JP2015011680A - Store management device, method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide store management device, method, and program capable of specifying a target to be turned attention properly in detection of a differential state in a store.SOLUTION: A store management device 10 comprises: a differential degree calculation part 11 for every area for calculating differential degree for every area by using information collected from every area of a store 20 to be managed; and a store differential degree calculation part 12 for calculating the differential degree of the whole store 20 to be managed based on the calculated differential degree for every area and a relation between areas which is preset.

Description

  The present invention relates to a store management device, a store management method, and a program for realizing these, for managing stores to be managed.

  For companies that have expanded the number of stores by franchise, etc., it is important to understand the status of each store in order to keep the quality of products and services at each store constant. It is difficult to grasp the situation of each store.

  Therefore, in order to reduce the load at the headquarters and enable efficient management, there is a need for a system that automatically extracts unique conditions at each store and reports the extraction results to the headquarters. (For example, refer to Patent Documents 1 to 5). In many cases, measures for improving services depend on the store managers of each store, and therefore, it is important to extract a unique state in order to share know-how between stores. Furthermore, the extraction of unique states is also important for examining problems in stores.

  Here, the specific example of the system which detects the peculiar state in a store is demonstrated. For example, Patent Document 1 detects a scene that matches a fraudulent event of a store customer, which is defined in advance, from a video obtained by photographing a retail scene. A system for notifying employees is disclosed.

  Patent Document 2 also discloses a system for detecting suspicious behavior in retail situations. In the system disclosed in Patent Document 2, by analyzing the video data above the cash register, the items scanned at the cash register are tracked, and the tracking result is compared with the actual POS data, so that the contents differ from the actual product. The situation entered at the cash register is identified as suspicious behavior.

A visual-based method and apparatus for detecting fraudulent events in a retail environment Method and apparatus for detecting suspicious behavior using video analysis JP 2008-226085 A JP 2008-234551 A JP 2010-238186 A

  By the way, in order to extract a unique state in the store and use the extracted abnormal state for the examination of problems and the extraction of know-how in store management, the target to be focused on at the time of extraction should be specified appropriately Is required. This is because if the management viewpoint is different, the object to be extracted changes, so that a single determination criterion cannot effectively extract a unique state in the store.

  In addition, the target should be identified by determining the characteristics of each employee, store customer, and service delivery content for each area, and considering the relationship between the determined characteristics. It is. This is because, for example, it is not possible to know what cause the extracted abnormal state has occurred simply by grasping how the employee side is moving. In addition, when it is determined that the behavior of the employee is in a peculiar state and the video is recorded, the target to be focused on is not necessarily the employee. That is, in this case, the behavior of the store customer that caused the employee's behavior may be a target to be noted.

  Furthermore, in the store form such as cafeteria, the inside of the store is divided into a plurality of areas with different service delivery contents. In such a store, the peculiar state in one area is in another area adjacent to it. The condition may be the cause. In addition, the peculiar state may be caused by the state of the area on the store customer side, or may be caused by the state of the area on the employee side.

  However, in the system disclosed in Patent Document 1 described above, it is only possible to detect a specific situation of store customers defined in advance, and the situation can be specified based on a plurality of different viewpoints, or the relationship between areas can be determined. It is impossible to specify the situation in consideration. For this reason, the system disclosed in Patent Document 1 has a problem that an object to be focused on cannot be appropriately specified. As a result, in the system disclosed in Patent Document 1, it is difficult to accurately grasp where the actual cause of the unique state is.

  In addition, in the system disclosed in Patent Document 2 described above, since a unique state is detected only with respect to employees as a target to be focused on, there is a problem that even in this system, the target to be focused on cannot be appropriately identified. is there. For this reason, the system disclosed in Patent Document 2 cannot accurately grasp the situation. For example, a store customer performs suspicious behavior such as changing the barcode outside the cash register area, which causes a cash register abnormality. It is impossible to specify when the person is awake.

[Object of the present invention]
An example of an object of the present invention is to provide a store management device, a store management method, and a program capable of solving the above-described problem and appropriately specifying a target to be focused on in detecting a unique state in a store. .

In order to achieve the above object, a store management apparatus according to one aspect of the present invention is provided.
An area-specific specificity calculating unit that calculates the specificity for each area using information collected from each area of the store to be managed;
A store specificity calculation unit that calculates the specificity of the entire store to be managed based on the calculated specificity for each area and the relationship between preset areas;
It is characterized by having.

In order to achieve the above object, a store management method according to one aspect of the present invention includes:
(A) calculating the specificity for each area using information collected from each area of the store to be managed; and
(B) calculating the specificity of the entire store to be managed based on the specificity for each area calculated in the step of (a) and the relationship between the preset areas;
It is characterized by having.

In order to achieve the above object, a program according to one aspect of the present invention is stored in a computer.
(A) calculating the specificity for each area using information collected from each area of the store to be managed; and
(B) calculating the specificity of the entire store to be managed based on the specificity for each area calculated in the step of (a) and the relationship between the preset areas;
Is executed.

  As described above, according to the present invention, it is possible to appropriately specify a target to be focused on in detecting a unique state in a store.

FIG. 1 is a block diagram showing a schematic configuration of a store management apparatus according to an embodiment of the present invention. FIG. 2 is a block diagram specifically showing the configuration of the store management apparatus according to the embodiment of the present invention. FIG. 3 is a flowchart showing the overall operation of the store management apparatus in the embodiment of the present invention. FIG. 4 is a flowchart specifically showing the calculation process of specificity shown in FIG. FIG. 5 is a block diagram illustrating an example of a computer that implements the store management apparatus according to the embodiment of the present invention. FIG. 6 is a layout diagram showing a specific layout of a store to be managed in the embodiment of the present invention. FIG. 7 is a diagram illustrating an example of areas set in the store illustrated in FIG. 6. FIG. 8 is a diagram illustrating an example of areas set in the store illustrated in FIG. 6. FIG. 9 is a diagram showing an example of the determination rule used in the embodiment of the present invention. FIG. 10 is a diagram showing an example of the degree of relationship between areas used in the embodiment of the present invention. FIG. 11 is a diagram illustrating an example of a calculation result of the specificity for each area and the specificity of the entire store in the embodiment of the present invention. FIG. 12 is a diagram illustrating an example of a calculation result displayed in the embodiment of the present invention.

(Embodiment)
Hereinafter, a store management device, a store management method, and a program according to an embodiment of the present invention will be described with reference to FIGS.

[Device configuration]
Initially, the structure of the store management apparatus in embodiment of this invention is demonstrated using FIG. FIG. 1 is a block diagram showing a schematic configuration of a store management apparatus according to an embodiment of the present invention.

  The store management apparatus 10 in this Embodiment shown in FIG. 1 is an apparatus for managing the shop 20 used as management object. In FIG. 1, the store 20 is represented by a plan view. As illustrated in FIG. 1, the store management apparatus 10 includes an area-specific specificity calculation unit 11 and a store specificity calculation unit 12.

  Of these, the area-specific specificity calculation unit 11 uses the information collected from each of the 20 areas A to H of the stores to be managed (hereinafter referred to as “store information”) to determine the specificity for each area. calculate. Then, the store specificity calculation unit 12 calculates the overall specificity of the store 20 to be managed based on the calculated specificity for each area and the relationship between the preset areas.

  Thus, in this Embodiment, in calculating the specificity of the whole store, the specificity in each area of the store 20 and the relationship between the areas are used. Therefore, for example, the specificity of the entire store is calculated such that the greater the difference in specificity between the employee-side area and the store-customer-side area that is highly related to the employee-side area, the larger the value. Let's say. In this case, the manager uses the uniqueness value of the entire store and the uniqueness of each area, so that the store customer normally receives service in an area, but the employee behaves abnormally in an adjacent area. Understand what is going on or vice versa. For this reason, the manager can specify the target to be focused on in the store 20 from the grasped situation in the detection of the unique state in the store 20.

  In FIG. 1, only one store 20 to be managed is illustrated, but in the present embodiment, the number of stores 20 is not particularly limited. Moreover, in FIG. 1, although the area of the store 20 is eight of AH, in this Embodiment, the number of areas of a store is not limited. Furthermore, information collection from each of the areas A to H is performed by the information collection device 30 arranged in each area in the present embodiment. A specific example of the information collection device 30 will be described later.

  Here, the configuration of the store management apparatus 10 in the present embodiment will be described more specifically with reference to FIG. FIG. 2 is a block diagram specifically showing the configuration of the store management apparatus according to the embodiment of the present invention.

  As shown in FIG. 2, in the present embodiment, the store management apparatus 10 further includes a storage unit 13 and a display unit 14. The store management device 10 is connected to an information collection device 30 disposed in the store 20 and acquires store information from the information collection device 30. In the present embodiment, the store information includes information related to human behavior in the area and information related to devices in the area.

  Specifically, examples of the information collection device 30 include a monitoring camera that photographs employees and store customers, an RFID reader that detects an RFID attached to a product, a register, and the like. In this case, the store information regarding the behavior of the person in the area includes video data obtained by photographing with the surveillance camera. The store information related to the devices in the area includes information including the time when the RFID tag is detected by the RFID reader and the identification information of the detected RFID tag, and information including the time when the input is performed in the register.

  In the present embodiment, the store information is not limited to the above-described example, and may be information that can be used for specifying a unique state of the store. The information collecting device 30 is not limited to the above-described example, and may be any device that can collect store information.

  In this embodiment, the area-specific specificity calculation unit 11 can use either or both of the above-described store information, that is, information related to human behavior in the area and information related to devices in the area. Further, the area-specific specificity calculation unit 11 applies the store information of each area to a preset rule (hereinafter referred to as a “determination rule”) for each area, thereby generating a unique state. Determine whether or not.

  The determination rule is a rule for determining whether or not a unique state has occurred in each area, and is stored in the storage unit 13 as shown in FIG. Judgment rules include the unique state in each area: “when the deviation from the steady state is a certain value or more”, “when the degree of coincidence with the predefined abnormal state is more than a certain value”, “ If the value satisfies the condition, etc.

  Specific examples of judgment rules include "employee being away from the area in charge beyond the threshold", "store customers staying at the same location for a certain period of time", "the equipment in the store is broken", etc. Is mentioned. In the present embodiment, the determination rule is appropriately set according to the type of the store 20, the layout of the store 20, the type of the information collection device 30, the layout of the information collection device 30, and the like, and is not particularly limited. .

  Further, the area-specific specificity calculation unit 11 calculates the specificity of the corresponding area for an area determined to have a unique state. Specifically, the area-specific specificity calculation unit 11 increases the value according to the degree of the specific state that occurs, for example, as the time that the employee is away from the assigned area beyond the threshold increases. The specificity of the corresponding area is calculated so as to increase.

  Further, in the present embodiment, the store specificity calculation unit 12 uses the degree of relationship between each area preset for each area and another area as the relation between the preset areas. And the store specificity calculation part 12 calculates the specificity of the whole store so that a value may become so large that the difference of specificity is large between areas with high degree of association.

  The degree of relationship between the areas is stored in the storage unit 13 as shown in FIG. The degree of relationship between areas is set such that, for area A, the degree of relation with area B is 60%, the degree of relation with area C is 10%, and the degree of relation with area D is 0%. . The setting is performed by the administrator 50 in consideration of the relevance to the business in the area A, the distance to the area A, and the like in each area.

  In the present embodiment, the relationship between the areas may be set between groups by grouping a plurality of areas in the store. For example, the areas A to H may be divided into a group of areas used by store customers and a group of areas used by employees, and the degree of relationship between the groups may be set. In this case, the store specificity calculation unit 12 can calculate the specificity of the entire store by using both the above-described relationship between areas and the relationship between groups.

  In the above example, the relationship between the areas is represented by numerical values, but the present embodiment is not limited to this. In the present embodiment, the relationship between the areas may be expressed using a polynomial, a conditional expression, or the like.

  In addition, in this embodiment, the area-specific specificity calculation unit 11 and the store specificity calculation unit 12 may calculate the above-described specificity for each time when the store information is collected, or for each set time The above-described specificity may be calculated.

  The display unit 14 displays image data for displaying the specificity for each area calculated by the area-specific specificity calculation unit 1 and the specificity of the entire store calculated by the store specificity calculation unit 12 on the screen. Generate. At this time, the display unit 14 displays the image so that the specificity for each area and the specificity of the entire store are displayed on the screen every time the store information is collected or every set time. Data can also be generated. The generated image data is output to a display device 40 such as a liquid crystal display device. Thereby, the administrator 50 can confirm each specificity on a screen.

[Device operation]
Next, operation | movement of the shop management apparatus 10 in embodiment of this invention is demonstrated using FIG.3 and FIG.4. In the following description, FIGS. 1 and 2 are referred to as appropriate. Furthermore, in the present embodiment, the store management method is implemented by operating the store management apparatus 10. Therefore, the description of the store management method in the present embodiment is replaced with the following description of the operation of the store management device 10.

  First, the whole operation | movement of the shop management apparatus 10 is demonstrated using FIG. FIG. 3 is a flowchart showing the overall operation of the store management apparatus in the embodiment of the present invention.

  As shown in FIG. 3, first, in the store management device 10, the area-specific specificity calculation unit 11 acquires store information of each area collected from the information week device 30 (step S <b> 1).

  Next, the area-specific specificity calculation unit 11 applies the store information acquired in step S1 to the determination rule stored in the storage unit 13 to determine whether or not a specific state has occurred in each area. (Step S2). For example, if the employee is away from the area in charge by exceeding the threshold, the area-specific specificity calculation unit 11 determines that a unique state has occurred in the corresponding area.

  If the result of determination in step S2 is that a unique state has occurred, the calculation of specificity for each area by the area-specific specificity calculation unit 11 and the calculation of the specificity of the entire store by the store specificity calculation unit 1 Is executed (step S3). A specific example of step S3 will be described later with reference to FIG.

  Next, when step S3 is completed, the display unit 14 generates image data and outputs it to the display device 40 in order to display the specificity for each area and the specificity for the entire store for each time (step S40). S4). Thereby, the specificity for each area and the specificity for the entire store are presented to the manager 50.

  Next, after execution of step S4, the store management apparatus 10 determines whether or not the manager 50 instructs the end of management (step S5). As a result of the determination in step S <b> 5, when the manager 50 instructs the end of management, the store management apparatus 10 ends the process. On the other hand, if the result of determination in step S5 is that the administrator 50 has not instructed termination of management, the store management apparatus 10 causes the area-specific specificity calculation unit 11 to execute step S1 again.

  Next, the calculation process of specificity shown in FIG. 3 will be described with reference to FIG. FIG. 4 is a flowchart specifically showing the calculation process of specificity shown in FIG.

  As shown in FIG. 4, first, the area-specific specificity calculation unit 11 acquires each area determined to have a unique state in step S2 from the store information acquired in step S1. Store information with the same time or acquired time zone is extracted (step S31).

  Next, the area-specific specificity calculation unit 11 uses the store information extracted in step S31 for each area determined to have a unique state in step S2 shown in FIG. Is calculated (step S32).

  For example, for an area where the employee is determined to exceed the threshold, the area-specific specificity calculation unit 11 includes the time or time zone when the threshold is exceeded and the store information extracted in step S3. The difference from the time or the time zone is obtained, and the specificity is calculated so that the value increases as the difference increases. Thereafter, the area-specific specificity calculation unit 11 notifies the store specificity calculation unit 12 of the calculated specificity.

  Next, the store specificity calculation unit 12 reads the degree of relationship between the areas stored in the storage unit 13 (step S33). Next, the store specificity calculation unit 12 calculates the specificity of the entire store using the specificity of each area calculated in step S32 and the degree of relationship between the areas read in step S33 (step S34). . Specifically, in the present embodiment, as described above, the store specificity calculation unit 12 determines the uniqueness of the entire store so that the value increases as the difference in specificity increases between areas with a high degree of association. Calculate the degree.

  Thereafter, the store specificity calculation unit 12 determines whether or not steps S31 to S34 are executed for all the store information acquired in step S1 (step S35). As a result of the determination in step S35, when steps S31 to S34 are not executed for all the store information acquired in step S1, the store specificity calculation unit 12 re-executes step S31 in the area-specific specificity calculation unit 11. Let it run. On the other hand, as a result of the determination in step S35, when steps S31 to S34 are executed for all the store information acquired in step S1, the store specificity calculation unit 12 ends the process.

  As described above, steps S31 to S34 are repeatedly executed for all the collected store information for each time or time zone. As a result, in step S4 shown in FIG. 3, the specificity for each area and the specificity of the entire store are displayed on the screen of the display device 40 for each time or time zone.

[Effects of the embodiment]
As described above, in this embodiment, the specificity for each area is calculated, and further, the specificity of the entire store is calculated based on this and the degree of relationship between the areas. Therefore, if the value of the degree of relationship between the area on the store customer side and the area on the employee side adjacent to it is set high, the manager will allow the store customer to service normally in a certain area depending on the calculated specificity. However, it is possible to grasp the situation where the employee is performing abnormal behavior in the adjacent area. That is, according to the present embodiment, the administrator can appropriately specify a target event, that is, a unique event of a person and an area.

  On the other hand, the manager can grasp the situation where the employee normally provides services in an area, but the employee is performing abnormal behavior in an adjacent area. A specific example of such a situation is a situation where a store customer is performing suspicious behavior such as changing the barcode outside the cash register area.

  Further, in the present embodiment, contrary to the above-described example, the store specificity calculation unit 12 is configured so that the value increases as the difference in specificity increases between areas with low relevance. It is also possible to calculate the degree. In this case, a case where a peculiar state occurs between unrelated areas is preferentially detected.

  Further, in this embodiment, not only when the above-mentioned unique state has occurred, but also when the employee takes a behavior specific to the store, the specificity of the entire store is increased or adjacent The difference in specificity between the areas to be increased. For this reason, the manager can also extract know-how in store management based on the calculation result of specificity. Furthermore, in the present embodiment, by accumulating cases, the administrator can utilize the accumulated cases for employee education and the like.

[program]
The program in the present embodiment may be a program that causes a computer to execute steps S1 to S5 shown in FIG. By installing and executing this program on a computer, the store management apparatus 10 and the store management method in the present embodiment can be realized. In this case, a CPU (Central Processing Unit) of the computer functions as the area-specific specificity calculation unit 11, the store specificity calculation unit 12, and the display unit 14, and performs processing.

  Here, a computer that realizes the store management apparatus 10 by executing the program according to the present embodiment will be described with reference to FIG. FIG. 5 is a block diagram illustrating an example of a computer that implements the store management apparatus according to the embodiment of the present invention.

  As shown in FIG. 5, the computer 110 includes a CPU 111, a main memory 112, a storage device 113, an input interface 114, a display controller 115, a data reader / writer 116, and a communication interface 117. These units are connected to each other via a bus 121 so that data communication is possible.

  The CPU 111 performs various calculations by developing the program (code) in the present embodiment stored in the storage device 113 in the main memory 112 and executing them in a predetermined order. The main memory 112 is typically a volatile storage device such as a DRAM (Dynamic Random Access Memory). Further, the program in the present embodiment is provided in a state of being stored in a computer-readable recording medium 120. Note that the program in the present embodiment may be distributed on the Internet connected via the communication interface 117.

  Specific examples of the storage device 113 include a hard disk drive and a semiconductor storage device such as a flash memory. The input interface 114 mediates data transmission between the CPU 111 and an input device 118 such as a keyboard and a mouse. The display controller 115 is connected to the display device 119 and controls display on the display device 119.

  The data reader / writer 116 mediates data transmission between the CPU 111 and the recording medium 120, and reads a program from the recording medium 120 and writes a processing result in the computer 110 to the recording medium 120. The communication interface 117 mediates data transmission between the CPU 111 and another computer.

  Specific examples of the recording medium 120 include general-purpose semiconductor storage devices such as CF (Compact Flash (registered trademark)) and SD (Secure Digital), magnetic storage media such as a flexible disk, or CD- An optical storage medium such as ROM (Compact Disk Read Only Memory) can be used.

  Next, an embodiment of the present invention will be described with reference to FIGS. Moreover, in the following description, FIGS. 1-4 are referred suitably.

  First, a store to be managed in this embodiment will be described with reference to FIGS. FIG. 6 is a layout diagram showing a specific layout of a store to be managed in the embodiment of the present invention. 7 and 8 are diagrams showing examples of areas set in the store shown in FIG.

  As shown in FIG. 6, in this embodiment, the store 20 is a self-service udon shop. In the store 20, eight monitoring cameras 30a, five RFID readers 30b, and one register 30c are arranged as the information collecting device 30. Among these, the surveillance camera 30a outputs video data at set intervals as store information.

  Each time the RFID tag 21 is detected, the RFID reader 30b outputs the detection time and the identification information of the detected RFID tag as store information. In the example of FIG. 6, the RFID tag 21 is attached to a tray 22 used by store customers. Further, the register 30c outputs the time as store information every time it is input.

  As shown in FIG. 7, the store 20 is referred to as an area used by store customers (hereinafter referred to as “store customer area”) and an area used by employees (hereinafter referred to as “employee area”). ) And may be separated. Furthermore, as shown in FIG. 8, the store 20 may be divided into eight areas A to H. In the following, the case where the store 20 is divided into eight areas A to H will be described. Areas A to D are aligned with the employee area, and areas E to H are aligned with the store customer area.

  Then, operation | movement of the shop management apparatus 10 in a present Example is demonstrated using FIGS. 9-12 along each step shown in FIG.

[Step S1: Store information acquisition processing]
First, the area-specific specificity calculation unit 11 acquires store information from the monitoring camera 30a, the RFID reader 30b, and the register 30c.

[Step S2: Singular State Determination Process]
Next, the area-specific specificity calculation unit 11 acquires the determination rule illustrated in FIG. 9 from the storage unit 13. FIG. 9 is a diagram showing an example of the determination rule used in the embodiment of the present invention. In the example of FIG. 9, different determination rules are set for the employee area and the store customer area. In FIG. 9, only a part of the determination rule is shown.

  Specifically, as shown in FIG. 9, regarding the area A in the employee area, “when the distance from the reference point in the area A of the employee position X exceeds the threshold value, a unique state is assumed”. Judgment rules are set. On the other hand, for the store customer area (areas E to H), “when 30 seconds is subtracted from the difference in reaction time between adjacent RFID readers and the square root of the obtained value exceeds the threshold value, A determination rule is set.

  Then, the area-specific specificity calculation unit 11 applies the store information acquired in step S1 to the determination rule, and determines whether or not a specific state has occurred in each area. Further, although not shown in FIG. 9, a plurality of determination rules may be set for one area. In this case, for example, if any one of the determination rules matches, the area-specific specificity calculation unit 11 may regard that a unique state has occurred, or match two or more determination rules. Under these conditions, it may be considered that a unique state has occurred.

[Step S3: Specificity Calculation Processing]
Next, the area-specific specificity calculation unit 11 first acquires store information acquired at a specific time in the area in order to calculate the specificity for an area that is determined to have a unique state. Then, the area-specific specificity calculation unit 11 calculates the specificity of the area using the acquired store information.

  When a plurality of types of store information is acquired for one corresponding area, the area-specific specificity calculation unit 11 calculates the specificity for each acquired store information. Then, the area-specific specificity calculation unit 11 can set the maximum specificity among the calculated specificities as the specificity of the corresponding area. In the present embodiment, the area-specific specificity calculation unit 11 sets the specificity to 0 (zero) for an area that is determined not to have a unique state.

  When the specificity of the area is calculated, the store specificity calculation unit 12 reads the degree of relationship between the areas from the storage unit 13. FIG. 10 is a diagram showing an example of the degree of relationship between areas used in the embodiment of the present invention. As shown in FIG. 10, in the present embodiment, the degree of relationship α between areas represents the degree of relationship between one area and another area as a value [%] of 0 to 100.

  Next, the store specificity calculation unit 12 calculates the specificity T of the entire store as shown in FIG. 11 using the following equations 1 and 2. FIG. 11 is a diagram illustrating an example of a calculation result of the specificity for each area and the specificity of the entire store in the embodiment of the present invention.

In the following equation 1, N represents a value obtained by subtracting 1 from the total number of areas, and i and j represent integers of 0 or more and N or less. C _i (= X) indicates the specificity of the i-th area, and C _j (= Y) indicates the specificity of the j-th area. α _ij indicates the degree of relationship between the i-th area and the j-th area. In this embodiment, C ₀ = specificity of area A, C ₁ = specificity of area B, C ₂ = specificity of area C, C ₃ = specificity of area D, C ₄ = specificity of area E, C ₅ = specificity of area F, C ₆ = specificity of area G, and C ₇ = specificity of area H.

  Further, in the above formulas 1 and 2, as can be seen from the conditional expression of formula 2, when the relationship between the singularities of both areas exceeds the assumed range among the combinations of the two areas (X ≧ Y and X × α / 100> Y) is set so that a value is added to the specificity T of the entire store.

  For example, as shown in FIG. 10, it is assumed that the specificity of area A is 80% and the specificity of area B is 10% at a certain time. In the example of FIG. 10, if the specificity of area A is X, the relationship with any of areas B to H will exceed the assumed range. In addition, the area B exceeds the assumed range in relation to the areas C to H when the specificity is X. As a result, the specificity of the entire store at this time is calculated as 5.75. As described above, in this embodiment, the store specificity calculation unit 12 calculates the degree of divergence between the specificity between areas and the degree of association between areas, and uses the result as the specificity of the entire store.

[Step S4: Specificity Presentation Processing]
Next, in order to display the specificity for each area and the specificity of the entire store for each time, the display unit 14 generates image data and outputs it to the display device 40. Thereby, the screen shown in FIG. 12 is displayed. FIG. 12 is a diagram illustrating an example of a calculation result displayed in the embodiment of the present invention.

  As shown in FIG. 12, in the present embodiment, on the display screen 41, for each time when store information is collected (for each event), the specificity for each area and the specificity for the entire store (store specificity) are displayed. Is displayed. In this embodiment, the administrator can rearrange the events in the order of calculation of the store specificity, the ascending order, or the descending order by clicking an arrow button provided in the store specificity column. Furthermore, an arrow button is also provided in each area column, and the administrator can rearrange the events in the order of calculation of the specificity of any area, in ascending order, or descending order.

  As described above, in this embodiment, the administrator can rearrange the events by using the arrow buttons, and thus can select a viewpoint to be emphasized in the observation of the singular state. As a result, the administrator can specify the target to be focused more reliably. This also allows the administrator to know the time that should be regarded as important.

  In the present embodiment, as shown in FIG. 10, the value of the relationship between the area on the store customer side and the area on the employee side adjacent thereto is set high, and if the difference between the two is large, the store The specificity value is high. In other words, in this embodiment, the store abnormality degree value is set to be higher when a unique state that is not assumed by the administrator occurs.

  Therefore, based on each specificity, the manager can easily grasp the situation where the store customer is normally receiving service in a certain area, but the employee is performing abnormal behavior in the adjacent area. it can. In this way, in this embodiment, the extraction of abnormal behavior hidden in normal operations, which is clearly different from the superficial singularity obtained by confirming the busy state of the store, and the know-how in the store are extracted. I can expect.

  If it is not determined that a unique state has occurred in any area in the store, the specificity of each area is 0 (zero) or close to 0, so the store specificity is also 0 (zero). ) Or close to zero. In addition, when it is determined that a peculiar state has occurred in all or most of the areas, it is a state assumed by the manager, so as can be seen from the above formulas 1 and 2, the store specificity is Low value.

  Part or all of the above-described embodiment can be expressed by (Appendix 1) to (Appendix 15) described below, but is not limited to the following description.

(Appendix 1)
An area-specific specificity calculating unit that calculates the specificity for each area using information collected from each area of the store to be managed;
A store specificity calculation unit that calculates the specificity of the entire store to be managed based on the calculated specificity for each area and the relationship between preset areas;
A store management apparatus comprising:

(Appendix 2)
The store specificity calculation unit uses the degree of relationship between the area preset for each area and another area as the relationship between the preset areas, and the degree of specificity between the areas having a high degree of association The specificity of the entire store is calculated so that the larger the difference is, the larger the value is.
The store management apparatus according to attachment 1.

(Appendix 3)
The area-specific specificity calculation unit uses, as the information, information on human behavior in the area, information on devices in the area, or both, and applies the information to a preset rule. For each area, determine whether a unique condition has occurred, and calculate the specificity of the area where a unique condition has occurred,
The store management apparatus according to appendix 1 or 2.

(Appendix 4)
Each area of the store to be managed is either an area used by store customers or an area used by employees,
The rule is set separately separately for an area used by the store customer and an area used by the employee.
The store management apparatus according to attachment 2.

(Appendix 5)
A display unit that generates image data for displaying the specificity for each area and the specificity of the entire store on a screen every time the information is collected or every time the specificity is calculated Have
The store management apparatus in any one of appendix 1-4.

(Appendix 6)
(A) calculating the specificity for each area using information collected from each area of the store to be managed; and
(B) calculating the specificity of the entire store to be managed based on the specificity for each area calculated in the step of (a) and the relationship between the preset areas;
The store management method characterized by having.

(Appendix 7)
In the step (b), the degree of relationship between the area set in advance for each area and another area is used as the relation between the areas set in advance, and the degree of specificity between the areas with the high degree of association is used. The specificity of the entire store is calculated so that the larger the difference is, the larger the value is.
The store management method according to attachment 6.

(Appendix 8)
In the step (a), as the information, any one or both of information related to human behavior in the area and information related to equipment in the area is used, and the information is applied to a preset rule. For each area, determine whether a unique condition has occurred, and calculate the specificity of the area where the unique condition has occurred.
The store management method according to appendix 6 or 7.

(Appendix 9)
Each area of the store to be managed is either an area used by store customers or an area used by employees,
The rule is set separately separately for an area used by the store customer and an area used by the employee.
The store management method according to attachment 7.

(Appendix 10)
(C) generating image data for displaying the specificity for each area and the specificity of the entire store on a screen every time the information is collected or every time the specificity is calculated, Further having
The store management method according to any one of appendices 6 to 9.

(Appendix 11)
On the computer,
(A) calculating the specificity for each area using information collected from each area of the store to be managed; and
(B) calculating the specificity of the entire store to be managed based on the specificity for each area calculated in the step of (a) and the relationship between the preset areas;
A program that executes

(Appendix 12)
In the step (b), the degree of relationship between the area set in advance for each area and another area is used as the relation between the areas set in advance, and the degree of specificity between the areas with the high degree of association is used. The specificity of the entire store is calculated so that the larger the difference is, the larger the value is.
The program according to appendix 11.

(Appendix 13)
In the step (a), as the information, any one or both of information related to human behavior in the area and information related to equipment in the area is used, and the information is applied to a preset rule. For each area, determine whether a unique condition has occurred, and calculate the specificity of the area where the unique condition has occurred.
The program according to appendix 11 or 12.

(Appendix 14)
Each area of the store to be managed is either an area used by store customers or an area used by employees,
The rule is set separately separately for an area used by the store customer and an area used by the employee.
The program according to attachment 12.

(Appendix 15)
(C) generating image data for displaying the specificity for each area and the specificity of the entire store on a screen every time the information is collected or every time the specificity is calculated, Further causing the computer to execute
The program according to any one of appendices 11 to 14.

  As described above, according to the present invention, it is possible to appropriately specify a target to be focused on in detecting a unique state in a store. INDUSTRIAL APPLICABILITY The present invention is useful for a store where service provision contents are divided for each area such as a cafe, and a store where an area used by store customers and an area used by employees are divided.

DESCRIPTION OF SYMBOLS 10 Store management apparatus 11 Area specificity calculation part 12 Store specificity calculation part 13 Memory | storage part 14 Display part 20 Store 21 RFID tag 22 Tray 30 Information collection apparatus 30a Monitoring camera 30b RFID reader 30c Register 40 Display apparatus 41 Display screen 50 Management 110 Computer 111 CPU
112 Main Memory 113 Storage Device 114 Input Interface 115 Display Controller 116 Data Reader / Writer 117 Communication Interface 118 Input Device 119 Display Device 120 Recording Medium 121 Bus

Claims (7)

An area-specific specificity calculating unit that calculates the specificity for each area using information collected from each area of the store to be managed;
A store specificity calculation unit that calculates the specificity of the entire store to be managed based on the calculated specificity for each area and the relationship between preset areas;
A store management apparatus comprising: The store specificity calculation unit uses the degree of relationship between the area preset for each area and another area as the relationship between the preset areas, and the degree of specificity between the areas having a high degree of association The specificity of the entire store is calculated so that the larger the difference is, the larger the value is.
The store management apparatus according to claim 1. The area-specific specificity calculation unit uses, as the information, information on human behavior in the area, information on devices in the area, or both, and applies the information to a preset rule. For each area, determine whether a unique condition has occurred, and calculate the specificity of the area where a unique condition has occurred,
The store management apparatus according to claim 1 or 2. Each area of the store to be managed is either an area used by store customers or an area used by employees,
The rule is set separately separately for an area used by the store customer and an area used by the employee.
The store management apparatus according to claim 2. A display unit that generates image data for displaying the specificity for each area and the specificity of the entire store on a screen every time the information is collected or every time the specificity is calculated Have
The store management apparatus in any one of Claims 1-4. (A) calculating the specificity for each area using information collected from each area of the store to be managed; and
(B) calculating the specificity of the entire store to be managed based on the specificity for each area calculated in the step of (a) and the relationship between the preset areas;
The store management method characterized by having. On the computer,
(A) calculating the specificity for each area using information collected from each area of the store to be managed; and
(B) calculating the specificity of the entire store to be managed based on the specificity for each area calculated in the step of (a) and the relationship between the preset areas;
A program that executes

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