JP5540645B2 - Information processing apparatus, information processing apparatus control method, and program - Google Patents

Description

  The present invention relates to an information processing apparatus, a control method for an information processing apparatus, and a program for detecting fraudulent behavior of a store clerk or a customer in a retail store such as a supermarket or a restaurant such as a family restaurant.

  Conventionally, Patent Document 1 has been proposed as a system for detecting fraud at the time of accounting processing of a store clerk in a retail store or a restaurant. The system described in Patent Document 1 includes a POS terminal (POS terminal), a camera that captures an image around the POS terminal, a photojournal recorder, and a search terminal. The photo journal recorder records journal data (transaction history data), image data around the POS terminal captured by the camera, and operation history (operation history data) of the POS terminal by the store clerk in association with each other. . Then, the administrator (operator) designates predetermined search conditions such as time and POS terminal operation information using the search terminal, thereby displaying journal data and image data that match the search conditions on the display.

JP 2005-115504 A

  However, the system described in Patent Document 1 only displays a list of recorded data (accounting processing contents and captured images at that time) that match the search conditions specified by the administrator. In order to detect whether or not it has been received, the administrator must check the recorded data step by step. In other words, since it is impossible for an administrator to execute search processing actively (voluntarily) and verify the recorded data that is the search result, it is not possible to determine whether or not fraud has been performed. There is a problem that it takes a lot of time and labor.

  Therefore, it is conceivable to automatically detect exception processing at the POS terminal in order to extract recorded data that is highly likely to be fraudulent. This exception handling is often abused as a means of fraud. For example, using a receipt that the customer did not receive, perform a “cancellation process”, which is one of the exception processes, and take a cash equivalent to the settlement amount of the receipt. By detecting “processing”, it is possible to narrow down the recorded data. Also, if the occurrence of exception processing is detected in real time and the recording data can be recorded on the basis of the detection time instead of searching the recording data as a post-processing, unnecessary data recording is eliminated, and more efficient. Cheating can be detected.

  In view of the above-described problems, an object of the present invention is to provide an information processing apparatus, a control method for the information processing apparatus, and a program capable of efficiently recording data useful as evidence of fraud.

An information processing apparatus according to the present invention includes a monitoring data acquisition unit that acquires monitoring data that is a monitoring result of a monitoring unit of a monitoring camera that monitors a situation around a checkout counter, and a main that stores at least a part of the monitoring data in a nonvolatile manner. In the storage unit and the accounting processing unit of the POS terminal provided at the checkout counter, an exception processing occurrence detection unit for detecting that an accounting processing exception has occurred, and accounting information that is the accounting processing result of the accounting processing unit is acquired. An accounting information acquisition unit, and a recording control unit that controls the recording of monitoring data in the main storage unit, and the exception processing occurrence detection unit receives accounting information including information indicating exception processing by the accounting information acquisition unit. by obtaining, detecting the occurrence of an exception process, the recording control unit, N time duration relative to the time of occurrence detection exception handling exception processing occurrence detection unit (however, N Monitoring data of 0), characterized in that recorded in the main storage unit.

Method of controlling an information processing apparatus of the present invention, the storage monitoring unit of the monitoring camera for monitoring the situation around the checkout counter, accounting unit of the POS terminal, and at least a portion of the monitoring data is the monitoring result of the monitoring unit in a nonvolatile In the control method of the information processing apparatus provided with the main storage section inside or outside, the information processing apparatus acquires the monitoring data that is the monitoring result of the monitoring section, and the accounting processing section, Controls exception detection occurrence detection step that detects the occurrence of accounting exception processing, accounting information acquisition step that acquires accounting information that is the accounting processing result of the accounting processing unit, and recording of monitoring data to the main storage unit In the exception processing occurrence detection step, the accounting information including information indicating the exception processing in the accounting information acquisition step is executed. The occurrence of exception processing is detected by acquiring the information, and in the recording step, monitoring data for N hours (where N> 0) with reference to the time of occurrence of exception processing in the exception processing occurrence detection step, It is recorded in the main storage unit.

According to these configurations, occurrence of exception processing is detected, and monitoring data for N hours (predetermined time) is recorded with reference to the occurrence detection time of the exception processing, thereby preventing unnecessary data recording. be able to. As a result, only monitoring data useful as evidence of fraud can be recorded, and thus fraud can be detected more efficiently.
Furthermore, according to this configuration, it is possible to accurately detect the occurrence of exception processing by using accounting information including information indicating exception processing (for example, information based on pressing of a cancel key, an exchange key, etc.). it can.
Note that “N hours based on the detection of the occurrence of exception processing” means a predetermined time starting before and after the detection of occurrence of exception processing, and after detection of the occurrence of exception processing starting from the detection of occurrence of exception processing. It indicates either a predetermined time as an end point or a predetermined time after the occurrence of exception processing is detected as a start point and an end point.

  In the information processing apparatus described above, the information processing apparatus further includes a sub-storage unit that stores the monitoring data for a predetermined time while being monitored, and the recording control unit stores the monitoring data in the sub-storage unit. It is preferable to record N hours of monitoring data including monitoring data before detection of occurrence of exception processing from the monitoring data thus recorded in the main storage unit.

  In the control method of the information processing device described above, the information processing device further includes a sub-storage unit that stores the monitoring data for a predetermined time while being updated while the monitoring unit is monitored, and the recording step Then, it is preferable to record N hours of monitoring data including monitoring data before detection of occurrence of exception processing from the monitoring data stored in the sub storage unit in the main storage unit.

  According to these configurations, since the sub storage unit (buffer) for storing the monitoring data for a predetermined time is updated as needed while the monitoring unit is being monitored, before the occurrence of exception processing is detected. Monitoring data can be recorded. Thereby, even if it is a fraudulent act that the monitoring data before the occurrence of exception processing is considered to be important, it can be detected without any trouble. For example, fraudulent behavior such as a store clerk withdrawing cash from a cash drawer often shows suspicious behavior such as the store clerk looking around before pressing the exchange key (exception processing occurs). Can also be recorded as monitoring data.

  In the information processing apparatus described above, the monitoring data for N hours is preferably monitoring data whose starting time is M hours before the occurrence detection of exception processing (where 0 <M ≦ N).

  In the control method for the information processing apparatus described above, the monitoring data for N hours may be monitoring data whose start time is M hours before the occurrence detection of exception processing (where 0 <M ≦ N). preferable.

  According to these configurations, it is possible to record monitoring data whose start time is M hours before the occurrence detection of exception processing (predetermined time). As a result, it is possible to reliably detect fraudulent acts in which the monitoring data before occurrence of exception processing is considered important.

  In the information processing apparatus described above, it is preferable that the exception processing occurrence detection unit detects the occurrence of exception processing by the operation of the operation unit that can be operated by the user when the exception processing occurs.

According to this configuration, by using the operation result of the operation unit by the user (store clerk or customer), even if the exception processing operation is postponed due to the congestion of the cash register, the exception processing is surely generated. Can be detected.
The “operation unit” may be mounted on the information processing apparatus, or may be mounted on a medium (such as a store clerk card or a membership card) possessed by a store clerk or a customer.

  The information processing apparatus described above further includes a placement detection unit that detects that a product or a receipt is placed on the predetermined placement unit, and the exception processing occurrence detection unit detects the product or receipt by the placement detection unit. It is preferable to detect the occurrence of exception processing by detecting receipt placement.

  According to this configuration, it is possible to quickly detect the occurrence of exceptional processing such as return or exchange of goods, cancellation or correction of receipts.

  The information processing apparatus described above further includes a sound acquisition unit that acquires sound around the checkout counter and a sound recognition unit that recognizes the acquired sound, and the exception processing occurrence detection unit is It is preferable to detect the occurrence of exception processing by recognizing or not recognizing a keyword.

  According to this configuration, a certain keyword (for example, “Wrong”, “Please return”, etc.) spoken by the store clerk or customer during the return processing is recognized, or the store clerk or customer usually By not recognizing a predetermined keyword uttered during processing (for example, “˜ is a dot”), it is possible to quickly detect the occurrence of exception processing.

  In the information processing apparatus described above, it is preferable that the information processing apparatus further includes a receipt reading unit that reads a receipt, and the exception processing occurrence detection unit detects the occurrence of exception processing by reading the receipt with the receipt reading unit.

  According to this configuration, since occurrence of exception processing such as return or exchange of goods, cancellation or correction of a receipt requires a normal receipt, occurrence of these exception processing can be detected quickly.

  In the information processing apparatus described above, the accounting processing unit is realized by a POS terminal connected to the information processing apparatus, and further includes a reading result output unit that outputs a reading result of the receipt reading unit to the POS terminal. It is preferable.

According to this configuration, information such as a receipt read result (transaction number ≒ receipt number, product code, product name, quantity, price, transaction occurrence date ≒ accounting date, store clerk ID ≒ cashier in charge, POS terminal ID ≒ cashier number, etc. ) Is output to the POS terminal, and subsequent exception processing can be performed smoothly.
If the exception process is a “cancellation process” for canceling the accounting process after the accounting process, the POS terminal side stores the accounting process information (settlement information) to be canceled based on the read result of the receipt. It is preferable to be able to read and change only part of it and re-register. In other words, the POS terminal uses only the receipt reading result (receipt number, etc.) as a key, changes the accounting processing information reading unit that reads out the accounting information of interest from the accounting processing database, and changes only part of the read accounting information. And a re-registration unit that re-registers in the accounting information database. According to this configuration, it is possible to save the trouble of re-inputting the product described in the receipt, and to improve the efficiency of the accounting process.

  In the information processing apparatus described above, the monitoring unit further includes a specific behavior determination unit that monitors the inside of the store including around the checkout counter, and determines at least one specific behavior of the clerk and the customer from the monitoring result of the monitoring unit, When the specific action is determined by the specific action determination unit, the recording control unit preferably records monitoring data for L hours (where L> 0) based on the specific action determination time in the main storage unit. .

According to this configuration, when the specific behavior of the store clerk or customer is determined, the monitoring data for L hours (predetermined time) based on the specific behavior determination time can be recorded.
Note that the monitoring data for L hours with reference to the specific action determination time is also applied to the same configuration and the same components as the monitoring data for N hours with reference to the detection time of occurrence of exception processing. Variations can be applied.

  In the information processing apparatus described above, it is preferable that the recording control unit adds tag information indicating a situation at the time of occurrence of exceptional processing or determination of specific action to the monitoring data, and stores the tag information in the main storage unit.

  In the information processing apparatus described above, the tag information includes the type of exception processing, the receipt read result, the position of the store clerk in the store, the presence of customers around the checkout counter, the image data in the store including the checkout counter, and the checkout counter It is preferable to include at least one piece of information among in-store audio data, exception processing occurrence date and time, and specific action determination date and time.

  According to these configurations, tag information (exception processing type, receipt read result, store clerk position in the store, presence / absence of customers around the checkout counter, around the checkout counter) The monitoring data can be searched and referenced using the image data in the store including, audio data in the store including around the checkout counter, information such as the date and time of occurrence of exception processing and the date and time of specific action determination) as search keys.

  In the information processing apparatus described above, it is preferable that the information processing apparatus further includes a printing unit that prints accounting information, which is a result of accounting processing by the accounting processing unit, on receipt paper.

  According to this configuration, the information processing apparatus of the present invention can be applied to a receipt printer.

  A program according to the present invention causes a computer to execute each step in the control method of the information processing apparatus described above.

  By using this program, it is possible to realize a control method for an information processing apparatus capable of efficiently recording data useful as evidence of fraud.

1 is a system configuration diagram of a store monitoring system according to a first embodiment. It is a functional block diagram of the store monitoring system concerning a 1st embodiment. It is a control block diagram of the receipt printer according to the first embodiment. It is a figure which shows the specific example of the data conversion which concerns on 1st Embodiment. It is explanatory drawing of the exception process database which concerns on 1st Embodiment. It is explanatory drawing of the accounting process database which concerns on 1st Embodiment. It is a flowchart which shows the information output process of the receipt printer which concerns on 1st Embodiment. It is a functional block diagram of the store monitoring system concerning a 2nd embodiment. It is a flowchart which shows the monitoring data recording process which triggered the acquisition of the accounting information by information processing apparatus based on 2nd Embodiment. It is a flowchart which shows the monitoring data recording process which triggered reading of the receipt by the information processing apparatus based on 2nd Embodiment, and the receipt content change process of a POS terminal. It is a flowchart which shows the monitoring data recording process which triggered the detection of the specific action by the information processing apparatus based on 2nd Embodiment. It is a figure which shows an example of the exception process generation | occurrence | production detection table which concerns on 2nd Embodiment. It is a functional block diagram which shows the other example of the exception process generation | occurrence | production detection pattern which concerns on 2nd Embodiment. It is a schematic diagram which shows the other example of the exception process generation | occurrence | production detection pattern which concerns on 2nd Embodiment. It is a figure which shows an example of the specific action generation | occurrence | production detection table which concerns on 2nd Embodiment. It is a flowchart which shows the other example of the specific action generation | occurrence | production detection pattern which concerns on 2nd Embodiment. It is a functional block diagram of the store monitoring system concerning a 3rd embodiment. It is a flowchart which shows the data recording process by the information processing apparatus based on 3rd Embodiment. It is a flowchart which shows the total report creation process by information processing apparatus based on 3rd Embodiment. It is a figure which shows an example of the totalization report (at the time of returned goods process) which concerns on 3rd Embodiment. It is a figure which shows an example of the totalization report (at the time of a misregistration process) which concerns on 3rd Embodiment. It is a figure which shows an example of the totalization report (at the time of an employee discount process) concerning 3rd Embodiment.

  Hereinafter, an information processing apparatus, a control method for the information processing apparatus, and a program according to the present invention will be described with reference to the accompanying drawings. In each embodiment shown below, the information processor of the present invention is illustrated as being applied to a store monitoring system. The store monitoring system is constructed to detect fraudulent behaviors of store clerk and customers in retail stores such as supermarkets and restaurants such as family restaurants.

[First Embodiment]
FIG. 1 is a system configuration diagram of the store monitoring system SY1 according to the first embodiment. As shown in the figure, the store monitoring system SY1 includes a POS terminal 1 that performs transaction processing, a receipt printer 2 that issues a receipt R, a customer display 4 that displays transaction information, and a clerk monitoring camera 3 that monitors the clerk. And a store management server 5 that supervises the store monitoring system SY1, and a report output printer 8 that prints the summary report 50. The POS terminal 1 and the receipt printer 2, the receipt printer 2 and the customer display 4, and the store management server 5 and the report output printer 8 are communicably connected via a serial interface (for example, a USB (Universal Serial Bus) interface). The POS terminal 1, the receipt printer 2, the clerk monitoring camera 3, and the store management server 5 are communicably connected via an in-store LAN 6 (wired LAN or wireless LAN).

  Although FIG. 1 illustrates a case where there is one POS terminal 1, a configuration in which a plurality of POS terminals 1 exist in the store monitoring system SY1 may be employed. In this case, a receipt printer 2, a clerk monitoring camera 3, and a customer display 4 corresponding to each POS terminal 1 are installed.

  The POS terminal 1 is a register installed in the cashier counter 7 and executes an accounting process based on product information input by a store clerk (operator). Then, accounting information (printing data for receipt R printing, display data for displaying the customer display 4, etc .; these are hereinafter collectively referred to as “output data”) is output to the receipt printer 2. To do.

  The clerk monitoring camera 3 is a CCD camera, for example, and is installed around the cashier counter 7 (such as the ceiling or the vicinity of the customer display 4). The imaging target is a store clerk who performs a cash register operation at the cashier counter 7, a customer at the time of accounting processing, a product placed on the cashier counter 7, and the like. A plurality of salesclerk monitoring cameras 3 may be installed for one cash register counter 7. The imaging result of the clerk monitoring camera 3 is output to the receipt printer 2.

  The receipt printer 2 issues (prints) a receipt R based on output data (print data) output from the POS terminal 1. The receipt printer 2 has a function of transferring output data (display data) output from the POS terminal 1 to the customer display 4 in addition to a function of issuing a receipt R, and a function of acquiring an imaging result of the clerk monitoring camera 3 , A function for determining the operation of the POS terminal 1 based on the output data (print data and display data), a function for converting the determination result into data of a predetermined format, the conversion data, and the imaging result of the clerk monitoring camera 3 are stored in the store management server. Various functions such as a function of transmitting to the terminal 5 are provided. In this way, by inputting / outputting various information with the receipt printer 2 as the main (filtering various information acquired by the receipt printer 2 and outputting necessary information), the POS backbone network (POS terminal 1 The main network) traffic is not affected. Further, when applying the present invention to an existing POS system, it is not necessary to change the POS backbone network itself.

  The store management server 5 acquires the conversion data and the image capturing result of the store clerk monitoring camera 3 from the receipt printer 2 and stores them in the database 51 (see FIG. 2). If necessary, the information stored in the database 51 is aggregated and output by the report output printer 8. Note that a general printer can be applied as the report output printer 8, and a description thereof will be omitted.

  Next, the functional configuration of the store monitoring system SY1 will be described with reference to FIG. The POS terminal 1 has an accounting processing unit 11 as a main functional configuration. The accounting processing unit 11 executes accounting processing including settlement processing and exception processing. In addition, output data generated with the accounting process is output to the receipt printer 2.

  In the present embodiment, exception processing refers to processing that is highly likely to be related to fraud. Specifically, “canceling process” for canceling input data during the accounting process of the POS terminal 1, “cancellation process (misregistration process)” for canceling the accounting process after the accounting process, and returning the merchandise. "Return processing" for product discount, "discount processing" for discounting products, "discount processing" for discounting products, and "exchange processing" for money exchange, cash in cash drawer "Inspection process" for checking sales, "withdrawal / refund process" for making a withdrawal or refund, "reissue process" for reissuing the receipt R, and the like.

  In the following description, each of these processes is distinguished as an exception process type. For convenience, processing other than exception processing among processing that can be executed by the POS terminal 1 (where transaction data is generated) is referred to as “normal processing”. The normal process includes a “settlement process” executed at the time of product purchase.

  The clerk monitoring camera 3 has an imaging unit 31 as a main functional configuration. The imaging unit 31 captures the periphery of the cashier counter 7, and the imaging data captured by the imaging unit 31 is associated with information such as a camera ID for identifying the clerk monitoring camera 3 and an imaging date and time. As a result, it is output to the receipt printer 2. The imaging date and time refers to a time measurement result of an RTC (Real Time Clock, not shown) provided in the clerk monitoring camera 3.

  The customer display 4 has a display unit 41 as a main functional configuration. The display unit 41 displays transaction information to be presented to the customer based on the display data output from the receipt printer 2.

  The receipt printer 2 has an output data acquisition unit 21, an operation determination unit 22, a data conversion unit 23, a conversion data output unit 24, an imaging result acquisition unit 25, a printing unit 26, and a display data output unit 27 as main functional configurations. doing. The output data acquisition unit 21 acquires output data output from the POS terminal 1 (accounting processing unit 11).

  The operation determination unit 22 analyzes the meaning of the output data acquired by the output data acquisition unit 21 and determines the operation of the POS terminal 1. Specifically, it is determined whether or not an operation for executing an exception process of the accounting process has been performed in the POS terminal 1. In addition, the type of exception processing and transaction amount are determined.

  The data conversion unit 23 converts the determination result of the operation determination unit 22 into data in a predetermined format that can be interpreted by the store management server 5. In the present embodiment, the data in the predetermined format is converted into XML (Extensible Markup Language) data (see FIG. 4C).

  The conversion data output unit 24 outputs the conversion data (XML data) converted by the data conversion unit 23 to the store management server 5. In the following description, the conversion data when the operation determination unit 22 determines that the operation is an operation for executing exception processing is referred to as “exception processing information”. In addition, conversion data (information regarding normal processing) when it is determined that the operation is not for executing exceptional processing is referred to as “normal processing information”.

  Further, when outputting the exception processing information, the conversion data output unit 24 outputs the imaging result acquired by the imaging result acquisition unit 25 described later together with the exception processing information. The imaging result to be output at this time is the imaging result of the clerk monitoring camera 3 for a predetermined time before and after the determination time of the operation determination unit 22 as a reference. That is, imaging results for a predetermined time before and after are output from when it is determined that exception processing has been executed in the POS terminal 1 (≈when exception processing occurs). In addition, as a recording method of the imaging result, a recording method of a recording control unit 83 (see FIG. 8) described later in the second embodiment can be applied. In this case, the receipt printer 2 includes a recording control unit 83 and a storage unit 80 (see FIG. 8).

  The imaging result acquisition unit 25 acquires an imaging result from the clerk monitoring camera 3 (imaging unit 31). If the output data is print data, the printing unit 26 prints this on receipt paper and issues a receipt R. When the output data is display data, the display data output unit 27 outputs the display data to the customer display 4 (display unit 41).

  The store management server 5 includes a database 51 and a total result output unit 52 as main functional configurations. The database 51 stores the conversion data output from the conversion data output unit 24 and the imaging result. Although details will be described later, the database 51 stores an exception processing database 51a (see FIG. 5) for storing exception processing information and information on all accounting processes (normal processing information and exception processing information). Accounting process database 51b (see FIG. 6).

  Based on the exception processing information stored in the exception processing database 51a, the tabulation result output unit 52 tabulates the occurrence status of exception processing for each clerk (for each clerk ID) or for each customer (for each customer ID). The results are output as a summary report 50. In the case of the present embodiment, the output method is assumed to be a print output by the report output printer 8, but it may be a display output on a display (not shown), or an e-mail or a Web application is used. It may be a notification to an administrator (store manager, etc.). A specific example of the tabulation method and tabulation report 50 will be described later in the third embodiment (see FIGS. 20 to 22).

  Next, the control configuration of the store monitoring system SY1 will be described with reference to FIG. The POS terminal 1 has a POS application 16. The POS application 16 is a main part of the accounting processing unit 11.

  The receipt printer 2 includes an input interface 61, an output interface 62, a character generator 63, a main processing unit 64, a printing mechanism 65, a conversion table 66, a data tap semantic analysis unit 67, an upper layer transmission unit 68, and a DVR application 69. Yes. Among these, the conversion table 66, the data tap semantic analysis unit 67, the upper layer transmission unit 68, and the DVR application 69 are unique configurations of the receipt printer 2 according to the present embodiment.

  Although not particularly illustrated, the main processing unit 64 and the data tap semantic analysis unit 67 are realized by a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and the like. The upper layer transmission unit 68 is realized by a wireless / wired LAN terminal or the like.

  When the output data (print data and display data) of the POS terminal 1 is acquired via the input interface 61, the main processing unit 64 refers to the character generator 63 and performs conversion processing to text data. When the output data from the POS terminal 1 is in the text data format, a process for extracting the text data is performed instead of the conversion process. The display data converted into text is output to the customer display 4 via the output interface 62. Further, the print data converted into text is output to the print mechanism 65. When the receipt printer 2 is designated as an invalid peripheral device, the text data is output only to the customer display 4. When the receipt printer 2 is designated as a valid peripheral device, the text data is output to the customer display 4 and the print mechanism 65.

  The data tap semantic analysis unit 67 determines the operation of the POS terminal 1 by tapping the display data or print data converted into text and performing semantic analysis with reference to the conversion table 66. The conversion table 66 can rewrite the conversion rule according to the file format of the POS application 16. For this reason, even when incorporated in various POS systems having different file formats, semantic analysis can be performed without hindrance, and the operation of the POS terminal 1 can be accurately determined. That is, the receipt printer 2 of the present embodiment includes the conversion table 66 and the data tap semantic analysis unit 67, so that the operation of the POS terminal 1 having various specifications can be determined. In addition, this makes it applicable to various POS systems and enhances versatility.

  After performing the semantic analysis, the data tap semantic analysis unit 67 converts the analysis result into data in XML format that can be interpreted by the store management server 5, and outputs the data to the upper layer transmission unit 68. That is, the exception process information and the normal process information are described in the XML language.

  FIG. 4 is a diagram illustrating a specific example of data conversion by the data tap semantic analysis unit 67. The data tap semantic analysis unit 67 performs data tap conversion on the text data to the customer display 4 (see FIG. 4A) and the text data to the print mechanism 65 (see FIG. 4B). The data is tapped by the function to be converted into XML data and converted into data for the upper layer (see FIG. 4C). In the figure, an example of conversion of output data (data for displaying / printing a product name, a unit price, and a subtotal amount) at the time of settlement processing is illustrated. As described above, by converting the data to the upper layer into a markup language, there are advantages such as easy publication of a document as a Web page and easy data conversion.

  Returning to the description of FIG. The DVR application 69 records the imaging result of the clerk monitoring camera 3 in a predetermined storage area (corresponding to the sub-storage unit 84 of the second embodiment), and the imaging result for a predetermined time among them is subjected to data tap semantic analysis. The exception processing determination by the unit 67 is used as a trigger to output to the upper layer transmission unit 68. The upper layer transmission unit 68 adds the imaging result output from the DVR application 69 to the XML data (exception processing information) output from the data tap semantic analysis unit 67 when the exception processing occurs, and sends it to the store management server 5. Send. Further, when normal processing occurs, only XML data (normal processing information) output from the data tap semantic analysis unit 67 is transmitted.

  The store management server 5 has an exception processing database 51a that stores exception processing information and the image of the clerk monitoring camera 3, and an accounting processing database 51b that stores exception processing information and normal processing information. The exception processing database 51 a is a database provided for the purpose of printing the summary report 50. The data recorded in the exception processing database 51 a is aggregated for each store clerk or each customer, for example, and printed by the report output printer 8. If other items are specified as the search key, the total report 50 can be output for each date, for each type of exception processing, and for each product subject to exception processing.

  The accounting process database 51b is a database provided for the purpose of recording all accounting processes (transaction data). Although not shown in particular, transaction data can be printed out or displayed as accounting history.

  Next, with reference to FIGS. 5 and 6, the contents recorded in the exception processing database 51a and the accounting processing database 51b will be described. FIG. 5 is an explanatory diagram of the exception processing database 51a. As shown in the figure, the exception processing database 51a stores exception processing information and the imaging result of the clerk monitoring camera 3 in association with each other. The exception process information includes a transaction number, transaction occurrence date, transaction type (exception process type), transaction amount, clerk ID, POS terminal ID, transaction data, and the like, which are determination results of the operation determination unit 22. Further, the imaging result includes an imaging date and time, a camera ID, imaging data, and the like.

  On the other hand, FIG. 6 is an explanatory diagram of the accounting process database 51b. As shown in the figure, the transaction processing database 51b stores normal processing information and exception processing information. Each item according to the exception processing information is stored as the normal processing information. In the figure, normal processing information and exception processing information are distinguished from each other, but they may be listed in the order of transaction numbers and stored as accounting processing information without distinction between the two. Further, the accounting process database 51b may include the exception process database 51a.

  Next, information output processing of the receipt printer 2 will be described with reference to the flowchart of FIG. When the receipt printer 2 acquires the output data of the POS terminal 1 (S11, output data acquisition unit 21), the main processing unit 64 converts it into text data (S12). Further, the data tap semantic analysis unit 67 determines the operation of the POS terminal 1 from the text data (S13, operation determination unit 22), and whether or not the operation is accompanied by execution of an exception process. (S14, operation determination unit 22).

  If it is accompanied by execution of exception processing (S14: Yes), the operation determination result is converted into XML data to generate conversion data (exception processing information) (S15, data conversion unit 23). In addition, the DVR application 69 collects the imaging results of the clerk monitoring camera 3 (S16, imaging result acquisition unit 25). Thereafter, the upper layer transmission unit 68 transmits the converted data (exception processing information) and the imaging result to the store management server 5 (S17, converted data output unit 24). On the other hand, if it is not accompanied by the execution of exception processing (S14: No), the operation determination result is converted into XML data to generate conversion data (normal processing information) (S18, data conversion unit 23), upper layer The converted data is transmitted to the store management server 5 by the transmitting unit 68 (S19, converted data output unit 24).

  In S <b> 16, the DVR application 69 may collect the imaging results according to the operation determination result by the data tap semantic analysis unit 67. Specifically, the imaging time to be collected (predetermined time before and after the determination time of the operation determination unit 22) is determined according to the contents of the transaction data (for example, the type of exception processing, the transaction amount, etc.) You may collect the imaging result within imaging time. According to this configuration, the imaging result suitable for the type of exception processing and the transaction amount (for example, when the transaction amount is large, the importance is increased and the imaging time is set longer) is transmitted to the store management server 5. can do.

  As described above, according to the receipt printer 2 of the first embodiment, the operation of the POS terminal 1 is determined based on the output data output from the POS terminal 1, and the determination result is output to the store management server 5. Therefore, the operation of the POS terminal 1 can be detected without requiring modification of the POS terminal 1. Thereby, since it is not necessary to change the POS application 16, the development burden accompanying the addition of the operation detection function can be greatly reduced, and the cost burden on the retail store side can also be reduced. In general, the file format differs depending on the POS application 16, but the receipt printer 2 of the present embodiment has a data tap conversion function, and therefore can be applied to various POS systems by rewriting the conversion table 66. , Its versatility can be enhanced.

  If it is determined that the operation of the POS terminal 1 is an operation for executing an exception process, exception process information indicating that is recorded in the exception process database 51a, and is stored for each clerk or each customer. Since the report can be output as the total report 50, the total report 50 can be used for educating the store clerk, grasping the customer service situation, detecting fraud. In addition, since the exception processing information is stored in the exception processing database 51a in association with the imaging result of the clerk monitoring camera 3, by printing the imaging result including the imaging result, the administrator can The situation when exception handling occurs can be grasped in more detail. Furthermore, since the imaging time to be recorded can be determined according to the type of exception processing and the transaction amount, it is possible to maintain the imaging results for the appropriate imaging time according to each transaction, It can be used as useful evidence when verifying.

  In the above embodiment, the information processing apparatus of the present invention is built in the receipt printer 2, but a part or all of the information excluding the printing unit 26 is an external device other than the receipt printer 2 or a store management server. 5 may be realized. For example, the imaging result of the clerk monitoring camera 3 is configured to be transmitted to the store management server 5 via the receipt printer 2, but the store management server 5 may be configured to directly acquire the imaging result. In this case, the DVR application 69 is installed in the store management server 5. Moreover, you may implement | achieve each part of the shop management server 5 with a POS system or a WWW server.

  Further, in the above embodiment, the conversion data is transmitted to the store management server 5 during all the accounting processes. However, the conversion data may be transmitted only when an exception process occurs. In addition, when exception processing occurs, it is described that the imaging result of the imaging time according to the exception processing type and transaction amount may be transmitted together with the conversion data, but it is the same regardless of the exception processing type and transaction amount. You may transmit the imaging result of imaging time. Furthermore, the imaging result may be transmitted together with the conversion data not only when exception processing occurs but also when normal processing occurs.

  In the above embodiment, the conversion data format is described as XML data, but another format such as CSV (Comma Separated Values) may be used.

[Second Embodiment]
Next, a second embodiment of the present invention will be described with reference to FIGS. An object of the present embodiment is to efficiently record monitoring data (corresponding to the imaging result of the first embodiment) useful as evidence of fraud by accurately specifying the occurrence of exception processing. A method for detecting the occurrence of exception processing will be described in detail. In the present embodiment, the same components as those in the first embodiment are denoted by the same reference numerals, and detailed description thereof is omitted. Moreover, the modification applied about the component similar to 1st Embodiment is applied similarly about this embodiment.

  FIG. 8 is a functional block diagram of the store monitoring system SY2 according to the second embodiment. The store monitoring system SY2 of this embodiment includes a POS terminal 1, a receipt printer 2, a receipt scanner 9 that reads a receipt R, an in-store monitoring camera 10 that monitors the store, and a store management server 5 that supervises the store monitoring system SY2. (External device). Although the system configuration is not particularly illustrated, the POS terminal 1 and the receipt printer 2, and the receipt printer 2 and the receipt scanner 9 are communicably connected via a serial interface. In the present embodiment, the imaging result of the in-store monitoring camera 10 is directly transmitted to the store management server 5 via the in-store LAN 6 (see FIG. 1). As indicated by the dotted frame, the receipt printer 2, the receipt scanner 9, and the store management server 5 constitute an information processing apparatus A2.

  The receipt scanner 9 has a reading unit 91 as a main functional configuration. The reading unit 91 reads the receipt R presented by the customer when a return process, a miss registration process, or the like occurs. Although details will be described later, in the present embodiment, exception processing can be detected by reading the receipt R.

  The POS terminal 1 includes an accounting processing unit 11, a reading result acquisition unit 12, an accounting processing information reading unit 13, and a re-registration unit 14 as main functional configurations. The accounting processing unit 11 executes accounting processing and outputs accounting information (corresponding to the output data of the first embodiment) as a result of the processing to the receipt printer 2.

  The reading result acquisition unit 12 reads the receipt R reading result (information such as transaction number, product code, product name, quantity, price, transaction occurrence date, clerk ID, POS terminal ID) by the receipt scanner 9 (reading unit 91). get. The accounting processing information reading unit 13 reads out the corresponding accounting processing information (transaction data) from the accounting processing database 51b (see FIG. 6) based on the reading result of the receipt R acquired by the reading result acquiring unit 12. The re-registration unit 14 is for changing only a part of the accounting process information read by the accounting process information reading unit 13 and re-registering it in the accounting process database 51b, and includes a concept including operation means such as a keyboard. It is. In this way, when canceling the accounting process after the accounting process, the store clerk can save the trouble of re-inputting the product described in the receipt R, so that the efficiency of the accounting process can be improved.

  On the other hand, the receipt printer 2 includes an accounting information acquisition unit 71, an exception processing occurrence detection unit 72, a printing unit 26, and a reading result output unit 74 as main functional configurations. The transaction information acquisition unit 71 acquires the transaction information output from the POS terminal 1 (accounting processing unit 11).

  The exception processing occurrence detection unit 72 detects the occurrence of exception processing by acquiring accounting information including information indicating exception processing by the accounting information acquisition unit 71. Although illustration of the customer display 4 (see FIG. 2 and the like) is omitted in FIG. 8, the occurrence of exception processing may be detected from display data to be displayed on the customer display 4. Further, as described above, the exception processing occurrence detection unit 72 also detects the occurrence of exception processing by reading the receipt R by the receipt scanner 9 (reading unit 91).

  The printing unit 26 prints the transaction information acquired by the transaction information acquisition unit 71 on a receipt sheet and issues a receipt R. When the receipt R 9 is read by the receipt scanner 9, the reading result output unit 74 outputs the reading result to the POS terminal 1.

  The in-store monitoring camera 10 has an imaging unit 32 (monitoring unit) as a main functional configuration. A plurality of in-store monitoring cameras 10 are arranged in the store, such as around the cashier counter 7 or in the store entrance. The imaging data of each in-store monitoring camera 10 is associated with information such as a camera ID for identifying each in-store monitoring camera 10 and an imaging date and time, and monitoring data (a monitoring result, corresponding to the imaging result of the first embodiment). Is output to the store management server 5.

  The store management server 5 includes a monitoring data acquisition unit 81, a specific behavior determination unit 82, a recording control unit 83, a storage unit 80, and a monitoring data search unit 86 as main functional configurations. The storage unit 80 includes a sub storage unit 84 (buffer) that stores the monitoring data for a predetermined time while the imaging unit 32 performs imaging, and stores the monitoring data stored in the sub storage unit 84. And a main storage unit 85 that stores a part of it in a nonvolatile manner.

  The monitoring data acquisition unit 81 acquires monitoring data from a plurality of in-store monitoring cameras 10 (imaging units 32) in real time. The specific behavior determination unit 82 determines at least one specific behavior of the clerk and the customer from the monitoring result acquired by the monitoring data acquisition unit 81. In other words, suspicious behavior such as a store clerk looking around (scratching) or a specific behavior that is often seen with exception processing is determined, such as a customer moving directly from the store entrance to the cashier counter 7.

  The recording control unit 83 controls the monitoring data recording to the main storage unit 85. Specifically, when the specific action is determined by the specific action determination unit 82, monitoring data for a predetermined time (L time) with respect to the specific action determination time is recorded in the main storage unit 85. In addition, even when the occurrence of exception processing is detected by the exception processing occurrence detection unit 72, the recording control unit 83 stores monitoring data for a predetermined time (N hours) with reference to the time when the occurrence of exception processing is detected. Record in the storage unit 85. In this case, the recording control unit 83 can record the monitoring data for a predetermined time including the monitoring data before the occurrence detection of the exception processing from the monitoring data stored in the sub storage unit 84 in the main storage unit 85. is there.

  Note that the L and N values of the “predetermined time (L time) based on the specific action determination time” and the “predetermined time (N time) based on the detection of occurrence of exception processing” are arbitrarily determined by the user. It can be set. “Monitoring data for a predetermined time (L hours) based on the specific action determination time” is monitoring data having a start time P hours before the specific action determination (however, 0 <P ≦ L). The value of P in this case can be arbitrarily set by the user. Similarly, “monitoring data for a predetermined time (N hours) with reference to the time when occurrence of exception processing is detected” starts M hours before the occurrence of exception processing (where 0 <M ≦ N). May be set as monitoring data, and the value of M in this case can be arbitrarily set by the user.

  By the way, the recording control unit 83 adds tag information indicating a situation at the time of exception processing occurrence or specific action determination to the monitoring data for the predetermined time, and causes the main storage unit 85 to store the tag information. Specifically, the tag information includes the exception processing type (transaction type), the position of the store clerk in the store, the presence or absence of customers around the cashier counter 7, the voice data in the store including the cashier counter 7, the exception processing occurrence date and time ( Transaction occurrence date / time), specific action determination date / time, etc. In addition, as the tag information, each item of the receipt R read result by the reading unit 91 and each item of the exception handling information shown in the first embodiment (see FIG. 5 and the like) can be used.

  The “location of the store clerk in the store” is specified by performing face authentication using the image data of the in-store monitoring camera 10 and comparing it with the face image of the store clerk stored in the face authentication database (not shown). Is possible. Further, a plurality of RFID (Radio Frequency Identification) readers are arranged in the store, and each store clerk in the store is allowed to have the store clerk card 200 (see FIG. 13B) incorporating the RFID. The position of may be specified. In this case, it is assumed that the store clerk card 200 is provided with a storage unit 201 (IC chip) in which a store clerk ID is recorded and a wireless communication unit 202 (antenna) for wireless communication with an RFID reader. The RFID reader communicates with the receipt printer 2 or the store management server 5 connected to the in-store LAN 6 via a wireless LAN router (not shown) or the like. In addition, the store clerk may have an electronic device equipped with a GPS (Global Positioning System) antenna to identify the position of each store clerk in the store.

  Further, “the presence / absence of customers around the cashier counter” can be determined by analyzing the image data of the in-store monitoring camera 10. Furthermore, “voice data in the store including around the cashier counter” can use the voice analysis result by arranging a plurality of microphones in the store such as around the cashier counter 7.

  The monitoring data search unit 86 searches for monitoring data using tag information added to the monitoring data, and is a concept including operation means such as a keyboard and a mouse. By specifying a store clerk ID or exception processing type as a search key of the monitoring data search unit 86, it is possible to print a summary report 50 (see FIGS. 20 to 22) described later in the third embodiment. It is.

  Next, the control method of the recording control unit 83 will be described in detail with reference to the flowcharts of FIGS. As described above, the recording control unit 83 records monitoring data in the main storage unit 85 using the acquisition of transaction information, reading of the receipt R, and detection of specific behavior as triggers. Therefore, each case of the monitoring data recording process will be described.

  FIG. 9 is a flowchart showing monitoring data recording processing triggered by acquisition of accounting information by the information processing apparatus A2. First, when the receipt printer 2 acquires accounting information from the POS terminal 1 (S21, accounting information acquisition unit 71), occurrence of exception processing occurs depending on whether or not the accounting information includes information indicating exception processing. Presence / absence is determined (S22, exception processing occurrence detection unit 72). Here, when occurrence of exception processing is detected (S22: Yes), the type of exception processing is further determined (S23, exception processing occurrence detection unit 72).

  The store management server 5 collects tag information at the time of occurrence of exception processing according to the type of exception processing determined by the receipt printer 2 (S24, recording control unit 83). For example, in the case of “cancellation processing” or “return processing”, as the tag information, the position of the store clerk in the store and the presence / absence of customers around the cashier counter 7 are collected, and in the case of “discount processing” or “discount processing” As the tag information, it is conceivable to collect audio data in the store including around the cashier counter 7. The presence or absence of customers around the cashier counter 7 can be determined by face detection by the in-store monitoring camera 10 or a human sensor using infrared rays, and the determination result is collected as tag information. As for the voice data in the store, the voice recognition results of the cashier counter 7 and the microphone arranged in the store are collected as tag information.

  Furthermore, the store management server 5 records the monitoring data for a predetermined time according to the type of exception processing determined by the receipt printer 2 together with the tag information (S25, recording control unit 83). For example, in the case of “cancellation processing” and “return processing”, monitoring data is recorded for 20 seconds before and after the exception processing is detected (total of 40 seconds), and in the case of “discount processing” and “discount processing” It is conceivable to record monitoring data for 30 seconds after the processing is detected. At this time, the recording control unit 83 reads out necessary monitoring data from the monitoring data stored in the sub storage unit 84 and stores it in the main storage unit 85.

  On the other hand, in S22, when the receipt printer 2 does not detect the occurrence of the exception process (S22: No), since the command is not transmitted from the receipt printer 2 to the store management server 5, the store management server 5 records the monitoring data. The process ends without being performed.

  In the above example, tag information is collected according to the type of exception processing, or the imaging time of monitoring data is determined according to the type of exception processing, but the same regardless of the type of exception processing. Tag information may be collected, or the imaging time of monitoring data may be set to the same time.

  FIG. 10 is a flowchart showing the monitoring data recording process triggered by reading of the receipt R and the receipt content changing process of the POS terminal 1 by the information processing apparatus A2. This example is a process in a case where an exception process that requires the customer to present a receipt R such as a “cancel process” or “return process” is performed. Further, in the figure, the parallelogram frame indicates that the process involves a store clerk's operation.

  The receipt printer 2 acquires the reading result of the receipt R from the receipt scanner 9 (S31), and detects the occurrence of exception processing (S32, exception processing occurrence detection unit 72). Further, the receipt R reading result is output to the POS terminal 1 (S33, reading result output unit 74).

  Further, the store management server 5 collects tag information when the receipt R is read (≈when exception processing occurs) (S34, recording control unit 83). In this case, it is conceivable to collect information such as the date and time when exception processing occurred as tag information. Further, the store management server 5 records monitoring data for a predetermined time with reference to the time when the receipt R is read together with the tag information (S35, recording control unit 83). Here, for example, 20 seconds before the receipt R is read as the reading start timing, and monitoring data with a recording time of 60 seconds may be recorded.

  On the other hand, when the POS terminal 1 obtains the reading result of the receipt R from the receipt printer 2 (S36, the reading result obtaining unit 12), a “cancel key” (a predetermined key provided on the keyboard of the POS terminal 1) by the store clerk. When pressed (S37), the corresponding accounting process information (transaction data) is read out from the accounting process database 51b (see FIG. 6) (S38, accounting process information reading unit 13). Thereafter, the receipt contents are changed by the store clerk, and the accounting process information is re-registered (S39, re-registration unit 14). A new receipt R is issued along with the re-registration, but the description of the process is omitted.

  FIG. 11 is a flowchart showing monitoring data recording processing triggered by detection of a specific behavior of a store clerk or customer by the information processing apparatus A2. In this example, all processes are executed by the store management server 5. When the store management server 5 detects the specific behavior of the clerk and / or customer from the acquired monitoring data (S41: Yes), the store management server 5 determines the occurrence detection pattern of the specific behavior (S42, specific behavior determination unit 82). The “specific behavior occurrence detection pattern” will be described later with reference to FIG. Thereafter, tag information is collected according to the occurrence detection pattern of the specific action (S43, recording control unit 83), and monitoring data for a predetermined time according to the occurrence detection pattern of the specific action is recorded together with the tag information. (S44, recording control unit 83).

  On the other hand, when the specific behavior of the store clerk and / or the customer is not detected in S41 (S41: No), the store management server 5 ends the process without recording the monitoring data.

  In the above example, tag information is collected according to the occurrence detection pattern of the specific action, or the imaging time of the monitoring data is determined according to the occurrence detection pattern of the specific action, but it does not depend on the occurrence detection pattern. The same tag information may be collected, or the imaging time of monitoring data may be set to the same time.

  Next, with reference to FIG. 12 to FIG. 16, the setting of the occurrence detection pattern that triggers the monitoring data recording process will be described. FIG. 12 is a diagram illustrating an example of the exception processing occurrence detection table. The table only needs to be stored so that it can be referred to from both the receipt printer 2 and the store management server 5, and may be stored in any of the receipt printer 2, the store management server 5, and other external devices. Also, the exception processing occurrence detection table can be divided and stored in each device.

  As shown in the figure, the exception process occurrence detection table includes, for each occurrence detection pattern, a pattern ID, an exception process occurrence detection pattern (an event that triggers the monitoring data recording process), the necessity of a detection target, Recording start timing and recording time (imaging time) are stored in association with each other. For example, in the example shown in the figure, the necessity of the detection target is “O” in “Pattern ID: a1” and “Pattern ID: a2”, so when accounting information indicating exception processing is acquired (pattern When the receipt R is read by the receipt scanner 9 (pattern ID: a2), the occurrence of exception processing is detected. “Pattern ID: a1” corresponds to the flowchart shown in FIG. 9, and “Pattern ID: a2” corresponds to the flowchart shown in FIG.

  In addition, when accounting information indicating exception processing is acquired, the recording start timing and recording time are “according to the type of exception processing”, respectively. Follow start timing and recording time. Further, when the receipt R is read, the monitoring data having a recording time of 60 seconds is read from the sub storage unit 84 and stored in the main storage unit 85 as the reading start timing 20 seconds before the receipt R is read. .

  Other exception detection occurrence detection patterns include button operation of the receipt printer 2 (pattern ID: a3), button operation of the clerk card 200 (pattern ID: a4), and a product or receipt R placed by a weight sensor (not shown). Placement detection (pattern ID: a5), product or receipt R placement detection by image recognition (pattern ID: a6), exception processing keyword detection by voice recognition (pattern ID: a7), normal processing keyword non-detection by voice recognition Detection (pattern ID: a8), LED extinction detection (pattern ID: a9), and the like can be set.

  As for “pattern ID: a3”, as shown in FIG. 13A, it is assumed that the receipt printer 2 is provided with an operation unit 75 that can be operated by a store clerk or a customer. The operation unit 75 is operated when a store clerk or a customer determines that an exception process has occurred, and the operation result is output to the exception process occurrence detection unit 72. The constituent elements other than the operation unit 75 are the same as those in FIG. As for “pattern ID: a4”, as shown in FIG. 13B, the clerk ID storage unit 201 in which the clerk ID is recorded on the clerk card 200 possessed by the clerk and the receipt printer 2 are wirelessly communicated. It is assumed that a wireless communication unit 202 for performing the operation and an operation unit 203 that can be operated by a store clerk are provided. The operation unit 203 is operated by the store clerk when it is determined that an exception process has occurred, and the operation result is sent to the radio communication unit 202 together with the store clerk ID read from the store clerk ID storage unit 201. To the exception processing occurrence detection unit 72 of the receipt printer 2. The exception processing occurrence detection unit 72 detects the occurrence of exception processing based on the operation result of the clerk card 200 when the received clerk ID matches the operator of the receipt printer 2 (the cashier person in charge). In this way, by setting “pattern ID: a3” and “pattern ID: a4” as detection targets, even when the exception processing operation is postponed due to congestion of the cash register, the exception processing is surely performed. The occurrence can be detected. Further, for “pattern ID: a4”, since the clerk ID is determined, the receipt printer 2 does not receive the operation result of the clerk card 200 at the adjacent register counter 7 by mistake.

  The “pattern ID: a5” is premised on the configuration shown in FIG. That is, together with the POS terminal 1 and the receipt printer 2, a predetermined placement unit 211 for placing the product or the receipt R, and detecting that the product or the receipt R is placed on the predetermined placement unit 211 are detected. It is assumed that the weight sensor 212 (placement detection unit) is provided on the register counter 7 and the receipt printer 2 and the weight sensor 212 are serially connected. The weight sensor 212 is a sheet-type weight measuring device, and outputs a detection result to the exception processing occurrence detection unit 72 of the receipt printer 2 when a product or the like is placed. Although “pattern ID: a6” is not particularly illustrated, a predetermined placement portion for placing the product or the receipt R and the product or the receipt R are placed on the predetermined placement portion. And a camera for recognizing the image by discriminating the image difference before and after placement (a placement detection unit to which the in-store monitoring camera 10 may be applied) is provided, and the receipt printer 2 acquires the detection result. It is assumed that it is possible. As described above, by detecting “pattern ID: a5” and “pattern ID: a6”, it is possible to quickly detect the occurrence of exceptional processing such as return or exchange of goods, cancellation or correction of receipt R, and the like. Can do.

  For “pattern ID: a7” and “pattern ID: a8”, a microphone (sound acquisition unit) that acquires sound around the register counter 7 and a sound recognition unit (not shown) that recognizes the acquired sound are provided. It is assumed that the receipt printer 2 can obtain the recognition result. In this way, by setting “pattern ID: a7” as a detection target, a predetermined keyword (for example, “incorrect”, “please return goods”, etc.) uttered by the store clerk or the customer at the time of exception processing, etc. Exception processing keywords) can be recognized and the occurrence of exception processing can be detected quickly. Further, by setting “pattern ID: a8” as a detection target, non-recognition of a predetermined keyword (for example, a normal processing keyword such as “to ga dot”) uttered during normal processing by a store clerk or a customer The occurrence of exception handling can be detected quickly.

  The “pattern ID: a9” is premised on the configuration shown in FIG. That is, together with the POS terminal 1 and the receipt printer 2, an LED floodlight 221 that can block the light by a product, a receipt R, or a hand, and an LED light receiver 222 that receives the light of the LED are a register counter 7 It is a premise that the receipt printer 2 and the LED light receiver 222 are serially connected. When the LED light receiver 222 detects that the light projected from the LED light projector 221 is blocked by any object placed on the predetermined placement unit 211, the detection result of the receipt printer 2 is detected. To the unit 72. As described above, by setting “pattern ID: a9” as a detection target, a store clerk or a customer can detect the occurrence of exception processing by using appropriate means such as a product, a receipt R, or a hand as needed. .

  Note that the exception processing occurrence detection table shown in FIG. 12 can be changed as appropriate by operating the store management server 5 or the like. In other words, it is possible to appropriately change the occurrence detection pattern to be detected, and the recording start timing and recording time of the monitoring data when the exception process is detected.

  Next, the specific behavior occurrence detection table will be described with reference to FIG. It is assumed that the table is stored in the store management server 5. Further, the contents can be appropriately changed by operating the store management server 5 or the like, similar to the exception processing occurrence detection table.

  As shown in the figure, the specific action occurrence detection table includes, for each occurrence detection pattern, a pattern ID, a specific action occurrence detection pattern (an event that triggers the monitoring data recording process), the necessity of a detection target, Recording start timing and recording time are stored in association with each other. For example, in the example shown in the figure, the necessity of the detection target is “◯” in “Pattern ID: b1” and “Pattern ID: b2”, so when the customer moves directly from the entrance to the cash register ( When a customer interrupts despite the presence of a pattern ID: b1) and a cashier queue (pattern ID: b2), the occurrence of a specific action is detected. These can be detected by performing customer face authentication with the in-store monitoring camera 10 and tracking the movement of the customer. In other words, a moving area is detected by taking a difference between frames per unit time from the monitoring data acquired from the in-store monitoring camera 10, and face detection is performed on the moving area (confirms that there is no portion corresponding to the face feature amount). ). As a result, the part where the face can be detected is determined as a person, and the determined individual is tracked. Further, when a plurality of RFID readers are arranged in the store, the customer can detect the position of the customer by holding the membership card in which the RFID is incorporated.

  In addition, as the occurrence detection pattern of the specific behavior, the customer handed the product or the receipt R to the clerk (pattern ID: b3), the clerk looked around (pattern ID: b4), and the clerk to the cashier counter 7 Can be set (pattern ID: b5).

  Here, the detection process of “pattern ID: b3” will be described with reference to the flowchart of FIG. The store management server 5 (specific behavior determination unit 82) performs face detection and face recognition of the clerk from the monitoring result of the in-store monitoring camera 10 (S51), and specifies the position of the clerk (S52). Similarly, the face detection and face recognition of the customer are performed from the monitoring result of the in-store monitoring camera 10 (S53), and the position of the customer is specified (S54). Furthermore, the movement of the customer's hand is traced (S55), and when it is determined that the customer has moved the hand toward the store clerk (S56), it is determined from the determination result that the product or the receipt R has been delivered ( S57). In this way, by setting “pattern ID: b3” as a detection target, it is possible to detect a characteristic operation of exception processing by a store clerk and a customer as a specific action. For “pattern ID: b4”, by repeating the process of detecting the moving area from the monitoring result of the in-store monitoring camera 10 and detecting the face of the person from the moving area, the movement of the clerk (head of the head) Position change). Thereby, when the position change of the head is severe (in the case of a movement looking around), it can be determined that there is a high possibility that the surroundings are looked around, that is, an illegal act is performed.

  For “pattern ID: b5”, it is determined from the in-store monitoring camera 10 that images the cashier counter 7 whether or not the same store clerk is continuously detected. Thereby, for example, an unnatural action such as going back and forth around the cashier counter 7 can be easily detected. Further, when a plurality of RFID readers are arranged in the store, such a store clerk's behavior can be detected by requiring the store clerk to have the store clerk card 200 in which the RFID is incorporated.

  As described above, according to the information processing apparatus A2 of the second embodiment, the occurrence of exception processing is detected, and monitoring data for a predetermined time with respect to the time of occurrence detection of the exception processing is recorded. Necessary monitoring data recording can be prevented. As a result, only monitoring data useful as evidence of fraud can be recorded, and thus fraud can be detected more efficiently. In addition, while the in-store monitoring camera 10 is being monitored, the sub-storage unit 84 that stores the monitoring data for a predetermined time while being updated as needed is provided, so that monitoring data before detection of occurrence of exception processing is also recorded. be able to. Thereby, even if it is a fraudulent act that the monitoring data before the occurrence of exception processing is considered to be important, it can be detected without any trouble.

  Further, not only when the occurrence of an exception process is detected, but also when a specific action of a store clerk or a customer is determined, monitoring data for a predetermined time based on the specific action determination time can be recorded. As a result, a store manager or the like can efficiently confirm fraud.

  Moreover, since the exception detection / specific behavior occurrence detection pattern that triggers the monitoring data recording process can be customized according to the store, it is convenient. Further, since the recording start timing and recording time can be set for each occurrence detection pattern, the convenience is further improved.

  The exception processing occurrence detection unit 72 of the above embodiment detects the occurrence of exception processing by acquiring accounting information including information indicating exception processing by the accounting information acquisition unit 71. However, in the POS terminal 1, When the receipt printer 2 can recognize that a key operation that triggers exception processing such as “cancel key” has been performed, the occurrence of exception processing may be detected by recognizing the key operation.

  In the above embodiment, the information processing apparatus A2 is configured by the receipt printer 2, the receipt scanner 9, and the store management server 5, but the store management server 5 may be omitted. In this case, the receipt printer 2 includes each part of the store management server 5. Further, each unit of the information processing device A2 may be provided in the POS terminal 1, or the storage unit 80 may be provided outside the information processing device A2.

  Further, in the above embodiment, the imaging result of the in-store monitoring camera 10 is recorded as the monitoring data. However, when the store clerk and / or the customer is monitored by the RFID reader (the monitoring unit in the claims is configured by the RFID reader) When read), the reading results of a plurality of RFID readers arranged in the store may be recorded as monitoring data. In addition, when the clerk and / or customer is monitored using GPS (when the monitoring unit in the claims is configured by a GPS data detection device), the GPS data (sales clerk and / or customer location information) is monitored. It may be recorded as data.

  Further, in the above embodiment, the case where the re-registration of the accounting process information is performed by using the read result of the receipt R (see FIG. 10), but a double hit due to an operation error occurs as an exception process. When this is detected, it may be possible to restore the state immediately before the error has occurred based on registered information in an accounting processing buffer (not shown) by pressing a predetermined button provided on the receipt printer 2. . Note that the occurrence of double hitting may be detected automatically by the receipt printer 2 side that the same product data is continuously input, or may be detected by operation of an operation unit (not shown) by a store clerk. In this case, the store clerk can perform the miss-registration process and the correct payment process at once by deleting only the duplicated products on the POS terminal 1 side.

[Third Embodiment]
Next, a third embodiment of the present invention will be described with reference to FIGS. An object of the present embodiment is to create a summary report 50 for easily and quickly determining fraudulent behavior of a store clerk and / or a customer. In the present embodiment, the same components as those in the above-described embodiments are denoted by the same reference numerals, and detailed description thereof is omitted. Moreover, the modification applied about the component similar to said each embodiment is applied similarly about this embodiment.

  FIG. 17 is a functional block diagram of the store monitoring system SY3 according to the third embodiment. The store monitoring system SY3 of this embodiment includes a POS terminal 1, a receipt printer 2, a store clerk monitoring camera 3 that monitors store clerk, and a store management server 5 that controls the store monitoring system SY3. As in the above-described embodiments, the POS terminal 1 and the receipt printer 2 are communicably connected via a serial interface. In addition, the imaging result of the clerk monitoring camera 3 is transmitted to the store management server 5 via the in-store LAN 6 (see FIG. 1). In the present embodiment, as indicated by the dotted frame, the information processing apparatus A3 is configured by the receipt printer 2 and the store management server 5.

  The POS terminal 1 has an accounting processing unit 11 as a main functional configuration. Further, the clerk monitoring camera 3 has an imaging unit 31 as a main functional configuration. Similar to the first embodiment, the imaging unit 31 is installed around the cashier counter 7 and images a store clerk, a customer, a product on the cashier counter 7, and the like. Imaging by the imaging unit 31 is always performed, and the imaging result is stored in the database 103 described later. At the time of accounting processing (including exception processing and purchase (checkout processing)), the imaging results at the time of each accounting processing (the imaging data for a predetermined time before and after the accounting processing) And is stored in the database 103 in association with the transaction data. The imaging unit 31 can capture moving images and still images. However, only a moving image may be imaged and one of the frames may be used as a still image.

  The receipt printer 2 includes a transaction information acquisition unit 71, a clerk / customer determination unit 92, and a printing unit 26 as main functional configurations. The accounting information acquisition unit 71 acquires accounting information from the POS terminal 1 (accounting processing unit 11).

  The store clerk / customer determination unit 92 determines at least one of a store clerk operating the POS terminal 1 and a customer at the time of transaction processing. In this embodiment, a clerk and / or a customer is determined based on information such as a clerk ID and a customer ID included in the acquired accounting information. In addition, when the store clerk possesses the store clerk card 200 (see FIG. 13B) and the customer possesses the membership card, the store clerk and / or the customer are identified based on the reading result of the RFID reader. You may judge. Furthermore, face authentication may be performed from the imaging result of the in-store monitoring camera 10, and the store clerk and / or customer may be determined based on the authentication result. As for face authentication, based on the face feature quantity, is it the same person as the person recorded in the face authentication database (the database in which the face feature quantity of a store clerk or customer is recorded, not shown)? It is possible to determine whether or not. The extraction of the facial feature amount will be described later with reference to FIG.

  The printing unit 26 prints the transaction information acquired by the transaction information acquisition unit 71 on a receipt sheet and issues a receipt R.

  On the other hand, the store management server 5 includes an exception processing information recording unit 101, a purchase information recording unit 102, a database 103, a fraud determination unit 104, a history information output unit 105, a search key designating unit 106, and an exception as main functional configurations. A processing information extraction unit 107 is included.

  The exception processing information recording unit 101, when the accounting information acquired by the accounting information acquisition unit 71 includes information indicating exception processing, the salesclerk ID of the salesclerk determined by the salesclerk / customer determination unit 92 or the customer ID of the customer Exception processing information associating predetermined items (including transaction data) including the exception processing type is generated and recorded in the database 103. That is, the exception processing information recording unit 101 generates exception processing information and records it in the database 103 only when exception processing occurs.

  The purchase time information recording unit 102 records purchase time information (corresponding to transaction data), which is the transaction information acquired by the transaction information acquisition unit 71 at the time of product purchase, in the database 103.

  The recording control unit 83 can function in the same manner as in the second embodiment. In other words, the sub-storage unit 84 (buffer) (not shown) stores imaging data for a predetermined time while being updated as needed, and the recording control unit 83 reads a part of the imaging data stored in the sub-storage unit 84. Thus, it can be recorded in the database 103 corresponding to the main storage unit 85. Note that the recording control unit 83 of the present embodiment adds customer data (color feature amount and face feature amount) obtained from the imaging result when the imaging result of the imaging unit 31 includes a person in the imaging result. Record in the base 103. The extraction of color feature amounts and face feature amounts will be described later with reference to FIG.

  As described above, the database 103 stores the exception processing information and the imaging result of the imaging unit 31 at the time of exception processing in association with each other, and stores the purchase time information and the imaging result of the imaging unit 31 at the time of purchase in association with each other. .

  The fraud determination unit 104 determines the possibility of fraud of at least one of the store clerk and the customer from the monitoring result of the imaging unit 31. For example, with regard to fraudulent clerk, among the specific behavior occurrence detection patterns shown in the second embodiment, “the clerk looked around (pattern ID: b4)” or “the clerk went in and out of the cashier many times. If (pattern ID: b5) "is detected, it can be determined that there is a possibility of fraud. Further, regarding customer fraud, for example, if it is detected that a product is taken away without going through the cashier counter 7, it can be determined that there is a possibility of fraud.

  In addition, the fraud determination unit 104 confirms that the customer at the time of return of the product and the customer at the time of purchase are not the same person, that there is no customer before the cashier counter 7 at the time of accounting processing, and that a specific person (for example, an employee) If it is detected that the customer at the time of the specific discount processing for discounting the product does not correspond to a specific person, it is determined that there is a possibility of fraud. Note that these determination processes will be described later with reference to FIG.

  When the accounting information acquired by the accounting information acquisition unit 71 includes information indicating exception processing and the fraud determination unit 104 determines that there is a possibility of fraud, the history information output unit 105 The exception processing information is totaled and a total report 50 is output. The history information output unit 105 also outputs a summary report 50 when a search key is specified by a search key specifying unit 106 described later. In this embodiment, the output method is assumed to be print output and transmission to an administrator (such as a store manager) using e-mail or a Web application. Although details will be described later, the totaling report 50 also prints / displays the imaging result of the imaging unit 31 associated with each exception processing information.

  The search key designating unit 106 designates a search key for outputting the total report 50 and is a concept including operation means such as a keyboard and a mouse. The search key includes the store clerk ID, customer ID, exception processing type, exception processing date and time, exception processing number, product subject to exception processing, presence / absence of customers in front of the cashier counter 7, the location of the cashier, and the area around the cashier counter 7 It is possible to specify information that can be specified from exception processing information, such as in-store audio data and imaging data, and information that can be specified from the imaging result of the imaging unit 31 (such as tag information shown in the second embodiment).

  The exception processing information extraction unit 107 extracts exception processing information corresponding to the search key specified by the search key specifying unit 106 from the database 103. At this time, if a plurality of items (for example, a store clerk ID and a customer ID) are specified, the exception processing information is extracted using them as the and condition or the or condition. The history information output unit 105 aggregates the exception processing information extracted by the exception processing information extraction unit 107 and outputs the history information.

  Next, the data recording process by the information processing apparatus A3 will be described with reference to the flowchart of FIG. This process is a process of recording customer data (color feature amount and face feature amount) necessary to determine whether the customer at the time of return and the customer at the time of purchase are the same person.

  When the receipt printer 2 acquires transaction information (S61, transaction information acquisition unit 71), the store management server 5 acquires imaging data of the in-store monitoring camera 10 (S62). Then, the recording control unit 83 extracts a difference between frames and a background difference (S63), and detects a moving area from the extraction result (S64). Further, face detection is performed from the detected moving area (S65), and the color feature amount of the clothing portion is extracted (S66). Further, the image of the face part subjected to the face detection is normalized (S67), and the face feature amount is extracted (S68). Thereafter, the extracted color feature value and face feature value are recorded in the database 103 together with the imaging result as customer data (S69).

  The face feature amount is also used to determine whether or not the customer at the time of the specific discount process corresponds to a specific person. The face feature amount in this case may be calculated in advance from a face image (photograph) of a specific person and stored in a face feature amount database (not shown). In this embodiment, it is assumed that “employee” is a specific person and fraud at the time of employee discount processing is determined.

  Next, a summary report creation process by the information processing apparatus A3 will be described with reference to a flowchart of FIG. This process is a process of creating a summary report 50 that is output when it is determined that there is a possibility of fraud of a store clerk or a customer. As described above, when it is determined that there is a possibility of fraud of a store clerk or a customer at the time of exception processing, the total report 50 is output. Therefore, the accounting information that triggers the processing includes information indicating exception processing. It is assumed that it is included.

  When the receipt printer 2 acquires transaction information (S71, transaction information acquisition unit 71), the store management server 5 generates exception processing information and records it in the database 103 (S72, exception processing information recording unit 101). Further, the fraud determination unit 104 determines the type of exception processing as described below, and determines the possibility of fraud according to the type.

  For example, when the type of exception processing is “returned” (S73: Yes), customer data (color feature amount and face feature amount) at the time of return processing and customer data (color feature amount and Facial feature amount) is acquired (S74), and the two are compared (S75). As a result, it is determined whether the customer at the time of return and the customer at the time of purchase are the same person (S76). If they are the same person (S76: Yes), it is determined that there is no possibility of fraud. finish. If they are not the same person (S76: No), it is determined that there is a possibility of fraud, and the history information output unit 105 acquires the image data and exception processing information (return history) of the corresponding customer from the database 103. Then, a summary report 50 is created (S78).

  On the other hand, when the type of the exception process is “miss registration” (S79: Yes), the fraud determination unit 104 acquires the face detection result based on the imaging data of the in-store monitoring camera 10 (S80), and before the register counter 7 It is determined whether or not a customer exists (S81). If there is a customer (S81: Yes), it is determined that there is no possibility of fraud and the process is terminated. If there is no customer (S81: No), it is determined that there is a possibility of fraud, and the history information output unit 105 causes the corresponding store clerk and customer image data from the database 103 and the corresponding cashier (clerk). Are acquired (S82), and a summary report 50 is created (S78).

  On the other hand, when the type of exception processing is “employee discount” (S83: Yes), the fraud determination unit 104 obtains discount target person data (face feature amount) from the face feature amount database (S84), and corresponds. It is determined whether the employee is a salesclerk (S85). If it is a corresponding sales clerk (S85: Yes), it is determined that there is no possibility of fraud and the process is terminated. If it is not the corresponding store clerk (S85: No), it is determined that there is a possibility of fraud, and the history information output unit 105 uses the database 103 to store the corresponding store clerk and customer image data and the corresponding cashier (store clerk). ) Is obtained (S86), and a summary report 50 is created (S78).

  Next, the contents of the summary report 50 will be described with reference to FIGS. FIG. 20 is a diagram illustrating an example of a summary report 50a that is output when it is determined that there is a possibility of fraud during the return processing. In this case, in addition to the report issuance date and time and report number, the customer's face image (still image) 121 at the time of return, the customer's face image (still image) 122 at the time of purchase, and a moving image are reproduced. A bar code 123, a return summary 124, a past return status 125 regarding the returned customer, and a video link description 126.

  In the example of the figure, the customer's face image 122 at the time of purchase is not displayed. This means that the information on the receipt R presented at the time of return does not exist in the database 103. For example, this is the case where a return is made using a product purchased at another store and a forged receipt R. Thereby, the administrator who confirms the total report 50a can determine that there is an extremely high possibility that an unauthorized return (fictitious return) has been performed.

  The barcode 123 is for confirming the imaging result of the imaging unit 31 at the time of return. As described in the description 126 of the video link, the barcode 123 is scanned by a barcode reader (not shown). By doing so, an image at the time of return can be displayed on a display (not shown).

  The return summary 124 is information obtained from the exception processing information recorded in the database 103, and includes a return occurrence time (exception processing occurrence date and time), a transaction number, and a return item (a product name of a product to be returned). , Return amount (transaction amount at the time of exception processing), cashier at the time of return (name of store clerk at the time of return processing determined from exception processing information or imaging result), presence / absence of purchase history (to receipt R presented at the time of return) Whether or not transaction data having the same content as the described information exists in the database 103).

  The past return status 125 regarding the returned customer includes the number of returns of the returned customer in the past (for example, within one year), the list of returned items and the ratio thereof, the number of cashiers at the time of returning the returned customer and Percentage, etc. are included. From these pieces of information, the manager can infer the frequency of return and the product that is the subject of the return, and can determine whether or not the return is a fraudulent return conspired by the customer and the store clerk. For example, as shown in the example of FIG. 5, when the cashier at the time of return is a person who has been determined, it can be determined that there is a high possibility that the customer and the store clerk are performing conspiracy and making an illegal return.

  In addition, the customer's face image 122 at the time of purchase is displayed on the total report 50a shown in FIG. 19 (the purchase corresponding history exists), or a plurality of salesclerks as cashiers at the time of return of returned customers. When the name is displayed, the administrator can determine that there is a low possibility of making an illegal return.

  FIG. 20 is a diagram illustrating an example of a summary report 50b that is output when it is determined that there is a possibility of fraud during misregistration processing. In this case, the total report 50b includes a report issuance date and time and a report number, an image (still image) 131 around the register counter 7 when a misregistration occurs, a bar code 132 for reproducing a moving image, and a misregistration overview 133. And a past misregistration occurrence state 134 regarding the cashier charge and a description 135 of the video link. Of these, the barcode 132 is for confirming the imaging result (moving image) of the imaging unit 31 when a misregistration occurs, and this is described in the description 135 of the video link.

  The misregistration summary 133 is information obtained from exception processing information recorded in the database 103, and includes a misregistration occurrence time (exception processing occurrence date and time), a transaction number, a cancellation amount (transaction amount at the time of exception processing), and a misregistration occurrence. The cashier at the time (the name of the store clerk when the misregistration occurs determined from the exception processing information or the imaging result), the presence of the target customer (whether there is a customer before the cashier counter 7 when the misregistration occurs), and the like. . In the example in the figure, the target customer is “None”, and it can be confirmed from the image 131 around the cashier counter 7 when the missed cash register occurs, so it can be determined that there is a high possibility of misregistration fraud. .

  The past misregistration occurrence state 134 regarding the cashier charge includes the total number of misregistrations of the cashier charge in the past (for example, within one year), the total working hours of the cashier charge during the same period (information obtained from the attendance management database not shown) ), The number of misregistration occurrences per unit time (for example, one hour), the misregistration occurrence time zone and its ratio, and the like. From this information, the manager can grasp how much misregistration is in the corresponding cashier in charge, and at what time period there are many misregistrations, so the results can be used as the result of the store clerk's operations. Can be used for education. Furthermore, there is a high possibility of misregistration fraud due to the fact that the number of misregistration occurrences in the situation where the target customer exists is clearly higher than the number of misregistration occurrences in the situation where there is no customer and the misregistration occurrence time is uneven. Judgment can be made.

  In addition, with respect to the total report 50b shown in FIG. 20, the customer 131 is included in the image 131 around the cashier counter 7 when the misregistration occurs (the target customer exists), or the number of misregistration occurrences is biased depending on the presence or absence of the customer. If not, the administrator can determine that the possibility of misregistration fraud is low.

  FIG. 22 is a diagram illustrating an example of a summary report 50c that is output when it is determined that there is a possibility of fraud at the time of employee discount processing. In this case, the total report 50c includes the report issuance date and report number, the customer face image (still image) 141 when the employee discount is generated, and the image (still image) 142 around the register counter 7 when the employee discount is generated. And a bar code 143 for reproducing a moving image at the time of employee discount occurrence, an employee discount summary 144, past employee discount occurrence status 145 related to cashiers, and a video link description 146. The barcode 143 and the video link description 146 are the same as those in the example of FIGS.

  The employee discount summary 144 is information obtained from the exception processing information recorded in the database 103. The employee discount occurrence time (exception processing occurrence date and time), transaction number, purchase amount, discount amount, and cashier in charge when an employee discount occurs (The name of the clerk at the time of employee discount occurrence determined from the exception processing information or the imaging result), the target employee (the name of the employee who is determined to be the same person from the facial feature amount), and the like. In this example, the amount obtained by subtracting the discount amount from the purchase amount is the transaction amount at the time of exception processing. Further, in the example of the figure, since the target employee is “no clerk applicable”, it can be determined that the possibility of unauthorized employee discount is high.

  The past employee discount occurrence status 145 related to the cash register manager includes the total number of discounts of the cash register manager in the past (for example, within one year), the total working hours of the cash register manager during the same period (obtained from the attendance management database not shown). Information), the number of employee discounts per unit time, the number of employee discounts (names and percentages of staff members who were eligible for employee discounts), etc. From these pieces of information, the manager can grasp to what extent the corresponding cash register manager is discounting the employee and to whom the employee is discounted. As a result, it is possible to determine that the possibility of fraudulent employee discount is high because the number of employee discount occurrences per unit time is extremely large and the number of employee discount charge is biased.

  Note that, in the aggregate report 50c shown in FIG. 22, if the number of employee discounts generated per unit time is small or the number of employee discounts is not biased, the administrator determines that the possibility of unauthorized employee discount is low. be able to.

  Incidentally, as described above, the summary report 50 shown in FIG. 20 to FIG. 22 can be output even when the administrator designates the search key at an arbitrary timing. For example, by specifying an exception processing number (transaction number) as a search key, it is possible to output a summary report 50 (any one of 50a, 50b, 50c) corresponding to the type of exception processing. Further, depending on the clerk ID and the exception processing type designation (and conditions), the past misregistration occurrence status 134 (see FIG. 21) related to the cashier charge, the past employee discount occurrence status 145 related to the cashier charge (see FIG. 22), and the like. , And can be output as a summary report 50.

  Further, it is preferable that a list of exception processes determined as “none” as a target customer by specifying presence / absence of a customer in front of the cashier counter 7 as a search key (classified for each store clerk or each exception process type). ) May be output. Furthermore, by specifying the position of the store clerk as a search key, a list of exception processing when the store clerk exists at the specified position (specified cash register counter) (classified by store clerk, customer, or exception processing type) It is also possible to output a total report 50 including (preferably). In this way, the administrator can output the required total report 50 at the required timing by specifying the search key.

  As described above, according to the information processing apparatus A3 of the third embodiment, the exception processing information in which the store clerk ID, the customer ID, and the predetermined items (transaction data) related to the exception processing are associated is recorded in the database 103. Since the exception processing information can be totaled for each clerk ID or customer ID and the total report 50 can be output, the fraudulent behavior of the clerk or customer can be easily and quickly determined from the total result. In other words, the administrator can confirm what kind of exception processing the store clerk or customer has been involved in the past and the number of times based on the output summary report 50, so that the contents are taken into consideration. Thus, it is possible to determine the presence or absence of cheating.

  Further, when it is determined that there is a possibility of fraud from the monitoring result of the store clerk or the customer, the total report 50 can be output without the administrator performing a special operation. In other words, since the administrator does not need to actively execute the search process, the labor required for verifying fraud can be greatly reduced. Further, since the possibility of fraud is objectively determined, it is possible to accurately determine the presence or absence of fraud without depending on the subjectivity or ability of the administrator.

  Further, since the total report 50 can be transmitted to a predetermined administrator using an e-mail or a Web application, history information can be transmitted regardless of the location of the administrator. In addition, the summary report 50 outputs the imaging result of the imaging unit 31 at the time of the accounting process (at the time of purchase or the occurrence of exception processing) together with the history information obtained from the exception processing information. Can be used as material for verifying fraud.

  In addition, since the administrator can check the status of the store clerk and the customer at the time of product purchase or fraud determination from both the still image and the moving image from the total report 50, the situation around the cashier counter 7 can be more accurately detected. Can be grasped. In addition, since the moving image can be reproduced by reading the barcodes 123, 132, and 143, the store manager or the like can quickly confirm the moving image.

  In the above embodiment, the case where the summary report 50 is printed out is illustrated. However, when the history information is output as a web page or the like, the moving image and the barcode 123, 132, 143 are displayed instead of the barcode. A linked icon may be displayed.

  Further, in the above embodiment, the total report 50 is printed from the report output printer 8 connected to the store management server 5, but the total report 50 may be printed by the receipt printer 2. Further, in the case of the total report 50 relating to the clerk of the store clerk, the total report 50 is printed from another receipt printer 2 (connected to the in-store LAN 6) other than the register counter 7 where the fraud is detected. You may do it. According to this configuration, when it is determined that there is a possibility of fraud, fraud verification of a store clerk or a customer can be performed in real time in the store.

  In the above embodiment, when the type of exception processing is misregistration processing, it is determined that there is a possibility of fraud on the condition that there is no customer at the time of exception processing, but other exception processing (for example, “returned goods” Processing ”,“ exchange processing ”,“ discount processing ”,“ discount processing ”, etc.).

  Further, in the above embodiment, the occurrence of exception processing is detected by including information indicating exception processing in the accounting information. However, as shown in the second embodiment, the receipt R is read, the store clerk, the customer, etc. The occurrence of exception processing may be detected by operating a predetermined operation unit, placing a product or a receipt R on a predetermined placement unit, and the like.

  In the above embodiment, the information processing apparatus A3 is configured by the receipt printer 2 and the store management server 5. However, the store management server 5 may be omitted. In this case, the receipt printer 2 includes each part of the store management server 5. In addition, each unit of the information processing apparatus A3 may be provided in the POS terminal 1, or the database 103 may be provided outside the information processing apparatus A3.

  As described above, according to the first to third embodiments, it is possible to detect the occurrence of exception processing in the receipt printer 2, and by recording the monitoring data on the basis of the exception processing occurrence time, Monitoring data useful for fraud verification can be efficiently recorded. In addition, the predetermined items at the time of exception processing are totaled for each clerk and / or customer, and output together with the imaging results of the clerk monitoring camera 3 as a total report 50, so that the administrator can easily and quickly determine the presence or absence of fraud. And the like.

  In addition, it is possible to provide each step of the control method (the flowchart shown in each said embodiment) of the store monitoring system SY1 thru | or SY3 which concerns on each said embodiment as a program. Further, the program can be provided by being stored in various recording media (CD-ROM, flash memory, etc.). That is, a program for causing a computer to function as each component of the receipt printer 2 and the information processing apparatuses A2 and A3 and a recording medium on which the program is recorded are also included in the scope of rights of the present invention.

  In each of the above embodiments, the information processing apparatus according to the present invention is realized by the receipt printer 2 or the store management server 5, but may be realized by another electronic device. Moreover, you may use for uses other than fraud detection of a shop assistant or a customer. In addition, regardless of the above-described embodiments, the apparatus configuration and processing steps of the store monitoring systems SY1 to SY3 can be appropriately changed without departing from the gist of the present invention.

  DESCRIPTION OF SYMBOLS 1 ... POS terminal 2 ... Receipt printer 3 ... Clerk monitoring camera 4 ... Customer display 5 ... Store management server 6 ... In-store LAN 7 ... Register counter 8 ... Report output printer 9 ... Receipt scanner 10 ... In-store monitoring camera 16 ... POS application 50 ... Total report 51 ... Database (first embodiment) 61 ... Input interface 62 ... Output interface 63 ... Character generator 64 ... Main processing unit 65 ... Print mechanism 66 ... Conversion table 67 ... Data tap semantic analysis unit 68 ... Upper layer Transmission unit 69 ... DVR application 103 ... Database (third embodiment) A2, A3 ... Information processing device R ... Receipt SY1, SY2, SY3 ... Store monitoring system

Claims (16)

A monitoring data acquisition unit that acquires monitoring data that is a monitoring result of the monitoring unit of the monitoring camera that monitors the situation around the register counter;
A main storage unit for storing at least a part of the monitoring data in a nonvolatile manner;
In the accounting processing unit of the POS terminal provided in the cashier counter, an exception processing occurrence detecting unit that detects that an accounting processing exception has occurred;
An accounting information acquisition unit for acquiring accounting information which is an accounting processing result of the accounting processing unit;
A recording control unit for controlling the recording of the monitoring data in the main storage unit,
The exception processing occurrence detection unit detects the occurrence of the exception processing by acquiring the accounting information including information indicating the exception processing by the accounting information acquisition unit,
The recording control unit records monitoring data for N hours (where N> 0) on the basis of the occurrence detection of the exception processing by the exception processing occurrence detection unit in the main storage unit. Information processing apparatus. A sub-storage unit that stores the monitoring data for a predetermined time while updating the monitoring unit as needed while the monitoring unit is monitored;
The recording control unit records the monitoring data for N hours including the monitoring data before the occurrence detection of the exception processing from the monitoring data stored in the sub storage unit in the main storage unit. The information processing apparatus according to claim 1.   3. The information according to claim 2, wherein the monitoring data for N hours is monitoring data having a start time M hours before the occurrence detection of the exception processing (where 0 <M ≦ N). Processing equipment.   The exception processing occurrence detection unit detects occurrence of the exception processing by an operation of an operation unit that can be operated by a user when the exception processing occurs. Information processing device. The apparatus further includes a placement detection unit that detects that a product or a receipt is placed on the predetermined placement unit,
The exception processing occurrence detection unit detects the occurrence of the exception processing by detecting the placement of the commodity or the receipt by the placement detection unit. The information processing apparatus according to item. An audio acquisition unit for acquiring audio around the register counter;
A voice recognition unit that recognizes the acquired voice;
4. The exception processing occurrence detection unit detects occurrence of the exception processing by recognizing or not recognizing a predetermined keyword by the voice recognition unit. The information processing apparatus described in 1. A receipt reading unit for reading receipts;
The information processing apparatus according to claim 1, wherein the exception processing occurrence detection unit detects the occurrence of the exception processing by reading the receipt by the receipt reading unit. The accounting processing unit is realized by a POS terminal connected to an information processing device,
The information processing apparatus according to claim 7 , further comprising a reading result output unit that outputs a reading result of the receipt reading unit to the POS terminal. The monitoring unit monitors the inside of the store including around the cashier counter,
From the monitoring result of the monitoring unit, further comprising a specific behavior determination unit that determines the specific behavior of at least one of the clerk and the customer,
When the specific action is determined by the specific action determination unit, the recording control unit records monitoring data for L hours (where L> 0) based on the specific action determination time in the main storage unit. The information processing apparatus according to claim 1, wherein the information processing apparatus is an information processing apparatus. 10. The information according to claim 9 , wherein the recording control unit adds tag information indicating a situation at the time of exception processing occurrence or specific action determination to the monitoring data, and stores the tag information in the main storage unit. Processing equipment. The tag information includes the type of the exception processing, the receipt read result, the position of the store clerk in the store, the presence of customers around the checkout counter, the image data in the store including the checkout counter, and the store including the checkout counter The information processing apparatus according to claim 10 , wherein the information processing apparatus includes at least one of voice data, exception process occurrence date and time, and specific action determination date and time. The information processing apparatus according to any one of claims 1 to 11, further comprising a printing unit for printing the transaction information is accounted result of the accounting unit in the receipt paper. A monitoring unit of a monitoring camera that monitors the situation around the checkout counter, an accounting processing unit of a POS terminal , and a main storage unit that stores at least a part of monitoring data as a monitoring result of the monitoring unit in a nonvolatile manner inside or outside A control method of an information processing apparatus provided,
The information processing apparatus is
A monitoring data acquisition step of acquiring monitoring data which is a monitoring result of the monitoring unit;
In the accounting processing unit, an exception processing occurrence detection step for detecting that an accounting processing exception has occurred,
An accounting information acquisition step of acquiring accounting information which is an accounting processing result of the accounting processing unit;
Executing a recording step for controlling recording of the monitoring data in the main storage unit,
In the exception processing occurrence detection step, the occurrence of the exception processing is detected by acquiring the accounting information including information indicating the exception processing in the accounting information acquisition step,
In the recording step, monitoring data for N hours (where N> 0) is recorded in the main storage unit based on the occurrence detection time of the exception processing in the exception processing occurrence detection step. A method for controlling an information processing apparatus. The information processing apparatus further includes a sub storage unit that stores the monitoring data for a predetermined time while being updated while the monitoring unit is being monitored,
In the recording step, the monitoring data for N hours including the monitoring data before the occurrence detection of the exception processing is recorded in the main storage unit from among the monitoring data stored in the sub storage unit. The method for controlling an information processing apparatus according to claim 13 , wherein the information processing apparatus is a control method. 15. The information according to claim 14 , wherein the monitoring data for N hours is monitoring data whose start time is M hours before the occurrence detection of the exception processing (where 0 <M ≦ N). A method for controlling a processing apparatus. The program for making a computer perform each step in the control method of the information processing apparatus of any one of Claim 13 thru | or 15 .

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