JP2022013005A - Information processing program, device, and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To determine whether or not a product packed in a cardboard box can be shipped by a judgment standard of common recognition in consideration of various conditions.
SOLUTION: At each base of the distribution process such as a shipping source such as a factory of a manufacturer, a wholesaler, a retailer, etc., when shipping a product to the next base, an external image of the product packed in a cardboard box is taken. Using a judgment model in which the information processing device machine-learns the appearance image taken at each site, the external information, and the appearance image of the product for which shipment availability has been determined, and the correspondence between the external information and the judgment result. Judgment of whether shipping is possible is performed, and the judgment result is returned to each base. The external information includes information on the sales form of the product, information specifying the distribution process, information on storage conditions in the warehouse, information on transportation conditions, environmental information at the time of distribution, and the like.
[Selection diagram] Fig. 1

Description

Disclosure techniques relate to information processing programs, information processing devices, and information processing methods.

In the process of packing products manufactured by manufacturers in cardboard boxes and distributing them to wholesalers and retailers, the cardboard boxes may be deformed or damaged when the cardboard boxes absorb the impact generated in the distribution process. .. In addition, the cardboard box may be deformed depending on the storage environment of the warehouse during the distribution process. In such a case, the product may be damaged during transportation, storage in the warehouse at the shipping destination, take-out by the consumer, etc., and the product is returned to the previous stage of the distribution process because it causes a safety problem. Sometimes. Therefore, it is determined whether or not the product can be shipped before shipping and before delivery.

As a technique for determining whether or not to ship to the next stage of the distribution process, for example, a cargo damage information management system that manages cargo damage information has been proposed. This system has a mobile terminal that captures cargo, and a cargo damage information management device that manages the captured image taken from the mobile terminal and key information for identifying the cargo as cargo damage information. In addition, this cargo damage information management device has an AI image analysis function that automatically determines the damage site, type, and level as cargo damage information.

In addition, an inspection system has been proposed that can prevent erroneous input of inspection results, perform accurate inspection work, and reduce the burden on workers during inspection work. In this inspection system, the ordering side terminal installed on the ordering side, the ordering side terminal installed on the ordering side, and the management server are connected so as to be able to communicate with each other. In the inspection terminal provided on the ordering side, a scanner device having an image pickup unit, a temperature measuring unit, and a reading unit and a touch panel type display unit are integrated by a wired connection so that communication with the ordering side terminal is possible. .. At the time of inspection on the ordering side, the operator automatically manages the temperature value and food image of the food simply by contacting the scanner device with the food to be inspected while checking the inspection items on the display unit. Import to the server.

Japanese Unexamined Patent Publication No. 2019-175121 Japanese Unexamined Patent Publication No. 2019-32769

In determining whether or not to ship to the next stage of the distribution process, the determination criteria may differ depending on each stage of the distribution process, the worker making the determination, and the like. If the judgment criteria are too strict, there is a problem that it leads to unnecessary disposal of the product. In addition, if the judgment criteria are too loose, the workload in each distribution process may increase, such as the occurrence of complaints on the downstream side of the distribution process.

It is desirable that each stage of the distribution process and each worker have a common understanding of the criteria. However, on the other hand, there is a problem that it is difficult to establish a uniform judgment standard because the judgment of whether or not the product can be shipped may differ depending on the sales form of the target product, the transportation and storage conditions in the distribution process, and the like.

As one aspect, the disclosed technology aims to determine whether or not a product packed in a cardboard box can be shipped based on a common recognition criterion that considers various conditions.

As one embodiment, the disclosed technique includes an external image of a cardboard box in which a product to be determined to be shipped is packed, and an external image including at least one of information on the product to be determined and information on distribution of the product to be determined. Get information and. Then, the disclosed technique determines whether or not the product to be determined can be shipped based on the model, the appearance image of the acquired product to be determined, and the external information. The model is a model in which the correspondence between the external image and the external information of the product for which the shipability has been determined and the determination result of the product shipmentability according to the damaged state of the cardboard box is machine-learned.

As one aspect, it has an effect that whether or not a product packed in a cardboard box can be shipped can be determined by a common recognition criterion considering various conditions.

It is a figure for demonstrating the outline of the service provided by the information processing system which concerns on 1st Embodiment. It is a block diagram which shows the schematic structure of the information processing system which concerns on 1st and 2nd Embodiment. It is a functional block diagram of the information processing apparatus which concerns on 1st Embodiment. It is a figure which shows an example of a shooting screen. It is a figure which shows an example of an external information DB. It is a figure which shows an example of the determination DB. It is a figure which shows an example of the area confirmation screen. It is a figure which shows an example of the determination result screen. It is a figure which shows an example of the determination history DB. It is a block diagram which shows the schematic structure of the computer which functions as the information processing apparatus which concerns on 1st and 2nd Embodiment. It is a flowchart which shows an example of a determination process. It is a flowchart which shows an example of the objection aggregation processing. It is a flowchart which shows an example of judgment aggregation processing. It is a figure which shows an example of the alert about safety. It is a figure for demonstrating another example of a shooting range. It is a functional block diagram of the information processing apparatus which concerns on 2nd Embodiment. It is a figure which shows an example of a problem screen. It is a figure which shows an example of an answer screen. It is a flowchart which shows an example of the test mode processing.

Hereinafter, an example of the embodiment according to the disclosed technology will be described with reference to the drawings.

<First Embodiment>
First, with reference to FIG. 1, an outline of the service provided by the information processing system according to the first embodiment will be described. The information processing system in the first embodiment determines whether or not the product can be shipped from each base in the distribution process to the next base. In the first embodiment, a case where each base of the distribution process is a shipping source such as a factory of a manufacturer, a wholesaler, and a retailer will be described. At each base, when shipping the product to the next base, an external image of the product packed in a cardboard box is taken. Then, the information processing system determines whether or not the product can be shipped using the external image, external information, and the determination model taken at each site (details will be described later), and returns the determination result to each site.

As shown in FIG. 2, the information processing system 100 according to the first embodiment includes an information processing device 10 and base terminals 30A, 30B, and 30C. The information processing device 10 and the base terminals 30A, 30B, and 30C are connected via a network. The base terminal 30A is a terminal used at the base A, the base terminal 30B is a terminal used at the base B, and the base terminal 30C is a terminal used at the base C. In the first embodiment, base A is assumed to be a shipping source, base B is assumed to be a wholesaler, and base C is assumed to be a retailer. The number of each of the information processing apparatus 10 and the base terminals 30A, 30B, and 30C included in the information processing system 100 is not limited to the example of FIG. 2, and a plurality of each may be included. Further, a plurality of wholesalers or storage businesses may be included as a base for the distribution process from the shipping source to the retailer. Hereinafter, when each of the base terminals 30A, 30B, and 30C is described without distinction, it is simply referred to as "base terminal 30".

The base terminal 30 is an information processing terminal provided with at least an information input / output function unit such as a camera and a touch panel display, and a communication function unit for communicating with the information processing device 10. The base terminal 30 can be realized by, for example, a smartphone, a tablet terminal, or the like. An application for using the service provided by the information processing system 100 operates on the base terminal 30.

Functionally, as shown in FIG. 3, the information processing apparatus 10 includes an acquisition unit 12, a determination unit 14, and a creation unit 16. Further, the external information DB (Database) 22, the determination DB 24, and the determination history DB 26 are stored in the predetermined storage area of the information processing apparatus 10.

The acquisition unit 12 has an external image of a cardboard box packed with products to be determined whether it can be shipped, information on the products to be determined (hereinafter referred to as “product information”), and information on distribution of the products to be determined (hereinafter referred to as “product information”). Acquires external information including at least one of (referred to as "distribution information"). The product information includes information on the sales form of the product. The distribution information includes at least one of information that identifies the distribution process, information on storage conditions in the warehouse, information on transportation conditions, and environmental information at the time of distribution.

Specifically, the acquisition unit 12 displays the shooting screen 40 as shown in FIG. 4, for example, on the base terminal 30. In the example of FIG. 4, the shooting screen 40 has a shooting area 402 in which an image taken by the camera of the base terminal 30 is displayed, and a basic information input area 404 for inputting basic information of the product to be shipped. included. The basic information includes product identification information, distribution condition information for use in specifying various conditions in the distribution process, and the like. The product identification information is, for example, a product code for identifying a brand of a product, information for identifying a manufacturing factory from which the product is manufactured, a manufacturing lot, or the like. The distribution condition information includes, for example, the date and time when the goods are loaded and unloaded into the warehouse of the base, the transportation company code which is the identification information of the transportation company which transports the goods to the next base, and the base which is the identification information of the next base which is the shipping destination. Code etc. are included. Further, the shooting screen 40 includes a transmission button 406 selected when transmitting an external image and basic information to the information processing apparatus 10.

The person in charge of the work who operates the base terminal 30 takes a picture so that the target part of the cardboard box in which the product to be determined whether to be shipped is packed is displayed in the picture area 402. Further, the person in charge of work inputs the basic information of the product in the basic information input area 404. The person in charge of work can input basic information by using an input function unit such as a touch panel display. Further, when a slip or the like in which the basic information is written in character information or a barcode is attached to the cardboard box, the basic information may be input by reading the character information or the barcode from the slip or the like. Further, when a tag such as RFID (radio frequency identifier) in which basic information is recorded is attached to the cardboard box, the basic information may be input by reading this tag.

The worker selects the send button 406 when the image of the appearance of the cardboard box has been taken and the basic information has been input. As a result, the appearance image and the basic information are transmitted from the base terminal 30 to the information processing apparatus 10, and the acquisition unit 12 acquires the appearance image and the basic information received by the information processing apparatus 10.

The acquisition unit 12 acquires external information corresponding to the acquired appearance image from the external information DB 22 or the like based on the acquired basic information. FIG. 5 shows an example of the external information DB 22. In the example of FIG. 5, the external information DB 22 includes a product information table 222, a base information table 224, a transportation information table 226, and the like.

In the product information table 222, the product name, sales form, etc. of the product indicated by the product code are stored in association with the product code. The sales form is, for example, information indicating whether the product is sold in a case where the product is sold as a packed cardboard box, or is sold separately by taking out and selling the product which is the contents of the cardboard box.

In the base information table 224, information such as a base name, a base classification, an address, and an average warehouse humidity is stored in association with the base code which is the identification information of the base. The base classification is information indicating whether the base is a shipping source such as a manufacturer, a wholesaler, or a retailer. The address is the address of the warehouse at the base. Warehouse average humidity is the average warehouse humidity measured over a given period of time in the past.

In the transportation information table 226, the transportation quality in the transportation company is stored in association with the transportation company code which is the identification information of the transportation company. The transportation quality is information evaluated based on the past transportation results such as whether or not the cardboard box is damaged during transportation.

The acquisition unit 12 acquires, for example, the sales form corresponding to the product code included in the basic information as external information. Further, the acquisition unit 12 has, for example, from the external information DB 22 the address corresponding to the base code of the shipping destination base included in the basic information and the address of the base (hereinafter referred to as “own base”) to which the basic information has been transmitted. Is extracted, the transportation route between the two bases is searched, and the transportation distance estimated from the searched transportation route is acquired as external information. Further, the acquisition unit 12 calculates, for example, the residence time of the product in the warehouse of the base from the entry / exit date and time included in the basic information, extracts the warehouse average humidity corresponding to the own base, and the residence time ×. Acquire the warehouse average humidity as external information. If it is possible to acquire the transition of the actual humidity during the period when the product was stored in the warehouse instead of the average humidity in the warehouse, the acquisition unit 12 may acquire the residence time × the cumulative humidity as external information. good. Further, the acquisition unit 12 acquires, for example, the transportation quality corresponding to the transportation company code included in the basic information from the external information DB 22 as external information.

The acquisition unit 12 may acquire different types of external information according to the base classification of its own base. For example, if the base classification is a retailer, the next shipping destination does not exist, so instead of the above estimated transportation distance, the actual transportation distance from the previous stage base to your own base is acquired as external information. You may. The actual transportation distance may be acquired, for example, by storing information acquired from a GPS mounted on a truck, a drive recorder, various meters, or the like, or by accessing a database managed by a transportation company. If your base is a retailer, there is no next shipping destination, so it is assumed that the decision on whether or not to ship is possible when the product is received in the warehouse of your base or before the product is displayed in the store. The retailer.

Further, each table included in the external information DB 22 is not limited to the case where it is stored in the information processing device 10, and may be stored in a storage device such as each base, each transportation company, or an external organization that manages them. good. In this case, the acquisition unit 12 accesses the corresponding storage device and acquires the corresponding external information. Further, the acquisition unit 12 may acquire external information from other than the external information DB 22. For example, the acquisition unit 12 may acquire information such as the weather, season, humidity, and temperature when the product is stored and transported from an external database that manages the weather information as external information.

The acquisition unit 12 passes the acquired appearance image, basic information, and external information to the determination unit 14.

The determination unit 14 determines whether or not the product to be determined can be shipped based on the appearance image and external information acquired from the acquisition unit 12 and the model and teacher data stored in the determination DB 24.

FIG. 6 shows an example of the determination DB 24. In the example of FIG. 6, the determination DB 24 includes a region extraction model 242, a similar data extraction model 244, and a teacher data table 246. The area extraction model 242 is a machine-learned model in which an external image of a cardboard box in which a product is packed and an area to be determined in the external image are associated with each other, and the area to be determined is extracted from the external image. It is a model of. As the region extraction model 242, for example, an object detection neural network such as SSD (Single Shot Multibox Detector) can be applied.

The similar data extraction model 244 is a model for extracting teacher data similar to the appearance image and external information of the product to be determined from the teacher data stored in the teacher data table 246, and is, for example, VAE (Variational Auto). -Encoder) etc. can be applied. In the teacher data table 246, a plurality of external images and external information about the products for which it has been determined whether or not they can be shipped in the past are stored as teacher data. Further, in the teacher data table 246, the determination result of whether or not the product indicated by the teacher data can be shipped is stored in association with each teacher data. Further, the teacher data table 246 stores information indicating the contents of the cardboard box in which the product indicated by the teacher data is packed, that is, information indicating the state of the product in association with each other. In the example of FIG. 6, as the information indicating the contents, the contents image of the product inside the cardboard box is stored.

Each of the region extraction model 242 and the similar data extraction model 244 can include a plurality of machine-learned models for each type of damaged state of the cardboard box in which the goods for which shipment availability has been determined are packed. Alternatively, each of the region extraction model 242 and the similar data extraction model 244 can be one model machine-learned using appearance images showing a plurality of types of damaged states.

Here, there are multiple types of damaged cardboard boxes, such as bulging, opening of notches, wrinkles associated with short flaps, dirt adhesion, rubbing, flap peeling, tearing, wetting, and flat parts. There are inward folds, corner folds, corner crushes, etc. Corrugated cardboard box breaks can be a combination of these types of breaks, in which case one machine-learned model with appearance images showing multiple types of break states was used. In this case, it is possible to more accurately determine whether or not the product can be shipped based on the presence or absence of damage. Further, when there is only one model, the model configuration can be simplified. On the other hand, when it is desired to determine whether or not a product can be shipped based on a specific type of damaged state, it is more accurate to use a machine-learned model using the teacher data of the specific type of damaged state based on the presence or absence of damage. It is possible to determine whether or not the product can be shipped.

Specifically, the determination unit 14 uses the area extraction model 242 to extract an area for determining whether or not the cardboard box is damaged from the appearance image of the product to be determined. When the region is extracted, the determination unit 14 displays, for example, the region confirmation screen 42 as shown in FIG. 7 on the base terminal 30, and accepts the modification of the region. In the example of FIG. 7, the area confirmation screen 42 includes an external image 422, a frame 424 showing the extracted area, and a determination button 426 selected when the area is determined and the determination is started. When modifying an area, the person in charge of work at the base operates the frame 424 to specify a predetermined area and selects the determination button 426.

The determination unit 14 calculates the degree of similarity between the appearance image and the external information in which the region to be determined is determined and the teacher data stored in the teacher data table 246 using the similar data extraction model 244. The determination unit 14 extracts a predetermined number of teacher data in descending order of similarity to the appearance image and external information of the product to be determined. The determination unit 14 determines whether or not the product to be determined can be shipped by using the determination result stored in association with the extracted teacher data in the teacher data table 246. More specifically, the determination unit 14 determines whether or not the product to be determined can be shipped based on whether or not the score obtained by summing up the determination results corresponding to the extracted predetermined teacher data is equal to or higher than the predetermined determination criterion. judge.

For example, the determination unit 14 can use the ratio of shipable or undeliverable in a predetermined number of determination results as a score. For example, in the case of the determination criterion that the ratio of shipability is 3/5 or more, when 5 determination results are extracted, the determination unit 14 determines if the determination result of shipability is 3 or more. It is judged that the product can be shipped. Further, for example, the determination unit 14 may give each determination result a weight that increases as the degree of similarity increases, and may use the sum of the weights of the determination results that can be shipped or cannot be shipped as a score.

Further, the determination unit 14 may set the determination criteria according to the external information of the product to be determined. For example, the determination unit 14 can be set so that the determination criteria are relaxed when the sales form of the product to be determined is sold separately than when the product is sold separately. Further, for example, the determination unit 14 may have different determination criteria depending on whether the shipping destination is a wholesaler or a retailer.

Further, the determination unit 14 may further use the numerical information of the damaged portion detected from the appearance image of the product to be determined to determine whether or not the product to be determined can be shipped. For example, the determination unit 14 detects numerical information such as the area, length, and angle of the damaged portion by image processing on the region to be determined of the appearance image, and estimates the degree of damage based on the numerical information. .. Then, for example, when the determination result based on the determination result of the similar data can be shipped and the degree of damage is small, the determination unit 14 can determine that the determination result can be shipped as the final determination result. The combination of the determination result of similar data and the determination based on the numerical information for the final determination can be appropriately set. Further, this combination method may also be different depending on the external information.

When the determination unit 14 determines whether or not the product to be determined can be shipped, the determination unit 14 displays the determination result screen 44 as shown in FIG. 8, for example, on the base terminal 30. In the example of FIG. 8, the determination result screen 44 has an external image 422 of the product to be determined, a frame 424 showing the area to be determined, a similar data display area 442 in which information on similar data is displayed, and a determination result. A display area 444 and an objection button 446 are included. In the similar data display area 442, a thumbnail image of an appearance image of a product to be determined, an appearance image of a predetermined number of teacher data similar to external information, and a determination result associated with the teacher data are displayed. .. In addition, a detail button is provided in association with each teacher data, and when the detail button is selected, external information included in the teacher data and a content image associated with the teacher data are displayed (illustrated). omit). By displaying this external information and the content image, it is possible to present a reason for the determination result and enhance the convincingness of the determination result.

The objection button 446 is selected by the person in charge of the work at the base when there is an objection to the determination result. When the objection button 446 is selected, objection information indicating that there is an objection to the determination result is transmitted from the base terminal 30 to the information processing apparatus 10.

The determination unit 14 passes the appearance image, basic information, external information, and the determination result of the product to be determined to the creation unit 16.

When the objection information is transmitted from the base terminal 30, the creation unit 16 acquires the objection information. Then, the creating unit 16 determines the appearance image, basic information, external information, and the determination result of the product to be determined delivered from the determination unit 14 and the acquired objection information, for example, as shown in FIG. It is stored in the history DB 26 as a determination history.

Further, when the determination result delivered from the determination unit 14 cannot be shipped, the creation unit 16 has the product identification information (for example, the product code, the manufacturing factory, and the product code) included in the basic information delivered together with the determination result. Create trace information that traces the distribution process based on the production lot). Specifically, the creating unit 16 searches the determination history DB 26 for the corresponding determination history using the product identification information as a key, and creates trace information recording each of the determination histories at each site. For example, in the present embodiment, it is assumed that the retailer, that is, the determination of whether or not the product indicated by the appearance image and the basic information transmitted from the base terminal 30C can be shipped cannot be shipped. In this case, the creating unit 16 creates and outputs trace information including a determination history in the retailer, a determination history in the wholesaler in the previous stage of the retailer, and a determination history in the shipping source in the previous stage of the wholesaler. With this trace information, it is possible to promptly take measures such as strengthening the inspection of other products that follow the same distribution process and collecting damaged products.

Further, the creating unit 16 aggregates the judgment history having the objection information among the determination history stored in the determination history DB 26 at a predetermined timing, and selects at least one of the bases and products in which the frequency of occurrence of the objection is equal to or higher than the predetermined value. Identify. The creation unit 16 creates and outputs an objection occurrence status report including information on the specified product and base, judgment history related to the product and base, and the like. With this objection occurrence report, it is possible to interview the person in charge of the work at the base where there are many dissents, and to urge the person in charge of the work to make a proper judgment.

In addition, the creating unit 16 updates the determination result associated with the teacher data related to at least one of the identified bases and products whose disputes occur frequency of a predetermined value or more. For example, when the frequency of objections to the determination result of shipability of the specified product is equal to or higher than a predetermined value, the creation unit 16 determines that at least a part of the teacher data of the teacher data is associated with the teacher data. Change the result to non-shipable. Further, for example, when the frequency of objections to the determination result of non-shipment is equal to or higher than a predetermined value for the specified base, the creation unit 16 has at least a part of the teacher data including the base corresponding to the external information in the teacher data. The judgment result associated with is changed so that it can be shipped.

Further, the creating unit 16 aggregates the judgment history stored in the judgment history DB 26 at a predetermined timing based on the judgment result, and identifies at least one of the products and bases whose shippable or non-shippable frequency is equal to or higher than the predetermined value. do. The creation unit 16 creates and outputs a judgment result report including information on the specified product and base, a judgment history related to the product and the base, and the like. Based on this determination result report, it is possible to take measures such as strengthening cardboard boxes and reviewing the distribution process for products whose frequency of determination that shipment is not possible is equal to or higher than a predetermined value. In addition, from the viewpoint of product loss and workload, it is possible to consider measures such as updating the determination results associated with the teacher data for the relevant product so that they can be shipped together. In addition, for products whose frequency of determination to be shipable is more than a predetermined value, consideration can be given to the environmental load by considering the weight reduction and thinning of the cardboard box.

In addition, based on this judgment result report, we will review the storage environment of products in the warehouse of the base and review the transportation route to the base for the bases where the frequency of judgment that shipping is not possible is more than the specified value. be able to. It should be noted that the creating unit 16 has acquired an image of the appearance of the cardboard box at the time of warehousing in the warehouse of the base and an image of the appearance at the time of leaving the warehouse, and by comparing the two, has the damage occurred in the warehouse of the base? , It may be determined whether the transportation route to the base has been damaged. In this case, the appearance image at the time of warehousing and delivery may also be stored in the determination history DB 26 as the determination history.

The information processing apparatus 10 can be realized by, for example, the computer 50 shown in FIG. The computer 50 includes a CPU (Central Processing Unit) 51, a memory 52 as a temporary storage area, and a non-volatile storage unit 53. Further, the computer 50 includes an input / output device 54 such as an input unit and a display unit, and an R / W (Read / Write) unit 55 that controls reading and writing of data to the storage medium 59. Further, the computer 50 includes a communication I / F (Interface) 56 connected to a network such as the Internet. The CPU 51, the memory 52, the storage unit 53, the input / output device 54, the R / W unit 55, and the communication I / F 56 are connected to each other via the bus 57.

The storage unit 53 can be realized by an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, or the like. The information processing program 60 for making the computer 50 function as the information processing device 10 is stored in the storage unit 53 as a storage medium. The information processing program 60 has an acquisition process 62, a determination process 64, and a creation process 66. Further, the storage unit 53 has an information storage area 70 in which information constituting each of the external information DB 22, the determination DB 24, and the determination history DB 26 is stored.

The CPU 51 reads the information processing program 60 from the storage unit 53, expands the information processing program 60 into the memory 52, and sequentially executes the processes included in the information processing program 60. The CPU 51 operates as the acquisition unit 12 shown in FIG. 3 by executing the acquisition process 62. Further, the CPU 51 operates as the determination unit 14 shown in FIG. 3 by executing the determination process 64. Further, the CPU 51 operates as the creation unit 16 shown in FIG. 3 by executing the creation process 66. Further, the CPU 51 reads information from the information storage area 70, and expands each of the external information DB 22, the determination DB 24, and the determination history DB 26 into the memory 52. As a result, the computer 50 that has executed the information processing program 60 functions as the information processing device 10. The CPU 51 that executes the program is hardware.

The function realized by the information processing program 60 can also be realized by, for example, a semiconductor integrated circuit, more specifically, an ASIC (Application Specific Integrated Circuit) or the like.

Next, the operation of the information processing system 100 according to the first embodiment will be described. When the application provided by the information processing system 100 is started in the base terminal 30 and the determination of whether or not to ship is instructed, the information processing apparatus 10 executes the determination process shown in FIG. Further, the information processing apparatus 10 executes the objection aggregation process shown in FIG. 12 and the determination aggregation process shown in FIG. 13 at predetermined timings. The determination process, the objection aggregation process, and the determination aggregation process are examples of information processing methods of the disclosed technology. Hereinafter, each of the determination process, the objection aggregation process, and the determination aggregation process will be described in detail.

First, the determination process shown in FIG. 11 will be described.

In step S11, the acquisition unit 12 displays, for example, the shooting screen 40 as shown in FIG. 4 on the base terminal 30 instructed to determine whether or not to ship. Then, the acquisition unit 12 acquires the appearance image of the cardboard box and the basic information of the product, which are photographed and input by the person in charge of the work at the base via the photographing screen 40.

Next, in step S12, the acquisition unit 12 acquires external information corresponding to the acquired appearance image from the external information DB 22 or the like based on the acquired basic information. The acquisition unit 12 passes the acquired appearance image, basic information, and external information to the determination unit 14.

Next, in step S13, the determination unit 14 uses the area extraction model 242 to extract an area for determining whether or not the cardboard box is damaged from the appearance image of the product to be determined. Then, the determination unit 14 displays, for example, the area confirmation screen 42 as shown in FIG. 7 on the base terminal 30, accepts the correction of the area, and determines the area.

Next, in step S14, the determination unit 14 determines the degree of similarity between the appearance image and the external information in which the region to be determined is determined and the teacher data stored in the teacher data table 246, and the similarity data extraction model 244. Is calculated using. Then, the determination unit 14 extracts a predetermined number of teacher data in descending order of the degree of similarity with the appearance image and the external information of the product to be determined.

Next, in step S15, the determination unit 14 sets the determination criteria according to the external information of the product to be determined. Then, the determination unit 14 acquires each of the determined determination results corresponding to the extracted predetermined teacher data from the teacher data table 246, and whether the score obtained by totaling each of the determination results corresponding to the teacher data is equal to or higher than the predetermined determination criterion. Based on whether or not, it is determined whether or not the product to be determined can be shipped.

Next, in step S16, the determination unit 14 displays the determination result screen 44 as shown in FIG. 8, for example, on the base terminal 30. Further, the determination unit 14 passes the appearance image, the basic information, the external information, and the determination result of the product to be determined to the creation unit 16. Then, the creating unit 16 stores the appearance image, the basic information, the external information, and the determination result of the product to be determined as the determination history in the determination history DB 26 as shown in FIG. 9, for example.

Next, in step S17, the creating unit 16 determines whether or not the determination result of whether or not the product to be determined can be shipped is whether or not it can be shipped. If the product cannot be shipped, the process proceeds to step S18, and if the product can be shipped, the process proceeds to step S19.

In step S18, the creating unit 16 traces the distribution process based on the product identification information (for example, the product code, the manufacturing factory, and the manufacturing lot) included in the basic information passed together with the determination result. Create and output.

Next, in step S19, the creation unit 16 determines whether or not the objection information transmitted from the base terminal 30 is accepted by selecting the objection button 446 on the determination result screen 44. If the objection information is received, the process proceeds to step S20, and if it is not accepted, the determination process ends.

In step S20, the creating unit 16 adds and stores information indicating that there is objection information to the judgment history stored in the judgment history DB 26 in step S16, and the judgment process ends.

Next, the objection aggregation process shown in FIG. 12 will be described.

In step S21, the creating unit 16 aggregates the determination history having the objection information among the determination history stored in the determination history DB 26, and identifies at least one of the base and the product in which the frequency of occurrence of the objection is equal to or more than a predetermined value.

Next, in step S22, the creation unit 16 creates and outputs an objection occurrence status report including information on the specified product and base, determination history related to the product and base, and the like.

Next, in step S23, the determination result associated with the teacher data related to at least one of the base and the product whose objectation frequency is equal to or higher than the predetermined value specified by the creation unit 16 is referred to as the original determination result. The result is updated to the opposite judgment result, and the objection aggregation process ends.

Next, the determination aggregation process shown in FIG. 13 will be described.

In step S31, the creating unit 16 aggregates the determination history stored in the determination history DB 26 based on the determination result, and identifies at least one of the product and the base where the frequency of shipability or non-shipment is a predetermined value or more.

Next, in step S32, the creation unit 16 creates and outputs a judgment result report including information on the specified product and base, judgment history related to the product and base, and the like, and the judgment aggregation process ends.

As described above, according to the information processing system according to the first embodiment, the information processing apparatus includes an external image of a cardboard box in which a product to be determined whether it can be shipped is packed, and product information and distribution information to be determined. Get external information, including at least one. In addition, the information processing device is machine-learned to associate the teacher data consisting of the appearance image and external information of the product for which shipment availability has been determined with the product shipment availability determination result according to the damaged state of the cardboard box. The model was remembered. Then, the information processing apparatus determines whether or not the product to be determined can be shipped based on the model and the acquired external image and external information of the product to be determined. As a result, it is possible to determine whether or not a product packed in a cardboard box can be shipped based on a common recognition criterion that takes into consideration various conditions.

In the first embodiment, the case of determining whether or not the product can be shipped by using the external information acquired at each base has been described, but the present invention is not limited to this. For example, it may be determined whether or not shipping is possible by using the external information acquired about the own base and the external information acquired at each of the bases prior to the own base in the distribution process. In this case, when determining whether or not to ship at each base, the determination history DB 26 is searched using the product identification information included in the acquired basic information as a key, and the external information included in the determination history in each of the previous stages is acquired. , You can combine it with the external information of your own base. Similarly, at the time of machine learning of the model, each teacher data may have external information of the base in the previous stage. As a result, it is possible to obtain a determination result that more reflects the situation of the distribution process.

Further, in the first embodiment, it is assumed that it is determined whether or not the cardboard box is damaged at the time of determining whether or not the cardboard can be shipped, but the present invention is not limited to this. For example, based on the damaged state of the cardboard box containing the product to be judged after a predetermined time, which is predicted using a machine-learned model of the correspondence between the teacher data acquired in time series and the judgment result. It may be determined whether or not the product to be determined can be shipped. In this case, even if the product is not damaged at the time of shipment, it may be damaged at the time of transportation, storage at the warehouse at the shipping destination, take-out by the consumer, etc., and it is considered that there is a safety problem before shipping. It can be determined that it is not possible.

Further, in the first embodiment, the judgment value obtained based on the appearance image and the external information of the judgment target product is determined to be undeliverable, and the judgment value obtained is higher than the specific reference value regarding safety. If so, you may want to send a safety alert. The determination value may be, for example, the degree of similarity between the appearance image and external information of the product to be determined and the teacher data whose determination result cannot be shipped. Further, as described above, when predicting the damage state after a predetermined time, the determination value according to the predicted damage state may be calculated. The alert is transmitted to the corresponding base terminal together with the determination result, and can be displayed as a warning text or the like as shown by the broken line portion in FIG. 14, for example.

Further, in the first embodiment, the case of using an external image obtained by photographing the determination target portion of the cardboard box has been described, but the photographing range is not limited to this. For example, as shown in FIG. 15, it may be possible to determine whether or not shipping is possible in units of pallets, for example, by using an external image of cardboard boxes loaded on a truck taken at once. As a result, it is possible to reduce the workload such as shooting for determining whether or not the product can be shipped and inputting basic information.

Further, in the above case, it may be determined whether or not the product packed in the cardboard box existing on the back surface of the cardboard box recognized from the appearance image of the product to be determined can be shipped. In this case, using a machine-learned model that associates the teacher data with the judgment result based on the damaged state of the cardboard box on the back, it is necessary to judge whether or not the product packed in the cardboard box on the back can be shipped. Just do it.

<Second Embodiment>
Next, the second embodiment will be described. In the information processing system according to the second embodiment, the same components as those of the information processing system 100 according to the first embodiment are designated by the same reference numerals and detailed description thereof will be omitted.

As shown in FIG. 2, the information processing system 200 according to the second embodiment includes an information processing device 210 and base terminals 30A, 30B, and 30C.

Functionally, as shown in FIG. 16, the information processing apparatus 210 includes a test processing unit 218 in addition to the functional configuration of the information processing apparatus 10 according to the first embodiment. In the information processing apparatus 210 according to the second embodiment, an operation mode and a test mode can be selected. When the operation mode is selected, the acquisition unit 12, the determination unit 14, and the creation unit 16 function in the same manner as in the information processing apparatus 10 according to the first embodiment to determine whether or not the product to be determined can be shipped. It is judged. When the test mode is selected, the test processing unit 218 functions to perform a test on the test subject.

The test processing unit 218 presents the appearance image for the test of the appearance image of the cardboard box, accepts the judgment of whether or not the appearance image for the test can be shipped from the test subject, and presents the correctness of the judgment by the test subject. ..

Specifically, the test processing unit 218 selects one teacher data from the teacher data stored in the teacher data table 246 of the determination DB 24. The selection method may be random, or the teacher data may be associated with information indicating the type of damage in advance, and the teacher data of the specified type of damage may be selected. The test processing unit 218 displays the problem screen 46 as shown in FIG. 17, for example, on the base terminal 30 used by the test subject. In the example of FIG. 17, on the problem screen 46, the appearance image 462 included in the selected teacher data, the frame 464 showing the determination area set in the appearance image 466, and the external information included in the selected teacher data are displayed. Is displayed. Further, the question screen 46 includes an answer button 468 for the test subject to select an answer. When the test subject selects the answer button 468 corresponding to shipability or non-shipment, the answer by the test subject is transmitted from the base terminal 30 to the information processing apparatus 210.

When the test processing unit 218 acquires the answer from the base terminal 30, the test processing unit 218 acquires the determination result stored in association with the selected teacher data from the teacher data table 246. Then, the test processing unit 218 displays the answer screen 48 as shown in FIG. 18, for example, on the base terminal 30. In the example of FIG. 18, the answer screen 48 displays the appearance image 462 and the frame 464 displayed on the question screen 46, and the answer matching information 482. The answer matching information 482 includes the answer selected by the test subject, and also includes the determination result corresponding to the teacher data as the correct answer.

Further, the answer screen 48 includes a next button 484 for displaying the next question and a result display button 486 for displaying the test result. The test processing unit 218 activates the next button 484 and deactivates the result display button 486 when there is an unimplemented problem among the preset number of problems. Further, the test processing unit 218 displays the next button 484 inactive and the result display button 486 actively when all the preset number of problems have been executed.

When the next button 484 is selected by the test subject, the test processing unit 218 selects the teacher data for the next question and displays the question screen 46 again. When the result display button 486 is selected by the test subject, the test processing unit 218 displays the test result on the base terminal 30. The test result can include the answer of the test subject for each question, the correct answer, the correct answer rate, the pass / fail judgment result based on the correct answer rate, and the like. In addition, the test result may include a message prompting the user to take the test again, a message prompting the supervisor to report, and the like.

The information processing device 210 can be realized by, for example, the computer 50 shown in FIG. The information processing program 260 for causing the computer 50 to function as the information processing device 210 is stored in the storage unit 53 of the computer 50. The information processing program 260 has an acquisition process 62, a determination process 64, a creation process 66, and a test processing process 268. Further, the storage unit 53 has an information storage area 70 in which information constituting each of the external information DB 22, the determination DB 24, and the determination history DB 26 is stored.

The CPU 51 reads the information processing program 260 from the storage unit 53, expands it into the memory 52, and sequentially executes the processes included in the information processing program 260. The CPU 51 operates as the test processing unit 218 shown in FIG. 16 by executing the test processing process 268. The other processes are the same as those of the information processing program 60 according to the first embodiment. As a result, the computer 50 that has executed the information processing program 260 functions as the information processing device 210.

The function realized by the information processing program 260 can also be realized by, for example, a semiconductor integrated circuit, more specifically, an ASIC or the like.

Next, the operation of the information processing system 100 according to the second embodiment will be described. When the application provided by the information processing system 100 is started in the base terminal 30 and the test mode is selected, the test mode processing shown in FIG. 19 is executed in the information processing apparatus 210.

In step S211th, the test processing unit 218 selects one teacher data from the teacher data stored in the teacher data table 246 of the determination DB 24. Then, the test processing unit 218 displays the problem screen 46 as shown in FIG. 17, for example, on the base terminal 30 used by the test subject.

Next, in step S212, the answer by the test subject transmitted from the base terminal 30 to the information processing apparatus 210 by selecting the answer button 468 corresponding to whether the test subject can or cannot ship on the question screen 46. Is acquired by the test processing unit 218.

Next, in step S213, the test processing unit 218 acquires the determination result stored in association with the selected teacher data from the teacher data table 246. Then, the test processing unit 218 displays the answer screen 48 as shown in FIG. 18, for example, on the base terminal 30.

Next, in step S214, the test processing unit 218 determines whether or not all the preset questions have been executed. When all the questions are completed, the test processing unit 218 displays the next button 484 inactive and the result display button 486 active on the answer screen 48, and when the result display button 486 is selected, the process is stepped. Move to S215. On the other hand, when there is an unimplemented question, the test processing unit 218 displays the next button 484 inactive and the result display button 486 inactive on the answer screen 48, and the next button 484 is selected. , The process returns to step S211.

In step S215, the test processing unit 218 displays the test result including the answer and the correct answer, the correct answer rate, the pass / fail judgment result based on the correct answer rate, various messages, etc. for each question on the base terminal 30, and performs the test mode processing. Is finished.

As described above, according to the information processing system according to the second embodiment, the information processing apparatus presents an external image for testing of the external image of the cardboard box, and the test subject presents an external image for testing. Accepts the judgment of whether or not the product can be shipped. Then, the information processing apparatus presents the correctness of the determination by the test subject. As a result, it is possible to give the work target person a common recognition of the determination criteria.

The test mode is a judgment standard when the work person makes a judgment regardless of the application, for example, in the case of an operation in which the judgment by the information processing system is used when it is difficult for the work person to judge whether or not the product can be shipped. It is useful as an educational tool for the common recognition of. In particular, if the worker has little experience, it is possible to recognize common criteria even if there are differences in cultural background and language used.

In addition, by disclosing the test mode to consumers on the Internet or the like and showing unified judgment criteria, it is possible to enlighten the appropriate judgment criteria with guaranteed safety. This makes it possible to reduce unnecessary disposal of products.

In the second embodiment, the case where the teacher data is used for the problem has been described, but the present invention is not limited to this. For example, an external image of a cardboard box for a test question and external information may be acquired from the outside and presented as a question. In this case, as in the first embodiment, the model may be used to determine whether or not the acquired appearance image and external information can be shipped, and the determination result may be the correct answer to the problem.

Further, in each of the above embodiments, the mode in which the information processing program is stored (installed) in the storage unit in advance has been described, but the present invention is not limited to this. The program according to the disclosed technology can also be provided in a form stored in a storage medium such as a CD-ROM, a DVD-ROM, or a USB memory.

The following additional notes will be further disclosed with respect to each of the above embodiments.

(Appendix 1)
An external image including an external image of a cardboard box in which a product to be determined to be shipped is packed, and external information including at least one of information on the product to be determined and information on distribution of the product to be determined is acquired.
A model in which the machine learning of the correspondence between the external image and the external information of the product for which the shipability has been determined and the determination result of the product shipmentability according to the damaged state of the cardboard box, and the acquired determination target An information processing program for causing a computer to execute a process including determining whether or not the product to be determined can be shipped based on the appearance image and the external information of the product.

(Appendix 2)
The information about the product includes information on the sales form of the product, and includes information on the sales form of the product.
The information processing program according to Appendix 1, wherein the information related to distribution includes at least one of information specifying a distribution process, information on storage conditions in a warehouse, information on transportation conditions, and environmental information at the time of distribution.

(Appendix 3)
When a plurality of bases are included in the distribution process, the determination at the predetermined base is based on the appearance image and the external information at each of the predetermined base in the distribution process and the base in the previous stage of the predetermined base. The information processing program according to Appendix 1 or Appendix 2 that determines whether or not the target product can be shipped.

(Appendix 4)
Each of the above-mentioned determination results corresponding to the presented appearance images is presented while presenting the appearance images of the top-ranked predetermined items whose shipmentability has been determined in descending order of similarity with the appearance images of the products to be determined. The information processing program according to any one of Supplementary note 1 to Supplementary note 3, which determines whether or not the product to be determined can be shipped based on whether or not the score obtained by summarizing the above is equal to or higher than a predetermined standard.

(Appendix 5)
The information processing program according to Appendix 4, which sets the predetermined criteria according to the external information of the product to be determined.

(Appendix 6)
The information processing program according to Appendix 5, which is set so that the predetermined standard is relaxed when the product to be determined is sold separately as compared with the case where the product to be determined is sold as a packed cardboard box. ..

(Appendix 7)
Information indicating the state of the contents of the product for which shipment availability has been determined is stored in association with the appearance image of the product for which shipment availability has been determined, and the upper predetermined quantity of the product for which shipment availability has been determined has been determined. The information processing program according to any one of Supplementary note 4 to Supplementary note 6, which presents information indicating the state of the corresponding contents when presenting the appearance image of the product.

(Appendix 8)
The model includes a plurality of models machine-learned for each type of the damaged state of the cardboard box in which the product whose shipmentability has been determined is packed, or uses the external image showing the plurality of types of the damaged state. The information processing program according to any one of Supplementary note 1 to Supplementary note 7, which is one model that has been machine-learned.

(Appendix 9)
The information processing according to any one of Supplementary note 1 to Supplementary note 8, which accepts an objection to the determination result regarding whether or not the product to be determined can be shipped, and specifies at least one of the base and the product in which the frequency of the objection is equal to or higher than a predetermined value. program.

(Appendix 10)
Addendum to update the determination result associated with the appearance image and the external information of the product for which the shipability has been determined, which is related to at least one of the specified bases and products whose frequency of occurrence of the objection is equal to or higher than a predetermined value. The information processing program according to 9.

(Appendix 11)
After a predetermined time, it is predicted using a model that machine-learns the correspondence between the appearance image and the external information of the product for which the shipability has been determined acquired in time series and the shipmentability determination result. The information processing program according to any one of Supplementary note 1 to Supplementary note 10, which determines whether or not the product to be determined can be shipped based on the damaged state of the cardboard box containing the product to be determined.

(Appendix 12)
The determination result of whether or not the product to be determined can be shipped, which is determined at each base in the distribution process, is stored in association with the external information about the product to be determined, and the frequency at which it is determined that the product can be shipped or cannot be shipped is predetermined. The information processing program according to any one of Supplementary note 1 to Supplementary note 11, which specifies a product having a value or higher and at least one of the above-mentioned bases.

(Appendix 13)
When it is determined that the product to be judged cannot be shipped and the judgment value obtained based on the appearance image and the external information of the product to be judged exceeds a specific reference value for safety, the safety is concerned. The information processing program according to any one of Supplementary note 1 to Supplementary note 12, which sends an alert.

(Appendix 14)
For the appearance image of the cardboard box, present the appearance image for testing,
Accepting the judgment of whether or not the appearance image for the test can be shipped from the test subject,
The information processing program according to any one of Supplementary note 1 to Supplementary note 13, which presents the correctness of the determination by the test subject.

(Appendix 15)
At the time of acquiring the appearance image of the product to be determined, the identification information of the product to be determined is acquired.
The information processing program according to any one of Supplementary note 1 to Supplementary note 14, which traces the distribution process of a product determined to be undeliverable based on the identification information acquired at each base of the distribution process.

(Appendix 16)
The information processing according to any one of Supplementary note 1 to Supplementary note 15, which determines whether or not the product to be determined can be shipped by further using the numerical information of the damaged portion detected from the appearance image of the product to be determined. program.

(Appendix 17)
The determination target is made using a machine-learned model in which the damaged state of the cardboard box existing on the back surface of the cardboard box recognized from the appearance image of the product for which shipment availability has been determined is further associated with the determination result. The information processing program according to any one of Supplementary note 1 to Supplementary note 16, which determines whether or not the product packed in the cardboard box existing on the back surface of the cardboard box recognized from the appearance image of the product can be shipped.

(Appendix 18)
The appearance image of the product to be determined is acquired at each of the warehousing and warehousing at each base in the distribution process, and the base at the time of warehousing is determined to be unable to ship the product to be judged. The information processing program according to any one of Supplementary note 1 to Supplementary note 17, which compares the external appearance image with the external appearance image at the time of delivery and determines whether or not the cardboard box is damaged at the base.

(Appendix 19)
An acquisition unit that acquires an external image of a cardboard box in which a product to be determined to be shipped is packed, and external information including at least one of information on the product to be determined and information on distribution of the product to be determined.
A model obtained by machine learning the correspondence between the external image and external information of a product for which shipment availability has been determined and the determination result of product shipment availability according to the damaged state of the cardboard box, and the acquired determination target. Based on the appearance image and the external information of the product, the determination unit for determining whether or not the product to be determined can be shipped, and the determination unit.
Information processing equipment including.

(Appendix 20)
An external image including an external image of a cardboard box in which a product to be determined to be shipped is packed, and external information including at least one of information on the product to be determined and information on distribution of the product to be determined is acquired.
A model obtained by machine learning the correspondence between the external image and external information of a product for which shipment availability has been determined and the determination result of product shipment availability according to the damaged state of the cardboard box, and the acquired determination target. An information processing method in which a computer executes a process including determining whether or not the product to be determined can be shipped based on the appearance image and the external information of the product.

100, 200 Information processing system 10, 210 Information processing device 12 Acquisition unit 14 Judgment unit 16 Creation unit 218 Test processing unit 22 External information DB
222 Product information table 224 Base information table 226 Transportation information table 24 Judgment DB
242 Area extraction model 244 Similar data extraction model 246 Teacher data table 26 Judgment history DB
30 Base terminal 40 Shooting screen 42 Area confirmation screen 44 Judgment result screen 46 Question screen 48 Answer screen 50 Computer 51 CPU
52 Memory 53 Storage unit 59 Storage medium 60, 260 Information processing program

Claims (15)

An external image including an external image of a cardboard box in which a product to be determined to be shipped is packed, and external information including at least one of information on the product to be determined and information on distribution of the product to be determined is acquired.
A model in which the machine learning of the correspondence between the external image and the external information of the product for which the shipability has been determined and the determination result of the product shipmentability according to the damaged state of the cardboard box, and the acquired determination target An information processing program for causing a computer to execute a process including determining whether or not the product to be determined can be shipped based on the appearance image and the external information of the product. The information about the product includes information on the sales form of the product, and includes information on the sales form of the product.
The information processing program according to claim 1, wherein the information related to distribution includes at least one of information specifying a distribution process, information on storage conditions in a warehouse, information on transportation conditions, and environmental information at the time of distribution. When a plurality of bases are included in the distribution process, the determination at the predetermined base is based on the appearance image and the external information at each of the predetermined base in the distribution process and the base in the previous stage of the predetermined base. The information processing program according to claim 1 or 2, which determines whether or not the target product can be shipped. The appearance images of the products whose shipping availability has been determined are presented in descending order of similarity to the appearance image of the product to be determined, and each of the determination results corresponding to the presented appearance images. The information processing program according to any one of claims 1 to 3, which determines whether or not the product to be determined can be shipped based on whether or not the score obtained by summarizing the above is equal to or higher than a predetermined standard. The information processing program according to claim 4, wherein the predetermined standard is set according to the external information of the product to be determined. The information processing according to claim 5, wherein the information processing according to claim 5 is set so that the predetermined standard is relaxed when the product to be determined is sold separately as compared with the case where the product to be determined is sold as a packed cardboard box. program. The model includes a plurality of models machine-learned for each type of the damaged state of the cardboard box in which the product whose shipmentability has been determined is packed, or uses the external image showing the plurality of types of the damaged state. The information processing program according to any one of claims 1 to 6, which is one model machine-learned. The item according to any one of claims 1 to 7, wherein an objection to the determination result regarding whether or not the product to be determined can be shipped is accepted, and at least one of the base and the product in which the frequency of the objection occurs is a predetermined value or more is specified. Information processing program. A request for updating the determination result associated with the appearance image and the external information of the product for which the shipability has been determined, which is related to at least one of the specified bases and products whose frequency of occurrence of the objection is equal to or higher than a predetermined value. Item 8 is the information processing program. The determination result of whether or not the product to be determined can be shipped, which is determined at each base in the distribution process, is stored in association with the external information about the product to be determined, and the frequency at which it is determined that the product can be shipped or cannot be shipped is predetermined. The information processing program according to any one of claims 1 to 9, which specifies a product having a value or higher and at least one of the bases. When it is determined that the product to be determined cannot be shipped and the determination value obtained based on the appearance image and the external information of the product to be determined exceeds a specific reference value for safety, it is related to safety. The information processing program according to any one of claims 1 to 10, which sends an alert. For the appearance image of the cardboard box, present the appearance image for testing,
Accepting the judgment of whether or not the appearance image for the test can be shipped from the test subject,
The information processing program according to any one of claims 1 to 11, which presents the correctness of the determination by the test subject. At the time of acquiring the appearance image of the product to be determined, the identification information of the product to be determined is acquired.
The information processing program according to any one of claims 1 to 12, which traces the distribution process of a product determined to be undeliverable based on the identification information acquired at each base of the distribution process. An acquisition unit that acquires an external image of a cardboard box in which a product to be determined to be shipped is packed, and external information including at least one of information on the product to be determined and information on distribution of the product to be determined.
A model obtained by machine learning the correspondence between the external image and external information of a product for which shipment availability has been determined and the determination result of product shipment availability according to the damaged state of the cardboard box, and the acquired determination target. Based on the appearance image and the external information of the product, the determination unit for determining whether or not the product to be determined can be shipped, and the determination unit.
Information processing equipment including. An external image including an external image of a cardboard box in which a product to be determined to be shipped is packed, and external information including at least one of information on the product to be determined and information on distribution of the product to be determined is acquired.
A model obtained by machine learning the correspondence between the external image and external information of a product for which shipment availability has been determined and the determination result of product shipment availability according to the damaged state of the cardboard box, and the acquired determination target. An information processing method in which a computer executes a process including determining whether or not the product to be determined can be shipped based on the appearance image and the external information of the product.

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