the ticket usage history information management server 2 that matches the analysis conditions entered in the operation terminal 3 (step S1-2). Specifically, the data analysis server 1 transmits information regarding the target station and target date related to the analysis conditions entered in the operation terminal 3 to the ticket usage history information management server 2. The ticket usage history information management server 2 then extracts data matching the target station and target date from the ticket usage history information D1 stored in the storage unit 22 and transmits it to the data analysis server 1.

[0042] In the data analysis server 1, which has acquired ticket usage history information D1 from the ticket usage history information management server 2, the control unit 11 removes personal information from the acquired ticket usage history information D1 (step S1-3). In other words, if the ticket usage history information D1 includes, as attribute information D1-7, information that can identify the user, such as the user's name and address, in addition to gender information D1-7-1 and age information D1-7-2, then that information will be excluded from the ticket usage history information D1.

[0043] After removing personal information from the ticket usage history information D1, the control unit 11 of the data analysis server 1 then aggregates the ticket usage history information D1 (step S1-4).

[0044] Specifically, the control unit 11 counts the number of entries in the ticket usage history information D1 where all of the following are common: entry / exit information D1-1, ticket gate used information D1-2, date of use information D1-3, time of use information D1-4, entry station information D1-5, exit station information D1-6, and attribute information D1-7. Furthermore, the information relating to the aggregated results will be designated as Aggregated Results Information D1A, and the information relating to the number of people included in Aggregated Results Information D1A will be designated as Aggregated Number Information D1-8A.

[0045] An example of aggregated result information D1A is shown in Figure 4. In Figure 4, in order to estimate the flow of people within the station premises of XX Station on October 6, 2021, an example of aggregated results is illustrated in step S1-2, when information regarding the usage history of IC cards as train tickets on October 6, 2021, is obtained at each ticket gate installed at XX Station.

[0046] Next, the control unit 11 of the data analysis server 1 performs a process on the aggregated result information D1A to make the number of people aggregated equal to or greater than a predetermined number (hereinafter referred to as "rounding process") (step S1-5). In other words, if the aggregated result information D1A includes aggregated results in which the number of people related to the aggregated number information D1-8A is less than a predetermined number (for example, 10 people), the control unit 11 combines multiple such aggregated results to obtain data in which the minimum number of people is equal to or greater than the predetermined number. The information after such processing is designated as the rounded aggregated result information D1B, and the information related to the rounded aggregated number included in the rounded aggregated result information D1B is designated as the rounded aggregated number information D1-8B.

[0047] If the aggregated result information D1A does not contain any aggregated results where the number of people related to the aggregated number information D1-8A is less than the specified number, this processing will not be performed, and the aggregated number information D1-8A will simply be rounded down to become the aggregated number information D1-8B.

[0048] For example, the control unit 11 can consolidate aggregated results where, for entry / exit information D1-1 is an exit, only the entry station information D1-5 is different and all other information is the same, and consolidate aggregated results where, for entry / exit information D1-1 is an entry, only the exit station information D1-6 is different and all other information is the same.

[0049] An example of rounding is shown in Figure 5. In this case, as shown in Figure 5(a), there are three aggregate results in which the number of people who are common to all stations except for departure station information D1-6 is less than 10. Therefore, these three aggregate results are combined, and the number is set to 10 or more (12 people), as shown in Figure 5(b). Furthermore, since there are three aggregate results where the number of people common to all entry station information other than D1-5 is less than 10, these three aggregate results are combined, and the number is set to 10 or more (11 people), as shown in Figure 5(b).

[0050] When combining multiple stations into one in this way, it is best to group stations located within a specific area, such as a particular city or town.

[0051] Furthermore, while it is preferable to group together information other than the entry station information D1-5 or exit station information D1-6 as described above, this method of rounding is not limited to this. If the minimum number of people in the aggregated results can be set to or above a predetermined number, information other than the other information can be grouped together. For example, although it is not preferable because it makes analysis by user attribute difficult, it is also possible to group together information other than the gender information D1-7-1 or age information D1-7-2 included in the attribute information D1-7.

[0052] Next, the control unit 11 divides the total number of users related to the rounded aggregated result information D1B into groups based on the platform on which it is estimated that the user used the service (step S1-6).

[0053] In other words, if multiple lines run between a railway station targeted for passenger flow estimation by this system and another specific railway station, the platform a user uses at the railway station targeted for passenger flow estimation will be determined by which of the lines the user uses in that section.

[0054] Therefore, the data analysis server 1's storage unit 12 is pre-stored with route-specific usage ratio information D3, which is information relating to the usage ratio of each route in a section where multiple routes run parallel, and this information can be used for segmentation. Furthermore, the information after the split will be designated as the aggregated results information D1C for the aggregated number of users after the split, and the information related to the aggregated number of users after the split, which is included in the aggregated results information D1C for the aggregated number of users after the split, will be designated as the aggregated number of users information D1-8C for the aggregated number of users after the split.

[0055] The route-specific usage ratio information D3 is information that defines the proportion of users for each route over the entire section where multiple routes connect specific stations. This information can be compiled by aggregating past usage data for each route and then stored in the memory unit 12.

[0056] Figure 6 shows an example of a division by platform. In this case, for example, as shown in Figure 6(a), if the rounded aggregated result information D1B is as follows: entry / exit information D1-1 is exit, ticket gate used information D1-2 is central ticket gate, date of use information D1-3 is October 6, 2021, time of use information D1-4 is in the 9 o'clock hour, entry station information D1-5 is XX station, exit station information D1-6 is OO station, gender information D1-7-1 is male, and age information D1-7-2 is 20s, and the number of people is 60, then there are two routes connecting XX station and OO station, route α and route β. Assuming that the arrival platform for line α at XX station is platform 1, the arrival platform for line β at XX station is platform 2, and the line usage ratio related to the line usage ratio information D3 for train travel from XX station to XX station is line α:line β = 1:2, then, as shown in Figure 6(b), the number of users of the above 60 will be divided in a 1:2 ratio, and the usage platform information D1-9 will be added to generate the usage platform division summary result information D1C.

[0057] Next, the control unit 11 divides the aggregated information D1C after platform division into sections for each passage that is estimated to have been used (step S1-7). In this case, the term "passage" is not limited to places specifically named as "passages," but broadly includes any place within the station premises that railway station users can pass through, such as plazas and shops.

[0058] Specifically, the data analysis server 1's storage unit 12 is pre-stored with information D4, which is information relating to the usage ratio of each passage, in cases where there are multiple passages that can be used to move between a specific platform and a specific ticket gate at a railway station targeted for pedestrian flow estimation by this system. This information can then be used for segmentation. Furthermore, the information after the division will be designated as the aggregated results information D1D for the divided access routes, and the information related to the number of users after the division included in the aggregated results information D1D for the divided access routes will be designated as the aggregated number of users after the divided access routes information D1-8D.

[0059] The D4 information on the proportion of users per passage is information that defines the proportion of users per passage when moving from a specific platform to a specific ticket gate, or from a specific ticket gate to a specific platform, when there are multiple passages between a specific platform and a specific ticket gate within the station premises of a railway station targeted by this system for pedestrian flow estimation. The usage ratio information D4 for each aisle can be created, for example, by acquiring and aggregating information on past usage records for each aisle using cameras, sensors, etc., installed in each aisle, and then storing it in the storage unit 12.

[0060] Furthermore, while it is preferable that the usage ratio information D4 for each aisle is based on actual usage data as described above, it is not limited to this, and for example, the percentage of users may be determined by simply allocating based on the number of aisles. Furthermore, the usage ratio for each passageway may be determined according to the characteristics of that passageway. In this case, for example, a passageway with an escalator could be given a higher usage ratio compared to a passageway with only stairs.

[0061] An example of division by aisle is shown in Figure 7. In this case, for example, as shown in Figure 7(a), the aggregated results information D1C after platform division is as follows: entry / exit information D1-1 is exit, ticket gate information D1-2 is central ticket gate, date of use information D1-3 is October 6, 2021, time of use information D1-4 is 9 o'clock, entry station information D1-5 is XX station, exit station information D1-6 is OO station, gender information D1-7-1 is male, age information D1-7-2 is 20s, and the platform used is Platform information D1-9 indicates that there were 20 people on platform 1, entry / exit information D1-1 indicates exit, ticket gate used information D1-2 indicates the central ticket gate, date of use information D1-3 indicates October 6, 2021, time of use information D1-4 indicates the 9 o'clock hour, entry station information D1-5 indicates XX station, exit station information D1-6 indicates OO station, gender information D1-7-1 indicates male, age information D1-7-2 indicates 20s, platform used information D1-9 indicates platform 2 If the information includes that the number of people is 40, and there are two passages, passage a and passage b, leading from platform 1 to the central ticket gate, and the usage ratio of the passages when moving from platform 1 to the central ticket gate according to the usage ratio information D4 is passage a:passage b=1:1, and there are three passages, passage c, passage d and passage e, leading from platform 2 to the central ticket gate, and the usage ratio of the passages when moving from platform 2 to the central ticket gate according to the usage ratio information D4 is passage c:passage d:passage e=1:1:2, then as shown in Figure 7(b), the number of 20 users moving from platform 1 to the central ticket gate is divided in a 1:1 ratio, and the number of 40 users moving from platform 2 to the central ticket gate is divided in a 1:1:2 ratio, and the usage passage information D1-10 is added, thereby generating the usage passage division summary result information D1D.

[0062] Next, the control unit 11 identifies the direction of movement in the passage based on the aggregated information D1D after the passage division (step S1-8).

[0063] In other words, since the direction of movement in a passage is constant when moving from a specific platform to a specific ticket gate using a specific passage, or when moving from a specific ticket gate to a specific platform using a specific passage, the passage usage ratio information D4 should include information on the direction of movement in the passage for each pattern of moving from a specific platform to a specific ticket gate using a specific passage, or from a specific ticket gate to a specific platform using a specific passage. Using this information, the direction of movement information D1-11, which is information on the direction of movement, should be added to each aggregate result included in the aggregate result information D1D after the passage division of usage. Furthermore, the information after adding the movement direction information D1-11 will be referred to as the aggregated result information D1E after adding the movement direction.

[0064] An example of the aggregated result information D1E after adding the direction of movement is shown in Figure 8.

[0065] By following the steps S1-1 to S1-8 described above, the number of users entering or exiting the station through the ticket gates, which is aggregated from the ticket usage history information D1, can be divided by the platform and passage used.

[0066] Once steps S1-8 are completed, the control unit 11 in the data analysis server 1 creates a human flow information provision screen G1, which is a screen for providing information related to the estimation results of human flow to companies and other users of this system, based on the aggregated result information D1E after the direction of movement has been added (step S1-9).

[0067] The passenger flow information screen G1 can be transmitted, for example, from the communication unit 13 to the operation terminal 3 via the communication network N, allowing companies and other entities using this system to verify the information, and enabling them to provide it to businesses such as shops within the station premises and advertising companies that display advertisements within the station premises.

[0068] The passenger flow information screen G1 includes, for example, a passenger count display G11 that shows the number of users for each passage and each usage time, a passenger count display G12 that shows the total number of users for a day by gender and age group, and a passenger count display G13 that shows the number of users for each departure point (ticket gate or platform) and arrival point (ticket gate or platform) within the station premises for a day.

[0069] In this case, the user count display G11 for each aisle should, for example, display bar graphs related to the two directions of movement within each aisle, overlaid on each aisle, for each time period, as shown in Figure 9.

[0070] Furthermore, the user count display G12 by attribute can be configured as shown in Figure 9, by creating pie charts separated by gender and displaying the proportion for each age group using the pie charts.

[0071] Furthermore, the user count display G13 for each OD (Origin / Destination) can be a bar graph showing the number of users traveling between the starting point (ticket gate or platform) and the destination (ticket gate or platform) in a single day, broken down by gender, as shown in Figure 9.

[0072] [Step 2 S2: Evaluating the value of advertising] Next, based on the estimation results of pedestrian flow within the station in step S1, the operation of this system in evaluating the advertising value of advertising locations set up at various points within the station will be explained according to the flowchart in Figure 3.

[0073] Furthermore, the advertising display locations in this invention are not limited to locations solely for advertising purposes, but rather to locations where any kind of promotional display is made. For example, the side of a store space within a train station facing the passageway also qualifies as an "advertising display location" because it is used for promotional purposes, such as a sign displaying the store name. Such advertising display locations are positioned to face a direction perpendicular to the direction of pedestrian movement in the passageway. In retail spaces, the advertising value of the side facing the aisle is directly linked to the value of the retail space itself. Therefore, by viewing the aisle-facing side of a retail space as an advertising display area and evaluating its advertising value, it is possible to assess the value of the retail space itself within the station.

[0074] When the aggregated information D1E after adding the direction of movement is generated in step S1-8, the control unit 11 estimates, based on the aggregated information D1E after adding the direction of movement, the number of people who see the advertisements displayed at each of the advertising locations installed in each passageway within the station, for each time period (step S2-1).

[0075] Specifically, as described above, the aggregated information D1E after adding the direction of movement includes information on the number of users moving between each ticket gate and each platform during each time period, divided by the passage used, and also includes information on the direction of movement of those users. Therefore, the control unit 11 aggregates the number of users for each passage during each time period and for each direction of movement based on the aggregated information D1E after adding the direction of movement.

[0076] First, if the advertising display location is positioned so that it faces parallel to the direction of people moving in the passageway where it is installed (along one of the directions of movement and opposite one of the directions of movement), the number of users moving in the opposite direction to the direction the advertising display location faces during each time period is estimated to be the number of people who see the advertising display location during that time period.

[0077] For example, if, for a passageway A extending in the north-south direction, the total number of users heading north in the 9 AM hour is 1,000, and the total number of users heading south in the 9 PM hour is 2,000, then it can be estimated that 1,000 people will see the south-facing advertising space in passageway A during the 9 AM hour, and 2,000 people will see the north-facing advertising space in passageway A during the 9 PM hour.

[0078] Furthermore, if the advertising display location is positioned to face a direction perpendicular to the direction of pedestrian movement in the passageway where it is installed, the total number of users moving in both directions perpendicular to the direction the advertising display location faces during each time period will be estimated as the number of people who see the advertising display location during that time period.

[0079] For example, if, for a north-south oriented passageway a, the total number of users heading north in the 9 AM hour is 1,000, and the total number of users heading south in the 9 PM hour is 2,000, then it can be estimated that 3,000 people will see the east-facing or west-facing advertisements located in passageway a during the 9 PM hour.

[0080] Next, the control unit 11 divides the estimated number of people who view each advertisement display location for each time period, which was aggregated in step S2-1, according to the attributes of the users, based on the attribute information D1-7 included in the aggregated result information D1E after adding the direction of movement (step S2-2).

[0081] Specifically, as described above, if the number of people who see the advertisement at the south-facing advertising display in the north-south-oriented passageway a is totaled 1,000 during the 9 o'clock hour, and attribute information D1-7 includes gender information D1-7-1 and age information D1-7-2, then the totaled 1,000 people will be divided by gender and age.

[0082] For example, the 1,000 people who see the advertisement at the south-facing advertising space in a north-south oriented passageway a during the 9 o'clock hour would be divided as follows: 80 teens (male), 80 teens (female), 100 men in their 20s, 80 women in their 20s, 100 men in their 30s, 80 women in their 30s, 80 men in their 40s, 70 women in their 40s, 70 men in their 50s, 60 women in their 50s, 50 men in their 60s, 40 women in their 60s, 30 men in their 70s, 30 women in their 70s, 30 men in their 80s, and 20 women in their 80s.

[0083] Next, the control unit 11 determines an evaluation for each advertising location, based on predetermined criteria, for each time period and attribute, using the number of people who see each advertising location, which was divided according to user attributes in step S2-2.

[0084] The criteria for determining the evaluation in this case should be based on the number of people who see the advertisements posted at each location, categorized by time of day and demographic, and the evaluation of each posting location should be based on the number of people. Furthermore, the evaluation method could be, for example, calculating a score based on the number of people, or dividing participants into multiple ranks based on the number of people (for example, ranks A through F in descending order of the number of people).

[0085] For example, one possible evaluation method for a specific advertisement display location could be to assign ranks based on the number of people who view it per hour: 100 or more per hour is rank A, 80 to less than 100 is rank B, 60 to less than 80 is rank C, 40 to less than 60 is rank D, 20 to less than 40 is rank E, and 0 to less than 20 is rank F. In this case, if the division is made as illustrated in step S2-2, the evaluation of the south-facing advertising display area in the north-south-extending passage a during the 9 o'clock hour will be determined as follows: rank B for teenage boys, rank B for teenage girls, rank A for boys in their 20s, rank B for girls in their 20s, rank A for boys in their 30s, rank B for girls in their 30s, rank B for boys in their 40s, rank C for girls in their 40s, rank C for boys in their 50s, rank C for girls in their 50s, rank D for boys in their 60s, rank D for girls in their 60s, rank E for boys in their 70s, rank E for girls in their 70s, rank E for boys in their 80s, and rank E for girls in their 80s.

[0086] Once steps S2-3 are completed, the control unit 11 in the data analysis server 1 creates an advertising value evaluation information provision screen, which is a screen for providing information related to the evaluation of each advertisement placement location determined in step S2-3 to companies and others using this system (step S2-4).

[0087] The advertising value evaluation information screen could, for example, display information related to the number of people who see each advertising location within the station, divided by time period and user attributes as generated in step S2-2, and information related to the evaluation (rank, score, etc.) of each advertising location, determined in step S2-3, for each time period and user attributes. The advertising value information screen can also be transmitted, for example, from the communication unit 13 to the operation terminal 3 via the communication network N, allowing companies using this system to verify the information, and enabling them to provide it to advertising businesses that display advertisements within the station premises.

[0088] [Explanation of the third effect] Next, the effects of the station pedestrian flow estimation system 100 according to this embodiment will be described.

[0089] According to the station premises pedestrian flow estimation system 100 of this embodiment, in step S1-4, the data analysis server 1 aggregates the number of users of the station to be targeted for pedestrian flow estimation based on the ticket usage history information D1. This is done by aggregating the number of common pieces of information in the ticket usage history information D1, including the ticket gate used information D1-2, so that the data is divided at least by the ticket gate used. Furthermore, in step S1-6, the number of people related to the aggregated result is divided by the platform that is estimated to have been used. This allows us to understand the number of users moving between each platform and each ticket gate, thereby improving the accuracy of estimating pedestrian flow between ticket gates and platforms within the station.

[0090] Furthermore, in step S1-4, the number of entries and exits D1-1, that is, information relating to whether the ticket gate usage history corresponds to entry or exit, is aggregated, and by dividing the number of users into those entering (moving from the ticket gate to the platform) and those exiting (moving from the platform to the ticket gate), it becomes possible to estimate the number of people in each direction of movement.

[0091] Furthermore, the data analysis server 1 stores route usage ratio information D3, which is information that pre-determines the proportion of users for each route in sections where multiple routes exist. By using this information to divide the number of users by platform, it is possible to easily divide the number of users by platform based on the predetermined usage ratio for each platform.

[0092] Furthermore, by dividing the number of users estimated to have been used by each platform in step S1-6 into those estimated to have been used by each passageway in step S1-7, it becomes possible to determine the number of users who moved between each platform and each ticket gate, and further to determine the number of users who moved between each passageway, thereby further improving the accuracy of estimating the flow of people between ticket gates and platforms within the station.

[0093] Furthermore, the data analysis server 1 stores pre-defined information D4, which is the proportion of users for each passage in locations where multiple passages exist between the ticket gate and the platform. By using this information to divide the number of users into passages that are estimated to have been used, the number of users can be easily divided into passages based on the predetermined proportion of usage for each passage.

[0094] Furthermore, in step S1-8, by identifying the direction of movement within each passage for the number of users estimated to have used it in step S1-7, it becomes possible to determine the proportion of users in each direction of movement within the passage.

[0095] Furthermore, in the rounding process of steps S1-5, the aggregated results from step S1-4 are combined so that the total number does not fall below a predetermined number. This ensures that the aggregation of the number of users at the stations targeted for pedestrian flow estimation is performed in a way that ensures each aggregated result does not fall below a predetermined number. This prevents the risk of individuals being identified due to the aggregated number being too small.

[0096] Furthermore, in step S1-4, by aggregating the number of users who share the same attribute information D1-7, i.e., gender, age group, etc., it becomes possible to aggregate the number of users by attribute. This makes it possible to understand not only the number of users but also the proportion of each attribute in the flow of people within the station.

[0097] Furthermore, regarding advertising locations, the effectiveness of the advertisement depends on the number of people who see it when it is displayed. By using an estimated number of people who will see each advertising location and determining the evaluation according to predetermined criteria, it becomes possible to obtain information related to the evaluation of the advertising effectiveness of each advertising location based on pedestrian traffic, in addition to simply estimating the flow of people within the station.

[0098] Furthermore, because the estimated number of viewers who will see each advertisement location is calculated for each time period, it is possible to determine an evaluation for each advertisement location on a time-by-time basis. This makes it possible, for example, to change the advertisements displayed according to the evaluation for each time period.

[0099] Furthermore, because the estimated number of viewers who will see each advertisement is calculated based on user attributes, it is possible to determine the effectiveness of each advertisement location for each target audience attribute. This makes it possible, for example, to display advertisements that are suitable for the target audience attributes at each advertisement location.

[0100] Furthermore, if the location of the advertisement is positioned to face the opposite direction of people's movement in the passageway, the number of people moving in the opposite direction of the advertisement can be estimated as the number of people who see the advertisement, thereby easily estimating the number of people who see the advertisement positioned to face the opposite direction of people's movement in the passageway.

[0101] Furthermore, if the advertising display location is positioned to face a direction perpendicular to the direction of people's movement in the passageway, the number of people who see the advertising display location can be estimated by estimating the number of users moving in the passageway in a direction perpendicular to the direction the advertising display location faces as the number of people who see the advertising display location. This makes it easy to estimate the number of people who see the advertising display location positioned to face a direction perpendicular to the direction of people's movement in the passageway.

[0102] [4. Variation] Next, a modified example of the station pedestrian flow estimation system 100 according to this embodiment will be described.

[0103] [1. Variation 1: Change in the rounding method] In the above explanation of the operation, we described a case in step S1-5 where, in the rounding process, if the aggregated result information D1A includes aggregated results in which the number of people related to the aggregated number information D1-8A is less than a predetermined number (for example, 10 people), multiple such aggregated results are combined to make the data such that the minimum number of people is equal to or greater than the predetermined number. However, the method of rounding is not limited to this.

[0104] For example, if the aggregated results include a number of people related to aggregated number information D1-8A that is less than a predetermined number, the number of people related to that aggregated result can be fixed to a predetermined value, and the rounding process can be performed without summing up multiple aggregated results. For example, if the aggregated results include a number of people less than 10 related to aggregated number information D1-8A, it is possible to fix the number of people related to that aggregated result to either 0 or 10, thereby preventing aggregated results with a number of people less than 10 related to aggregated number information D1-8A from occurring.

[0105] Furthermore, the timing of the rounding process is not limited to immediately after obtaining the aggregated result information D1A in step S1-4. For example, after obtaining the aggregated result information D1E with added movement direction in step S1-8, it is also possible to perform rounding. In this case, by performing rounding only on groups where the final aggregated result after division is less than a predetermined number (for example, less than 10 people) to make the number of people equal to or greater than the predetermined number, the risk of individuals being identified is reduced. At the same time, for groups where rounding is unnecessary (the final aggregated result after division is equal to or greater than the predetermined number), rounding is not performed, and information regarding the estimation results of passenger flow can be provided based on accurate data close to the original ticket usage history information D1.

[0106] [2. Variation 2; Change in the method for estimating the number of ad viewers] In step S2-1 of the above explanation of the operation, we described a case where the advertisement is placed so that it faces a direction perpendicular to the direction of movement of people in the passageway in which it is installed, and estimated the total number of users moving in both directions perpendicular to the direction the advertisement is facing during each time period as the number of people who see the advertisement during that time period. However, it is conceivable that the proportion of users who see the advertisement among those moving in a direction perpendicular to the direction the advertisement is facing may be less than the proportion of users who see the advertisement among those moving in a direction opposite to the direction the advertisement is facing.

[0107] Therefore, if the advertising display location is positioned to face a direction perpendicular to the direction of movement of people in the passageway in which it is installed, the number of people who see the advertising display location during that time period may be estimated by multiplying the total number of users moving in both directions perpendicular to the direction the advertising display location faces by a predetermined weighting coefficient.

[0108] In this case, for example, if, for a passageway a extending in the north-south direction, the total number of users heading north in the 9 AM hour is 1,000, and the total number of users heading south in the 9 PM hour is 2,000, then the total of 3,000 people would be multiplied by a predetermined weighting coefficient of 50% (0.5), resulting in an estimated 1,500 people who would see the east-facing or west-facing advertisements displayed in passageway a during the 9 AM hour.

[0109] [3. Modification 3: Changing the target of acquisition of ticket usage history information] In the above explanation of the configuration, we described the case where the ticket usage history information D1 is information relating to the usage history of an IC card as a ticket. However, the ticket usage history information D1 is information relating to the usage history of tickets at the ticket gates of each railway station that can be targeted for pedestrian flow estimation by this system, and it does not necessarily have to be limited to the usage history of an IC card, as long as it includes entry / exit information D1-1, ticket gate used information D1-2, date of use information D1-3, time of use information D1-4, entry station information D1-5, exit station information D1-6, and attribute information D1-7. For example, when a smartphone or wearable device equipped with an IC chip and payment functionality is used as a ticket, information related to its usage history may be stored.

[0110] [4 Modification 4: Changes to the pedestrian flow information display screen] In the above description of the operation, we explained the case where the human flow information provision screen G1 shown in Figure 9 is used as the screen for providing information related to the human flow estimation results to companies and other entities using this system in step S1-9. However, this is not the only screen that can be used to provide information related to the human flow estimation results.

[0111] For example, as shown in Figure 10, the direction of pedestrian flow may be represented by the direction of the arrows displayed on the station layout map, and the amount of pedestrian flow may be represented by the color of the arrows.

[0112] In Figure 10, the station layout diagram G14 displays the first pedestrian flow indicator arrow G141 and the second pedestrian flow indicator arrow G142, which represent the direction of pedestrian flow by the direction of the arrow and the amount of pedestrian flow by the color of the arrow. The first pedestrian flow indicator arrow G141 and the second pedestrian flow indicator arrow G142 are displayed at the same location on the station layout map, facing opposite directions. The color of the arrow indicates the amount of pedestrian flow in the direction the arrow points at that location within the station.

[0113] In the diagram, the arrows only represent light and dark, but it is preferable to represent the amount of pedestrian traffic by hue, for example, by having the arrows, which are displayed in green when pedestrian traffic is low, gradually change to red as pedestrian traffic increases. Furthermore, although undesirable because it is more difficult to perceive than changes in hue, it is also possible to represent the volume of pedestrian traffic by using differences in brightness and saturation.

[0114] Furthermore, the pedestrian flow information provision screen G1A also has input fields G15 for the date of use and G16 for the time of use, and is configured to display information corresponding to the entered date of use and time of use. In other words, the colors of the first pedestrian flow display arrow G141 and the second pedestrian flow display arrow G142 change according to the entered date of use and time of use.

[0115] Furthermore, the passenger flow information screen G1A includes a passenger count display per passage G11A that displays the number of users for each passage, a passenger count display by attribute G12A that displays the number of users by gender and age group, and a passenger count display by OD (destination / destination) G13A that displays the number of users for each departure point (ticket gate or platform) and arrival point (ticket gate or platform) within the station premises.

[0116] The G11A, which displays the number of users per aisle, shows the number of users for each aisle at the date and time entered in the G15 and G16 input fields, using a bar graph with different colors to indicate the direction.

[0117] Furthermore, the user count display by attribute G12A, as shown in Figure 10, displays the total number of users at the date and time entered in the usage date input field G15 and the usage time input field G16, separated by gender and age group, in a single pie chart.

[0118] Furthermore, the user count display G13A for each OD (Origin / Destination) location, as shown in Figure 10, displays the number of users at the date and time entered in the usage date input field G15 and the usage time input field G16, which represent movement between the originating ticket gate or platform and the destination ticket gate or platform, using a bar graph with different colors to indicate attributes.

[0119] Furthermore, the pedestrian flow information display screen G1A displays the legend display G17, as shown in Figure 10. The legend display G17 is the section where the colors that represent the legend are displayed for the pedestrian flow indicated by the colors of the first pedestrian flow display arrow G141 and the second pedestrian flow display arrow G142, the direction indicated by the colors of the bar graphs in the number of users per passage display G11A, the attributes indicated by the colors of the pie charts in the number of users per attribute display G12A, and the attributes indicated by the colors of the bar graphs in the number of users per OD display G13A.

[0120] In Figure 10, the case where a pedestrian flow indicator arrow is displayed for only one location within the station premises is illustrated. However, a diagram showing a wide area within the station premises may be used, and pedestrian flow indicator arrows may be displayed for multiple locations simultaneously. Furthermore, by specifying a particular point from such a wide-area display, it may be possible to switch to a display that zooms in on that specific point, as shown in Figure 10. [Explanation of symbols]

[0121] 100 Station Pedestrian Flow Estimation System 1. Data analysis server (advertising placement evaluation device) 11 Control unit (evaluation means, estimation means) 12 Storage section 13 Communications Department 2. Ticket Usage History Information Management Server 21 Control Unit 22 Memory section 23 Communications Department 3. Operating terminal 31 Control Unit 32 Storage section 33 Communications Department 34 Display section 35 Control section D1 Ticket Usage History Information D1A Aggregation Results Information D1B Rounded-out summary results information D1C Platform Usage Analysis Results D1D Summary of results after partitioning of access routes D1E Summary of results after adding direction of movement information D2 User attribute information D3 Usage Ratio Information by Route D4 Information on usage rates for each aisle

Claims

1. Regarding the location where the advertisement is displayed, an estimation means estimates the number of people who will see the advertisement based on the ticket usage history information and obtains estimated viewer count information. An evaluation means that uses the estimated number of viewers information to determine the effectiveness of the advertising campaign according to the number of viewers in the estimated number of viewers information, Equipped with, The estimation means divides the number of people aggregated from the ticket usage history information into platforms and passages where use is estimated to have been performed, uses the direction of movement in the passage when moving from a specific platform to a specific ticket gate or from a specific ticket gate to a specific platform using a specific passage as the direction of movement information in the passage, and estimates the number of people who will see the advertisement display location based on the relationship between the direction of movement information and the orientation of the advertisement surface.

2. The aforementioned estimated number of viewers is information that estimates the number of viewers for each time period. The advertising location evaluation device according to claim 1, characterized in that the evaluation means determines an evaluation for each time period for the advertising location.

3. The aforementioned estimated number of viewers is information obtained by estimating the number of viewers for each attribute of the viewers. The advertising location evaluation device according to claim 1 or 2, characterized in that the evaluation means determines an evaluation for each target viewer attribute for the advertising location.

4. The aforementioned advertising display locations are provided near the passageway, facing in a direction opposite to the direction of pedestrian movement in the passageway. The advertising location evaluation device according to claim 1, characterized in that the estimation means estimates the number of people moving in the opposite direction to the direction the advertising location faces as the number of viewers.

5. The aforementioned advertising display locations are provided near the passageway and are oriented perpendicular to the direction of pedestrian movement in the passageway. The advertising location evaluation device according to claim 1, characterized in that the estimation means estimates the number of people moving along the passage in a direction perpendicular to the direction the advertising location faces as the number of viewers.

6. The aforementioned advertising display locations are provided near the passageway and are oriented perpendicular to the direction of pedestrian movement in the passageway. The advertising display location evaluation device according to claim 1, characterized in that the estimation means estimates the number of viewers by multiplying the number of people moving along the passage in a direction perpendicular to the direction the advertising display location faces by a predetermined coefficient.

7. The advertising display location evaluation device according to any one of claims 1 to 6, characterized in that the evaluation means determines a score for each advertising display location based on an estimated number of viewers who see the advertising display location.

8. The advertising display location evaluation device according to any one of claims 1 to 7, characterized in that the evaluation means determines a rank for each advertising display location based on an estimated number of viewers who see the advertising display location.

9. An advertising placement location evaluation method in an advertising placement location evaluation device, Regarding the location where the advertisement is displayed, the estimation step involves estimating the number of people who will see the advertisement based on the ticket usage history information, and obtaining information on the estimated number of viewers. An evaluation step in which the advertising effect is evaluated according to the number of viewers in the estimated number of viewers information, using the estimated number of viewers information, Includes, The estimation step is characterized by dividing the number of people aggregated from the ticket usage history information into each platform and passage that is estimated to have been used, defining the direction of movement in the passage when moving from a specific platform to a specific ticket gate or from a specific ticket gate to a specific platform using a specific passage as the direction of movement information in the passage, and estimating the number of people who will see the advertisement display location based on the relationship between the direction of movement information and the orientation of the advertisement surface.

10. Computers, Estimation means for estimating the number of people who will see an advertisement at an advertisement location based on ticket usage history information, and obtaining estimated viewer count information. An evaluation means that uses the estimated number of viewers information to determine the effectiveness of the advertising campaign according to the number of viewers in the estimated number of viewers information. To make it function as, The estimation means divides the number of people aggregated from the ticket usage history information into platforms and passages where use is estimated to have been performed, uses the direction of movement in the passage when moving from a specific platform to a specific ticket gate or from a specific ticket gate to a specific platform using a specific passage as the direction of movement information in the passage, and estimates the number of people who will see the advertisement display location based on the relationship between the direction of movement information and the orientation of the advertisement surface.

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