Determination device, determination system, determination method, and recording medium

Abstract

This determination device includes: a signal information acquisition means for acquiring signal information from a basket tag on a shopping basket carried by a customer when product identification information in a product tag on a product carried by the customer and basket identification information stored in the basket tag are read by a reading device installed in a gate through which the customer passes; a determination means for determining whether or not the product identification information indicates a product purchased by the customer on the basis of the signal information acquired when the basket identification information is read; and an output control means for outputting the result of determination.

Description

Determination device, determination system, determination method, and recording medium

[0001] The present disclosure relates to a determination device, a determination system, a determination method, and a recording medium.

[0002] There are devices that acquire product information for purchase by customers by reading products in a shopping cart with a determination device installed at a gate. Such devices are designed to improve the accuracy of reading the product information. For example, Patent Document 1 discloses a device that determines whether a product is eligible for purchase based on changes in received signal strength over time for each product.

[0003] International Publication No. 2019-065684

[0004] However, the determination method of Patent Document 1 may not be able to correctly determine whether or not an item is eligible for purchase.

[0005] An example of an object of the present disclosure is to provide a determination device that can improve the accuracy of determining whether a customer who has passed through a gate has purchased an item.

[0006] A determination device in one aspect of the present disclosure includes a signal information acquisition means for acquiring signal information from a basket tag when a reading device installed at a gate through which a customer passes reads product identification information in a product tag attached to a product held by the customer and basket identification information stored in a basket tag attached to a shopping basket held by the customer; a determination means for determining whether the product identification information is a product purchased by the customer based on the signal information when the basket identification information is read; and an output control means for outputting the determination result.

[0007] In one aspect of the present disclosure, a determination method involves a computer using a reading device installed at a gate through which a customer passes to read product identification information in a product tag attached to a product held by the customer and basket identification information stored in a basket tag attached to a shopping basket held by the customer, acquiring signal information from the basket tag, and determining whether the product identification information is a product purchased by the customer based on the signal information obtained when the basket identification information is read, and outputting the determination result.

[0008] In one aspect of the present disclosure, a recording medium acquires signal information from the basket tag when a reading device installed at a gate through which a customer passes reads product identification information in a product tag attached to a product carried by the customer and basket identification information stored in a basket tag attached to a shopping basket carried by the customer, and determines whether the product identification information is a product purchased by the customer based on the signal information obtained when the basket identification information is read, and outputs the determination result.

[0009] According to the present disclosure, it is possible to provide a determination device that can improve the accuracy of determining whether or not a product is purchased by a customer who has passed through a gate.

[0010] FIG. 1 is a block diagram showing an example configuration of a determination system according to the present disclosure. FIG. 2 is a schematic diagram showing an example of a gate according to the present disclosure. FIG. 3 is a diagram showing a hardware configuration in which a determination device according to the present disclosure is realized by a computer device and its peripheral devices. FIG. 4 is a flowchart showing the determination operation according to the present disclosure. FIG. 5 is a block diagram showing an example configuration of a determination system according to the present disclosure. FIG. 6 is a block diagram showing an example configuration of a determination system according to the present disclosure. FIG. 7 is a diagram for explaining re-learning of a trained model for each reading condition of a reading device according to the present disclosure. FIG. 8 is a diagram for explaining re-learning of a trained model for each reading condition of a reading device according to the present disclosure.

[0011] Hereinafter, embodiments of a determination device, a determination system, a determination method, and a non-transitory recording medium for recording a program according to the present disclosure will be described in detail with reference to the drawings. The disclosed technology is not limited to these embodiments.

[0012] 1 is a block diagram showing an example of a configuration including a determination device 100 according to the present disclosure. As shown in Fig. 1, in the determination system 10, the determination device 100 is connected to a reading device 200 and an output device 300 via a network.

[0013] The determination device 100 is a device that determines whether or not a customer will purchase a product based on product identification information in an RFID (Radio Frequency Identification) tag attached to the product read by the reading device 200. The reading device 200 is a sensor that reads product identification information of a product to be purchased by a customer passing through a gate and basket identification information of a shopping basket carried by the customer. The output device 300 is a device that outputs information on a product determined to be purchased by the customer, and is, for example, a display installed near the exit of the gate or a display on the customer's terminal. The store in the present disclosure is, for example, a retail store that sells clothing, food, etc.

[0014] (RFID tag) Products sold by a store are equipped with product tags made up of RFID tags in advance, and shopping baskets used in this store are also equipped with basket tags made up of RFID tags in advance. The product tags and basket tags can be read by reading device 200. The product tags are attached to any position (e.g., the outer surface) of the product. Similarly, the basket tag is attached to any position (e.g., the outer surface) of the shopping basket. Note that the basket tags may be attached to multiple surfaces (e.g., multiple side surfaces) of the shopping basket to prevent the RFID tag from being overlooked.

[0015] (Gate) FIG. 2 is a schematic diagram illustrating an example of a gate in the present disclosure. Gate 1 as shown in FIG. 2 is provided, for example, near the exit of a store. Gate 1 is provided with a reading device 200. Reading device 200 has an RFID reader 201 and an antenna 202. The gate shown in FIG. 2 is a walk-through gate in which, as a customer walks through aisle A within gate 1, reading device 200 reads product identification information stored in a product tag attached to product P carried by the customer and basket identification information stored in a basket tag attached to shopping basket B. Note that in the example gate shown in FIG. 2, two antennas 202 are provided on each side of aisle A near the center of the gate in the direction of travel, but the number of antennas 202 is not limited to the configuration example shown in FIG. 2.

[0016] The RFID reader 201 of the reading device 200 is a control circuit that communicates with RFID tags via an antenna 202 in accordance with a predetermined communication protocol and reads the identification information stored in the RFID tags of products and shopping carts. The antenna 202 is installed in a position where it can transmit and receive radio waves to and from RFID tags passing through the gate 1, and transmits radio waves to the RFID tags and receives radio waves transmitted from the RFID tags. The antenna 202 may be provided as a separate transmitting antenna and a separate receiving antenna.

[0017] In the example of gate 1 in Fig. 2, output device 300 may be provided near the exit of gate 1 and configured to output a list of products determined to be purchased. Purchased products are products that a customer who passes through gate 1 is carrying and intends to purchase. In addition, a configuration may be provided in which, when it is detected that the customer has exited gate 1, payment processing for the products determined to be purchased is performed using pre-registered payment information.

[0018] Returning to FIG. 1 , the determination device 100 includes a signal information acquisition unit 101, a determination unit 102, and an output control unit 103. FIG. 3 is a diagram illustrating an example of a hardware configuration in which the determination device 100 according to the present disclosure is realized by a computer device 500 including a processor. As shown in FIG. 3 , the determination device 100 includes a CPU (Central Processing Unit) 501, memories such as a ROM (Read Only Memory) 502 and a RAM (Random Access Memory) 503, a storage device 505 such as a hard disk for storing a program 504, a communication interface 508 for network connection, and an input / output interface 509 for inputting and outputting data. The determination device 100 is also connected to each component via a bus 510. The determination device 100 shown in FIG. 1 can also be configured using cloud computing or the like.

[0019] The CPU 501 runs an operating system to control the entire determination device 100 according to the present disclosure. The CPU 501 also reads programs and data into memory from a recording medium 506 attached to, for example, a drive device 507. The CPU 501 also functions as the signal information acquisition unit 101, the determination unit 102, and the output control unit 103 according to the present disclosure, or as part of these, and executes processing or commands in the flowchart shown in FIG. 4, which will be described later, based on the program.

[0020] The recording medium 506 is, for example, an optical disk, a flexible disk, a magneto-optical disk, an external hard disk, or a semiconductor memory. The semiconductor memory or the like that is part of the recording medium is a non-volatile storage device that stores the program. The program may also be downloaded from an external computer (not shown) that is connected to a communication network.

[0021] As described above, the first embodiment shown in Fig. 1 is realized by the computer hardware shown in Fig. 3. However, the means for realizing each unit included in the determination device 100 in Fig. 1 is not limited to the configuration described above. The determination device 100 may be realized by a single physically coupled device, or may be realized by a system consisting of two or more physically separated devices connected by wire or wirelessly.

[0022] The signal information acquisition unit 101 is a means for acquiring signal information from a basket tag when a reading device provided at the gate 1 through which a customer passes reads product identification information in a product tag attached to a product carried by the customer and basket identification information stored in a basket tag attached to a shopping basket carried by the customer. The signal information acquisition unit 101 acquires signal strength by measuring a received signal strength indicator (RSSI) value from the basket tag received by the antenna 202. While the present specification describes a case in which the signal information is an RSSI value, the signal information is not limited to an RSSI value and may also include a maximum RSSI value, a minimum RSSI value, etc. Furthermore, the signal information may also include the number of times the reading device 200 reads each unit of product identification information, the reading time, and the number of antennas 202 that have read an electronic product code (EPC) stored in the basket tag.

[0023] The determination unit 102 is a means for determining whether the product identification information is a purchased product of the customer based on signal information obtained when the basket identification information is read. Incidentally, if there is a product in the shopping basket, the product tag may not be properly read by the reading device 200. This occurs, for example, when multiple products are stacked in the shopping basket, causing interference with the radio waves used for reading by products containing metal or liquid. In contrast, the radio waves of the basket tag are not interfered with by the products in the shopping basket, making it less likely to be overlooked. Therefore, the determination unit 102 determines whether the product identification information read by the reading device 200 is a purchased product of the customer by comparing the signal information obtained when the basket identification information is read with a threshold value. That is, if the RSSI value from the basket tag is equal to or greater than a predetermined value, the determination unit 102 determines that the product identification information read by the reading device 200 is a purchased product. On the other hand, if the RSSI value from the basket tag is less than the predetermined value, the determination unit 102 determines that the product corresponding to the product identification information read by the reading device 200 is not a purchased product. A non-purchased product is a product that is not in the possession of a customer passing through gate 1, for example, a product that is outside gate 1.

[0024] The determination unit 102 may determine whether the product identification information is a purchased product by the customer by estimating the position of the shopping cart based on signal information received when the cart identification information is read. In this case, the determination unit 102 estimates the relative distance between the reading device 200 and the car tag by, for example, analyzing the signal information received by the reading device 200. The relative distance of the car tag can be estimated by analyzing, for example, the magnitude of the RSSI value, phase information, etc. using well-known techniques. If the distance from the reading device 200 to the car tag is less than a predetermined distance, the determination unit 102 determines that the product identified by the product identification information read by the reading device 200 is a purchased product. On the other hand, if the distance from the reading device 200 to the car tag is equal to or greater than the predetermined distance, the determination unit 102 determines that the product identified by the product identification information read by the reading device 200 is not a purchased product.

[0025] The output control unit 103 is a means for outputting the determination result. The output control unit 103 may output a screen listing the products determined to be purchased by the customer. The output control unit 103 outputs the list of purchased products to, for example, the output device 300 or the customer's mobile terminal.

[0026] 4 is a flowchart showing an outline of the operation of the determination device 100 according to the present disclosure. The processing according to this flowchart may be executed based on program control by the processor described above. The determination device 100 may start the flow according to this flowchart, for example, when the signal information received from the reading device 200 is equal to or greater than a predetermined value.

[0027] As shown in Fig. 4, first, the signal information acquisition unit 101 acquires signal information from the basket tag when the reader 200 installed at the gate 1 through which the customer passes reads the product identification information stored in the product tag attached to the product carried by the customer and the basket identification information stored in the basket tag attached to the shopping basket carried by the customer (step S101). Next, the determination unit 102 determines whether the product identification information corresponds to the product purchased by the customer based on the signal information obtained when the basket identification information is read (step S102). Finally, the output control unit 103 outputs the determination result (step S103). This concludes the flow of the determination device 100.

[0028] In the determination device 100 of this embodiment, the determination unit 102 determines whether the product identification information is a product purchased by a customer based on signal information when the basket identification information is read. As a result, for example, based on signal information from a basket tag attached to a shopping basket in which a customer has placed an item, it can be determined that the product identification information is that of a basket held by a customer at gate 1. This improves the accuracy of determining whether the product was purchased by a customer who passed through gate 1.

[0029] (Variation 1 of the First Embodiment) Next, a variation of the first embodiment will be described. Below, to the extent that the description of this embodiment is not unclear, the description of the same content as the above description will be omitted. In the first embodiment, the determination unit 102 determined whether the product identification information is a product purchased by a customer based on the signal information obtained when the basket identification information was read. In this variation, the determination unit 102 determines whether the product identification information is a product purchased by a customer based on the difference between the signal information of the product identification information and the signal information from the basket tag. That is, the signal information acquisition unit 101 further acquires signal information from the product tag when reading the product identification information in the product tag attached to a product held by the customer.

[0030] When a shopping cart tag and the product tag of a product in the shopping cart are read, the distances from the reading device 200 to the basket tag and the product tag are the same, and therefore, if the RFID tags have the same specifications, the signal information received from the reading device 200 will be the same. Even if the basket tag and the product tag are RFID tags with different performance, if the distances from the reading device 200 to the reading device 200 are the same, differences due to predetermined specifications will appear in the signal information received from the reading device 200. Therefore, the determination unit 102 determines whether the product is a purchased product by comparing the signal information with a threshold value determined according to the specifications or performance of the basket tag and the product tag. That is, if the difference between the signal information from the product tag and the signal information from the basket tag is less than the predetermined threshold, the determination unit 102 determines that the product identification information read by the reading device 200 is a purchased product. On the other hand, if the difference between the signal information from the product tag and the signal information from the basket tag is equal to or greater than the predetermined threshold, the determination unit 102 determines that the product identification information read by the reading device 200 is not a purchased product. In this modification, the difference between the signal information from the product tag and the signal information from the basket tag indicates a relative value.

[0031] In this modification, the determination unit 102 determines that the product identification information read by the reading device 200 is a purchased product based on the difference between the signal information from the product tag and the signal information from the basket tag. In this case, the determination is made using the signal information from the product tag as well, thereby improving the accuracy of the determination.

[0032] (Second Modification of the First Embodiment) Next, another modification of the present disclosure will be described in detail with reference to the drawings. Fig. 5 is a block diagram showing a determination system 11 according to the present disclosure. In the determination system 11, similar to the determination system 10, a determination device 110 is connected to a reading device 210 and an output device 310 via a network.

[0033] In this modification, it is assumed that a plurality of reading devices 210 are provided on both sides of a passageway of a gate through which customers pass. Fig. 5 is a block diagram showing an example of a configuration including a determination device 110 according to the present disclosure. As shown in Fig. 5, the determination device 110 includes a signal information acquisition unit 111, a detection unit 112, a selection unit 113, a determination unit 114, and an output control unit 115. The configurations of the signal information acquisition unit 111 and the output control unit 115 are similar to the corresponding configurations in the first embodiment, and therefore description thereof will be omitted.

[0034] The detection unit 112 is a means for detecting the position of a customer's shopping basket from an image captured by a camera installed near the gate. The camera may be installed at a position where it can detect the position of the shopping basket inside the gate, and may be attached to the gate itself or the ceiling of the gate. The detection unit 112 detects which reader 210 inside the gate the customer's shopping basket is closest to.

[0035] The selection unit 113 is a means for selecting the reading device 210 to be used based on the position of the shopping cart. The selection unit 113 outputs to the determination unit 114 signal information received by the reading device 210 that is closest to the shopping cart held by the customer.

[0036] The determination unit 114 determines whether the commodity identification information is a commodity purchased by the customer based on signal information when the commodity identification information is read by the selected reading device 210. The determination method by the determination unit 114 is the same as in the first embodiment.

[0037] In this modification, the detection unit 112 detects the position of the customer's shopping cart from an image captured by a camera installed near the gate, and the selection unit 113 selects the reading device 210 to use based on the position of the shopping cart. The determination unit 114 then determines whether the product identification information is a product purchased by the customer based on signal information received when the product identification information is read by the selected reading device 210. In this case, the determination is made using signal information received by the reading device 210 closest to the shopping cart, thereby improving the accuracy of the determination.

[0038] [Second Embodiment] Next, a second embodiment of the present disclosure will be described in detail with reference to the drawings. Fig. 6 is a block diagram showing a determination system 12 according to the present disclosure. In the determination system 12, similar to the determination system 10, a determination device 120 is connected to a reading device 220 and an output device 320 via a network.

[0039] In the following, the description of the present embodiment will be omitted to the extent that the description thereof does not become unclear. The functions of each component in each embodiment of the present disclosure can be realized not only by hardware but also by a computer device or software under program control, similar to the computer device shown in FIG.

[0040] 6, the determination device 120 includes a signal information acquisition unit 121, a determination unit 122, a learning unit 123, and an output control unit 124. The configuration of the signal information acquisition unit 121 is similar to the corresponding configuration in the first embodiment, and therefore a description thereof will be omitted. In addition, in this embodiment, the learning unit 123 is an optional component.

[0041] In this embodiment, the determination unit 122 uses a machine-learned trained model to determine whether or not a product is purchased by a customer based on the characteristics of the signal information from the product tag and the characteristics of the signal information from the car tag. The determination unit 122 inputs the signal information from the product tag of each product and the signal information from the car tag into the trained model stored in the storage device 505, and determines whether or not each of the read product identification information is a product purchased by a customer passing through gate 1.

[0042] Specifically, when the signal information is an RSSI value, the determination unit 122 determines whether the signal information is a purchased item by the customer based on the magnitude of each RSSI value of the signal information from the product tag and the cart tag. That is, this trained model determines that the read product identification information is a purchased item when the magnitude of the RSSI value from the product tag is equal to or greater than a first predetermined value and the magnitude of the RSSI value from the cart tag is equal to or greater than a second predetermined value. The first predetermined value and the second predetermined value are thresholds for determining the read product identification information that are set according to the specifications of the product tag and the cart tag, respectively. On the other hand, even if the magnitude of the RSSI value from the product tag is equal to or greater than the first predetermined value, the determination unit 122 determines that the product of the read product identification information is not a purchased item when the magnitude of the RSSI value from the cart tag is less than the second predetermined value. Similarly, even if the magnitude of the RSSI value from the basket tag is equal to or greater than a second predetermined value, if the magnitude of the RSSI value from the product tag is less than a first predetermined value, the judgment unit 122 judges that the product identified by the read product identification information is not a purchased product.

[0043] (Trained Model) The determination device 120 stores a trained model in the storage device 505 for determining whether an item is purchased by a customer. This trained model is a model generated by machine learning the correlation between the characteristics of signal information from the item tag when the reading device 220 reads item identification information and the characteristics of signal information from the basket tag when the reading device 220 reads basket identification information, and whether the item is purchased. For example, the trained model is expressed as a mathematical formula using the signal information from the item tag and the signal information from the basket tag as explanatory variables. Examples of signal information include an RSSI value indicating the signal strength of the read item identification information, the number of times the item identification information is read, the reading time, the number of antennas 222 that have read the EPC stored in the RFID tag, and attribute information of the item to which the RFID tag is attached. The trained model may be a model expressed as a mathematical formula using multiple pieces of signal information from the above-mentioned signal information. The determination device 120 uses this trained model to estimate whether the read item identification information is a purchased item based on the signal information from the item tag and the signal information from the basket tag.

[0044] The trained model is generated by a learning means of the determination device 120 or a device other than the determination device 120. The learning algorithm may be any machine learning method such as a neural network, a support vector machine (SVM), or logistic regression.

[0045] The learning unit 123 is a means for re-learning the trained model based on the reading conditions of the reading device 220. When the learning unit 123 is provided, the determination unit 122 uses the re-trained trained model to determine whether or not the product is purchased by the customer based on the characteristics of the signal information from the product tag and the characteristics of the signal information from the car tag.

[0046] The signal information received from the RFID tag when reading the product identification information stored in the RFID tag varies depending on the reading conditions of the reader 220. Using FIGS. 7 and 8, we will explain the re-training of the trained model for each reading condition of the reader 220. FIG. 7 shows a graph of the transition of RSSI values ​​when a customer passes through a gate when a trained model re-trained under the reading conditions of the reader 220 is used. FIG. 8 shows a graph of the transition of RSSI values ​​when a customer passes through a gate when a trained model similar to FIG. 7 is used under different reading conditions. As shown in FIG. 7, when a trained model re-trained under the reading conditions of the reader 220 is used, it is easy to distinguish between the graphs of RSSI values ​​for tag A inside the gate and tag B outside the gate. In contrast, when a trained model not re-trained under the reading conditions of the reader 220 is used, as shown in FIG. 8, it is difficult to distinguish between the graphs of RSSI values ​​for tag A inside the gate and tag B outside the gate. Similarly, even in the case of a trained model that uses signal information other than RSSI values, by optimizing the trained model by re-training it for each reading condition of the reading device 220, it becomes easier to distinguish between signal information when an RFID tag inside the gate is read and signal information when an RFID tag outside the gate is read.

[0047] That is, the trained model retrained by the training unit 123 is a model that has been further retrained to determine the correlation between the characteristics of the signal information from the product tag when reading the product identification information and the characteristics of the signal information from the basket tag when reading the basket identification information, and whether the product is purchased, under the reading conditions of the reading device 220. More specifically, the trained model is a model that has been retrained to determine the correlation by inputting multiple sets of training datasets that include the characteristics of the signal information from the product tag and the characteristics of the signal information from the basket tag, obtained under the reading conditions of the reading device 220, and the results of whether the product is purchased.

[0048] The reading conditions include, for example, the store environment where the reader 220 is installed, the weather, and the radio wave environment. The store environment includes, for example, the store location (e.g., a street store or a store in a mall), the store ceiling height, the material of the store floor or ceiling, the layout of the product shelves, or how crowded the store is. The radio wave environment includes, for example, the position of the antenna inside the gate, the number of antennas, the material of the shopping cart, or the material of the product to which the RFID tag is attached.

[0049] The output control unit 124 outputs the determination result and a screen listing the products determined to be purchased by the customer. The output control unit 124 outputs the screen listing the purchased products to, for example, the output device 320 or the customer's mobile terminal.

[0050] In the determination device 120 of this embodiment, the determination unit 122 uses a machine-learned trained model to determine whether an item is purchased by a customer based on the characteristics of signal information from the item tag when reading the item identification information and the characteristics of signal information from the basket tag when reading the basket identification information. As a result, even if the reading device 220 reads item identification information from an item tag outside the gate, the product identification information of an item in a shopping basket held by a customer inside the gate can be determined based on the signal information from the basket tag. This improves the accuracy of determining whether an item was purchased by a customer who passed through the gate.

[0051] Furthermore, in this embodiment, when the learning unit 123 is provided, the determination unit 122 uses the re-trained trained model to determine whether or not the product is purchased by the customer based on the characteristics of the signal information from the product tag and the characteristics of the signal information from the car tag. In this case, as shown by comparing Figures 7 and 8, it becomes easier to distinguish between the product identification information of the RFID tag inside the gate and the product identification information of the RFID tag outside the gate.

[0052] Although the present disclosure has been described above with reference to various embodiments, the present disclosure is not limited to the above embodiments. The configuration and details of each of the present disclosures may include embodiments to which various modifications that would be apparent to those skilled in the art are applied within the scope of the present disclosure. The present disclosure may also include embodiments in which the details described herein are appropriately combined or substituted as necessary. For example, details described using a particular embodiment may also be applied to other embodiments to the extent that no contradiction occurs. For example, although multiple operations are described in sequence in the form of a flowchart, the order of the descriptions does not limit the order in which the multiple operations are performed. Therefore, when implementing each embodiment, the order of the multiple operations may be changed as long as it does not interfere with the content.

[0053] Some or all of the above-described embodiments can be described as follows: However, some or all of the above-described embodiments are not limited to the following.

[0054] (Supplementary Note 1) A determination device comprising: a signal information acquisition means for acquiring signal information from a basket tag when a reading device provided at a gate through which a customer passes reads product identification information in a product tag attached to a product held by the customer and basket identification information stored in a basket tag attached to a shopping basket held by the customer; a determination means for determining whether the product identification information is a product purchased by the customer based on the signal information when the basket identification information is read; and an output control means for outputting the determination result.

[0055] (Supplementary Note 2) The determination device according to Supplementary Note 1, wherein the determination means determines whether the commodity identification information is a commodity purchased by the customer by comparing signal information obtained when the basket identification information is read with a threshold value.

[0056] (Supplementary Note 3) The determination device according to Supplementary Note 1, wherein the determination means determines whether the product identification information is a product purchased by the customer by estimating the position of the shopping cart based on signal information when the cart identification information is read.

[0057] (Appendix 4) The signal information acquisition means further acquires signal information from the product tag when reading product identification information in the product tag attached to the product held by the customer, and the determination means determines whether the product identification information is a product purchased by the customer based on the difference between the signal information from the product tag and the signal information from the basket tag, in the determination device described in Appendix 1.

[0058] (Supplementary Note 5) The signal information acquisition means acquires signal information from the basket tag when reading product identification information in a product tag attached to a product carried by the customer and basket identification information stored in a basket tag attached to a shopping basket carried by the customer using a plurality of reading devices provided on both sides of a gate through which the customer passes, and further comprises: a detection means for detecting the position of the shopping basket from an image captured of the gate; and a selection means for selecting a reading device to be used based on the position of the shopping basket, and the determination means determines whether the product identification information is a product purchased by the customer based on the signal information when the basket identification information is read by the selected reading device. This is a determination device described in any of Supplementary Notes 1 to 4.

[0059] (Appendix 6) The signal information acquisition means further acquires signal information from the product tag when reading product identification information in the product tag attached to the product held by the customer, and the determination means uses a machine-learned model to determine whether the product is a purchased product of the customer based on characteristics of the signal information from the product tag and characteristics of the signal information from the basket tag, in the determination device described in Appendix 1.

[0060] (Supplementary Note 7) The determination device according to Supplementary Note 6, wherein the trained model is a model generated by machine learning a correlation between the features of signal information from the product tag and the features of signal information from the basket tag and whether the product is a purchased product.

[0061] (Supplementary Note 8) The determination device according to Supplementary Note 7, wherein the trained model is a model obtained by further re-learning the correlation under the reading conditions of the reading device.

[0062] (Appendix 9) The determination device described in Appendix 8, wherein the trained model is a model in which the correlation is re-trained by inputting multiple sets of training datasets including features of signal information from the product tag and the features of signal information from the basket tag obtained under the reading conditions of the reading device, and results of whether the product is a purchased product.

[0063] (Appendix 10) A determination device described in Appendix 8 or Appendix 9, wherein the reading conditions of the reading device include at least one of the store environment in which the gate is installed, the weather at the time the signal information is acquired, and the radio wave environment inside the gate.

[0064] (Supplementary Note 11) The determination device according to any one of Supplementary Note 8 to Supplementary Note 10, further comprising a learning unit that re-learns the correlation in the reading conditions of the reading device.

[0065] (Supplementary Note 12) The determination device according to any one of Supplementary Notes 1 to 11, further comprising an output control means for outputting a screen showing a list of products determined to be purchased by the customer.

[0066] (Supplementary Note 13) A determination system having a reading device provided at a gate through which customers pass, and a determination device according to any one of Supplementary Notes 1 to 12.

[0067] (Supplementary Note 14) A determination method in which a computer, when reading product identification information in a product tag attached to a product held by the customer and basket identification information stored in a basket tag attached to a shopping basket held by the customer using a reading device installed at a gate through which the customer passes, acquires signal information from the basket tag, determines whether the product identification information is a product purchased by the customer based on the signal information obtained when the basket identification information is read, and outputs the determination result.

[0068] (Supplementary Note 15) The determination method according to Supplementary Note 14, wherein signal information obtained when the basket identification information is read is compared with a threshold value to determine whether the commodity identification information is a commodity purchased by the customer.

[0069] (Supplementary Note 16) The determination method according to Supplementary Note 14, wherein the method determines whether the product identification information is a product purchased by the customer by estimating the position of the shopping cart based on signal information when the cart identification information is read.

[0070] (Appendix 17) The determination method described in Appendix 14 further includes, when reading product identification information in a product tag attached to a product held by the customer, acquiring signal information from the product tag, and determining whether the product identification information is a product purchased by the customer based on a difference between the signal information from the product tag and the signal information from the basket tag.

[0071] (Appendix 18) A determination method described in any of Appendices 14 to 17, comprising: acquiring signal information from the basket tag when reading product identification information in a product tag attached to a product carried by the customer and basket identification information stored in a basket tag attached to a shopping basket carried by the customer using a plurality of reading devices provided on both sides of a gate through which the customer passes; detecting the position of the shopping basket from an image captured of the gate; selecting a reading device to be used based on the position of the shopping basket; and determining whether the product identification information is a product purchased by the customer based on the signal information obtained when the basket identification information is read by the selected reading device.

[0072] (Appendix 19) The determination method described in Appendix 14 further includes, when reading product identification information in a product tag attached to a product held by the customer, acquiring signal information from the product tag, and using a machine-learned trained model, determining whether the product is a purchased product of the customer based on the characteristics of the signal information from the product tag and the characteristics of the signal information from a basket tag.

[0073] (Supplementary Note 20) A recording medium storing a program that causes a computer to execute the following process: when a reading device installed at a gate through which a customer passes reads product identification information in a product tag attached to a product held by the customer and basket identification information stored in a basket tag attached to a shopping basket held by the customer, the reading device acquires signal information from the basket tag, and determines whether the product identification information is a product purchased by the customer based on the signal information obtained when the basket identification information is read, and outputs the determination result.

[0074] Some or all of the configurations described in Supplements 2 to 12, which are dependent on Supplement 1 described above, may also be dependent on Supplement 14 and Supplement 20 in the same dependent relationship as Supplements 2 to 12. Not limited to Supplements 1, 14, and 20, some or all of the configurations described as Supplements may also be dependent on various hardware, software, various recording devices for recording software, or systems, within the scope of each of the above-mentioned embodiments.

[0075] 10, 11, 12 Determination system 100, 110, 120 Determination device 101, 111, 121 Signal information acquisition unit 102, 114, 122 Determination unit 103, 115, 124 Output control unit 112 Detection unit 113 Selection unit 123 Learning unit 200, 210, 220 Reading device 300, 310, 320 Output device 500 Computer device 501 CPU 502 ROM 503 RAM 504 Program 505 Storage device 506 Recording medium 507 Drive device 508 Communication interface 509 Input / output interface 510 Bus

Claims

1. A determination device comprising: signal information acquisition means for acquiring signal information from the basket tag when reading product identification information in a product tag provided on a product held by the customer and basket identification information stored in a basket tag provided in a shopping basket held by the customer by a reading device provided at a gate through which the customer passes; determination means for determining whether the product identification information is a product purchased by the customer based on the signal information when the basket identification information is read; and output control means for outputting a determination result.

2. The determination device according to claim 1, wherein the determination means determines whether the product identification information is a product purchased by the customer by comparing the signal information when the basket identification information is read with a threshold value.

3. The determination device according to claim 1, wherein the determination means determines whether the product identification information is a product purchased by the customer by estimating the position of the shopping basket based on the signal information when the basket identification information is read.

4. The signal information acquisition means further acquires signal information from the product tag when reading product identification information in a product tag provided on a product held by the customer, and the determination means determines whether the product identification information is a product purchased by the customer based on the difference between the signal information from the product tag and the signal information from the basket tag. The determination device according to claim 1.

5. The signal information acquisition means acquires signal information from the basket tag when reading product identification information in a product tag provided on a product held by the customer and basket identification information stored in a basket tag provided in a shopping basket held by the customer by a plurality of reading devices provided on both sides of a gate through which the customer passes, and further includes detection means for detecting the position of the shopping basket from an image of the gate, and selection means for selecting a reading device to be used based on the position of the shopping basket. The determination means determines whether the product identification information is a product purchased by the customer based on the signal information when the basket identification information is read by the selected reading device. The determination device according to any one of claims 1 to 4.

6. The signal information acquisition means further acquires signal information from the merchandise tag when reading the merchandise identification information in the merchandise tag provided on the merchandise held by the customer. The determination means determines whether the merchandise is the purchased merchandise of the customer based on the characteristics of the signal information from the merchandise tag and the characteristics of the signal information from the basket tag by using a learned model obtained by machine learning. The determination device according to claim 1.

7. The learned model is a model generated by machine learning the correlation between the characteristics of the signal information from the merchandise tag, the characteristics of the signal information from the basket tag, and whether the merchandise is the purchased merchandise. The determination device according to claim 6.

8. The learned model is a model obtained by further re-learning the correlation under the reading conditions of the reading device. The determination device according to claim 7.

9. The learned model is a model obtained by re-learning the correlation by inputting a plurality of sets of learning data sets including the characteristics of the signal information from the merchandise tag, the characteristics of the signal information from the basket tag, and the result of whether the merchandise is the purchased merchandise obtained under the reading conditions of the reading device. The determination device according to claim 8.

10. The reading conditions of the reading device include at least one of the store environment where the gate is installed, the weather at the time of acquiring the signal information, and the radio wave environment inside the gate. The determination device according to claim 8 or claim 9.

11. The determination device according to any one of claims 8 to 10 further includes a learning means for further re-learning the correlation under the reading conditions of the reading device.

12. The determination device according to any one of claims 1 to 11 further includes an output control means for outputting a screen of a list of the merchandise determined to be the purchased merchandise of the customer.

13. A determination system having a plurality of reading devices provided at a gate through which a customer passes and the determination device according to any one of claims 1 to 12.

14. When a computer reads the merchandise identification information in the merchandise tag provided on the merchandise held by the customer and the basket identification information stored in the basket tag provided in the shopping basket held by the customer by a reading device provided at a gate through which the customer passes, the computer acquires the signal information from the basket tag, determines whether the merchandise identification information is the purchased merchandise of the customer based on the signal information when the basket identification information is read, and outputs the determination result. A determination method.

15. The determination method according to claim 14, wherein when the signal information read from the basket identification information is compared with a threshold value, it is determined whether the product identification information is the product purchased by the customer.

16. The determination method according to claim 14, wherein the position of the shopping basket is estimated based on the signal information when the basket identification information is read, and it is determined whether the product identification information is the product purchased by the customer.

17. Further, when reading the product identification information in the product tag provided on the product held by the customer, signal information from the product tag is acquired, and based on the difference between the signal information from the product tag and the signal information from the basket tag, it is determined whether the product identification information is the product purchased by the customer. The determination method according to claim 14.

18. When a plurality of reading devices provided on both sides of the gate through which the customer passes read the product identification information in the product tag provided on the product held by the customer and the basket identification information stored in the basket tag provided on the shopping basket held by the customer, signal information from the basket tag is acquired, the position of the shopping basket is detected from the image of the gate, a reading device to be used is selected based on the position of the shopping basket, and based on the signal information when the basket identification information is read by the selected reading device, it is determined whether the product identification information is the product purchased by the customer. The determination method according to any one of claims 14 to 17.

19. Further, when reading the product identification information in the product tag provided on the product held by the customer, signal information from the product tag is acquired, and using a learned model that has been machine - learned, it is determined whether the product is the product purchased by the customer based on the characteristics of the signal information from the product tag and the characteristics of the signal information from the basket tag. The determination method according to claim 14.

20. A recording medium storing a program for causing a computer to execute a process of acquiring signal information from a basket tag when a reading device provided on a gate through which a customer passes reads product identification information in a product tag provided on a product held by the customer and basket identification information stored in a basket tag provided on a shopping basket held by the customer, determining whether the product identification information is the product purchased by the customer based on the signal information when the basket identification information is read, and outputting the determination result.

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