Information processing device, information processing method, and recording medium

Abstract

An information processing device according to the present disclosure comprises an acquisition unit, a type identification unit, a volume identification unit, and a determination unit. The acquisition unit acquires an image. The type identification unit identifies the type of luggage captured in the image on the basis of the image. The volume identification unit identifies the volume of the luggage on the basis of the specified type of the luggage. The determination unit determines whether the total volume of the luggage carried into a predetermined space does not exceed a threshold value on the basis of the identified volume of the luggage.

Description

Information processing device, information processing method, and recording medium

[0001] The present disclosure relates to an information processing device, an information processing method, and a program.

[0002] A technology related to this disclosure is disclosed in Patent Document 1. Patent Document 1 discloses a technology for monitoring baggage carried on board an aircraft and outputting an alert based on the monitoring results. This technology determines whether the available storage space in a storage shelf falls below a threshold based on the dimensions (length, width, height) of the baggage identified by image analysis, the number of pieces of baggage carried on, or an image of the interior of the storage shelf. Then, this technology outputs an alert based on the result of this determination.

[0003] Japanese Patent Application Laid-Open No. 2022-109883

[0004] The technology disclosed in Patent Document 1 has the following problems. First, it is not easy to accurately determine the dimensions of luggage using image analysis. Also, the capacity of each piece of luggage varies. Therefore, the above determination based on the number of pieces of luggage does not provide sufficient accuracy. Furthermore, when there are many storage shelves, a large number of cameras are required to capture images of the interior of the shelves. As a result, the cost burden increases.

[0005] An example of a purpose of this disclosure is to provide a new technology for monitoring luggage brought into a predetermined space.

[0006] According to this disclosure, an information processing device is provided that has: an acquisition means for acquiring an image; a type identification means for identifying the type of luggage shown in the image based on the image; a capacity identification means for identifying the volume of the luggage based on the identified type of luggage; and a determination means for determining whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of the luggage.

[0007] This disclosure also provides an information processing method in which one or more computers acquire an image, identify the type of luggage shown in the image based on the image, identify the volume of the luggage based on the identified type of luggage, and determine whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of the luggage.

[0008] Furthermore, according to this disclosure, a program is provided that causes a computer to function as: an acquisition means for acquiring an image; a type identification means for identifying the type of luggage shown in the image based on the image; a capacity identification means for identifying the volume of the luggage based on the identified type of luggage; and a determination means for determining whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of the luggage.

[0009] According to one aspect of the present disclosure, a new technology for monitoring luggage brought into a predetermined space is realized.

[0010] FIG. 1 is a diagram showing an example of a functional block diagram of an information processing device. FIG. 2 is a flowchart showing an example of a processing flow of the information processing device. FIG. 3 is a diagram showing an example of a hardware configuration of the information processing device. FIG. 4 is a diagram showing another example of a functional block diagram of an information processing device. FIG. 5 is a diagram showing an example of an image processed by the information processing device. FIG. 6 is a diagram showing an example of information processed by the information processing device. FIG. 7 is a diagram showing another example of a functional block diagram of an information processing device. FIG. 8 is a diagram showing an example of information processed by the information processing device. FIG. 9 is a diagram showing an example of information processed by the information processing device. FIG. 10 is a diagram for explaining an example of processing executed by the information processing device.

[0011] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In this disclosure, the drawings relate to one or more embodiments. In all drawings, similar components are designated by similar reference numerals, and descriptions thereof will be omitted as appropriate.

[0012] First Embodiment Fig. 1 is a functional block diagram showing an overview of an information processing device 10. Fig. 2 is a flowchart showing an example of the flow of processing executed by the information processing device 10.

[0013] 1, the information processing device 10 includes an acquisition unit 11, a type identification unit 12, a capacity identification unit 13, and a determination unit 14. These functional units execute the process of the flowchart in FIG.

[0014] In S10, the acquisition unit 11 acquires an image. In S11, the type identification unit 12 identifies the type of luggage shown in the image based on the image acquired in S10. In S12, the capacity identification unit 13 identifies the volume of the luggage based on the type of luggage identified in S11. In S13, the determination unit 14 determines whether the total volume of the luggage brought into the specified space exceeds a threshold value based on the volume of the luggage identified in S12.

[0015] In this way, the information processing device 10 identifies the type of luggage shown in the image and determines the volume of the luggage based on the identified type of luggage. Then, based on the identified volume of the luggage, the information processing device 10 determines whether the total volume of the luggage brought into the specified space exceeds a threshold. Such information processing device 10 realizes a new technology for monitoring luggage brought into a specified space.

[0016] Incidentally, the technology disclosed in Patent Document 1 requires the dimensions (length, width, and height) of a package to be determined through image analysis. However, it is not easy to accurately determine package dimensions through image analysis. Depending on the camera's angle of view, it may not be possible to accurately estimate the length, width, and depth. In contrast, the information processing device 10 identifies the type of package shown in the image and determines the volume of the package based on the identified type of package. Such an information processing device 10 only needs to identify the type of package through image analysis, and does not need to determine the dimensions of the package. As a result, the problems with the technology disclosed in Patent Document 1 described above can be avoided.

[0017] In one embodiment of the technology disclosed in Patent Document 1, the lengths of luggage in a predetermined direction are accumulated and, based on the accumulated results, a determination is made as to whether the available storage space in the storage shelf meets a threshold value. However, there are various types of luggage, such as vertically long and horizontally long. Therefore, if the determination is based on the result of accumulating only the length in one direction, such as the vertical direction, there is a concern that an item may be erroneously determined to be storable even when it is actually unable to be stored. In response to this, the information processing device 10 determines the volume of the luggage based on the identified luggage type and, based on the identified luggage volume, determines whether the total volume of the luggage brought into the specified space exceeds a threshold value. Using the information processing device 10 that makes the above determination based on the volume of each luggage, the above-mentioned erroneous determination can be avoided.

[0018] Furthermore, the technology disclosed in Patent Document 1 determines whether the available storage space in a storage shelf meets a threshold value based on the number of pieces of luggage. However, the capacity of each piece of luggage varies. Therefore, a determination based on the number of pieces of luggage does not provide sufficient accuracy. In contrast, the information processing device 10 identifies the volume of each piece of luggage based on the identified type of luggage, and determines whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of each piece of luggage. In this way, the information processing device 10, which makes the above determination based on the volume of each piece of luggage, improves the accuracy of the determination compared to a determination based on the number of pieces of luggage.

[0019] Furthermore, the technology disclosed in Patent Document 1 determines whether the available storage space in a storage shelf meets a threshold value based on an image of the interior of the storage shelf. In this case, a large number of cameras are required according to the number of storage shelves. As a result, the cost required for the cameras increases. In contrast, the information processing device 10 only needs to photograph luggage at a predetermined point where luggage passes, such as an entrance gate. With such an information processing device 10, fewer cameras are required, thereby reducing costs.

[0020] <<Second Embodiment>> <Overview> An information processing apparatus 10 according to a second embodiment is a specific implementation of the configuration of the information processing apparatus 10 according to the first embodiment. A detailed description will be given below.

[0021] <Hardware Configuration> First, an example of the hardware configuration of the information processing device 10 will be described. Each functional unit of the information processing device 10 is realized by any combination of hardware and software. Those skilled in the art will understand that there are various variations in the realization method and device. The software includes programs that are pre-stored in the device before shipping, and programs downloaded from recording media such as CDs (Compact Discs) or servers on the Internet.

[0022] FIG. 3 is a block diagram illustrating an example of the hardware configuration of an information processing device 10. As shown in FIG. 3, the information processing device 10 has a processor 1A, a memory 2A, an input / output interface 3A, a peripheral circuit 4A, and a bus 5A. The peripheral circuit 4A includes various modules. The information processing device 10 does not necessarily have to have the peripheral circuit 4A. Note that the information processing device 10 may be composed of multiple devices that are physically and / or logically separated. In this case, each of the multiple devices may have the above hardware configuration.

[0023] The bus 5A is a data transmission path for the processor 1A, memory 2A, peripheral circuit 4A, and input / output interface 3A to mutually transmit and receive data. The processor 1A is, for example, a central processing unit (CPU) or a graphics processing unit (GPU). The memory 2A is, for example, a random access memory (RAM) or a read-only memory (ROM). The input / output interface 3A includes interfaces for acquiring information from input devices, external devices, external servers, external sensors, cameras, etc., and interfaces for outputting information to output devices, external devices, external servers, etc. The input / output interface 3A also includes an interface for connecting to a communication network such as the Internet. Examples of input devices include a keyboard, mouse, microphone, physical buttons, touch panel, code reader, etc. The code reader reads information such as barcodes and two-dimensional codes. In one example, the code reader reads codes on tickets, etc. The output device includes, for example, a display, a projection device, a speaker, a printer, a mailer, etc. The processor 1A can issue commands to each module and perform calculations based on the results of those calculations.

[0024] <Usage Scenarios> The information processing device 10 is used in situations where it is necessary to determine whether the total volume of baggage brought into a specified space exceeds a threshold. An example of such a situation is boarding an aircraft. Passengers are allowed to bring baggage into the cabin. However, there is an upper limit to the total volume of baggage that can be stored in the cabin. If baggage brought into the cabin exceeds this limit, safety will be compromised, and measures such as transferring the baggage to cargo will be necessary. For example, the information processing device 10 is used in such situations to determine whether the total volume of baggage brought into the cabin of an aircraft exceeds a threshold.

[0025] The usage scenarios illustrated here are merely examples, and the usage scenarios of the information processing device 10 are not limited to these examples.

[0026] <Functional Configuration> Next, the functional configuration of the information processing device 10 will be described in detail. Fig. 4 is an example of a functional block diagram of the information processing device 10. As shown in the figure, the information processing device 10 has an acquisition unit 11, a type identification unit 12, a capacity identification unit 13, a determination unit 14, and an output unit 16. Each functional unit will be described below.

[0027] The acquisition unit 11 acquires an image generated by a camera.

[0028] The camera is installed in a position where it can capture images of luggage being brought into the specified space. For example, the camera is installed in a position where it can capture images of a person bringing luggage into the specified space. Specifically, the camera may be installed in a position where it can capture images of a gate or entrance that must be passed through to enter the specified space. The camera may also be installed in a position where it can capture images of an aisle or area that must be passed through to enter the specified space. An example of a specified space is an aircraft cabin. In this case, the camera may be installed in a position where it can capture images of the boarding gate, the entrance to the cabin (aircraft), the waiting area before boarding, the aisle connecting the boarding gate and the cabin, the aisle within the cabin, etc. Note that the specified space is not limited to an aircraft cabin, but may also be a passenger cabin of a bus, ship, etc. Furthermore, the specified space is not limited to a passenger cabin in a moving object such as the above, but may also be a waiting space provided indoors or outdoors. Furthermore, the specified space is not limited to a space where people can stay or wait, but may also be a space intended for storing or accommodating luggage, such as a locker room, a warehouse, or the loading dock of a truck.

[0029] An example of an image P generated by a camera is shown in Figure 5. The image P shown in Figure 5 is an image generated by a camera installed at a position and orientation that allows it to capture a person passing through the boarding gate from above. Note that the position and orientation of the camera are merely examples and are not limiting.

[0030] The camera detects visible light to generate an image. The camera may also detect other electromagnetic waves, such as infrared or ultraviolet light, to generate an image. The camera may continuously capture moving images or may capture still images at predetermined times. The camera may continue to generate images from the start of a person's entry into a predetermined space until the person's entry is completed.

[0031] The acquisition unit 11 can acquire images generated by the camera through real-time processing. The information processing device 10 and the camera may be connected to each other so that they can communicate with each other. The camera may then transmit the images it generates to the information processing device 10 through real-time processing. Alternatively, the images generated by the camera may be stored in a predetermined image storage device in real time. The acquisition unit 11 may then acquire the images stored in this image storage device.

[0032] "Acquisition" includes at least one of the following: a device going to retrieve data or information stored in another device or storage medium (active acquisition), and a device inputting data or information output from another device (passive acquisition). Examples of active acquisition include making a request to another device and receiving a response, and accessing and reading information from another device or storage medium. An example of passive acquisition is receiving information that is distributed (or transmitted, push notification, etc.). Furthermore, acquisition may be selecting and acquiring from received data or information, or selecting and receiving distributed data or information.

[0033] 4 , the type identification unit 12 detects luggage (objects) from the images acquired by the acquisition unit 11. Then, the type identification unit 12 identifies the type of the detected luggage (the type of luggage shown in the images) based on the images acquired by the acquisition unit 11.

[0034] The type identification unit 12 can detect and identify the type of luggage using any well-known image analysis technology. For example, the type identification unit 12 may use an object detection model or a classifier generated by machine learning to achieve the detection and identification. For example, the classifier estimates which of multiple predefined types the type of luggage shown in the image corresponds to.

[0035] There are various ways to define the type of luggage, but multiple types can be defined by grouping items that have similar appearances and capacities. In one example, luggage types include, but are not limited to, suitcases, backpacks, handbags, shopping bags, etc.

[0036] The various types of luggage exemplified above may include various sizes. For example, suitcases come in a variety of capacities, such as large suitcases and small suitcases. In this case, the method of defining luggage types exemplified above may result in poor accuracy in determining the volume of luggage based on the type of luggage. However, in certain usage situations, such as carrying luggage into an airplane cabin, there may be an upper limit on the size of each piece of luggage that can be carried into a certain space. For this reason, simply defining the type of luggage as "suitcase" without further subdividing it into large suitcases and small suitcases allows for the volume of the luggage to be determined from the type of luggage with sufficient accuracy.

[0037] The type of luggage can be appropriately defined depending on the characteristics of such a usage scenario. Note that the above-described method of defining luggage types is merely an example and is not limited to this. For example, suitcases may be subdivided according to size, such as large suitcases and small suitcases. The same applies to other luggage. In one example, the size of the luggage (large, medium, small, etc.) may be estimated by comparing the body size of the person carrying the luggage with the size of the luggage. Note that this image analysis method is merely an example and is not limited to this. In the following Variation 4, another example of a method for estimating the size of luggage (large, medium, small, etc.) using image analysis will be described.

[0038] The capacity specifying unit 13 specifies the capacity of the package based on the type of package specified by the type specifying unit 12 .

[0039] A standard value for the capacity of each type of luggage is set in advance and stored in a predetermined storage device. An operator can set the standard value for the capacity of each type of luggage. The predetermined storage device may be provided within the information processing device 10, or may be provided in an external device communicatively connected to the information processing device 10. The same assumption regarding the predetermined storage device applies hereinafter.

[0040] The capacity specifying unit 13 specifies the standard value of each type of luggage indicated by the information as the capacity of each type of luggage. For example, assume that X is set as the standard value of the capacity of a suitcase. In this case, the capacity specifying unit 13 specifies X as the capacity of the luggage specified as a suitcase by the type specifying unit 12.

[0041] The determination unit 14 determines whether the total volume of the luggage brought into the specified space exceeds a threshold value based on the type of luggage identified by the type identification unit 12 and the volume of the luggage identified by the volume identification unit 13.

[0042] First, the process of calculating the total volume of luggage will be described. The determination unit 14 can calculate the total volume of luggage brought into a specified space by adding up the volumes of the various types of luggage detected from the image by the type identification unit 12. There are various ways to realize this calculation, but one example will be described below. Note that the following example is merely an example and is not limiting.

[0043] The determination unit 14 counts the number of pieces of luggage detected in the image for each type of luggage based on the identification result of the type identification unit 12. For example, the type identification unit 12 processes images generated from the start to the end of a person's entry into a predetermined space in real time, and detects pieces of luggage from each image. The determination unit 14 counts the number of pieces of luggage detected in images generated from the start to the end of a person's entry into a predetermined space for each type of luggage.

[0044] Then, for each type of luggage, the determination unit 14 calculates the volume of luggage brought into the specified space by multiplying the count value by the volume (the standard value) of each type of luggage identified by the volume identification unit 13. Then, the determination unit 14 adds up the volumes of luggage brought into the specified space calculated for each type of luggage to calculate the total volume of luggage brought into the specified space.

[0045] The process of counting the number of packages detected in the image for each package type can be realized by various methods. For example, the determination unit 14 may increment the count value for the package type by one when the package type identification unit 12 detects a package in the image.

[0046] Alternatively, when the type identification unit 12 detects a package in an image, the determination unit 14 may track the package within the image. Object tracking within an image can be achieved using any well-known technology. The determination unit 14 may then increment the count value of the package type by one when the tracked package satisfies a predetermined condition. The predetermined condition may be various, such as "passing a predetermined position within the image" or "being continuously detected in the image for a predetermined period of time or more," but is not limited to these. In this way, by tracking the detected package within the image and incrementing the count value of the package type when the predetermined condition is satisfied, the accuracy of the counting can be improved.

[0047] Next, a process for determining whether the total volume of luggage brought into a predetermined space exceeds a threshold will be described. The determination unit 14 can execute at least one of the following two determination processes.

[0048] (Determination process 1) A process for determining whether the total volume of luggage brought into a specified space exceeds the upper limit of the total volume of luggage that can be brought into a specified space. (Determination process 2) A process for determining whether the total volume of luggage brought into a specified space exceeds the upper limit guideline determined based on the situation at the time.

[0049] First, determination process 1 will be described. In determination process 1, the upper limit of the total volume of luggage that can be brought into the specified space is the threshold value. As a variant, the threshold value may be a value obtained by multiplying the upper limit of the total volume of luggage that can be brought into the specified space by a specified correction coefficient that is greater than 0 and less than 1. The upper limit of the total volume of luggage that can be brought into the specified space is, for example, the total volume of luggage storage space in the specified space, but is not limited to this.

[0050] The determination unit 14 compares the total volume of luggage brought into the specified space with the threshold value stored in advance in a specified storage device, and determines whether the total volume of luggage brought into the specified space exceeds the threshold value. When images generated from the start to the end of a person's entry into the specified space are processed in real time, the total volume of luggage brought into the specified space is updated in real time. The determination unit 14 can continue to compare the latest value of the total volume of luggage brought into the specified space with the threshold value from the start to the end of a person's entry into the specified space.

[0051] Next, we will explain Determination Process 2. In Determination Process 2, a "current upper limit guideline" is determined based on the above-mentioned "upper limit of the total volume of luggage that can be brought into a specified space" and the "current situation."

[0052] An example of the situation at that time is "the ratio of the total number of people entering a specified space to the upper limit."

[0053] The "total number of people who have entered a specified space by a certain point in time" can be determined by various methods. For example, in the case of an airplane, passengers are allowed to pass through the gate by entering their own identification information, ticket information, etc. into a gate system (such as an aircraft boarding gate). Based on this input information, the total number of people who have entered the cabin by a certain point in time may be counted. Alternatively, the total number of people who have entered a specified space by a certain point in time may be determined by analyzing images generated by the camera to detect people and counting the number of detected people.

[0054] The "upper limit" in the "ratio of the total number of people entering a specified space to the upper limit" is the expected number of people entering the specified space. In the case of an aircraft, each seat in the cabin is reserved in advance. In this case, the number of reserved seats is determined as the expected number of people entering the cabin. The determination unit 14 can identify the upper limit based on reservation information registered in a system that manages the reservation status of the aircraft. Note that instead of the expected number of people entering the specified space, the number of people that the specified space can accommodate (e.g., the number of seats) may be used as the upper limit. The number of people that the specified space can accommodate is stored in advance in a specified storage device. The determination unit 14 can identify the upper limit based on this information.

[0055] "The ratio of the total number of people entering a designated space to the upper limit" is the total number of people who have entered the designated space up to that point in time relative to the planned number of people entering the designated space (or the number of people who can be accommodated). This ratio indicates what percentage of the people who are scheduled to enter the designated space have already entered the designated space. Alternatively, this ratio indicates what percentage of the number of people who can be accommodated have entered the designated space. Hereinafter, this ratio may be referred to as the "occupancy rate."

[0056] In one example, the "approximate upper limit at that time" is determined based on the "occupancy rate (current situation)" and the "maximum total volume of luggage that can be brought into the specified space." For example, if the "occupancy rate (current situation)" is M%, then M% of the "maximum total volume of luggage that can be brought into the specified space" becomes the "approximate upper limit at that time."

[0057] Another example of the situation at that time is "the ratio of the time elapsed since people started entering the specified space to the length of time from when people started entering the specified space until when they finished." The "maximum guideline at that time" can be determined by replacing the above-mentioned "occupancy rate" with "the ratio of the time elapsed since people started entering the specified space to the length of time from when people started entering the specified space until when they finished."

[0058] In the case of the determination process 2, the above-mentioned "guideline for the upper limit at that time" becomes the threshold value.

[0059] The determination unit 14 identifies the "current situation" described above and, based on the identification result, identifies the "current upper limit guideline" as a threshold. Then, the determination unit 14 compares the total volume of luggage brought into the specified space with the threshold, and determines whether the total volume of luggage brought into the specified space exceeds the threshold. When images generated between the start and end of a person's entry into the specified space are processed in real time, the total volume of luggage brought into the specified space is updated in real time. The determination unit 14 can continue comparing the latest value of the total volume of luggage brought into the specified space with the "current upper limit guideline" from the start to the end of a person's entry into the specified space.

[0060] The output unit 16 can output the determination result of the determination unit 14. For example, the output unit 16 may perform a warning process when it is determined that the total volume of baggage brought into a specified space exceeds a threshold. Examples of the warning process include, but are not limited to, displaying warning information on a display device (such as a display or a projection device), outputting warning information via a speaker, turning on a warning lamp, etc. In the example of an aircraft, a display device, a speaker, a warning lamp, etc. may be installed at the boarding gate or inside the aircraft. Furthermore, the warning process may include transmitting warning information to a pre-registered external device. The pre-registered external device may be, for example, a mobile terminal, and specifically, may be a mobile terminal carried by a flight attendant, a worker managing boarding of the aircraft, etc.

[0061] The warning information indicates that the total volume of luggage brought into the specified space has exceeded a threshold. The fact that the total volume of luggage brought into the specified space has exceeded a threshold is indicated by text, a warning image, a warning sound, a lit or flashing lamp, etc.

[0062] The output unit 16 may also generate and output an information provision screen D as shown in Fig. 6. The output unit 16 may output the information provision screen D on a display device (such as a display or a projection device) installed at a predetermined position. In the example of an aircraft, the display device may be installed at the boarding gate, inside the aircraft, or the like. The output unit 16 may also transmit the information provision screen D to a pre-registered external device and cause it to output the information provision screen D. The pre-registered external device may be, for example, a mobile terminal, and specifically may be a mobile terminal carried by a cabin crew member, a worker managing boarding onto the aircraft, or the like.

[0063] 6 includes a graph shown in (A), an image shown in (B), and a table shown in (C). Note that the information screen D may not include any one or two of these.

[0064] The graph shown in (A) shows the ratio of the total volume of luggage brought into a specified space to the upper limit of the total volume of luggage that can be brought into the specified space. The graph shows this ratio at the current time. As the total volume of luggage brought into the specified space increases, the ratio also changes accordingly.

[0065] The image shown in (B) is an image generated by the camera described above. The image shown in (B) may be a live image. That is, the image generated by the camera may be displayed in real time.

[0066] The table shown in (C) shows the number of pieces of luggage brought into a specified space for each type of luggage. The table shows the current count value. As the number of pieces of luggage brought into a specified space increases, the count value changes accordingly. Note that the displayed number of each type of luggage can be modified by operating the UI (user interface) component in the "debug" column.

[0067] Next, an example of the flow of processing by the information processing device 10 will be described with reference to the flowchart of FIG.

[0068] In S10, the information processing device 10 acquires an image. The information processing device 10 acquires an image generated by a camera installed in a position where it can capture an image of luggage being brought into the specified space. The information processing device 10 can continue acquiring the image from the start of a person's entry into the specified space to the end of the entry.

[0069] In S11, the information processing device 10 identifies the type of luggage shown in the image based on the image acquired in S10. The information processing device 10 can continue this process from the start of entry of a person into the specified space to the end of entry.

[0070] In S12, the information processing device 10 identifies the volume of the luggage based on the type of luggage identified in S11. The information processing device 10 can continue this process from the start of entry of the person into the specified space to the end of entry.

[0071] In S13, the information processing device 10 determines whether the total volume of the luggage brought into the specified space exceeds a threshold value based on the luggage volume identified in S12. The information processing device 10 can continue this process from the start of entry of people into the specified space to the end of entry.

[0072] Although not shown, the information processing device 10 can output a determination result. For example, when the information processing device 10 determines that the total volume of luggage brought into a predetermined space exceeds a threshold, the information processing device 10 can perform a warning process.

[0073] <Effects> According to the information processing device 10 of the second embodiment, the same effects as those of the information processing device 10 of the first embodiment are achieved.

[0074] Furthermore, the information processing device 10 can output the determination result. For example, when the information processing device 10 determines that the total volume of luggage brought into the specified space exceeds a threshold, it can perform a warning process. Based on the warning process, the worker can recognize that the total volume of luggage brought into the specified space has exceeded the threshold. The worker can then perform appropriate work. For example, the worker can guide the worker not to bring any more luggage into the specified space, or move some of the luggage brought into the specified space to another location.

[0075] <<Third Embodiment>> An information processing device 10 according to a third embodiment can output characteristic information. Based on the information, a worker can understand the status of the luggage brought into a specified space. This will be described in detail below.

[0076] 7 is an example of a functional block diagram of the information processing device 10. As shown in the figure, the information processing device 10 includes an acquisition unit 11, a type identification unit 12, a capacity identification unit 13, a determination unit 14, a registration unit 15, and an output unit 16.

[0077] The registration unit 15 links at least one of the type of luggage identified by the type identification unit 12 and the capacity of the luggage identified by the capacity identification unit 13 with the time the luggage was brought into the specified space, and registers them in a specified storage device.

[0078] The registration unit 15 may register the time when the image used to identify the type of package was generated (photographing time) as the time when the package was brought into the specified space. Alternatively, if the count value is incremented for each type of package as described in the second embodiment, the registration unit 15 may register the time when the count is incremented as the time when the package was brought into the specified space. The registration unit 15 may also register other similar times as the time when the package was brought into the specified space.

[0079] The output unit 16 can generate and output an information provision screen D as shown in FIG. 8. The output unit 16 can generate the information provision screen D using the information registered by the registration unit 15.

[0080] The output unit 16 can output the information screen D on a display device (such as a display or a projection device) installed at a predetermined position. In the example of an aircraft, the display device may be installed at a boarding gate, inside the aircraft, or the like. The output unit 16 can also transmit the information screen D to a pre-registered external device and output it. The pre-registered external device may be, for example, a mobile terminal, and specifically may be a mobile terminal carried by a cabin crew member, a worker managing boarding on the aircraft, or the like.

[0081] 8 includes a table shown in (A) and a graph shown in (B). Note that the information provision screen D may include either one of them without the other.

[0082] The table shown in (A) shows the types of luggage brought into the designated space at each timing (each time). At 10:01:34, it shows that one carry-on bag and one bag were brought into the designated space.

[0083] The graph shown in (B) has a time axis and an axis representing the total volume of luggage brought into the specified space. The graph also shows the change in the total volume of luggage brought into the specified space over time and a threshold value. The threshold value indicates the "upper limit of the total volume of luggage that can be brought into the specified space" described in the second embodiment. In the example of FIG. 8 , the horizontal axis indicates the elapsed time since people began entering the specified space, but it may also indicate time. The graph shown in (B) further shows the number of pieces of luggage brought into the specified space by each type up to each timing.

[0084] As shown in Figure 8, the output unit 16 can output information indicating the type of luggage brought into the specified space at each timing and the total volume of luggage brought into the specified space up to each timing.

[0085] As a modified example, the output unit 16 may display the "current upper limit (threshold) determined based on the current situation" described in the second embodiment instead of or in addition to the "upper limit (threshold) of the total volume of luggage that can be brought into the specified space" in the graph shown in FIG. 8B. The "upper limit (threshold) of the total volume of luggage that can be brought into the specified space" is constant as shown in the figure. However, the "current upper limit (threshold) determined based on the current situation" has a different value at each timing.

[0086] As a modified example, the output unit 16 may display part or all of the information of the information provision screen D of Fig. 8 on the information provision screen D of Fig. 6. For example, the output unit 16 may display the table shown in (A) of the information provision screen D of Fig. 8 and / or the graph shown in (B) of the information provision screen D of Fig. 8 instead of the image shown in (B) of the information provision screen D of Fig. 6.

[0087] Other configurations of the information processing apparatus 10 of the third embodiment are similar to those of the information processing apparatus 10 of the first and second embodiments.

[0088] The information processing device 10 of the third embodiment achieves the same effects as the information processing device 10 of the first and second embodiments. Furthermore, the information processing device 10 can output an information screen D including characteristic information as shown in Fig. 8. Based on the information screen D, a worker can grasp the status of the luggage brought into the specified space.

[0089] For example, a worker can grasp the types of luggage brought into a specified space at a certain time and the total volume of luggage brought into the specified space up to that time.

[0090] In addition, the worker can determine whether the total volume of luggage that has been brought into the specified space up to this point in time exceeds the upper limit of the total volume of luggage that can be brought into the specified space.

[0091] In addition, the worker can determine whether the total volume of luggage brought into the specified space up to that point in time exceeds the upper limit guideline determined based on the situation at that time.

[0092] <<Fourth Embodiment>> The information processing device 10 of the fourth embodiment can output characteristic information different from that of the third embodiment. Based on the information, a worker can understand the status of the luggage brought into a specified space. This will be described in detail below.

[0093] 7 is an example of a functional block diagram of the information processing device 10. As shown in the figure, the information processing device 10 includes an acquisition unit 11, a type identification unit 12, a capacity identification unit 13, a determination unit 14, a registration unit 15, and an output unit 16.

[0094] The registration unit 15 associates at least one of the type of luggage identified by the type identification unit 12 and the volume of the luggage identified by the volume identification unit 13 with the total number of people who entered the specified space up to the time the luggage was brought into the specified space, and registers them in a specified storage device. The "total number of people who entered the specified space up to a certain time" can be identified by the method described in the second embodiment.

[0095] The output unit 16 can generate and output an information provision screen D as shown in FIG. 9. The output unit 16 can generate the information provision screen D using the information registered by the registration unit 15.

[0096] The output unit 16 can output the information screen D on a display device (such as a display or a projection device) installed at a predetermined position. In the example of an aircraft, the display device may be installed at a boarding gate, inside the aircraft, or the like. The output unit 16 can also transmit the information screen D to a pre-registered external device and output it. The pre-registered external device may be, for example, a mobile terminal, and specifically may be a mobile terminal carried by a cabin crew member, a worker managing boarding on the aircraft, or the like.

[0097] 9 includes a table shown in (A), a graph shown in (B), and a graph shown in (C). Note that the information provision screen D may not include any one or two of these.

[0098] The table shown in (A) shows the types of luggage brought into the designated space at each timing (each time). It shows that one carry-on bag and one bag were brought into the designated space at 10:01:34. The table also shows the identification information assigned to the people who entered the designated space at each timing. In this example, serial numbers (identification information) starting from 1 are assigned to the people who entered the designated space at each timing. Therefore, these serial numbers indicate the total number of people who entered the designated space up to a certain timing.

[0099] The graph shown in (B) has an axis representing the ratio of the total number of people to the upper limit (person occupancy rate) and an axis representing the total volume of luggage brought into the specified space. The graph also shows the change in the total volume of luggage brought into the specified space relative to the person occupancy rate and the threshold value. The person occupancy rate is as described in the second embodiment. The threshold value indicates the "current upper limit guideline (threshold value) determined based on the situation at that time" as described in the second embodiment. In the example of FIG. 9, the horizontal axis indicates the person occupancy rate as well as the total number of people entering the specified space. The graph shown in (B) further shows the number of pieces of luggage brought into the specified space by each timing for each type of luggage.

[0100] The graph shown in (C) shows the total number of people who entered a specified space by each time. The graph has time on one axis and the total number of people who entered the specified space on the other axis. The graph shows the change in the total number of people who entered the specified space over time.

[0101] As shown in Figure 9, the output unit 16 can output information indicating the type of luggage brought into the specified space at each timing and the total volume of luggage brought into the specified space up to the timing when the occupancy rate reaches a specified value.

[0102] As a modification, the output unit 16 may display the "upper limit (threshold) of the total volume of luggage that can be brought into the specified space" in the graph shown in FIG. 9B instead of or in addition to the "current upper limit (threshold) determined based on the current situation." As shown in the figure, the "current upper limit (threshold) determined based on the current situation" varies depending on the timing. However, the "upper limit (threshold) of the total volume of luggage that can be brought into the specified space" is constant.

[0103] As a modified example, the output unit 16 may display part or all of the information of the information provision screen D of Fig. 9 on the information provision screen D of Fig. 6. For example, instead of the image shown in (B) of the information provision screen D of Fig. 6, the output unit 16 may display at least one of the table shown in (A) of the information provision screen D of Fig. 9, the graph shown in (B) of the information provision screen D of Fig. 9, and the graph shown in (C) of the information provision screen D of Fig. 9.

[0104] Other configurations of the information processing apparatus 10 of the fourth embodiment are similar to those of the information processing apparatus 10 of the first to third embodiments.

[0105] According to the information processing device 10 of the fourth embodiment, the same effects as those of the information processing devices 10 of the first to third embodiments are achieved. Furthermore, the information processing device 10 can output an information provision screen D including characteristic information as shown in Fig. 9. Based on the information provision screen D, a worker can understand the status of the luggage brought into the specified space.

[0106] For example, workers can grasp the type of luggage brought into a specified space at a certain time and the total volume of luggage brought into the specified space by the time the occupancy rate reaches a specified value.

[0107] In addition, the worker can determine whether the total volume of luggage that has been brought into the specified space up to this point in time exceeds the upper limit of the total volume of luggage that can be brought into the specified space.

[0108] In addition, workers can determine whether the total volume of luggage brought into a specified space up to this point in time exceeds the upper limit guideline determined based on the occupancy rate at that time.

[0109] <<Fifth Embodiment>> An information processing device 10 according to a fifth embodiment divides luggage brought into a predetermined space into groups based on a predetermined rule, and calculates the total volume of luggage brought into the predetermined space for each group. This will be described in detail below.

[0110] First, the prerequisites will be explained. In the fifth embodiment, seats exist in a predetermined space. A seat is assigned in advance to each person entering the predetermined space. For example, the predetermined space is an airplane cabin. The seats are passenger seats provided in the cabin. Passengers reserve a seat in the cabin in advance. Only passengers who have reserved a seat can enter the cabin.

[0111] Typically, passengers store their luggage near their seats or in storage spaces corresponding to their seats. Therefore, the information processing device 10 groups the luggage brought into a designated space based on the seats of the passengers who brought each piece of luggage. The information processing device 10 then calculates the total volume of luggage brought into the designated space for each group. This information processing device 10 can accurately identify the luggage brought into each partial area within the designated space.

[0112] The functional configuration of the information processing device 10 will be described below. The determination unit 14 groups the luggage brought into the specified space based on the seats assigned to the people carrying the luggage shown in the image. The determination unit 14 then calculates the total volume of the luggage brought into the specified space for each group. The determination unit 14 then determines, for each group, whether the total volume of the luggage brought into the specified space exceeds a threshold.

[0113] First, we will explain the "process of identifying a seat assigned to a person carrying luggage shown in an image." As described above, seats exist in a predetermined space, and a person entering the predetermined space reserves one seat in advance. Reservation information is stored in a predetermined storage device. The reservation information records, for each seat, the identification information of the person reserving each seat (the person assigned each seat). Information that identifies a person includes, but is not limited to, name, address, customer identification information, etc.

[0114] The determination unit 14 uses the reservation information to identify the seat assigned to the person carrying the baggage shown in the image.

[0115] First, the determination unit 14 identifies the person carrying the luggage shown in the image. This identification can be achieved using any technology. For example, appearance information (e.g., facial images, facial features, etc.) of each person who has reserved a seat may be stored in advance in a predetermined storage device. The determination unit 14 may then identify the person carrying the luggage shown in the image through image analysis (e.g., facial recognition) using the appearance information. Alternatively, if a person is permitted to pass through a gate connected to a predetermined space by inputting their own identification information into a gate system (e.g., an aircraft boarding gate), the person carrying the luggage shown in the image may be identified by synchronizing the input with the timing of capturing the image. For example, the determination unit 14 can determine that the person carrying the luggage shown in an image capturing the location of the gate system is the person identified by the identification information entered into the gate system at the time the image was captured. In one example, a boarding pass scanner (two-dimensional code reader) installed at the boarding gate can read the boarding pass and obtain the seat information registered and linked to the passenger. Meanwhile, seat information can be linked to baggage information by capturing a photograph of the person's baggage with a camera.

[0116] After identifying the person carrying the luggage in the image, the determination unit 14 identifies the seat of that person based on the reservation information.

[0117] Next, a description will be given of the "process of grouping baggage brought into a predetermined space based on the seats assigned to the people carrying the baggage shown in the image."

[0118] The determination unit 14 classifies luggage shown in the image into a predetermined group based on the seat assigned to the person carrying the luggage. Information indicating the group to which each of multiple seats in a predetermined space belongs is stored in advance in a predetermined storage device. The determination unit 14 realizes the grouping of luggage based on the seats based on the information. Specifically, the determination unit 14 classifies luggage shown in the image into a group to which the seat assigned to the person carrying the luggage belongs.

[0119] In one example, seats are classified by aisle within a specified space, by zone within a specified space, or by storage space within a specified space. That is, each seat may be defined to belong to one of a plurality of aisles. Also, each seat may be defined to belong to one of a plurality of zones. Also, each seat may be defined to belong to one of a plurality of storage spaces. For example, in the case of an airplane, the aisle used by the passenger of each seat is defined for each seat. Also, the available storage space is defined for each seat. Also, the zone in which each seat is installed is defined. The zones are divided, for example, into the front of the aircraft, the middle of the aircraft, the rear of the aircraft, etc. However, the method of defining the zones is not limited to this.

[0120] Based on information indicating the group to which such seats belong, the determination unit 14 groups the luggage brought into the specified space by aisle within the specified space, by zone within the specified space, or by storage space within the specified space.

[0121] Next, the "process of calculating the total volume of luggage brought into a predetermined space for each group" will be described.

[0122] After grouping the luggage brought into the specified space as described above, the determination unit 14 calculates the total volume of luggage brought into the specified space for each group. The determination unit 14 can perform this calculation in accordance with the method described in the second embodiment. For example, the determination unit 14 counts the number of different types of luggage brought into the specified space for each group. Then, based on the counting results, the determination unit 14 calculates the total volume of luggage brought into the specified space for each group.

[0123] Next, the "process of determining whether the total volume of luggage brought into a predetermined space for each group exceeds a threshold" will be described.

[0124] After calculating the total volume of luggage brought into the specified space for each group as described above, the determination unit 14 determines whether the calculated total volume exceeds a threshold for each group. The determination unit 14 can achieve this determination in accordance with the method described in the second embodiment. For example, the determination unit 14 allocates the threshold described in the second embodiment to each group at a predetermined allocation ratio. Then, the determination unit 14 makes the above determination by comparing the total volume of luggage brought into the specified space calculated for each group with the threshold allocated to each group.

[0125] The output unit 16 outputs the determination result of the determination unit 14. If there is a group whose total volume of luggage brought into the specified space exceeds a threshold, the output unit 16 can output information indicating the group. For example, the information provision screen D described above may include this information.

[0126] Other configurations of the information processing apparatus 10 of the fifth embodiment are similar to those of the information processing apparatus 10 of the first to fourth embodiments.

[0127] The information processing device 10 of the fifth embodiment achieves the same effects as the information processing devices 10 of the first to fourth embodiments. Furthermore, the information processing device 10 can group luggage brought into a predetermined space based on a predetermined rule and calculate the total volume of luggage brought into the predetermined space for each group. For example, the information processing device 10 can group luggage by aisle within the predetermined space, by zone within the predetermined space, or by luggage storage space within the predetermined space. The information processing device 10 can then calculate the total volume of luggage brought into the predetermined space for each such group.

[0128] With this information processing device 10, the worker can grasp the total volume of the luggage brought in not only for the entire predetermined space but also for each partial area within the predetermined space, and can determine whether the total volume of the luggage brought in for each partial area within the predetermined space exceeds a threshold.

[0129] <<Sixth Embodiment>> An information processing device 10 according to a sixth embodiment predicts the future value of the total volume of luggage brought into a specified space based on the total volume of luggage brought into the specified space up to the present time. This will be described in detail below.

[0130] The determination unit 14 predicts the future value of the total volume of luggage brought into the specified space based on the total volume of luggage brought into the specified space up to the present time.

[0131] The determination unit 14 can predict the future value of the total volume of luggage brought into a specified space based on the total volume of luggage brought into the specified space up to the present time and at least one of the following judgment criteria:

[0132] ・Weather information for the day ・Seasonal and event information for the day ・Attribute information for people who have not yet entered the designated space (statistical values ​​of people's attributes) ・Information on luggage of people who have not yet entered the designated space, identified by analyzing images of the waiting room (total luggage volume)

[0133] In addition, if the specified space is a space for passengers of a moving body (e.g., an airplane cabin), the judgment unit 14 can make the above prediction based on the total volume of luggage brought into the specified space up to the present time and at least one of the judgment criteria described above and the following judgment criteria.

[0134] ・Destination of the moving object ・Travel time of the moving object ・Departure time of the moving object ・Arrival time of the moving object

[0135] The determination unit 14 may obtain the weather information for the day from, for example, an external server that provides "weather information for the day," or may obtain the weather information for the day by other means. The weather information for the day includes the weather, temperature, humidity, etc. The type and amount of luggage that a person brings into a specified space may change depending on the weather for the day.

[0136] Furthermore, the determination unit 14 can identify "season and event information for the current day" based on the calendar information and information indicating the season and event for each day. The calendar information and information indicating the season and event for each day may be stored in advance in a predetermined storage device. The event information may be information regarding long holidays such as the New Year holidays, Golden Week, summer vacation period, etc., or other information. The type and amount of luggage that a person brings into a specified space may change depending on the season and event for the day.

[0137] Furthermore, the determination unit 14 can acquire "attribute information of people who have not yet entered the predetermined space" based on the reservation information indicating the reservation status of seats in the predetermined space and information on people who have entered the predetermined space up to now. As described in the second embodiment, people who have entered the predetermined space up to now can be identified using information entered into a gate system (such as an aircraft boarding gate) or facial recognition based on images generated by a camera. The determination unit 14 can then identify the remaining people, excluding those who have entered the predetermined space up to now, as people who have not yet entered the predetermined space from among those who are scheduled to enter the predetermined space indicated by the reservation information. The determination unit 14 then determines attribute information of the identified people based on the reservation information. The attribute information indicates gender, age, whether the person is single, whether they are traveling with a family, etc. The type and amount of luggage that a person brings into the predetermined space may vary depending on the person's attributes.

[0138] The determination unit 14 may calculate statistical values ​​of the attributes of people who have not yet entered the specified space. Then, the determination unit 14 may predict the future value of the total volume of luggage brought into the specified space based on the statistical values. For example, the determination unit 14 may calculate the number of people with a specified attribute (e.g., the number of women, the number of women in their 20s to 40s, the number of families).

[0139] Furthermore, the determination unit 14 can acquire "information on luggage of people who are not within the specified space" identified by analyzing waiting room images taken of the waiting room. In this example, a waiting room camera is installed to take pictures of the waiting room. The acquisition unit 11 acquires the waiting room image generated by the waiting room camera. The type identification unit 12 identifies the type of luggage shown in the waiting room image based on the waiting room image. The capacity identification unit 13 identifies the volume of the luggage based on the type of luggage identified by the type identification unit 12. The determination unit 14 calculates the total volume of the luggage shown in the waiting room camera based on the type of luggage identified by the type identification unit 12 and the volume of the luggage identified by the capacity identification unit 13.

[0140] The determination unit 14 can also acquire information indicating the destination of the mobile body, the travel time of the mobile body, the departure time of the mobile body, and the arrival time of the mobile body, which is stored in advance in a predetermined storage device. The type and amount of luggage that a person brings into a predetermined space can change depending on the destination of the mobile body, the travel time of the mobile body, the departure time of the mobile body, the arrival time of the mobile body, etc.

[0141] There are various methods for predicting the future value of the total volume of luggage brought into a specified space based on the total volume of luggage brought into the specified space up to the present time and the above-mentioned judgment criteria. In one example, the determination unit 14 can achieve this prediction using an estimation model generated in advance by machine learning. The estimation model receives the total volume of luggage brought into the specified space up to the present time and the above-mentioned judgment criteria as input, and outputs the future value of the total volume of luggage brought into the specified space.

[0142] The "future value of the total volume of luggage brought into a specified space" is, for example, the value at the time when people have finished entering the specified space. This value can be said to be the value at the time when the above-mentioned occupancy rate reaches 100%. This value can also be said to be the value at the time when people have finished entering the specified space.

[0143] The determination unit 14 can continue to calculate the future value of the total volume of luggage brought into the specified space from the start of a person's entry into the specified space to the end of the entry.

[0144] The determination unit 14 may further calculate the difference between the "future value of the total volume of luggage brought into the specified space" and the "upper limit of the total volume of luggage that can be brought into the specified space" described in the second embodiment. Furthermore, when the "future value of the total volume of luggage brought into the specified space" exceeds the above-mentioned "upper limit of the total volume of luggage that can be brought into the specified space," the determination unit 14 may convert the difference into the number of each type of luggage. The determination unit 14 can calculate, using a predetermined calculation algorithm, how many pieces of each type of luggage the difference corresponds to.

[0145] The determination unit 14 can continue to calculate the difference and convert it into the number of various types of luggage from the time when the person starts entering the specified space until the time when the person finishes entering the specified space.

[0146] The output unit 16 can output the "future value of the total volume of luggage brought into the specified space" calculated by the determination unit 14. The output unit 16 can also output the difference between the "future value of the total volume of luggage brought into the specified space" calculated by the determination unit 14 and the "upper limit of the total volume of luggage that can be brought into the specified space." The output unit 16 can also output the result of converting the difference calculated by the determination unit 14 into the number of each type of luggage. The output unit 16 can output this information using the same output method as in the first to fifth embodiments.

[0147] Other configurations of the information processing apparatus 10 of the sixth embodiment are similar to those of the information processing apparatuses 10 of the first to fifth embodiments.

[0148] The information processing device 10 of the sixth embodiment achieves the same effects as the information processing devices 10 of the first to fifth embodiments. Furthermore, the information processing device 10 can predict the future value of the total volume of luggage brought into a specified space. Based on this predicted value, a worker can grasp the future state of the total volume of luggage brought into a specified space.

[0149] Furthermore, the information processing device 10 can predict the future value of the total volume of luggage brought into a specified space based on the total volume of luggage brought into the specified space up to the present time and the characteristic determination materials described above. With this information processing device 10, it is possible to accurately predict the future value of the total volume of luggage brought into a specified space.

[0150] Generally, a situation in which the total volume of luggage brought into a designated space exceeds the upper limit of the total volume of luggage that can be brought into the designated space can occur around the time when people finish entering the designated space after a certain amount of time has passed since they started entering the designated space. If a situation in which the total volume of luggage brought into the designated space exceeds the upper limit of the total volume of luggage that can be brought into the designated space at such a relatively late time is detected, various inconveniences can occur.

[0151] For example, if the total volume of baggage brought into the designated space exceeds the upper limit of the total volume of baggage that can be brought into the designated space, workers must perform work to move some of the baggage brought into the designated space to another location. If this work is started relatively late as described above, inconveniences such as delays in the departure of the aircraft may occur.

[0152] By predicting the future total volume of luggage brought into a specified space using the information processing device 10, the worker can know in advance that the total volume of luggage brought into the specified space will exceed the upper limit of the total volume of luggage that can be brought into the specified space. As a result, the worker can start the above-mentioned work at a relatively early timing.

[0153] Furthermore, the information processing device 10 can convert the difference between the "future value of the total volume of luggage brought into the specified space" and the "upper limit of the total volume of luggage that can be brought into the specified space" into the number of each type of luggage and output the result. Based on this information, workers can determine how many of each type of luggage need to be moved to another location.

[0154] <<Seventh Embodiment>> An information processing device 10 according to a seventh embodiment has a configuration for reducing a sense of unfairness between a person who has brought a lot of luggage into a predetermined space and a person who has not brought any luggage into the predetermined space. This will be described in detail below.

[0155] The determination unit 14 identifies a person whose luggage volume brought into a specified space exceeds the upper limit per person based on the type of luggage identified by the type identification unit 12 and the volume of the luggage identified by the volume identification unit 13. Then, the registration unit 15 registers the identified person in a first list. The registration unit 15 can register the identification information of the identified person, the seat of the identified person, the reservation information of the identified person, an image of the identified person, etc. in the first list.

[0156] A single person may bring multiple pieces of luggage into a predetermined space. As a result, the volume of the luggage brought into the predetermined space may exceed the upper limit per person. The determination unit 14 calculates the total volume of at least one piece of luggage brought into the predetermined space by each person based on the type of luggage identified by the type identification unit 12 and the volume of the luggage identified by the volume identification unit 13. The determination unit 14 then compares the calculated total with the upper limit per person to detect a person whose volume of luggage brought into the predetermined space exceeds the upper limit per person. The upper limit per person is stored in advance in a predetermined storage device.

[0157] The information processing device 10 can execute various processes using the first list.

[0158] In one example, the output unit 16 can output the first list. The output unit 16 can output the first list using the same output method as in the first to fifth embodiments. Based on the first list, the worker identifies people whose luggage volume into a specified space exceeds the upper limit per person.

[0159] For example, if the total volume of luggage brought into the designated space exceeds the upper limit of the total volume of luggage that can be brought into the designated space, the worker needs to move some of the luggage brought into the designated space to another location. In this case, the worker can identify people whose luggage volume brought into the designated space exceeds the upper limit per person based on the first list, and move that person's luggage to another location.

[0160] In another example, the information processing device 10 can impose a penalty on a person whose luggage volume brought into a predetermined space exceeds the upper limit per person. Note that the information processing device 10 may impose a penalty on a person whose luggage volume brought into a predetermined space exceeds the upper limit per person when a predetermined condition is met. The predetermined condition is that "the total volume of luggage brought into the predetermined space exceeds the upper limit of the total volume of luggage that can be brought into the predetermined space." In other words, the information processing device 10 does not need to impose a penalty if the total volume of luggage brought into the predetermined space does not exceed the upper limit of the total volume of luggage that can be brought into the predetermined space.

[0161] The penalty may be, for example, the payment of an additional fee. For example, payment method information (credit card information, point information, electronic money information, etc.) associated with each person may be stored in advance in a predetermined storage device. In this case, the information processing device 10 executes the payment process for the additional fee using the payment method information of the person registered in the first list.

[0162] When the information processing device 10 detects that a person has brought more luggage into the designated space than the upper limit per person, the worker may call out to that person. The worker may then explain the penalty to the person and, upon consent, have the person bring more luggage than the upper limit into the designated space. If the person does not consent to the penalty, the worker may move some of the person's luggage to another location at that time.

[0163] However, there may be a case where a person (hereinafter referred to as the "first person") has luggage moved to another location even though the volume of the luggage brought into the designated space does not exceed the upper limit per person. For example, if a person enters the designated space late, the total volume of the luggage brought into the designated space may already exceed the upper limit of the total volume of luggage that can be brought into the designated space by the time the person enters the designated space. Therefore, a person who enters the designated space late may have their luggage moved to another location even though the volume of the luggage brought into the designated space does not exceed the upper limit per person. Furthermore, there may be a person who, in response to a request from a worker, agrees to have their luggage moved to another location even though the volume of the luggage brought into the designated space does not exceed the upper limit per person.

[0164] The worker can input the identification information of the first person into the information processing device 10 and register it in a predetermined storage device. The input of the identification information is realized via any widely known input device. The registration unit 15 can register the first person in the second list in response to the input. The registration unit 15 can register the identification information of the first person, the seat of the first person, the first reservation information, an image of the first person, etc. in the second list.

[0165] The information processing device 10 can execute various processes using the second list.

[0166] In one example, the output unit 16 can output the second list. The output unit 16 can output the second list using a method similar to the output method described in the above embodiment. The worker identifies the first person based on the second list.

[0167] The worker may provide a gift, a coupon, or the like to the first person at any timing, such as when the first person is in the predetermined space, when the first person leaves the predetermined space, etc. The worker may also express gratitude for the first person's cooperation in storing the luggage at any timing, such as when the first person is in the predetermined space, when the first person leaves the predetermined space, etc.

[0168] In another example, the information processing device 10 may perform a process of adding points or electronic money to point information, electronic money information, or the like linked to the identification information of the first person. The information processing device 10 can execute this process in cooperation with an external server that manages points and electronic money.

[0169] Other configurations of the information processing apparatus 10 of the seventh embodiment are similar to the configurations of the information processing apparatuses 10 of the first to sixth embodiments.

[0170] The information processing device 10 of the seventh embodiment achieves the same effects as the information processing devices 10 of the first to sixth embodiments. The information processing device 10 also includes a configuration for reducing the sense of unfairness felt between a person who brings a lot of luggage into a designated space and a person who does not bring any luggage into the designated space. This information processing device 10 can reduce the sense of unfairness and increase customer satisfaction.

[0171] <<Modifications>> Modifications applicable to the first to seventh embodiments will be described below. In any of the modifications, the same effects as those of the first to seventh embodiments are achieved.

[0172] <Modification 1> In the above embodiment, an example was shown in which the standard value of the volume of each type of luggage is defined by a single value such as X. In Modification 1, the standard value of the volume of each type of luggage is defined by a single value such as X. １ ~X ２ It is defined as a certain numerical range.

[0173] In this case, the capacity specifying unit 13 calculates the capacity of the luggage based on the type of luggage specified by the type specifying unit 12. １ ~X ２ It is specified within a certain numerical range, such as:

[0174] Then, the determination unit 14 calculates the total volume of the luggage brought into the specified space based on the luggage volume specified within a certain numerical range. In this case, the total volume of the luggage brought into the specified space is calculated as Y １ ~Y ２ It is expressed as a certain numerical range, as shown below.

[0175] Y １ is a value obtained by adding up the lower limits of the capacities of various types of luggage identified by the capacity identification unit 13. ２ is a value obtained by adding up the upper limits of the capacities of various types of luggage identified by the capacity identification unit 13.

[0176] The output unit 16 can output the "total volume of luggage brought into a specified space" indicated in a certain numerical range. The output unit 16 can output the information in the same manner as the output method described in the above embodiment.

[0177] The information processing device 10 identifies the volume of each piece of luggage based on the type of luggage. This method can identify the total volume of luggage brought into a specified space with a certain degree of accuracy. However, even luggage of the same type may have slightly different volumes. Furthermore, the volume of luggage may vary depending on how packed the luggage is.

[0178] According to the first modification, the total volume of the cargo brought into the specified space can be determined within a certain range of values ​​based on the range of values ​​that the various cargoes can take. Based on this information, the worker can grasp in more detail all the possibilities for the total volume of the cargo brought into the specified space.

[0179] <Modification 2> The determination unit 14 can determine whether the total volume of baggage brought into a predetermined space exceeds a threshold value based on the following formula (1).

[0180]

[0181] α １ is the capacity of the first type of luggage (standard value of capacity). １ is the number of first type of baggage brought into the specified space up to the present time.

[0182] α ２ is the capacity of the second type of luggage (standard value of capacity). ２ is the number of second type of baggage that has been brought into the specified space up to the present time.

[0183] α ３ is the capacity of the third type of luggage (standard value of capacity). ３ is the number of pieces of the third type of baggage that have been brought into the specified space up to the present time.

[0184] Although equation (1) shows three terms corresponding to the first to third types of luggage, the number of terms corresponding to each type of luggage may be one, two, four or more.

[0185] β and γ are terms related to other fluctuation factors, which may include at least one of the following:

[0186] ・Weather information for the day ・Seasonal and event information for the day ・Attribute information for people who have not yet entered the designated space (statistical values ​​of people's attributes) ・Information on luggage of people who have not yet entered the designated space, identified by analyzing images of the waiting room (total luggage volume)

[0187] In addition, when the specified space is a space for passengers of a moving body (for example, a cabin of an aircraft), in addition to or instead of the above-mentioned fluctuation factors, at least one of the following factors may also be cited as a fluctuation factor.

[0188] ・Destination of the moving object ・Travel time of the moving object ・Departure time of the moving object ・Arrival time of the moving object

[0189] These fluctuation factors have been explained in the sixth embodiment, so the explanation will be omitted here.

[0190] The operator of the information processing device 10 may use data analysis such as regression analysis to identify which of the candidate variation factors has a high correlation with the total volume of luggage brought into a specified space.The operator may then determine the identified item as the other variation factor.While Equation (1) includes two terms corresponding to the two variation factors β and γ, it may also include one term corresponding to one variation factor, or three or more terms corresponding to three or more variation factors.

[0191] The determination unit 14 can calculate values ​​such as β and γ from the details of the fluctuation factors described above based on a predetermined calculation model. The calculation model may be an arithmetic expression, a correspondence table showing the correspondence between the details of the fluctuation factors and the values ​​such as β and γ, or other similar factors.

[0192] C ａｐ is the upper limit of the total volume of luggage that can be brought into a given space.

[0193] P ｃ is the total number of people who have entered the specified space up to now.

[0194] P ｍ is the expected number of people entering a given space. ｍ may be the number of people that a given space can accommodate.

[0195] P ｃ / P ｍ is the occupancy rate described in the second embodiment.

[0196] Th is a threshold correction coefficient, which takes a value greater than 0 and less than 1.

[0197] The left side of equation (1) indicates the total volume of luggage brought into the specified space up to the present time. The right side of equation (1) indicates the "threshold value according to the current situation (the upper limit guideline for that time)" explained in the second embodiment. By comparing the value of the left side and the value of the right side, equation (1) determines whether the total volume of luggage brought into the specified space exceeds the threshold value.

[0198] As in the second modification, by calculating the total volume of luggage brought into a specified space up to the present time while taking into account other variable factors, the calculation accuracy is improved.

[0199] <Modification 3> As described in the above embodiment, there are cases where a part of a package brought into a predetermined space is moved to another location. In this modification, a camera is installed in a position where it can capture an image of the package being moved to the other location. For example, the camera may be installed in a position where it can capture an image of a person bringing a package to the other location.

[0200] Then, the information processing device 10 calculates the total volume of the luggage moved to other locations by a process similar to the "process for calculating the total volume of luggage brought into a specified space" described in the above embodiment. For example, as described in the above embodiment, the information processing device 10 can count the number of luggage moved to other locations for each type of luggage, and calculate the total volume of the luggage moved to other locations based on the count value and the volume (standard value) of each type of luggage.

[0201] Then, when some of the luggage brought into the specified space is moved to another location, the information processing device 10 subtracts the "total volume of luggage moved to another location" from the "total volume of luggage brought into the specified space." Through this process, the information processing device 10 can calculate the "total volume of luggage brought into the specified space" after some of the luggage brought into the specified space has been moved to another location.

[0202] <Modification 4> As described in the second embodiment, the types of luggage may be subdivided according to size, such as large suitcases and small suitcases. In this case, the information processing device 10 needs to estimate the size of the luggage (large, medium, small, etc.) through image analysis. The information processing device 10 of Modification 4 estimates the size of the luggage using the method described below.

[0203] As a premise, the floor at the position where the camera C photographs the package has a pattern of regularly-spaced squares, as shown in Fig. 10. The type identification unit 12 uses this pattern to identify the size of the package.

[0204] First, the type identification unit 12 analyzes the image and counts the number of squares in the image that correspond to the length of one side of the package. The product of this square count value and the actual length of one side of the square indicates an estimate of the length of one side of the package. This product may be used as is as the length of one side of the package, but the count value may change depending on the height of the package (distance from the floor) at the time of photographing. Therefore, the type identification unit 12 corrects the product of the above-mentioned square count value and the actual length of one side of the square based on the height of the package at the time of photographing. The type identification unit 12 then uses the corrected value as the length (size) of one side of the package.

[0205] Specifically, the type identification unit 12 can calculate the length (size) of one side of the package based on the following formula (2).

[0206]

[0207] The "number of squares" is the number of squares equal to the length of one side of the package in the image described above.

[0208] H ｃ is the height of the camera C (distance from the floor). The height of the camera C is stored in advance in a predetermined storage device. The type identification unit 12 refers to the above information stored in advance in the predetermined storage device and determines H ｃ Identify.

[0209] H ｏ is the height of the luggage (distance from the floor). A standard value of the height of luggage when carried by a person in a normal manner is stored in advance in a predetermined storage device for each type of luggage (suitcase, handbag, backpack, etc.). After identifying the type of luggage (suitcase, handbag, backpack, etc.) by image analysis, the type identification unit 12 refers to the information stored in advance in the predetermined storage device and calculates the height of the identified type of luggage (H ｏ Identify.

[0210] F ｐ is the actual length of one side of the square. ｐ The type identification unit 12 refers to the information stored in advance in a predetermined storage device and determines F ｐ Identify.

[0211] After calculating the length of one side of the package as described above, the type identification unit 12 identifies the size of the package based on the calculation result. A standard range of the length of one side of each size of package is stored in advance in a predetermined storage device. The type identification unit 12 refers to this information and identifies a size that includes the calculated length of one side within the standard range.

[0212] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0213] In addition, in the flowcharts used in the above explanation, multiple steps (processes) are described in order. However, the order of the steps performed in each embodiment is not limited to the order described. In each embodiment, the order of the steps shown in the drawings can be changed as long as it does not cause any problems in terms of the content.

[0214] Some or all of the above embodiments may be described as, but are not limited to, the following notes. 1. An information processing device having: an acquisition means for acquiring an image; a type identification means for identifying the type of luggage shown in the image based on the image; a capacity identification means for identifying the volume of the luggage based on the identified type of luggage; and a determination means for determining whether the total volume of the luggage brought into a specified space exceeds a threshold based on the identified volume of the luggage. 2. The information processing device described in 1, having: a registration means for linking and registering at least one of the identified type and volume of the luggage with the time the luggage was brought into the specified space; and an output means for outputting information indicating the type of luggage brought into the specified space at each timing and the total volume of the luggage brought into the specified space up to each timing. 3. The information processing device described in 2, wherein the output means outputs information indicating the threshold, which has a different value for each timing. 4. 5. The information processing device of any one of 1 to 4, wherein the output means has a time axis and an axis of the total volume of the luggage brought into the specified space, and outputs a graph showing the change over time in the total volume of the luggage brought into the specified space and the threshold. 5. The information processing device of any one of 1 to 4, comprising: registration means for linking and registering at least one of the type and volume of the identified luggage with the total number of people who had entered the specified space up to the time when the luggage was brought into the specified space; and output means for outputting information showing the type of luggage brought into the specified space at each time and the total volume of the luggage brought into the specified space up to the time when the ratio of the total number of people to an upper limit value reaches a predetermined value. 6. The information processing device of 5, wherein the output means outputs information showing the threshold, which has a different value for each ratio. 7. The information processing device of 6, wherein the output means has an axis of the ratio and an axis of the total volume of the luggage brought into the specified space, and outputs a graph showing the change in the total volume of the luggage brought into the specified space against the ratio, and the threshold.8. An information processing device according to any one of 1 to 7, wherein seats exist within the specified space, and the determination means groups the luggage brought into the specified space based on seats assigned to people carrying the luggage shown in the image, and calculates the total volume of the luggage for each group. 9. An information processing device according to 8, wherein the determination means groups the luggage by aisle within the specified space, by zone within the specified space, or by luggage storage space within the specified space. 10. An information processing device according to any one of 1 to 9, wherein the determination means predicts a future value of the total volume of the luggage brought into the specified space based on the total volume of the luggage brought into the specified space up to the present time. 11. 12. The information processing device according to 10, wherein the predetermined space is a space for passengers of a mobile body, and the determination means predicts a future value of the total volume of luggage brought into the predetermined space based on at least one of the destination of the mobile body, the travel time of the mobile body, the departure time of the mobile body, the arrival time of the mobile body, weather information for the day, seasonal and event information for the day, attribute information of people who have not yet entered the predetermined space, and information on luggage of people who have not entered the predetermined space identified by analyzing a waiting room image taken of the waiting room. 12. The information processing device according to 10, wherein the determination means converts the difference into the number of each type of luggage when the future value of the total volume of luggage brought into the predetermined space exceeds an upper limit of the total volume of luggage that can be brought into the predetermined space. 13. The information processing device according to any one of 1 to 12, further comprising registration means for registering in a list people whose volume of luggage brought into the predetermined space exceeds the upper limit per person. 14. An information processing method in which one or more computers acquire an image, identify the type of luggage shown in the image based on the image, identify the volume of the luggage based on the identified type of luggage, and determine whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of the luggage.15. A program causing a computer to function as: an acquisition means for acquiring an image; a type identification means for identifying the type of luggage shown in the image based on the image; a capacity identification means for identifying the volume of the luggage based on the identified type of luggage; and a determination means for determining whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of the luggage.

[0215] Some or all of Supplements 2 to 13 that are dependent on the information processing device of Supplement 1 described above may also be dependent on the information processing method of Supplement 14 and the program of Supplement 15 in the same dependent relationship as Supplement 1 and Supplements 2 to 13. Furthermore, within the scope of each of the above-mentioned embodiments, some or all of the configurations described as Supplements can be realized in various hardware, software, various recording means for recording software, or systems.

[0216] This application claims priority based on Japanese Patent Application No. 2024-084595, filed May 24, 2024, the disclosure of which is incorporated herein by reference in its entirety.

[0217] REFERENCE SIGNS LIST 10 Information processing device 11 Acquisition unit 12 Type identification unit 13 Capacity identification unit 14 Determination unit 15 Registration unit 16 Output unit 1A Processor 2A Memory 3A Input / output I / F 4A Peripheral circuit 5A Bus

Claims

1. An information processing device having: an acquisition means for acquiring an image; a type identification means for identifying the type of luggage shown in the image based on the image; a capacity identification means for identifying the volume of the luggage based on the identified type of luggage; and a determination means for determining whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of the luggage.

2. An information processing device as described in claim 1, comprising: a registration means for linking and registering at least one of the type and volume of the identified luggage with the total number of people who have entered the specified space up to the time when the luggage is brought into the specified space; and an output means for outputting information indicating the type of luggage brought into the specified space at each time and the total volume of the luggage brought into the specified space up to the time when the ratio of the total number of people to an upper limit value reaches a specified value.

3. The information processing device according to claim 2, wherein the output means outputs information indicating the threshold value, which has a different value for each of the ratios.

4. An information processing device as described in claim 3, wherein the output means has an axis of the ratio and an axis of the total volume of the luggage brought into the specified space, and outputs a graph showing the change in the total volume of the luggage brought into the specified space against the ratio and the threshold value.

5. An information processing device as described in any one of claims 1 to 4, wherein seats exist within the specified space, and the determination means groups the luggage brought into the specified space based on the seats assigned to the people carrying the luggage shown in the image, and calculates the total volume of the luggage for each group.

6. The information processing device according to claim 5, wherein the determining means groups the luggage by aisle within the specified space, by zone within the specified space, or by luggage storage space within the specified space.

7. An information processing device described in any one of claims 1 to 6, wherein the determination means predicts the future value of the total volume of the luggage brought into the specified space based on the total volume of the luggage brought into the specified space up to the present time.

8. The information processing device of claim 7, wherein the specified space is a space for passengers of a mobile body, and the determination means predicts the future value of the total volume of luggage brought into the specified space based on at least one of the destination of the mobile body, the travel time of the mobile body, the departure time of the mobile body, the arrival time of the mobile body, the weather information for the day, the season and event information for the day, attribute information of people who have not yet entered the specified space, and information on the luggage of people who have not yet entered the specified space identified by analyzing a waiting room image taken of the waiting room.

9. The information processing device according to claim 2, wherein said output means outputs information indicating said threshold value, the value of which varies for each timing.

10. An information processing device as described in claim 9, wherein the output means has a time axis and an axis of the total volume of the luggage brought into the specified space, and outputs a graph showing the change over time in the total volume of the luggage brought into the specified space and the threshold value.

11. An information processing device as described in any one of claims 1 to 10, comprising: a registration means for linking and registering at least one of the type and volume of the identified luggage with the total number of people who have entered the specified space up to the time when the luggage is brought into the specified space; and an output means for outputting information indicating the type of luggage brought into the specified space at each time and the total volume of the luggage brought into the specified space up to the time when the ratio of the total number of people to an upper limit value reaches a specified value.

12. An information processing device as described in claim 7 or 8, wherein the determination means converts the difference into the number of each type of luggage if the future value of the total volume of the luggage brought into the specified space exceeds the upper limit of the total volume of luggage that can be brought into the specified space.

13. An information processing device according to any one of claims 1 to 12, further comprising means for registering in a list a person whose luggage volume brought into the predetermined space exceeds the upper limit per person.

14. An information processing method in which one or more computers acquire an image, identify the type of luggage shown in the image based on the image, identify the volume of the luggage based on the identified type of luggage, and determine whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of the luggage.

15. An information processing method as described in claim 14, wherein the one or more computers link and register at least one of the type and volume of the identified luggage with the total number of people who have entered the specified space up to the time the luggage is brought into the specified space, and output information indicating the type of luggage brought into the specified space at each time and the total volume of the luggage brought into the specified space up to the time when the ratio of the total number of people to an upper limit value reaches a specified value.

16. The information processing method according to claim 15, wherein the one or more computers output information indicating the threshold value, which has a different value for each of the ratios.

17. An information processing method as described in claim 16, wherein the one or more computers output a graph having an axis of the ratio and an axis of the total volume of the luggage brought into the specified space, and showing the change in the total volume of the luggage brought into the specified space against the ratio and the threshold value.

18. A recording medium having recorded thereon a program that causes a computer to function as: an acquisition means for acquiring an image; a type identification means for identifying the type of luggage shown in the image based on the image; a capacity identification means for identifying the volume of the luggage based on the identified type of luggage; and a determination means for determining whether the total volume of the luggage brought into a specified space exceeds a threshold value based on the identified volume of the luggage.

19. A recording medium as described in claim 18, which records the program that causes the computer to function as: a registration means that links and registers at least one of the type and volume of the identified luggage with the total number of people who have entered the specified space up to the time when the luggage is brought into the specified space; and an output means that outputs information indicating the type of luggage brought into the specified space at each time and the total volume of the luggage brought into the specified space up to the time when the ratio of the total number of people to the upper limit value reaches a specified value.

20. A recording medium according to claim 19, wherein said output means outputs information indicating said threshold value, which has a different value for each of said ratios.

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