System and Management Device

Abstract

To appropriately reproduce a target odor or taste or manage odor or taste.SOLUTION: In a system for reproducing odor or reproducing taste based on information in a metaverse space in services in the metaverse space, a non-fungible token is associated with code data of odor information or taste information. The system further includes a first reproducing device for executing reproduction processing of odor or taste corresponding to the odor information or the taste information for a second user who differs from a first user and utilizes services in a metaverse space by utilizing the code data, a use request including information for identifying the first user and a second reproducing device as authentication information is transmitted to a block chain, and the first reproducing device executes the reproduction processing according to a confirmation result based on possession information of a non-fungible token within the block chain.SELECTED DRAWING: Figure 31A

Description

Technical Field

[0001] The present invention relates to a system and a management device that execute information processing for managing smell and taste reproduction processing based on smell and taste information.

Background Art

[0002] In recent years, technologies related to methods for expressing (quantifying) smells numerically have been proposed. For example, Patent Document 1 discloses a technique for measuring the activity of each receptor by applying a predetermined ligand to a receptor array in which predetermined receptors are arranged comprehensively. Patent Document 1 also discloses a method for reproducing the smell of a target substance by combining two or more standard substances (perfumes) based on the activation degrees of each receptor measured for the target substance and the standard substance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, appropriate reproduction of the target smell or taste, or appropriate management of the smell or taste itself has not been performed.

[0005] In addition to games, the development of technologies related to virtual spaces and augmented reality is remarkable in other forms of entertainment and even in the world of shopping.

[0006] From this background, various devices that can access the five senses of humans, such as VR (Virtual Reality) goggles, have emerged. However, VR devices related to smell are still in the stage of development.

[0007] As described above, the applicant has developed a technology that reproduces scents based on the human sense of smell. Therefore, it is envisioned that this technology could be applied to reproducing scents or tastes in virtual spaces or augmented reality worlds.

[0008] However, if smells or tastes can be accurately reproduced remotely in this way, it is expected that the information used to reproduce those smells or tastes (hereinafter referred to as "smell information") itself will have economic value.

[0009] In this case, methods and systems for appropriately protecting the owners of scent information or for making scent information subject to economic trading have not been considered.

[0010] This invention has been made in view of these circumstances and aims to reproduce a target smell or taste, or to appropriately manage smell or taste.

[0011] The present invention also aims to provide a system or apparatus that enables the economic trading of information such as scent. [Means for solving the problem]

[0012] To achieve the above objective, according to one aspect of the present invention, a system for reproducing smells or tastes based on information in the metaverse space in a service in the metaverse space, comprising: multiple computers corresponding to each of multiple nodes constituting a blockchain, communicating via peer-to-peer communication; a management device capable of issuing transactions to the blockchain, registering non-fungible tokens on the blockchain in response to an issuance request from the original owner of smell or taste information, and verifying the legitimacy of the non-fungible tokens based on ownership information, wherein the non-fungible tokens are associated with code data of smell or taste information, and the blockchain receives the code data from the original owner. In response to the transfer to a user, the system records changes in ownership information of non-fungible tokens, returns the result of verification of the legitimacy of using the smell or taste information based on the non-fungible tokens, and further includes a first playback device that uses code data to perform smell or taste playback processing corresponding to the smell or taste information for a second user who uses the service in the metaverse space, unlike the first user. As a usage request from the first user's device, a usage request is sent to the blockchain containing authentication information that identifies the first user and the second playback device, and the first playback device performs playback processing according to the verification result based on the ownership information of non-fungible tokens in the blockchain.

[0013] Preferably, the first playback device controls the playback process according to spatial information relating to an avatar corresponding to a second user in the metaverse space, and the spatial information includes settings for virtual temperature, humidity, or wind speed that are set as the environment for the avatar in the metaverse space.

[0014] Preferably, the first user's device is a server device for distributing images and sounds of the virtual space to the second user, and in response to the images distributed from the server device, it sends a usage request to the management device, causing it to execute playback processing linked to the first playback device.

[0015] Preferably, the system further includes a server device for distributing images and sounds from the metaverse space to the first user's device and the second user's device, and when the first user's avatar in the metaverse space approaches the second user's avatar in the metaverse space within a predetermined distance, the server device sends a usage request to a management device, causing it to execute playback processing linked to the first playback device.

[0016] Preferably, the system further includes a second playback device for a first user using a service in the metaverse space, which uses code data to perform a playback process of scent or taste corresponding to scent or taste information, and when the avatar of the second user in the metaverse space approaches the avatar of the first user in the metaverse space within a predetermined distance, the server device sends a usage request to the management device, causing the second playback device to perform a playback process in conjunction with the second playback device.

[0017] Preferably, the first regeneration device controls the regeneration process according to usage conditions corresponding to a second user in the metaverse space, and the usage condition information includes an upper limit for the regeneration process of the recorded smell or taste. If the number of times the legitimacy of a usage request from the first user's device is verified, or at least one of the regeneration time, exceeds the upper limit, the management device does not send a verification result to the regeneration device that permits regeneration, even if the legitimacy has been verified.

[0018] Preferably, the management device initiates a transaction to change the ownership information of a non-fungible token in response to the transfer of code data from the original owner to the user.

[0019] Preferably, the management device, upon request, verifies that the user is the owner of the non-fungible token based on ownership information of the non-fungible token held within the blockchain.

[0020] Preferably, when the legitimacy is confirmed, the management device transmits, to the first playback device, code data for executing playback processing using substances related to reception of a plurality of types of scents or tastes.

[0021] According to another aspect of this invention, there is provided a management device that manages scent reproduction or taste reproduction based on information in a metaverse space in services in the metaverse space, the management device including: an interface for executing communication via a network; and an arithmetic device for controlling the operation of a playback device that issues a transaction to a blockchain and executes scent reproduction or taste reproduction via the interface, the arithmetic device registering a non-fungible token in the blockchain in response to an issuance request from an original owner of scent information or taste information, the non-fungible token being associated with code data of the scent information or taste information, recording a change in ownership information of the non-fungible token in the blockchain in response to transfer of the code data from the original owner to a first user, including, as a usage request from the device of the first user, information identifying the first user and the playback device as authentication information in a usage request transmitted to the blockchain, and distributing the code data to the playback device according to a confirmation result based on the ownership information of the non-fungible token in the blockchain, the code data being for the playback device to execute a scent or taste reproduction process corresponding to the scent information or taste information for a second user who uses services in the metaverse space and is different from the first user.

Advantages of the Invention

[0022] According to the present invention, it is possible to appropriately reproduce a target scent or taste, or manage a scent or taste.

Brief Description of the Drawings

[0023] [Figure 1] It is a diagram showing an outline of a scent reproduction method according to this embodiment. [Figure 2A] It is a diagram showing an outline of a scent reproduction method according to this embodiment. [Figure 2B]It is a diagram showing an overview of the odor reproduction method according to this embodiment. [Figure 3] It is a diagram showing an outline of the configuration of the spraying control system. [Figure 4] It is a block diagram showing the hardware configuration of the server. [Figure 5] It is a functional block diagram showing an example of the functional configuration of the server. [Figure 6] It is a flowchart showing the operation of the spraying control process. [Figure 7] It is a diagram showing an overview of the odor reproduction method according to another embodiment. [Figure 8] It is a block diagram showing the configuration of the conversion device. [Figure 9] It is an example of a graph showing the correlation between the value of the target variable and the value after conversion when using the conversion device for conversion. [Figure 10] It is an example of a graph showing the correlation between the value of the target variable and the value after conversion when using the conversion device for conversion. [Figure 11] It is an example of a graph showing the correlation between the value of the target variable and the value after conversion when using the conversion device for conversion. [Figure 12] It is an example of a graph showing the correlation between the value of the target variable and the value after conversion when using the conversion device for conversion. [Figure 13] It is a block diagram showing the configuration of the prediction model creation device. [Figure 14] It is an example of a graph showing the correlation between the value of the target variable and the value after conversion when using the conversion device for conversion. [Figure 15] It is an example of a graph showing the correlation between the value of the target variable and the value after conversion when using the conversion device for conversion. [Figure 16A] It is a system configuration diagram showing an overview of the third embodiment. [Figure 16B] It is a system configuration diagram showing an overview of the third embodiment. [Figure 17] It is a functional block diagram for explaining the functional configuration of the management server 3000. [Figure 18]This figure shows a first example of a transaction of scent code (scent information) using blockchain and non-fungible tokens (NFTs) according to the third embodiment. [Figure 19] This figure shows a second example of a transaction of scent code (scent information) using blockchain and non-fungible tokens (NFTs) according to the third embodiment. [Figure 20A] This diagram shows the configuration of a system for managing NFTs using smart contracts. [Figure 20B] This diagram shows the configuration of a system for managing NFTs using smart contracts. [Figure 21A] This diagram shows the workflow for managing NFTs using smart contracts. [Figure 21B] This diagram shows the workflow for managing NFTs using smart contracts. [Figure 22] This diagram shows the transaction when an NFT according to the third embodiment is sold. [Figure 23] This figure shows a flowchart for actively reproducing odors according to the third embodiment. [Figure 24] This figure shows a first example of a transaction when using the odor reproduction device according to the third embodiment. [Figure 25] This figure shows a second example of a transaction when using the odor reproduction device according to the third embodiment. [Figure 26] This figure shows a third example of a transaction when using the odor reproduction device according to the third embodiment. [Figure 27] This figure shows a fourth example of a transaction when using the odor regeneration device RE according to the third embodiment. [Figure 28] This figure shows a third example of a transaction of scent code (scent information) using blockchain and non-fungible tokens (NFTs) according to the third embodiment. [Figure 29] This figure shows a flowchart for passively reproducing odors according to the third embodiment. [Figure 30] This is a conceptual diagram illustrating the outline of the fourth embodiment. [Figure 31A] This is a diagram illustrating the outline of the fifth embodiment. [Figure 31B] This is a diagram illustrating the outline of the fifth embodiment. [Figure 32] This is a conceptual diagram illustrating the configuration of a modified example of the fifth embodiment. [Figure 33A] This figure shows the system configuration for the metaverse environment in a modified version of the fifth embodiment. [Figure 33B] This figure shows the system configuration for the metaverse environment in a modified version of the fifth embodiment. [Figure 34] This is a conceptual diagram illustrating the outline of the sixth embodiment. [Figure 35A] This figure shows an example of NFT management using IPFS. [Figure 35B] This figure shows an example of NFT management using IPFS. [Modes for carrying out the invention]

[0024] (First Embodiment) <Overview>

[0025] Generally, when the receptor is an olfactory receptor, odor molecules bind to proteins called olfactory receptors expressed on the surface of olfactory nerve cells in the nasal cavity. This triggers information transmission within the olfactory nerve cells, and the odor information is then transmitted to the brain. Genomic analysis suggests that there are approximately 400 types of olfactory receptors in humans. It is understood that certain groups of olfactory receptors are activated to different degrees in response to specific odor molecules, and these stimuli are transmitted to the brain and combined to allow the brain to distinguish various odors.

[0026] This embodiment describes an example in which odors are reproduced based on the results of measuring the activity level of each receptor after applying a predetermined ligand to a receptor array that comprehensively arranges the olfactory receptors (ORs) described above. In this embodiment, an example is described in which multiple receptors (for example, 30 types of receptors) that have a significant impact on human perception among olfactory receptors are used as the predetermined receptors. Note that this method is not limited to olfactory receptors and can be similarly implemented for taste receptors. The embodiment will be described below with reference to the drawings.

[0027] Figure 1 shows an overview of a smell reproduction method to which the information processing device according to this embodiment is applied. Figure 1 shows an example in which content introducing food and beverages (e.g., ramen) from a restaurant is delivered to viewers, and the smell of the food and beverages is reproduced on the viewers' side using a predetermined device. Examples of content include content delivered via terrestrial broadcasting, satellite broadcasting, the internet, etc.

[0028] In the example shown in Figure 1, a designated camera captures images of customers consuming food and beverages in a restaurant, while a CO odor capture device captures the odor (e.g., gas) of the food and beverages.

[0029] The collected odors are analyzed by the receptor information determination device 2 and converted into response information for a predetermined receptor.

[0030] The converted response information is sent to Server 1. Then, Server 1 sends the response information (such as scent information, for example, a scent code) along with the content to each content playback device RE.

[0031] The content playback device RE transmits the above-mentioned content to a designated display device TV based on a request to view the content. The content playback device RE also transmits spraying information to the odor spraying device 3 based on response information corresponding to the above-mentioned content.

[0032] The fragrance spraying device 3 is equipped with multiple types of fragrance cartridges CA, and the fragrance (e.g., gas, liquid, or powder) extracted from these multiple types of fragrance cartridges CA is sprayed (ejected, ejected) through a variable spray nozzle (nozzle NO). Response information and spraying information will be explained using Figures 2A and 2B.

[0033] In this embodiment, an example is described in which a fragrance is released from the release device (fragrance spraying device 3), but the release is not limited to fragrances; any substance related to the reception of smell or taste may be released. Here, substances related to the reception of smell or taste include agonists, antagonists, modulators, etc.

[0034] Agonists are substances that enhance or express the effects of olfactory receptors or gustatory receptors when they bind to them.

[0035] Antagonists are substances that inhibit or suppress the action of olfactory or gustatory receptors by preventing agonist binding.

[0036] A modulator is a substance that does not respond to stimuli itself, but amplifies or reduces the stimuli response of an agonist or antagonist. In other words, a modulator is a substance that binds to a site different from the ligand-binding site, increasing or decreasing the action of olfactory or gustatory receptors.

[0037] Figures 2A and 2B illustrate an example of the process from extracting features from collected odors to generating response information and finally generating spray information.

[0038] In code ST1, the receptor information determination device 2 applies a predetermined ligand (odor molecule) to a receptor array that comprehensively arranges predetermined receptors, and measures the activity level (primary receptor response information) of each receptor. The method for measuring the activity level of each receptor is not particularly limited; for example, data may be obtained by actual tests as described in Patent Document 1 or described later, or it may be done by collecting manually entered data or virtual data obtained from a machine learning model.

[0039] In code ST2, the receptor information determination device 2 extracts the characteristic quantities of the target odor based on the measured activity level of each receptor. The method for extracting the characteristic quantities is not particularly limited, but for example, the method described in Patent Document 1 can be used.

[0040] Feature quantities are the response characteristics of olfactory receptors to a test substance (response information; receptor response information), and examples include the response intensity, response intensity area, response duration, response speed, peak time, response rise (timing), and number of peaks for each receptor.

[0041] Code ST3 generates response information for each receptor (secondary receptor response information) based on the features described above. In the examples in Figures 2A and 2B, four types of receptors, OR1 to OR4, are shown, but the number of types of receptors is not particularly limited. Also, in the examples in Figures 2A and 2B, the features of each receptor are shown in binary, but the method of quantifying the features is not particularly limited; for example, they may be shown in other number systems such as decimal, or as strings.

[0042] Response information, in other words, is a characteristic value for odor molecules at multiple types of receptors, and is information that shows at least one of the following characteristics: response intensity, response intensity area, response duration, response rate, peak time, response rise, and number of peaks. However, response information is not limited to the above and may also be various parameters for odor molecules at multiple types of receptors.

[0043] In codes ST4 and ST5, the above response information is encoded, converted into an N-dimensional code (where N is an integer greater than or equal to 1), and transmitted.

[0044] In this embodiment, an example of an N-dimensional code being a two-dimensional code will be described. The two-dimensional code according to this embodiment comprises a data section in which a bit sequence corresponding to the target data is represented as a pattern in which white or black cells, which are the constituent units of the symbol, are arranged in a matrix, and one or more finder patterns arranged separately from the data section. The data section described above includes information based on receptor response information obtained using olfactory receptors or gustatory receptors that are responsive to extracellular substances (e.g., odor molecules) (e.g., the response characteristics and response information described above).

[0045] In other words, code ST4 is a control method for the information processing device (server 1), and can be understood as an encoding step that converts the (receptor) response information into an N-dimensional code (for example, a two-dimensional code) by performing a predetermined encoding on the (receptor) response information described above.

[0046] In code ST6, the viewer decodes the aforementioned N-dimensional code and converts it back into the original response information.

[0047] In other words, code ST6 is a control method for the information processing device (server 1), and can be understood as a decoding step that converts the N-dimensional code (for example, a two-dimensional code) into (receptor) response information by performing a predetermined decoding on the aforementioned N-dimensional code (for example, a two-dimensional code).

[0048] In code ST7, for example, the response information is converted by the server 1 described above into spraying information for spraying the reproduced scent. Figures 2A and 2B show the spraying information for cartridges CA1 to CA4 corresponding to receptors OR1 to OR4. That is, cartridge CA1 is filled with a fragrance to stimulate receptor OR1.

[0049] Figures 2A and 2B illustrate an example where receptors and cartridges correspond one-to-one, but this is not limited to this example. More types of cartridges may be used than the number of types of receptors, or fewer types may be used. In other words, one cartridge CA may provide (agonize) or modulate (antagonize or modulate) responses from multiple receptors. By using cartridge CAs that stimulate multiple receptors in this way, the size of the odor spraying device 3 can be reduced and costs can be lowered.

[0050] For example, when stimulating receptors OR1 and OR3, the following cartridge CA may be used to spray the odor. • Cartridge CA filled with substances that stimulate receptors OR1 and OR3.

[0051] Furthermore, for example, when stimulating receptors OR1 to OR5, the following three types of cartridge CA may be used to spray the odor. Cartridge CA is filled with substances (agonists) that stimulate receptors OR1, OR3, OR5, and OR6. • Cartridge CA filled with substances (agonists) that stimulate receptors OR2, OR4, and OR6. • Cartridge CA filled with a substance (antagonist) that prevents other substances from binding to the OR6 receptor.

[0052] The spraying information is information used to reproduce a target scent by spraying one or more fragrances from a combination of multiple types of fragrances, and includes, for example, the spraying time, spraying volume, spraying temperature, number of sprays, nozzle slitting amount, and spraying direction of the fragrance.

[0053] In code ST8, based on the spraying information described above, the scent spraying device 3 sprays fragrance to provide the content viewer with a scent (fragrance) that reproduces the target scent.

[0054] Various devices can be envisioned as the odor spraying device 3, including display devices (televisions), smartphones, projection devices (projectors), HMDs (head-mounted displays), etc.

[0055] Furthermore, the content does not necessarily have to be related. For example, a scent specified by a designated user may be sprayed. In this case, it is assumed that a scent item and the corresponding response information or spraying information are stored in a designated storage unit in advance.

[0056] In the example above, an N-dimensional code obtained by replacing the target scent with electronic data is used as digital scent information. However, for example, the extracted feature quantities (code ST2) or secondary receptor response information (code ST3) may also be used (and distributed) as digital scent information. In other words, the feature quantities, secondary receptor response information, or N-dimensional code can each be considered to represent the data structure of the receptor response information used by Server 1 (information processing device).

[0057] In this embodiment, when reproducing a target scent, a substance related to scent reception (e.g., fragrance) is sprayed (released). However, in a modified example, when reproducing a target taste, as described later, a substance related to taste reception (e.g., seasoning) is released. In other words, "spraying" as used in this embodiment is a sub-concept of "release".

[0058] <System Configuration>

[0059] Figure 3 shows an overview of the system configuration of the spray control system (odor reproduction system) according to this embodiment.

[0060] The spray control system according to this embodiment is configured such that a server 1, a collection device CO, a receptor information determination device 2, a content playback device RE, a display device TV, and an odor spraying device 3 are interconnected via a predetermined network N such as the Internet.

[0061] Server 1 performs various processes in cooperation with the operation of the receptor information determination device 2, the content playback device RE, the display device TV, and the odor spraying device 3.

[0062] The odor capture device CO captures the corresponding odor of the content. As shown in Figure 1, the odor may be captured in real time when filming the video related to the content, or it may be captured at a time separate from the filming of the video related to the content.

[0063] The receptor information determination device 2 analyzes the odor collected by the odor collection device CO described above. The receptor information determination device 2 may also analyze the components contained in the odor (for example, gas or liquid), but in this embodiment, it analyzes receptor response information obtained using olfactory receptors responsive to the above-mentioned odor (odor molecules) (the result of measuring the activity of each receptor by applying a predetermined ligand to a receptor array in which receptors are comprehensively arranged). This makes it possible to reproduce the target odor using components different from the target odor when reproducing the odor.

[0064] Furthermore, the receptor information determination device 2 may analyze response characteristics using receptors as described in Patent Document 1, or it may analyze response characteristics from components contained in odor molecules.

[0065] The content playback device RE displays (plays) video content on the display device TV. The content playback device RE also transmits spraying information to the scent spraying device 3 so that fragrance is sprayed from the scent spraying device 3 at predetermined timings in the video content.

[0066] In this embodiment, a content playback device RE is provided because a display device TV, such as a digital signage screen, is also assumed. However, content may be transmitted directly from server 1 to the display device TV, or spraying information may be transmitted directly from server 1 to the scent spraying device 3.

[0067] The display device TV displays content. In this embodiment, an example is described in which the display device TV is equipped with a scent spraying device 3, which will be described later, but the display device TV and the scent spraying device 3 may be separate and independent devices. Also, although an example is described in which the display device TV is a display device, it is not limited to this and may be a projection device such as a projector.

[0068] The fragrance spraying device 3 reproduces the target scent by spraying fragrance based on spraying information. In this embodiment, an example is described in which the fragrance spraying device 3 is provided with a mounting section (not shown) for attaching a cartridge CA (fragrance cartridge) and a nozzle NO (variable spray nozzle), but it is not limited to this example.

[0069] Cartridge CA is a cartridge for filling with fragrance to be sprayed by a predetermined information processing device (server 1, content playback device RE, etc.), and is filled with a composition that selectively responds only to specific receptors. Note that this composition is not limited to one that selectively responds only to specific receptors, but may be a composition that responds to multiple receptors. Note that multiple types of cartridge CA with different compositions are installed in the fragrance spraying device 3.

[0070] Nozzle NO is a spray nozzle that sprays a predetermined fragrance based on spray control (spray information) by a predetermined information processing device (server 1, content playback device RE, etc.).

[0071] <Hardware Configuration>

[0072] Figure 4 is a block diagram showing the hardware configuration of Server 1 according to this embodiment. Server 1 includes a CPU (Central Processing Unit) 11, ROM (Read Only Memory) 12, RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an output unit 16, an input unit 17, a storage unit 18, a communication unit 19, and a drive 20.

[0073] The CPU 11 executes various processes according to the program stored in the ROM 12 or the program loaded from the storage unit 18 into the RAM 13. The RAM 13 also stores data necessary for the CPU 11 to execute various processes. The CPU 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output interface 15 is also connected to this bus 14.

[0074] The input / output interface 15 is connected to an output unit 16, an input unit 17, a storage unit 18, a communication unit 19, and a drive 20. The output unit 16 consists of a display, speakers, etc., and outputs various information as images and sounds. The input unit 17 consists of a keyboard, mouse, etc., and inputs various information. The storage unit 18 consists of a hard disk, DRAM (Dynamic Random Access Memory), etc., and stores various data. The communication unit 19 communicates with other devices via a network N, including the Internet.

[0075] The drive 20 is appropriately equipped with removable media 21, which may consist of a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory. Programs read from the removable media 21 by the drive 20 are installed in the storage unit 18 as needed. The removable media 21 can also store various types of data stored in the storage unit 18, just like the storage unit 18.

[0076] Although not shown in the diagram, the CO collection device, receptor information determination device 2, content playback device RE, display device TV, and odor spraying device 3 have the hardware configuration shown in Figure 4.

[0077] <Functional Configuration>

[0078] Figure 5 is a functional block diagram showing an example of the functional configuration of Server 1 according to this embodiment.

[0079] In the CPU 11 of Server 1, the response information acquisition unit 31, image acquisition unit 32, model information acquisition unit 33, spray information determination unit 34, spray control unit 35, display control unit 36, etc., function during operation.

[0080] The response information acquisition unit 31 acquires receptor response information obtained using multiple types of receptors, including olfactory receptors (or gustatory receptors) that are responsive to extracellular substances. Specifically, the response information acquisition unit 31 acquires the above-mentioned response information analyzed using the receptor information determination device 2.

[0081] The acquired response information (receptor response information) is stored in the response information DB41. Here, the response information is stored in association with the content (or the time information of the content) mentioned above. In this way, for example, the target scent can be reproduced at the appropriate timing in the content.

[0082] The image acquisition unit 32 acquires content that includes at least one of audio information and video information. The content is, for example, image information captured by the video camera shown in Figure 1 in the case of real time. The content is, for example, content distributed from terrestrial broadcasting, satellite broadcasting, or various distribution servers in the case of non-real-time situations. Note that if only the reproduction of the target's scent is performed, the acquisition of various types of content by the image acquisition unit 32 is not required.

[0083] The model information acquisition unit 33 acquires model information for the display device TV, the odor spraying device 3, etc. This allows, for example, the determination of appropriate spraying information for the odor spraying device 3 in the process of determining spraying information described later. Specifically, it allows the determination of spraying information according to the type of cartridge CA of the odor spraying device 3. The acquired model information is stored in the model information DB 42.

[0084] The model information acquisition unit 33 may also acquire information about the fragrance (cartridge). This allows, for example, in the process of determining the spray information described later, to refer to a table (or learning model) corresponding to the cartridge (type) when associating receptor information with spray information.

[0085] The spray information determination unit 34 determines spray information regarding the scent spraying of multiple types of fragrances according to the response information.

[0086] For example, the spray information determination unit 34 determines the spray information based on the above-mentioned response information and a predetermined mapping table (not shown). It is assumed that the mapping table already associates the response information with the spray information and stores it in the mapping DB 43.

[0087] Here, for example, the mapping table is configured such that the response information and the spraying information are correlated as follows. • The higher the "response intensity," the greater the "fragrance spray volume." • The higher the "area of ​​response intensity (integral value)", the greater the "fragrance spray volume". • The higher the "response duration," the longer the "fragrance spray time." • The faster the "response speed," the higher the "fragrance spray temperature." • The earlier the "peak time," the higher the "fragrance spray temperature." • The greater the "response rise time," the higher the "fragrance spray temperature." • The higher the "peak count," the higher the "fragrance spray frequency." • The higher the "response intensity," the smaller the "spray nozzle restriction amount." The following correlation between response information and spraying information is merely an example and is not limited to that; these pieces of information may be combined. For example, a combination such as a higher "response speed" and "response rise time" corresponds to a higher "fragrance spray temperature" is conceivable.

[0088] Furthermore, for example, the spray information determination unit 34 determines spray information based on response information using a learning model. The learning model is pre-generated by machine learning using receptor response information and spray information corresponding to said receptor response information as training data, and is stored in the correspondence DB 43.

[0089] The spray information determination unit 34 may also determine the spray information by taking into consideration the model information described above. That is, the spray information determination unit 34 may determine the spray information using the above-described correspondence table or learning model corresponding to the number (types) of cartridges CA included in the model information.

[0090] Furthermore, the spray information determination unit 34 may determine spray information related to odor spraying according to spatial parameters, in addition to the response information described above.

[0091] Spatial parameters are parameters relating to the state of the space in which the odor is sprayed or the positional relationship with the target (person or object) to which the odor is sprayed. Specifically, these include various parameters such as the size of the room or space in which the odor is sprayed, the distance between the odor spraying device 3 and the nose, airflow rate, airflow direction, temperature, and humidity. The spatial parameters are preferably acquired by a predetermined acquisition unit (not shown) from spatial parameters sensed by sensors provided on the odor spraying device 3 or other external devices.

[0092] For example, in cases where the position of a person's nose (face) can be determined to some extent, such as in a movie theater (when spraying directly), the spray information determination unit 34 may control the spray direction, spray volume, spray concentration, etc., based on the distance from the nose, temperature, humidity, etc.

[0093] Furthermore, for example, in the case of a large space such as a sports stadium (where spraying is performed indirectly), the spraying direction, spray volume, spray concentration, etc., should be controlled by the spraying information determination unit 34 based on the size of the space, airflow, air direction, temperature, humidity, etc.

[0094] The correspondence between environmental parameters and spraying information may be performed using a correspondence table as described above, or it may be performed using a learning model.

[0095] The spray control unit 35 sprays at least one of several types of fragrances (several types of cartridges CA) based on the spraying information. In other words, the spray control unit 35 transmits the spraying information to the fragrance spraying device 3 (display device TV).

[0096] The display control unit 36 ​​transmits the above-mentioned content to the display device TV. The display control unit 36 ​​associates the content with identification information for the spraying information. This allows, for example, multiple types of target scents to be sprayed multiple times at multiple timings while the content is being displayed.

[0097] <Processing details>

[0098] Figure 6 shows an example of the spray control process according to this embodiment. In this embodiment, an example in which the spray control process is performed by Server 1 is described, but it is not limited to this, and for example, the spray control process may be performed in the odor spraying device 3.

[0099] In step S11, the response information acquisition unit 31 acquires response information of the receptor corresponding to the target odor.

[0100] In step S12, the image acquisition unit 32 acquires video information as content.

[0101] In step S13, the model information acquisition unit 33 acquires model information for the odor spraying device 3, etc.

[0102] In step S14, the spray information determination unit 34 determines spray information regarding the scent spraying of multiple types of fragrances according to the response information.

[0103] In step S15, the spray control unit 35 transmits the spray information to the odor spraying device 3 (display device TV).

[0104] In step S16, the display control unit 36 ​​transmits the content to the display device TV.

[0105] <Advantageous effects of this embodiment>

[0106] According to the above-described embodiment, fragrance can be sprayed in correspondence with the temporal position (time axis) of the content during content playback (viewing). This allows users to view the content using not only sight and hearing, but also smell, thereby improving immersion in the content and a sense of unity with the filming location. Furthermore, for example, VR goggles (HMD) can function as the above-described fragrance spraying device to further enhance immersion.

[0107] Furthermore, according to the above-described embodiment, by releasing a desired scent in synchronization with the video, for example, an advertising effect can be expected. For example, even outdoors, by providing a display type equipped with a scent spraying function and having the customer select a predetermined menu (by having the customer select a button), the scent appropriate for that dish can be instantly reconstructed and sprayed along with the video of the dish. By changing this reconstruction pattern, it is possible to accommodate the scents of various dishes.

[0108] Furthermore, according to the above-described embodiment, it becomes possible to communicate with friends in distant locations through scent. For example, when describing an experience, incorporating scent as an element, in addition to words, gestures, images, and photographs, adds depth to the sharing of the experience. This enables smoother and deeper communication.

[0109] Furthermore, the above-described embodiment can also be used for presentations. For example, when developing a product, it may be necessary to explain it in an online meeting. In particular, fragrance can be an important factor in food and cosmetics. However, it is difficult for people in remote locations to directly smell the scent. Therefore, by applying the above-described embodiment, it becomes possible to share the scent with people in remote locations, on the other side of the screen, in a way similar to screen sharing, and it is expected that the probability of successful business negotiations will increase.

[0110] Although one embodiment of the present invention has been described above, the present invention is not limited to the embodiments described above, and any modifications, improvements, etc. that can achieve the objectives of the present invention are included in the present invention.

[0111] (modified version)

[0112] In the above embodiment, an example was described in which nozzle NO sprays fragrance according to the spraying time, etc. However, nozzle NO may spray fragrance in the direction of a person based on information acquired by a predetermined human presence sensor. In addition, when outdoors, a wind direction sensor may be used to determine the spraying direction according to the wind direction. This makes it possible to reproduce the target scent with greater accuracy for users viewing the content. You may do so.

[0113] Furthermore, while the above-described embodiment explained an example of reproducing a target scent associated with content, it is not limited to this. For example, a predetermined scent (e.g., "the scent of soy sauce ramen") may be isolated, retrieved from a predetermined storage (library), and reproduced. This allows for reproduction using fragrances (in cartridge CA) that replace rare natural fragrances, or reproduction of toxic scents with non-toxic fragrances. In addition, this makes it possible to provide users with a relaxing effect by using pre-set (using pre-prepared response information) fragrances such as "calming fragrances," "concentration-enhancing fragrances," and "sleep-promoting fragrances."

[0114] Furthermore, although the above-described embodiment does not demonstrate an alert function based on odor, Server 1 may be made to function as an infectious disease checker, cancer checker, Parkinson's disease checker, or health management toilet based on odor. For example, it is conceivable that an odor could be collected and reproduced by a medical professional in a remote location for use in diagnosis.

[0115] Furthermore, while the above-described embodiments explained examples of generating response information using olfactory and gustatory receptors in humans, response information may also be generated using receptors other than those in humans. This allows for applications such as repellents (e.g., insect repellents) and attractants. It also allows for applications in pest control.

[0116] Furthermore, while the above-described embodiment explains an example of reproducing the target scent at a timing corresponding to the content, the scent may be sprayed at various timings.

[0117] For example, in response to user operation, a request may be sent from the odor spraying device 3 to the server 1. Upon receiving the request, the spray control unit 35 may send spraying information. Upon receiving the spraying information, the odor spraying device 3 may reproduce the target odor.

[0118] Alternatively, for example, the odor spraying device 3 may receive spraying information in advance and reproduce the target odor by controlling the odor spraying device 3 in response to user operation.

[0119] Furthermore, although the above-described embodiment described an example in which the spray control unit 35 transmits spray information, the number of sprays may be managed based on an upper limit on the number of times the target scent is sprayed.

[0120] For example, the spray control unit 35 may decide whether or not to transmit spray information based on the upper limit number of times stored in a predetermined storage unit and the number of times spraying has already been performed.

[0121] The above-mentioned upper limit and the number of times sprayed may be managed by the odor spraying device 3. In this case, the spraying control unit 35 transmits the above-mentioned upper limit along with the spraying information. The odor spraying device 3 may then decide whether or not to transmit the spraying information based on the upper limit and the number of times sprayed stored in a predetermined storage unit.

[0122] Furthermore, while the above-described embodiment described odor spraying control in which fragrances are sprayed (released) to reproduce a target smell, it can also be applied to taste release control in which seasonings are released to reproduce a target taste.

[0123] In other words, instead of the response information to odor molecules mentioned above, information such as response intensity, area of ​​response intensity, response duration, response speed, peak time, response rise time, and number of peaks is input as response information to taste.

[0124] In addition, instead of the odor spraying information mentioned above, taste release information is output, which includes information such as the release time, release amount, release temperature, number of releases, and nozzle narrowing amount for substances related to taste reception (e.g., seasonings).

[0125] Furthermore, while the above-described embodiment explained an example of reproducing smell (or taste) when playing video content, it can also be applied in virtual spaces such as the so-called metaverse.

[0126] For example, in virtual travel using avatars (domestic travel, international travel, space travel, etc.), it is conceivable that the avatar could emit scents such as perfume in accordance with its actions and words. Furthermore, it is conceivable that a specific perfume scent code could be converted into an NFT (Non-Fungible Token) using blockchain technology, making it valid as copyright or circulating as a cryptocurrency.

[0127] This allows for the immediate delivery of products that involve scent or taste (such as perfumes) to consumers, eliminating the need for physical transportation.

[0128] Furthermore, in the above-described embodiment, response information is converted into spray information using a correspondence table and a learning model, but the response information may be transmitted directly without using these. In this case, the odor spraying device 3 can reproduce the odor to some extent by using a cartridge CA that corresponds one-to-one with the receptor OR.

[0129] This allows for different approaches depending on the situation, such as sending response information to the low-cost version of the odor spraying device 3 without using a correspondence table.

[0130] (Second Embodiment)

[0131] Figure 7 shows an overview of a smell reproduction method to which the information processing device according to the second embodiment is applied. Figure 7 shows an example in which content introducing food and beverages (e.g., ramen) from a restaurant is delivered to viewers (in real time), and the smell of the food and beverages is reproduced on the viewers' side using a predetermined device. Examples of content include content delivered via terrestrial broadcasting, satellite broadcasting, the internet, etc.

[0132] In the example shown in Figure 7, a designated camera captures images of customers consuming food and beverages in a restaurant, while a CO odor capture device captures the odor (e.g., gas) of the food and beverages.

[0133] The collected odors are analyzed by the real-time odor analyzer NA (gas detection device U100) and converted into response information for a predetermined receptor by the receptor information determination device 2 (conversion device).

[0134] The converted response information is sent to Server 1. Then, Server 1 sends the spray information along with the content to each content playback device RE.

[0135] The content playback device RE transmits the aforementioned content to a designated display device TV based on a request to view the content. The content playback device RE also transmits spraying information corresponding to the aforementioned content to the odor spraying device 3.

[0136] The fragrance spraying device 3 is equipped with multiple types of fragrance cartridges CA, and the fragrance (for example, liquid or powder) extracted from these multiple types of fragrance cartridges CA is sprayed (ejected, ejected) through a variable spray nozzle (nozzle NO).

[0137] The receptor information determination device 2 (conversion device) shown in Figure 7 will be explained with reference to Figures 8 to 15.

[0138] First, before describing the conversion device U1, the prediction model creation device U2, the conversion information creation method, the prediction model creation method, and the program for each embodiment, we will first describe the overview of the conversion device U1.

[0139] First, let me explain the purpose of using the conversion device U1.

[0140] Gas sensors have been proposed as a system for identifying the type of odor. However, gas sensors alone cannot accurately distinguish and identify the type of odor that humans perceive. This is because the detection elements of gas sensors are composed of materials that do not conform to human senses (olfaction). Therefore, even if various detection elements and analysis methods are proposed, it remains difficult to identify and distinguish the type of odor.

[0141] While there are approaches that use machine learning to forcibly link gas sensor output with human sensory evaluation, high-precision judgments have not yet been achieved with these approaches because sensory evaluation data varies from person to person. Another approach involves adopting a notation method that represents the chemical structure of molecules as an alphanumeric string, such as SMILES notation, to strengthen the link between gas sensor output and sensory evaluation results. However, although prediction accuracy improves, the fact that information on odorless molecules is mixed in prevents highly accurate identification, discrimination, and prediction of odor types. In contrast, if gas sensor output can be expressed as a quantitative numerical value of human olfaction, it will be possible to determine odors with high precision that is in line with human olfaction.

[0142] The conversion device U1 is a device that converts output information from a device having a predetermined gas detection function for a predetermined odor molecule (hereinafter also referred to as gas detection device U100) into response information that indicates the response of an olfactory receptor. Thus, the conversion device U1 converts output information of different values ​​from each of the gas detection devices U100 with different analytical methods for the same odor molecule into a single response information that represents the response of the olfactory receptor U200 to obtain the same result. This allows the conversion device U1 to associate the output information of the gas detection device U100 with a single response information, regardless of the differences in the analytical methods of the gas detection devices U100. For example, the conversion device U1 can associate a single response information, so to speak, as a standard meter for odor, with output information of different values ​​and units from multiple gas detection devices U100 for a single odor molecule. In the following embodiment, the conversion device U1 converts the output information into response information using a pre-trained learning model.

[0143] Next, we will describe the gas detection device U100.

[0144] The gas detection device U100 is, for example, a gas sensor or a mass spectrometer (gas chromatograph-mass spectrometer). The gas sensor outputs predetermined electrical signals (e.g., voltage, resistance, or current), frequency changes, changes in light wavelength, or the degree of activation due to exposure of olfactory receptors to odor molecules, depending on the type and concentration of odor molecules. For example, the gas detection device U100 outputs an electrical signal with a larger voltage value the greater the concentration of odor molecules it comes into contact with. The mass spectrometer, for example, outputs a graph showing the mass charge and its intensity with respect to the type and concentration of odor molecules.

[0145] Next, I will explain the olfactory receptor U200.

[0146] Olfactory receptor U200 can be realized, for example, by using a known olfactory receptor as shown in Patent Document 1, etc. Olfactory receptor U200 is, for example, a nucleic acid mounted in contact with a substrate (not shown). The nucleic acid includes a nucleic acid containing a gene encoding a predetermined receptor. Multiple types of nucleic acids are in contact with the substrate, and the various nucleic acids are arranged on the substrate at a distance from each other. By bringing cells into contact with the nucleic acids on the substrate, cells that transiently express olfactory receptors corresponding to the various nucleic acids are generated in situ.

[0147] In this embodiment, the receptor may cause a change in the cellular state when the test substance is brought into contact with the cell. Specifically, changes in intracellular calcium concentration or intracellular cAMP concentration may occur. Such changes can be measured using cAMP-sensitive dyes, cAMP-sensitive fluorescent proteins, calcium-sensitive dyes, or calcium-sensitive fluorescent proteins. For example, the activation level of the receptor can be quantitatively calculated by measuring the change in brightness caused by a cAMP-sensitive dye or cAMP-sensitive fluorescent protein. The activation level is used as response information or response data indicating the response of the olfactory receptor U200.

[0148] The olfactory receptor may be a human, mammalian, insect, or nematode olfactory receptor. Furthermore, the olfactory receptor is not limited to liquid test substances, but may be in a form that responds to contact with gaseous test substances. The latter form of olfactory receptor can be used as either a gas detection device U100 or an olfactory receptor U200. In other words, it is also possible to convert between the response information of the olfactory receptor to a gaseous test substance and the response information of the olfactory receptor to a liquid test substance.

[0149] Olfactory receptors are not limited to being expressed in the cells described above, but may also exist in a cell-free form.

[0150] For example, liposomes formed from a lipid bilayer such as a cell membrane, in which various olfactory receptors exist on the membrane, may be arranged on a substrate, isolated from each other. The size of the liposomes is not particularly limited, and they are typically around 100 nm in diameter. The method for producing the liposomes is not particularly limited, but it may include a step of separating cells expressing olfactory receptors into a cell membrane fraction (which may contain intracellular signaling proteins such as G proteins, adenylyl cyclase, and cyclic nucleotide-dependent channels) and a cytoplasmic fraction (which may contain intracellular signaling substances such as GDP, GTP, ATP, and cAMP), and then mixing and stirring the two fractions to fuse them.

[0151] Alternatively, the olfactory receptor protein itself may be used as a substrate probe. In this case, nanodiscs that maintain the three-dimensional structure of the olfactory receptor in a state where it spans the cell membrane are preferred. Nanodiscs are, for example, membrane scaffold proteins (MSPs) made from mutants of apolipoprotein A1 (APOA1), and because they can accumulate lipid bilayers in a disc-like manner (Timothy H. Bayburt, Yelena V. Grinkova, and Stephen G. Sligar Nano Letters 2002 2 (8), 853-856), they can maintain membrane proteins in a state where they span the lipid membrane even outside the cell (Civjan NR, Bayburt TH, Schuler MA, Sligar SG. Direct solubilization of heterologously expressed membrane proteins by incorporation into nanoscale lipid bilayers. Biotechniques. 2003 Sep;35(3):556-60, 562-3). Furthermore, the substrate on which the nanodiscs are placed is not particularly limited, but may be a carbon nanotube FET (Yang H, Kim D, Kim J, Moon D, Song HS, Lee M, Hong S, Park TH. Nanodisc-Based Bioelectronic Nose Using Olfactory Receptor Produced in Escherichia coli for the Assessment of the Death-Associated Odor Cadaverine. ACS Nano. 2017 Dec 26;11(12):11847-11855. doi: 10.1021 / acsnano), etc. The method for producing the nanodiscs is not particularly limited, but may include a step of forming nanodiscs by self-assembly by mixing a membrane protein solubilized from MSP expressed and recovered in E. coli, etc., with a phospholipid dissolved in water with a surfactant, and removing the surfactant by dialysis or the like.

[0152] By using these cell-free olfactory receptors and measuring changes in current, voltage, impedance, etc., in response to the test substance, the degree of receptor activation can also be quantitatively evaluated.

[0153] Next, the conversion device U1, the conversion information production method, and the program according to the second embodiment of the present invention will be described with reference to Figures 8 to 12. In this embodiment, a gas sensor is described as an example of the gas detection device U100.

[0154] The conversion device U1 converts output information from a predetermined gas detection device U100 to response information indicating the response of olfactory receptors U200 to a predetermined odor molecule. Furthermore, the conversion device U1 according to this embodiment outputs the converted response information and also outputs words (phrases) that represent the characteristics of a predetermined odor from the converted response information. As shown in Figure 8, the conversion device U1 comprises an output information acquisition unit U11, a conversion unit U12, and an output unit U13.

[0155] The output information acquisition unit U11 is implemented, for example, by the operation of the CPU. The output information acquisition unit U11 acquires output information output from the gas detection device U100 for a predetermined odor molecule. For example, the output information acquisition unit U11 acquires the voltage value output from the gas detection device U100 as output information by sensing a predetermined odor (odor molecule). The output information acquisition unit U11 may also acquire output information measured remotely by the gas detection device U100.

[0156] The conversion unit U12 is implemented, for example, by the operation of a CPU. Based on the output signals output from multiple gas detection devices U100 for each of the multiple odor molecules and the response information indicating the response of the olfactory receptor U200 to each of the multiple odor molecules, the conversion unit U12 converts the acquired output information into response information indicating the response of the olfactory receptor U200 using a machine learning-developed prediction model, with the output information output from multiple gas detection devices U100 for each of the multiple odor molecules as explanatory variables and the response information indicating the response of the olfactory receptor U200 to each of the multiple odor molecules as the objective variable.

[0157] The conversion unit U12 uses a predictive model trained with machine learning, where numerical, functional, spatial, or time-series indicators, or variables newly created through feature engineering, are used as explanatory variables, based on mathematical, statistical, or machine learning methods used to calculate the output information from the gas detection device U100. The conversion unit U12 also uses a predictive model trained with machine learning, where numerical, functional, spatial, or time-series indicators, or variables newly created through feature engineering, are used as the target variable, based on mathematical, statistical, or machine learning methods used to calculate the response information from the olfactory receptor U200. For example, the conversion unit U12 uses a predictive model trained with machine learning, where time-series data and the number of feature patterns of output information from multiple gas detection devices U100 are used as explanatory variables, and time-series data and the number of feature patterns of response information from multiple olfactory receptors U200 are used as the target variable, to convert the acquired output information into response information.

[0158] In this embodiment, the conversion unit U12 uses a predictive model trained with machine learning that uses the presence or absence of output information from multiple gas detection devices U100 as explanatory variables. In this embodiment, the conversion unit U12 also uses a predictive model trained with machine learning that uses the presence or absence of responses from multiple receptors contained in the olfactory receptor U200 as the objective variable. In this embodiment, the conversion unit U12 also uses a predictive model trained with machine learning that uses the mass charge and intensity of the output information output from the gas detection device U100 as explanatory variables. As a result, the conversion unit U12 converts the conversion voltage value, which is expressed as a voltage value, resistance value, current value, frequency change, or wavelength change of light, into response information that indicates the activation degree of the olfactory receptor U200.

[0159] The output unit U13 is implemented, for example, by the operation of the CPU. The output unit U13 outputs the converted response information. The output unit U13 outputs, for example, by displaying the response information. The output unit U13 outputs, for example, the activation level as a numerical value as response information.

[0160] Next, the program of this embodiment will be described.

[0161] Each component included in the conversion device U1 can be implemented by hardware, software, or a combination thereof. Here, implementation by software means that it is implemented by a computer loading and executing a program.

[0162] Programs can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memory (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (random access memory)). Display programs may also be supplied to a computer using various types of transient computer-readable media. Examples of transient computer-readable media include electrical signals, optical signals, and electromagnetic waves. Transitory computer-readable media can be supplied to a computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

[0163] Next, an embodiment of this design will be described. (Example 1)

[0164] An array sensor containing 400 olfactory receptors was used as the olfactory receptor U200. A predetermined odor was then exposed to olfactory receptor-expressing cells for a predetermined time. Odor concentrations ranging from 500 μM to 10 μM were used. Additionally, output information was acquired by exposing 12 types of gas detection devices U100 (gas sensors) to the predetermined odor for a predetermined time. This output information was then converted into response information using a conversion device U1. Furthermore, the activation level of cells expressing olfactory receptor U200 after exposure was measured.

[0165] Here, the odor molecules measured were hexyl acetate, hexyl butyrate, butyl butyrate, 2,7-octadienol, cis-2-penten-1-ol, toluene, beta-ionone, benzothiazole, cyclotene, acetic acid, coumarin, 1,2,4-trimethyl benzene, 2-ethylhexanol, propionaldehyde, 4-Isopropylphenol, Bis(methylthio)methane, 1,2,4,5-tetramethyl benzene, 3-methyl-1-butanol, E-2-nonenal, and m-cresol.

[0166] For data processing, Python was used as the language for the prediction model. Furthermore, the prediction model algorithms—random forest, support vector machine, and gradient-boosted decision tree—were evaluated. The prediction model itself was constructed using regression. Supervised learning was used for training. Model evaluation was primarily performed using the coefficient of determination.

[0167] When using regression with the random forest method, as shown in Figure 9, with the predicted values ​​(response information) output from the prediction model on the vertical axis and the actual values ​​of the dependent variable (activation level of olfactory receptor U200 expressing cells) on the vertical axis, we were able to obtain a regression coefficient of determination of 0.834 (maximum of 1.0).

[0168] When using regression with a support vector machine, a regression coefficient of determination of 0.871 was obtained, as shown in Figure 10. Furthermore, when using regression with a gradient-boosted decision tree, a regression coefficient of determination of 0.847 was obtained, as shown in Figure 11. This indicates that the predicted values ​​have a sufficient correlation with the actual values ​​of the dependent variable. In other words, it was found that the output information can be quantified.

[0169] (Example 2)

[0170] A model was created that learns sensor data for a particular odor molecule and predicts the olfactory receptor U200 that responds and its activation level. The experimental conditions and procedure for the gas detection device U100 and the olfactory receptor U200 cell array sensor were the same as in Example 1. Classification was used for data processing. Python was used as the programming language. A neural network was used as the algorithm. A classification model was created to correlate the output information of the gas detection device U100 with the response information of the olfactory receptor U200. Supervised learning was used for training. The number of hidden layers is not specified, but in this example, two layers were used. Model evaluation was performed using the overall accuracy and the loss function. The output information from the gas detection device U100 was used as the explanatory variable, and the response information indicating the response of the olfactory receptor U200 was used as the dependent variable.

[0171] As shown in Figure 12, after approximately 500 training iterations, the prediction accuracy remained high at around 0.9, and the loss remained low at around 0.3. Therefore, we were able to create the aforementioned prediction model.

[0172] As described above, the conversion device U1, conversion information production method, and program according to the first embodiment provide the following effects.

[0173] (1) The conversion device U1 is a conversion layer that converts output information output from a predetermined gas detection device U100 for a predetermined odor molecule into response information indicating the response of an olfactory receptor U200. The conversion layer includes an output information acquisition unit U11 that acquires output information output from a predetermined gas detection device U100 for a predetermined odor molecule, a conversion unit U12 that converts the acquired output information into response information based on the output signals output from multiple gas detection devices U100 for each of the multiple odor molecules and the response information indicating the response of an olfactory receptor U200 for each of the multiple odor molecules, and an output unit U13 that outputs the converted response information. This makes it possible to convert output information obtained from various gas detection devices U100 into one type of response information and output it. Therefore, correlations between gas detection devices U100 can be taken.

[0174] (2) The conversion unit U12 uses output information from multiple gas detection devices U100 for each of the multiple odor molecules as explanatory variables, and response information indicating the response of olfactory receptors U200 to each of the multiple odor molecules as the objective variable. Using a machine learning-developed prediction model, the acquired output information is converted into response information indicating the response of olfactory receptors U200. By using machine learning, the conversion accuracy can be further improved.

[0175] (3) The conversion unit U12 uses a predictive model trained on machine learning, which uses numerical, functional, spatial or time-series indicators, or variables newly created by feature engineering, calculated using mathematical, statistical, or machine learning methods from the output information output from the gas detection device U100, as explanatory variables. This improves the conversion accuracy.

[0176] (4) The conversion unit U12 uses a predictive model trained on machine learning, with a target variable being a numerical, functional, spatial or time-series index, or a variable newly created by feature engineering, which is calculated using mathematical, statistical, or machine learning methods for the response information of the olfactory receptor U200. This improves the conversion accuracy.

[0177] (5) The conversion unit U12 uses a machine learning-developed prediction model, with the time-series data and number of feature patterns of output information output from multiple gas detection devices U100 as explanatory variables and the time-series data and number of feature patterns of response information from multiple olfactory receptors U200 as the target variable, to convert the acquired output information into response information. This improves the conversion accuracy.

[0178] (6) The conversion unit U12 uses a predictive model trained with machine learning, which uses the presence or absence of output information from multiple gas detection devices U100 as explanatory variables. This improves the conversion accuracy.

[0179] (7) The conversion unit U12 uses a predictive model trained on machine learning, with the presence or absence of responses from multiple receptors included in the olfactory receptor U200 as the target variable. This improves the conversion accuracy.

[0180] (Third embodiment)

[0181] Next, a prediction model creation apparatus U2, a prediction model creation method, and a program according to the third embodiment of the present invention will be described with reference to Figure 13. In describing the third embodiment, the same reference numerals are used for components that are the same as those in the previously described embodiments, and their descriptions are omitted or simplified.

[0182] The predictive model creation apparatus U2, predictive model creation method, and program according to the third embodiment are an apparatus, method, and program for creating a predictive model according to the first embodiment.

[0183] The predictive model creation device U2 creates a predictive model that converts the output information from the gas detection device U100 into quantified data for a given odor molecule. As shown in Figure 13, the predictive model creation device U2 comprises an explanatory variable acquisition unit U21, an objective variable acquisition unit U22, and a predictive model creation unit U23.

[0184] The explanatory variable acquisition unit U21 is implemented, for example, by the operation of the CPU. The explanatory variable acquisition unit U21 acquires output information from multiple gas detection devices U100 for each of multiple odor molecules as explanatory variables. The explanatory variable acquisition unit U21 may output information such as the sum of the outputs of multiple gas detection devices U100 (e.g., 20 types), the average value, presence or absence of reaction, various indicators, the product of the output feature quantity and the number of gas detection devices U100, the product of time series data, the number of feature quantity patterns and the number of gas detection devices U100, etc.

[0185] The target variable acquisition unit U22 is implemented, for example, by the operation of the CPU. The target variable acquisition unit U22 acquires response information as the target variable, which shows the response of the olfactory receptor U200 to each of multiple odor molecules. The target variable acquisition unit U22 may output information such as the total value of the output of the olfactory receptor U200 (e.g., 400 spots), the average value, presence or absence of response, various indicators, the product of the output feature quantity and the number of spots of the olfactory receptor U200, the product of the time series data, the number of feature quantity patterns, and the number of spots of the olfactory receptor U200, etc.

[0186] The predictive model creation unit U23 is implemented, for example, by the operation of the CPU. The predictive model creation unit U23 creates a predictive model by using the acquired explanatory variables and the acquired target variable in machine learning. The predictive model creation unit U23 creates the predictive model using correlation coefficients, principal factor analysis, logistic regression, etc.

[0187] Next, we will explain the operation of the predictive model creation device U2 (the method for creating predictive models).

[0188] First, the explanatory variable acquisition unit U21 acquires output information as explanatory variables. Next, the target variable acquisition unit U22 acquires response information as the target variable. Then, the prediction model creation unit U23 creates a prediction model using the explanatory variables and the target variable.

[0189] Next, the program of this embodiment will be described.

[0190] Each component included in the predictive model creation device U2 can be implemented by hardware, software, or a combination thereof. Here, implementation by software means that it is implemented by a computer loading and executing a program.

[0191] Programs can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memory (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (random access memory)). Display programs may also be supplied to a computer using various types of transient computer-readable media. Examples of transient computer-readable media include electrical signals, optical signals, and electromagnetic waves. Transitory computer-readable media can be supplied to a computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

[0192] As described above, the predictive model creation apparatus U2, predictive model creation method, and program according to the third embodiment provide the following effects. (7) A prediction model creation device U2 for creating a prediction model that converts output information output from a gas detection device U100 for a predetermined odor molecule into quantified data, comprising: an explanatory variable acquisition unit U21 that acquires output information output from multiple gas detection devices U100 for each of multiple odor molecules as explanatory variables; an objective variable acquisition unit U22 that acquires response information showing the response of olfactory receptors U200 to each of the multiple odor molecules as an objective variable; and a prediction model creation unit U23 that creates a prediction model by using the acquired explanatory variables and the acquired objective variable in machine learning. This makes it possible to create a prediction model that converts output information obtained from various gas detection devices U100 into response information and outputs it. Since the output information can be quantified by converting it into response information, a conversion device U1 that can correlate gas detection devices U100 can be configured.

[0193] (Fourth Embodiment)

[0194] Next, the conversion device U1, the conversion information creation method, and the program according to the fourth embodiment of the present invention will be described with reference to Figures 14 and 15. In describing the fourth embodiment, the same reference numerals are used for components that are the same as those in the previously described embodiments, and their descriptions are omitted or simplified.

[0195] The conversion device U1 according to the fourth embodiment differs from the first and third embodiments in that it uses a mass spectrometer (gas chromatograph-mass spectrometer) as the gas detection device U100. Furthermore, the conversion device U1 according to the fourth embodiment differs from the first and third embodiments in that it uses the output of the gas detection device U100 (mass spectrometer) as output information. The conversion device U1 according to the fourth embodiment acquires a set of intensity plots against mass charge output from the gas detection device U100 as output information. For example, the conversion device U1 acquires a set of intensity plots against mass charge obtained as a result of detecting a gaseous compound by the gas detection device U100 as output information. That is, the conversion device U1 acquires data of the mass charge (including noise) of fragment ions generated when gas molecules are ionized, prior to the process of identifying the molecular structure of the gaseous compound by the gas detection device U100, as output information. The conversion device U1 also converts the output information into response information of the olfactory receptor U200 using a predictive model that uses the mass charge data (including noise) as explanatory variables. As a result, the conversion device U1 converts the output information into olfactory receptor response information, regardless of the characteristics of the different devices, using the gas detection device U100. Note that the gas detection device U100 may be a device for collection, measurement, and analysis, not limited to detection.

[0196] Next, an embodiment of the fourth embodiment will be described. (Example 3)

[0197] The data acquisition method for the gas detection device U100 involved diluting the odor molecule solution 10,000 times with a solvent, then collecting 1 μL with a syringe and introducing it into the gas detection device U100. The mass-charge data for each molecular species obtained during detection was used for conversion. The experimental conditions and procedure for the olfactory receptor cell array sensor were the same as in Example 1.

[0198] For data processing, a model was created using random forest regression, similar to Example 1. Python was used as the programming language. Supervised learning was employed. The coefficient of determination was used for model evaluation. As shown in Figure 14, the mass charge data acquired by the gas detector U100 was graphed, and the intensity of each pixel in the image was read. The read data was used as output information. The output information from the gas detector U100 (mass spectrometer) was used as the explanatory variable, and the response information showing the response of the olfactory receptor U200 was used as the dependent variable.

[0199] As a result, as shown in Figure 15, with the predicted value (response information) output from the prediction model on the vertical axis and the actual value of the dependent variable (activation level of olfactory receptor U200 expressing cells) on the vertical axis, we were able to obtain a regression coefficient of 0.828.

[0200] As described above, the prediction model creation apparatus U2, prediction model creation method, and program according to the fourth embodiment provide the following effects. (8) The conversion unit U12, as the gas detection device U100, uses the output signal of the mass spectrometer as output information. This allows the mass spectrometer to also correlate the output information with the gas detection devices U100 by converting it into response information. In particular, by using the mass charge data (including noise) as output information, the conversion unit U12 can shorten the time from the collection of gaseous compounds to the conversion into response information showing the response of the olfactory receptor U200 compared to using data after the molecular structure has been identified as output information. Furthermore, since it uses data that is closer to the data after detection (raw data) compared to using data after the molecular structure has been identified as output information, it is possible to provide a conversion device U1 with a higher coefficient of determination (higher accuracy).

[0201] Although preferred embodiments of the conversion device, predictive model creation device, conversion information creation method, predictive model creation method, and program of the present invention have been described above, this disclosure is not limited to the embodiments described above and can be modified as appropriate.

[0202] For example, in the fourth embodiment described above, a gas chromatography-mass spectrometer was used as the gas detection device U100, but it is not limited to this. The gas detection device U100 may be a device that does not have gas chromatography. The gas detection device U100 may also be a direct ionization mass spectrometer (DART-MS). The gas detection device U100 may also be an atmospheric pressure mass spectrometer that performs analysis at atmospheric pressure.

[0203] Furthermore, although the above embodiment states that the conversion unit U12 performs the conversion using a machine learning-based predictive model, it is not limited to this. The conversion unit U12 may perform the conversion without using a machine learning-based predictive model.

[0204] (Third embodiment)

[0205] Figures 16A and 16B are system configuration diagrams illustrating the overview of the third embodiment.

[0206] The third embodiment, as shown in Figures 16A and 16B, illustrates a system for economically protecting information such as scent and enabling transactions.

[0207] In other words, when reproducing odors using a device (e.g., a sprayer) based on the technology of Embodiment 1 or 2, there is a risk of failing to reproduce the desired odor. One reason for this is that, for example, data tampering is easy when reproducing odor information.

[0208] Furthermore, when trading products related to scents, it was difficult to prove their uniqueness and the consistency of transaction history because scents are intangible.

[0209] Therefore, in Embodiment 3, by authenticating scent information using blockchain and non-fungible tokens (NFTs), it becomes possible to prove the "uniqueness of the scent" in the sense described later, improving the difficulty of tampering and enabling the reproduction of the desired scent.

[0210] Furthermore, by defining conditions such as a usage limit in the NFT contract, it is possible to virtually create an "empty" state where the relevant scent information has been used up.

[0211] This means, for example, that it becomes possible to virtually recreate a situation in the real world where a perfume bottle has been used a certain number of times after purchase. The conditions defined within the contract can be not limited to the maximum number of uses, but also include the duration of the scent or the effective range of the scent.

[0212] Furthermore, defining the duration and the valid range within which reproduction processing is permitted will stimulate scent-based communication within the virtual space. For example, if a third party's avatar is assigned a scent code, the scent will be reproduced based on the contract, allowing the user to perceive the scent assigned to that avatar.

[0213] Here, an NFT is a unique token issued and managed on a designated blockchain, which can prove the uniqueness of the digital data it is associated with.

[0214] In subsequent embodiments, including this embodiment, the target for issuing NFTs is described using scent information (digital scent information; scent code) as an example, but it is not limited to this, and for example, it may be taste information (digital taste information; taste code). In other words, the reproduction and management of a target scent can be replaced with the reproduction and management of a target taste.

[0215] One example of what can be used to issue NFTs is the scent of perfume.

[0216] In this case, the party requesting the issuance of an NFT for the scent information would be, for example, the "author (corporation or individual)."

[0217] Of course, strictly speaking in Japan, a "work of authorship" is defined as "an original expression of thoughts or feelings that falls within the scope of literature, scholarship, art, or music." In other countries, it is currently impossible to say definitively whether "information," particularly "information about smells," corresponds to a "work of authorship" under conventional law.

[0218] Therefore, in this specification, the original owner who initially generates and possesses the scent and taste information will be referred to as the "author of the scent and taste information." Furthermore, a person who creates the scent and taste information by adjusting the scent and taste information provided by the "original author" will be referred to as the "derivative author," equivalent to the "author of a derivative work." As will be described later, the "original author" is recorded in the NFT, and both the "original author" and the "derivative author" may also be recorded within the NFT, with sales revenue and commission income being distributed according to the agreement.

[0219] Therefore, in the case of perfume, the "author" could be, for example, the person who designed the composition of the perfume (typically the perfume manufacturer), or the person who generated the scent information for the perfume (or the person who manages the scent information for the perfume).

[0220] The following explanation uses the case of handling olfactory information as an example. However, a similar structure can be used when handling taste information.

[0221] With a configuration like the one described here, the following configuration can be achieved.

[0222] 1) When playing a "scent" on a playback device, the ownership of the "scent information" is verified as legitimate by an NFT stored within the blockchain.

[0223] Conversely, NFTs are used because the ownership of "scent information" can be changed (it can be bought and sold). The significance lies in the circulation of "scent information," which in turn allows the original owner to gain profits with real value. NFTs are managed by blockchain and are used from the perspective of "proof of ownership" as they cannot be tampered with.

[0224] 2) The "scent information" is preferably converted into an "scent code" of an N-dimensional code (more preferably a 2-dimensional code) and traded.

[0225] 3) The "scent code" is, in principle, delivered from the "management server" to the playback device each time playback is performed.

[0226] 4) For playback on a playback device, the NFT owner must send a usage request from the playback device to the "author of the scent (original holder)," and the blockchain must authenticate that the sender of the usage request is the NFT owner. A usage fee will then be paid in cryptocurrency each time.

[0227] The "author (original holder) of the scent" will be able to monitor how the scent information is being used. Furthermore, they can set usage conditions (maximum number of uses, maximum usage time) for the "use of the scent information." In addition, the "author (original holder) of the scent" can collect a usage fee each time the "scent information is used."

[0228] 5) However, the NFT owner does not necessarily need to own the playback device itself; it is also possible to play it from someone else's playback device.

[0229] In other words, the "scent information (scent code)" itself can be distributed to others independently (it may even be reproducible).

[0230] Even in that case, the NFT owner must designate a playback device owned by another person as the recipient of the "scent code," send a usage request to the "author of the scent (original owner)," and the blockchain must authenticate that the sender of the usage request is the NFT owner.

[0231] Note that the hardware configuration of the servers, devices, etc. shown in Figures 16A and 16B is basically the same as the hardware configuration shown in Figure 4, so a detailed explanation is omitted.

[0232] In Figures 16A and 16B, the information processor server 2000 is a server that receives scent materials or raw materials and performs the task of converting them into scent codes, and has basically the same configuration as server 1 described in Figure 5. Furthermore, the server (management server) 3000 according to the third embodiment is an information processing device that performs blockchain management of scent information.

[0233] Here, Figure 17 is a functional block diagram illustrating the functional configuration of the management server 3000.

[0234] Furthermore, in the CPU 3040 of server 3000, as will be described later, when operating by a program stored in memory, the request reception module (hereinafter, "request reception MD") 3041 and the NFT authentication module (hereinafter, "NFT authentication processing MD") 3043, etc., which verify authentication etc. for NFTs associated with the scent code, are in operation.

[0235] Request reception MD3041 receives requests from owners of NFTs related to specific scent information managed on the blockchain, to use the scent information.

[0236] The NFT authentication process MD3043 authenticates NFTs related to scent information, thereby proving the uniqueness of the scent information or verifying the integrity of the transaction history.

[0237] Referring to Figure 17, the management server 3000 includes a network communication unit 3300 for exchanging data with the terminal 1000 of the original copyright holder HA of the scent information, the information processor server 2000, and the blockchain BC via the network N, an input / output interface (hereinafter referred to as input / output I / F) 3090 for taking data into the server or outputting data from the server between the network communication unit 3300 and the other, a computing unit 3040, and a non-volatile storage device 3080.

[0238] The arithmetic unit 3040 performs the functions of a request receiving module (hereinafter referred to as a request receiving MD) 3041 for registering and editing information in the odor code database (hereinafter referred to as the odor code DB) 3082 stored in the non-volatile memory device 3080, and an NFT issuance processing module (hereinafter referred to as the NFT issuance processing MD) 3042 for registering and editing information in the odor code DB 3082 and the author information database (hereinafter referred to as the author information DB) 3083 stored in the non-volatile memory device 3080, and for issuing NFTs to the blockchain BC.

[0239] The computing unit 3040 further executes the following functions: an NFT authentication processing module (hereinafter referred to as NFT authentication processing MD) 3043 for verifying the legitimacy of a usage request received by the request reception MD 3041 by requesting authentication of the legitimacy of the usage request from the blockchain BC; an NFT update processing module (hereinafter referred to as NFT update processing MD) 3044 for issuing an NFT update transaction to the blockchain BC when the scent spraying device 3 for content playback processes the scent code; and a scent code distribution processing module (hereinafter referred to as scent code distribution processing MD) 3045 for distributing the corresponding scent code from the scent code DB) 3082 to the content playback device of the scent spraying device 3 when the legitimacy of the usage request is verified by the NFT authentication processing MD 3043. As described later, the information processing module (hereinafter referred to as information processing MD) 3046 performs training processing of an artificial intelligence model based on the data stored in the training data DB 3084, which is stored in the non-volatile memory device 3080, and also performs processing using the generated trained model.

[0240] The hardware configuration of the management server 3000 is basically the same as that shown in Figure 4, so we will not repeat the explanation.

[0241] The main components of the management server 3000 consist of computer hardware and software executed by the CPU 11. Generally, such software is stored on a storage medium and distributed, or distributed via a network, retrieved via a disk drive 20 or network communication unit 19, and temporarily stored in a storage unit 18, which is composed of an SSD or the like. It is then read from the storage unit 18 into RAM 13 in memory and executed by the CPU 11. In the case of a network connection, the software may be loaded directly into RAM and executed without being stored in the storage unit 18.

[0242] The arithmetic unit 3040 is a CPU, which may be a single-core processor or a multi-core processor. That is, it may be a single-core processor or a multi-core processor.

[0243] As an example of using NFTs to manage scent information, the aforementioned perfume scent can be managed in real space or virtual space (metaverse).

[0244] In the real world, for example, when emitting a scent corresponding to a specific perfume from a designated emitter (device), it can be used to determine whether the scent of the perfume belongs to the rightful author or whether the user has the right to use the scent of the perfume.

[0245] In a virtual space, for example, when a user's avatar purchases a certain perfume within the virtual space, it can be used, as described above, to determine whether the scent of the perfume belongs to the legitimate author or whether the user's avatar has the right to use the scent of the perfume.

[0246] It should be noted that the term "virtual space" is a broad concept that also includes VR (Virtual Reality) and AR (Augmented Reality).

[0247] It should be noted that this differs from the embodiments described above in that it is not essential to use receptor response information related to odors as odor information. In other words, the odor information is not limited to the presence or absence of the aforementioned receptor response information; it is sufficient to have the information necessary to generate an odor.

[0248] In other words, odor information generated using electrical sensors or the results of sensory evaluations conducted by humans may be used, without using receptor response information based on odor.

[0249] Furthermore, odor information may be managed in a predetermined format.

[0250] Here, "uniqueness of scent" includes not only demonstrating the legitimate ownership of the "scent information" managed using the aforementioned NFTs, but also demonstrating the uniqueness of the scent itself.

[0251] In other words, while considering the "uniqueness of scent itself" is important because the economic value of a scent is considered to be significant in the fact that "it is perceived as the same scent by the person perceiving it," there has traditionally been no objective way to define "human perception of scent."

[0252] The following explains the advantages of proving the uniqueness of the scent itself.

[0253] Traditionally, the uniqueness of a scent itself has been proven by defining the scent based on the components of the odorant.

[0254] However, in this case, it was difficult to eliminate counterfeit perfumes that imitated the aforementioned perfume. That is, counterfeit perfumes, created by slightly altering the amount or ratio of the ingredients in the original perfume, cannot be eliminated by means of patent rights, for example, because their ingredients differ from the original perfume. Furthermore, if the changes in ingredients are minute, it is difficult for users to perceive the difference when smelling the perfume, making it difficult to distinguish between the two.

[0255] Therefore, as described above, by appropriately managing odor information (receptor response information) on the blockchain using NFTs, it becomes possible to determine whether an odor detected and analyzed using an olfactory receptor sensor is identical to an odor managed using NFTs, regardless of the odor components.

[0256] In other words, the uniqueness of a scent can be verified using blockchain and NFTs. This allows for actions such as claiming copyright infringement of NFTs.

[0257] Thus, by standardizing (absolute reference) the smell based on the receptor response pattern, even if the smell is composed of other substances (e.g., perfume), uniqueness can be ensured based on the same result (how humans feel).

[0258] In general, NFTs contain identifiers to indicate uniqueness. Therefore, one "smell information" corresponds to "the same smell" (e.g., the same type of perfume). Each may be distinguished by an identifier. The smell code is an N-dimensional code representing smell information. (The same applies to taste information.)

[0259] This "identifier" corresponds to the token ID of the NFT.

[0260] Although not particularly limited, the identifier can be configured, for example, as follows. Token ID: (Smell identification code) + (Identification number within the same smell)

[0261] Here, the "(identification number within the same smell)" corresponds to, for example, the "edition number" when there is an upper limit set for the number of prints in the case of prints. With such a configuration, it is also possible to increase the rarity value of the "smell information (code)".

[0262] Also, the above-mentioned "uniqueness of smell" may mean that for the "smell information (code)" associated with the NFT, it is proven that the "smell information (code)" is generated by the legitimate original author through the electronic signature of the private key corresponding to the "account number" ( = public key of the "original author") recorded in the NFT.

[0263] The external-owned account (address) of the original author can be identified from the public key of the "original author". The NFT can also manage the "uniqueness of the smell itself". For example, by product name or token ID.

[0264] "Consistency of the transaction history of scent information" means that the information of the current owner managed by the NFT and the transaction history based on transaction data managed on the blockchain are consistent, and that the current owner is the legitimate owner.

[0265] The legitimacy of using scent or taste information means that the following conditions are met: "uniqueness of the scent" and "consistency in the transaction history of the scent information."

[0266] Figure 18 shows a first example of a transaction of scent code (scent information) using a blockchain and non-fungible tokens (NFTs) according to the third embodiment.

[0267] Figure 18 shows an example where a management server manages the wallet, but a separate wallet may be provided for each owner's device. Also, in the figure, Device A refers collectively to the content playback device and the scent spraying device.

[0268] Specifically, in cases where a wallet is created for each owner's device, for example, a wallet is created for each of the one or more users who have acquired (purchased, transferred, etc.) the right to use the perfume scent. The address of that wallet is then managed on the blockchain as the address of the owner of the nonfungible token (NFT). In this case, the owner of the right to use the perfume scent is managed as the owner of the nonfungible token (NFT).

[0269] Referring to Figures 16A, 16B, and 18, when the management server 3000 manages the wallet, for example, a wallet is created associated with the person who generated the perfume scent information (or the person who manages the perfume scent information: the author (original holder)). The address of this wallet (hereinafter referred to as AAA) is then managed on the blockchain as the address of the owner of the nonfungible token (NFT). Furthermore, information about the owner of the right to use the perfume scent is managed as metadata and content data linked to the nonfungible token (NFT) using distributed storage such as IPFS (InterPlanetary File System) located outside the blockchain. Alternatively, information about the owner of the right to use the perfume scent may be managed on the blockchain as information other than that of the owner of the nonfungible token (NFT).

[0270] In this specification, the owner of a non-fungible token (NFT) and the owner of the right to use the perfume scent are described as essentially the same person. However, for example, the owner of the right to use the non-fungible token may be managed independently of the NFT owner.

[0271] Figure 19 shows a second example of a transaction of scent code (scent information) using blockchain and non-fungible tokens (NFTs) according to the third embodiment.

[0272] In the example shown in Figure 19, in addition to what is shown in Figure 18, a smart contract (SC) is used to reference NFTs and automatically perform history updates, etc.

[0273] Figures 20A and 20B show the configuration of a system for managing NFTs using smart contracts.

[0274] Smart contracts are implemented on the blockchain BC to automatically execute protocols in accordance with the received contract terms. The smart contracts according to this embodiment are implemented on the blockchain BC, for example, by an administrator.

[0275] A smart contract consists of a computer program implemented on the computer network that constitutes the blockchain BC. The computer program is executed on the computer network that makes up the blockchain BC. The computer program has program code that defines its operation as a smart contract. The smart contract operates when the computer program is executed on the computer network that makes up the blockchain BC. The smart contract is stored in an address (contract address) on the blockchain BC.

[0276] Figures 21A and 20B show the workflow for managing NFTs using smart contracts.

[0277] NFTs have a unique identifier (NFT-ID) to distinguish them from other NFTs. However, fungible tokens like "Ether," the internal currency of Ethereum, do not have an identifier like an NFT-ID because they have the same value as other fungible tokens and do not need to be distinguished.

[0278] NFTs, like fungible tokens, are tradable on the blockchain BC. NFT transaction history is recorded on the blockchain BC. The blockchain BC also records the NFT owner and ownership history.

[0279] An NFT is, for example, a token issued in accordance with the Ethereum Request for Comments (ERC) 721 standard. An NFT compliant with the ERC721 standard is called an NFT-721 token. In this embodiment, as an example, the NFT will be described as being an NFT-721 token.

[0280] The NFT71 can be traded (ownership changed), has its own value, and since its owner and transaction history are recorded on the blockchain BC, it is effective as collateral. Moreover, since the NFT is managed on the blockchain BC, there is no risk of it being a counterfeit or stolen item.

[0281] In the embodiment, the NFT is used as a certificate (certificate NFT) to prove the owner of the scent code.

[0282] Therefore, referring to FIGS. 21A and 20B, first, as a premise, it is assumed that the author of the scent provides the source of the scent (for example, the actual perfume) that is the source of the scent information to the operator of the information processor server 2000.

[0283] Then, when a request for encoding of scent information is transmitted from the author terminal 1000 to the information processor server 2000 (S1010), the information processor server 2000 authenticates that the sender is the author and then generates a code for the scent information (S1012).

[0284] The management server 3000 receives the scent information code (scent code) from the information processor server 2000 (S1014), issues a receipt notice of the scent code to the author terminal 1000 (S1016), and when the author terminal 1000 confirms the receipt of the scent code (S1016), requests the management server 3000 to issue an NFT, and the management server 3000 executes an NFT issuance process for the blockchain BC (S1020).

[0285] On the blockchain BC, the issuance of the NFT is recorded by a smart contract (S1022).

[0286] Furthermore, the aforementioned "certificate NFTs" can be traded (ownership changed) just like regular NFTs. Owners can buy and sell certificate NFTs, for example, on the NFT open market.

[0287] As shown in Figure 20A, blockchains such as Ethereum have addresses AD01, AD02, and AD03 that manage tokens (crypto assets) such as fungible tokens and NFTs. These addresses AD01, AD02, and AD03 are called Ethereum addresses in the context of Ethereum.

[0288] The addresses AD01, AD02, and AD03, used to manage tokens, are also user accounts on the blockchain BC. Each of these addresses (accounts) on the blockchain BC is associated with a fungible token or NFT owned by the user.

[0289] In the blockchain BC, examples of addresses include AD01, the address of HA, the original author of the scent code; AD02, the address of HB, the transferee of ownership; and AD03, the address of the administrator of the management server. Transactions (transfers) of fungible tokens or NFTs take place between these addresses.

[0290] The administrator is the person who manages NFT transactions and updates, and has the address AD03 (administrator account).

[0291] Users HA and HB can access the tokens associated with their respective addresses AD01 and AD02 via a wallet application running on their respective devices. User HA's device may be, for example, a smartphone, tablet, or personal computer. User HB's device may also be a smartphone, tablet, or personal computer, or a content playback device connected to the scent spraying device 3 may function as a device. Users HA and HB can use the wallet application to perform token-related operations, such as trading tokens associated with their respective addresses AD01 and AD02 (e.g., sending internal currency, changing ownership).

[0292] The following describes the process for changing ownership.

[0293] Referring again to Figures 21A and 20B, when the content playback device RE connected to the scent regeneration spraying device 3 requests a change of ownership via a smart contract (S1030), the management device that receives the request issues a sale transaction via a smart contract (S1032).

[0294] In blockchain BC, a smart contract executes a change of ownership upon receiving a sale transaction (S1034).

[0295] Figure 22 shows a transaction when an NFT according to the third embodiment is sold.

[0296] Figure 22 illustrates a case where the owner of a scent code changes from the author of account number AAA to the owner of account number BBB.

[0297] Referring to Figures 20A, 20B, and 22, before sale, the NFT records "Account Number: AAA", "Product Name: XXX", "Owner (and Possessions) Account Number: AAA", and balance information "Balance: 0 ETH" (the unit of the internal currency Ether is represented in ETH).

[0298] Here, "account number" is the public key assigned to the account, which is generated from the private key by the wallet application. The account address is generated from the public key through a predetermined procedure (conversion using a predetermined hash function).

[0299] Figure 22 shows an operation related to NFTs, for example, in which the transferee HB (account number BBB: externally owned account) sends a sale transaction to the management server 3000 to the author HA (account number: AAA), thereby rewriting the NFT record, which currently lists author HA (account number: AAA: externally owned account) as the owner, to list the transferee HB as the owner.

[0300] The sale transaction will be sent from the transferee HB (account number BBB) to the author HA (account number AAA), with a transaction fee of 10 ETH and a transfer price of 100 ETH listed in the transaction details.

[0301] As a result of the sale transaction, the owner of a certain scent code (product name: XXX) has been changed to the transferee HB (account number BBB), and the balance of the author HA (account number: AAA) has increased by 100 ETH.

[0302] The execution of a sale transaction is not particularly limited, but if it is an Ethereum smart contract, it will be executed as a decentralized application program on blockchain BC. As for the consensus algorithm, which node among nodes 400.1 to 400.M on blockchain BC will obtain the right to generate a new block may be determined by the POS (Proof of Stake) method, or another smart contract method, such as the POW (Proof of Work) method, may be adopted.

[0303] Author HA's terminal 1000 is a terminal that requests the issuance of an NFT regarding the scent code. Author HA's terminal 1000 consists of a computer equipped with a processor and memory connected to the processor. Computer programs are stored in the memory. Computer programs are executed by the processor.

[0304] The management server 3000 can obtain information (NFT information) regarding NFTs requested from author HA's terminal 100 via the network. NFT information is, for example, a scent code associated with the NFT and stored in blockchain BC. Alternatively, the scent code may be stored in IPFS as NFT information.

[0305] Next, we will describe the configuration of the odor regeneration process in the "odor regeneration device," such as the odor spraying device 3.

[0306] Figure 23 is a flowchart showing the process for actively reproducing odors according to the third embodiment.

[0307] Referring to Figures 21A, 20B, and 23, a cartridge for regenerating scents is installed in the spraying device connected to the content playback device RE (S1040), and the content playback device RE reads the information stored in the cartridge's memory (S1042). Here, the cartridge's memory is a non-volatile memory such as flash memory.

[0308] While not limited to these, the cartridge may be "restricted" or the contents of the "scent code" may be changed as appropriate depending on the information on the cartridge (such as the time elapsed since initial use or the number of times it has been played).

[0309] For example, the release control unit may restrict use when the usage limit is reached based on the number of uses since the initial use of cartridge CA, which is stored in the cartridge's memory, or when the usage limit is reached based on the usage time stored in the memory. Furthermore, if a predetermined number of days (e.g., six months) have elapsed since the start of use of cartridge CA (e.g., at the time of manufacture, installation, or initial use), the release control unit may alert the user that the cartridge CA has deteriorated over time, output a message prompting the user to replace cartridge CA, or restrict the use of the fragrance spraying device 3. Alternatively, the release control unit may adjust the release information according to the usage status of cartridge CA. For example, when using a cartridge that has been in use for a predetermined period, the release control unit may spray more fragrance from cartridge CA than usual or extend the spraying time.

[0310] For example, when a user issues a drive request to the content playback device RE via a button, remote control, or instruction from another computer (S1044), the management server 3000 requests blockchain BC to verify the authentication of the user who issued the drive request by referencing the NFT (S1046).

[0311] While not particularly limited, for example, the playback device RE encrypts data such as information about the scent code and the contents of the NFT using its own private key, creates an electronic signature, and sends it to the management server 3000.

[0312] In Blockchain BC, NFTs and smart contracts are used to authenticate that the requester of an authentication request is the owner of the NFT based on an electronic signature (S1048-1), compare it with the contents of the NFT recorded in Blockchain BC (S1048-2), and send a reply to the management server 3000.

[0313] When the management server 3000 confirms that the owner of the "scent code" requested by blockchain BC and the owner's transaction history have been authenticated (S1050-1), it performs the authentication process (S1050-2) and sends (distributes) the requested scent code to the playback device RE (S1052).

[0314] When the regeneration device RE receives a scent code, it reads the code (S1054-1), drives the device, and performs the scent regeneration process (S1054-2). Although not particularly limited, for example, the regeneration time per request may be limited to a predetermined time.

[0315] Once the odor regeneration process is complete, the regeneration device RE sends an update request for the NFT content, along with an electronic signature, to the management server 3000 (S1056). This requests an update to the cumulative regeneration count or cumulative regeneration time recorded in the NFT.

[0316] The management server 3000 issues an update transaction for the smart contract to the blockchain BC (S1058), and the blockchain BC verifies the digital signature (S1060-1), records the update transaction data (S1060-2), and performs the update process for the NFT state data (S1060-3).

[0317] Figure 24 shows a first example of a transaction when using the odor reproduction device according to the third embodiment.

[0318] The first example of a transaction shows that the owner of the smell code is the owner of account number BBB, and that the usage count is updated.

[0319] Referring to Figure 24, before the update, the NFT recorded "Account Number: AAA", "Product Name: XXX", "Owner (and Possessions) Account Number: BBB", balance information ("Balance: 0 ETH"), and "Number of Uses: 100".

[0320] The update transaction is sent from owner HB (account number BBB) to author HA (account number: AAA), with a transaction fee of 10 ETH and an update fee of 0.01 ETH listed in the transaction details.

[0321] The execution of the update transaction changes the balance recorded in the NFT for a certain scent code (product name: XXX) to "Balance: 0.01 ETH," and the number of uses decreases to 99.

[0322] Here, the execution of update transactions is not particularly limited, but if it is an Ethereum smart contract, it will be executed as a distributed application program on blockchain BC. As for the consensus algorithm, which node among nodes 400.1 to 400.M on blockchain BC will obtain the right to generate a new block may be determined by the POS (Proof of Stake) method, or another smart contract method, such as the POW (Proof of Work) method, may be adopted.

[0323] Figure 25 shows a second example of a transaction when using the odor reproduction device according to the third embodiment.

[0324] In Figure 25, compared to the configuration described in Figure 24, the number of available uses is updated by a smart contract, and the available data is not recorded within the NFT itself, but only within the state data.

[0325] Figure 26 shows a third example of a transaction when using the odor reproduction device according to the third embodiment.

[0326] In Figure 26, compared to the configuration described in Figure 25, the number of available uses is updated by a smart contract, and the usage time is executed as a function of the smart contract. After use, the number of available uses becomes 99, and the usage time of 1 hour is recorded. The available data and usage time are not recorded within the NFT itself, but only within the state data.

[0327] The regeneration device RE can be configured so that odor regeneration is not performed after the usage time exceeds a predetermined period.

[0328] Figure 27 shows a fourth example of a transaction when using the odor regeneration device RE according to the third embodiment.

[0329] In Figure 26, compared to the configuration described in Figure 25, the number of available uses is updated by the smart contract, and the validity period is executed as a function of the smart contract. After use, the number of available uses is recorded as 99, and the validity period is recorded as changing from 1000 hours to 999 hours. The available use data and validity period are not recorded within the NFT, but only within the state data.

[0330] After the effective duration has elapsed, the regeneration device RE can be configured not to regenerate the odor.

[0331] Figure 28 shows a third example of a transaction of scent code (scent information) using blockchain and non-fungible tokens (NFTs) according to the third embodiment.

[0332] In Figure 28, as mentioned above, authors include, for example, the person who developed the composition of the perfume (typically a perfume manufacturer) or the person who generated the scent information for the perfume. Furthermore, the person who generated the scent information for the perfume may, for example, independently reconstruct the scent of the perfume generated by the perfume manufacturer and manage a scent that has been altered with at least partially different compositions.

[0333] Furthermore, a third party in Figure 28 could be, for example, a user (user B) different from the owner (user a) of the playback device RE. Specifically, one scenario is envisioned where a third party (user B) possesses a perfume scent (NFT) and allows nearby user a to smell the scent they possess. In this case, as shown by the arrow from the third party to the management server in Figure 28, the third party sends the scent information (scent code), information identifying the third party, and information identifying device A, which is the playback device RE, as signature information to device A (the emitter), which is the playback device RE, via the management server.

[0334] Furthermore, "proximity" can refer to situations where users are in close proximity in real space, or where the avatars corresponding to user a and user B are in close proximity in virtual space.

[0335] Furthermore, if a third party does not possess the designated scent code, it is conceivable that the scent information (scent code) owned by the third party will be sent from device A to the management server and then to the nearby owner (user a).

[0336] It should also be noted that the author and the owner of the scent information may be the same person.

[0337] Specifically, when a user is made to smell a natural object (for example, a grassland in the metaverse), it is conceivable that the owner in the metaverse (landowner, coder, etc.) and the author of the scent of the grassland in that land may be the same person.

[0338] Furthermore, if the owner of a restaurant (for example, a ramen shop) allows a designated user nearby to smell the ramen, the owner becomes both the author and owner of the ramen smell.

[0339] In addition, the third party in Figure 28 may send information to the management server indicating that it has come into proximity with a designated user, instead of odor information.

[0340] Furthermore, as mentioned above, the third party does not need to possess a device that emits odors (an emitter).

[0341] Figure 29 is a flowchart showing the case of passively reproducing odor according to the third embodiment.

[0342] Figure 29 corresponds to the flow chart for actively reproducing odors shown in Figure 23.

[0343] The difference from the case in Figure 23 is that the process starts when the management server 3000 receives a scent code from a third party (S1045), and as mentioned above, when the third party sends the scent code to the management server 3000, it also sends the following information as signature information. a) Scent code b) Information identifying the third party who owns the scent code c) Information identifying the owner (user a) of the playback device RE (c may be information that identifies the playback device RE itself.)

[0344] The rest of the processing flow is the same as in Figure 23, so we will not repeat the explanation.

[0345] (Fourth Embodiment)

[0346] Figure 30 is a conceptual diagram showing an overview of the fourth embodiment.

[0347] The server (management server) according to the fourth embodiment controls whether device A (for example, an odor emitter) can be operated or not.

[0348] In other words, when a user who is both the owner of the regeneration device RE and the owner of the scent code sends a usage request along with signature information to the management server, the management server authenticates whether the user is the legitimate owner of the scent based on the NFT information recorded on the blockchain BC. Based on the authentication result, the management server determines whether the owner meets the usage conditions and decides whether the scent can be used. In accordance with this determination, device A, which is the regeneration device RE, controls the regeneration operation.

[0349] For example, for a user who owns an NFT containing scent information that allows them to release a specific perfume 10 times, it is conceivable that the operation of a scent releaser would be controlled in order to manage the NFT owner, usage history (behavioral history; number of times used, number of times available, etc.), and usage conditions.

[0350] This allows us to virtually recreate the state of an empty perfume bottle. It also allows us to recreate the process of buying perfume by weight.

[0351] Furthermore, the management server can manage usage history using NFTs, allowing it to change the scent of the perfume according to the time elapsed since the perfume was first released. This makes it possible to recreate the scent when the perfume is first applied (top note), the scent after some time has passed (middle note), and the scent that lingers until the perfume's fragrance disappears (base note).

[0352] Note that the hardware configuration of the server, devices, etc. shown in Figure 30 is the same as the hardware configuration shown in Figures 20A and 20B, for example, so its explanation is omitted.

[0353] The server (management server) according to the fourth embodiment is an information processing device that performs device operation control based on NFTs.

[0354] Furthermore, the configuration of the management server 3000 is the same as that shown in Figure 17.

[0355] In other words, when the server's CPU 3040 is operating, the operation control module within the request reception MD3041, NFT authentication processing MD3043, scent code distribution processing MD3045, and information processing MD3046 all function.

[0356] Request reception MD3041 receives requests from owners of NFTs related to specific scent information managed on the blockchain BC to use the scent information.

[0357] NFT authentication process MD3043 performs authentication of NFTs related to scent information.

[0358] The MD3045 odor code distribution process determines whether or not the odor information can be used based on authentication.

[0359] The operation control unit generates and distributes a signal to control the operation of the playback device RE when it determines in the odor code distribution process MD3045 that the recorded odor information can be used.

[0360] (Fifth embodiment)

[0361] Figures 31A and 31B show an overview of the fifth embodiment.

[0362] In Figures 31A and 31B, the information processor server 2000 is a server that receives scent materials or raw materials from the original author and performs the task of converting them into scent codes, and has basically the same configuration as server 1 described in Figure 5. The management server 3000 according to the fifth embodiment is also an information processing device that performs blockchain management of scent information. In response to a request from terminal 1000 to encode scent information, the information processor server 2000 generates a scent code and sends it to the management server 3000. Furthermore, in accordance with a request from terminal 1000 to issue an NFT, the management server 3000 issues an NFT to blockchain BC.

[0363] In the fifth embodiment, the metaverse service provider server 4000 provides image and audio information of the virtual space (metaverse) to the terminal 2200 of the owner (user a) of the playback device 2210 (the content playback device and the scent spraying device are collectively referred to as the "playback device") which corresponds to the content playback device RE. Here, it is assumed that the administrator of the metaverse service provider server 4000 is the owner of the scent code through the sale of the NFT. Furthermore, although the terminal 2200 is assumed to play 2D images on an LCD display or the like and play sound through a speaker, it may also play images on a head-mounted display and play sound via headphones, for example.

[0364] From the metaverse service provider server 4000, a request to use the scent code is sent to the management server 3000 in conjunction with the provision of image information in the metaverse. Here, the request to use the scent code includes an electronic signature that includes information indicating the owner of the scent code and the playback device 2210. Here, "information indicating the playback device 2210" means information that can identify the playback device and transmit information, such as the playback device's identification number or the playback device's global address.

[0365] The management server 3000 performs authentication verification of the NFT on the blockchain BC, and once it verifies that the sender of the usage request is the legitimate owner, it distributes the scent code to the designated playback device 2210.

[0366] Upon completion of the odor code regeneration process, the regeneration device 2210 sends an NFT transaction update request to the management server 3000 to update information regarding the usage history (behavior history; number of uses, number of available uses, etc.).

[0367] The management server 3000 issues an NFT update transaction to update the usage history information of the scent code, which is managed on the blockchain BC.

[0368] This usage history information makes it possible to control the odor code regeneration process, similar to the fourth embodiment.

[0369] Furthermore, as will be explained in the modified fifth embodiment described later, it is also possible to configure the system to control the reproduction of scents or flavors corresponding to scent information or taste information according to the location information and environmental information of the user's avatar in the metaverse space.

[0370] Figure 32 is a conceptual diagram illustrating the configuration of a modified example of the fifth embodiment.

[0371] The management server 3000 according to the modified version of the fifth embodiment reproduces the smell using spatial information in the metaverse space.

[0372] Note that the hardware configuration of the server, devices, etc. shown in Figure 32 is the same as the hardware configuration shown in Figure 4.

[0373] Figures 33A and 33B show the configuration of the system relating to the metaverse environment in a modified example of the fifth embodiment.

[0374] The management server 3000 according to the modified version of the fifth embodiment is an information processing device that performs odor reproduction based on metaverse spatial information.

[0375] Furthermore, in the CPU of the management server 3000, the information processing MD3046 includes functional blocks that, when operating, acquire location information of the user's avatar within the metaverse from the metaverse service provider server 4000 (location information acquisition MD), acquire environment information of the metaverse set by the metaverse service provider server 4000 (environment information acquisition MD), and smell control module (smell control MD).

[0376] In Figures 33A and 33B, in response to a request from terminal 1000 to encode scent information, the information processor server 2000 generates a scent code and sends it to the management server 3000. Furthermore, in accordance with a request from terminal 1000 to issue an NFT, the management server 3000 issues an NFT to blockchain BC. Here as well, the administrator of the metaverse service provider server 4000 may become the owner of the scent code through the sale of the NFT. Alternatively, the owner of the scent code may become user b through the sale of the NFT, and this user may be different from user a, who owns the playback device 2210 on which the scent code is reproduced.

[0377] The location information acquisition MD of the management server 3000 acquires the spatial location information of the avatars of the first user (user a) and the second user (user b) in a predetermined metaverse space from the metaverse service provider server 4000.

[0378] The environment information acquisition MD acquires environment information surrounding the avatars of the first and second users in the metaverse space.

[0379] The scent control MD generates or controls scent information corresponding to the scents perceived by the avatars of the first and second users in the metaverse space, based on location information or environmental information.

[0380] The metaverse service provider server 4000 provides metaverse video information and audio information to the playback devices 2110 and 2210 of the terminals 2200 and 2100 of the first user (user a) and the second user (user b), respectively. Here, the terminals 2200 and 2100 are assumed to be devices that play 2D images on LCD displays and play sound through speakers, but for example, images may be played on a head-mounted display and sound may be played via headphones. Here again, the content playback device and the scent spraying device (scent playback device) are collectively referred to as the "playback device".

[0381] In other words, the management server 3000 adjusts the scent played for the user corresponding to the metaverse avatar, depending on the scene and situation.

[0382] For example, a server can be controlled to release scents that depend on (correlate with) spatial information within a virtual space.

[0383] Examples of spatial information include the following: • Temperature, humidity, and wind speed settings • The size of the space (for example, enclosed spaces such as inside buildings, tunnels, caves, or valleys). • Diffusion rate, volume of enclosed space, and set values ​​for ventilation rate

[0384] For example, the server could be controlled to release scents that depend on (correlate with) its location within the virtual space.

[0385] Examples of location information include the following: • The relative positions of the avatars corresponding to the first user (user a) and the second user. • The coordinates (position) of the avatar in the virtual space.

[0386] Here, the "relative positional relationship between avatars" can be calculated from the distance to other users' avatars, based on the "positional information of the first user's avatar in the given metaverse space" mentioned above.

[0387] Furthermore, the "coordinates (position) of the avatar in the virtual space" shall correspond to the "position information of the first user's avatar in the predetermined metaverse space" as described above.

[0388] Furthermore, regarding the smells and tastes to be reproduced based on spatial information, a table like the one below is prepared in advance, and in response to a usage request from the metaverse service provider server 4000, reproduction condition data corresponding to this spatial information can be sent to the management server 3000. The management server 3000 delivers the reproduction condition data along with the smell code to the reproduction device 2210, and the reproduction device 2210 performs reproduction processing according to the reproduction condition data.

[0389] [Table 1]

[0390] Note that the regeneration conditions in the table above are examples, and the settings may be changed based on prior experiments. The reference temperature, humidity, and wind speed may also be different values. Furthermore, the coefficients of the regeneration conditions may be changed depending on the type of odor. For taste, different settings can be made for temperature and humidity, and the coefficients of the regeneration conditions may be changed depending on the type of taste. Alternatively, regeneration conditions may be set for each possible combination of temperature, humidity, and wind speed.

[0391] Next, let's explain the process of reproducing scents based on the relative positions of avatars, for example, as follows:

[0392] In the metaverse image information provided by the metaverse service provider server 4000, when the relative positional relationship between avatars satisfies predetermined conditions, a request to use the scent code is sent, for example, from the metaverse service provider server 4000 to the management server 3000. Here, the request to use the scent code includes an electronic signature indicating that the user is the owner of the scent code and that the playback device 2210 is involved.

[0393] The management server 3000 performs authentication verification of the NFT on the blockchain BC, and once it verifies that the sender of the usage request is the legitimate owner, it distributes the scent code to the designated playback device 2210.

[0394] Upon completion of the odor code regeneration process, the regeneration device 2210 sends an NFT transaction update request to the management server 3000 to update information regarding the usage history (behavior history; number of uses, number of available uses, etc.).

[0395] The management server 3000 issues an NFT update transaction to update the usage history information of the scent code, which is managed on the blockchain BC.

[0396] This usage history information makes it possible to control the odor code regeneration process, similar to the fourth embodiment.

[0397] In addition to the above settings, it may be possible to allow users to freely specify (and accept) the range and locations where the scent will be perceived.

[0398] Furthermore, it may have a function that allows users to smell only the scents they wish to smell, thanks to a scent filter.

[0399] Furthermore, the scent may be emitted only to avatars specified by the user. For example, as described above, suppose that user b becomes the owner of the scent code through the sale of the NFT, and is a different person from user a, who owns the playback device 2210 where the scent code is played back. In this case, user b sends permission to use the scent code from terminal 2100 to the metaverse service provider server 4000 in advance. Then, when the relative positions of the avatars satisfy predetermined conditions (for example, the distance in the virtual space is less than or equal to a predetermined value), a request to use the scent code is sent from the metaverse service provider server 4000 to the management server 3000. Here, the request to use the scent code includes an electronic signature indicating that user b is the owner of the scent code and the playback device 2210. The management server 3000 performs an authentication check of the NFT on blockchain BC, and once it authenticates that the sender of the request to use the scent code is the legitimate owner, it delivers the scent code to the designated playback device 2210. Upon completion of the scent code playback process, the playback device 2210 sends an NFT transaction update request to the management server 3000 to update information regarding the usage history (behavior history; number of uses, number of uses, etc.). The management server 3000 issues an NFT update transaction to update the scent code usage history information managed by blockchain BC. In this way, even when the owner of the scent code is user b, the playback process of the scent code can be controlled using this usage history information, similar to the fourth embodiment.

[0400] Furthermore, the release rate may be adjusted based on the cumulative amount of odor in the virtual space and the cumulative amount of odor released by the odor emitter (diffuser).

[0401] Furthermore, the system may have a function to explore scents within the virtual space. For example, scents may be visualized by appropriately coloring them. It may also be possible to explore which scent is associated with which location in the virtual space.

[0402] Furthermore, the system may be linked to information about the user's (user's) body in the real world. For example, scents may be generated in response to the user's body information such as age and gender, or to their diet and physical condition.

[0403] Furthermore, the history of the scent (for example, the release history) may be managed. In addition, the history and the scent itself may be made visible.

[0404] Furthermore, the user's scent emission history may be linked and managed in conjunction with rewards such as cryptocurrency.

[0405] Furthermore, attribute information of third parties (visitors) within a designated virtual space may be linked and managed.

[0406] Furthermore, things that are impossible in reality, or that exist conceptually but cannot be perceived, may be virtually represented (recreated) as scents.

[0407] It may be linked to time (time of day) in the real world. For example, the scent may change according to morning, noon, and night.

[0408] Furthermore, the transmission of scents within the virtual space can be controlled to occur at speeds and decays impossible in the real world. This allows for the representation of a different flow of time than in reality, for example, by making one day in the real world equivalent to one year in the virtual space. It also enables the representation of various surreal spaces.

[0409] Furthermore, the aforementioned "adjustment of odor release amount" can be described as adjusting the strength of the effect on the sense of smell via the odor emitter.

[0410] Furthermore, regulating the release amount requires not only simply adjusting the release amount, but also adjusting the release amount based on the degree of olfactory stimulation.

[0411] Specifically, odor intensity is generally quantified using a 5-point scale, where the weakest state (the lowest concentration at which the presence of the odor can be perceived) is assigned a value of "1," and the odor intensity where there is no difference even when the concentration of odor molecules is increased beyond that point is assigned a value of "5."

[0412] In other words, when the odor intensity is 5 or higher, it exceeds the dynamic range of the olfactory sense, causing sensitivity to saturate (they no longer perceive differences in the perception cycle). Therefore, releasing odor at a saturating concentration (for example, an odor intensity of "5") is meaningless, and it is important to adjust the release amount not only based on the release volume but also taking into account the dynamic range of the olfactory sense.

[0413] Examples of the above functions are shown below.

[0414] For example, you can apply your favorite perfume to your avatar, and then, based on the relative positions of avatars in the virtual space, you can make other avatar users smell the fragrance.

[0415] Furthermore, users can enjoy virtual reality (VR) based on settings such as temperature, humidity, and wind speed. Specifically, since scents are perceived more strongly downwind, scent can be used to aid positioning in first-person hunting games. The temperature, humidity, and wind speed settings can also be used to recreate situations such as "summer → southerly wind → scent of the sea" along the Pacific coast of Japan.

[0416] Furthermore, the intensity of the burnt smell from the explosion in the virtual space (the strength and speed of the odor) can be used to clearly convey the sense of distance from the explosion site.

[0417] Furthermore, when using aromas, perfumes, or flavors in a room set up within the virtual space, the diffusion rate of the scent in the enclosed space, the volume of the enclosed space, and the ventilation rate can be used as set values.

[0418] Additionally, the scope of who can access the scent can be set to, for example, family, friends, or third parties.

[0419] Furthermore, it allows for differentiation between formal and informal attire (e.g., dress codes for each area) and regional restrictions (considering national and religious factors).

[0420] Furthermore, adjustments can be made to narrow the range in which odors are detected within a densely populated virtual space, and the amount of odor released can be adjusted to avoid placing an excessive burden on the human nose and brain.

[0421] Furthermore, by incorporating a function that allows the scent to be launched like a ball or bullet and hit opponents or objects, it can be used, for example, in virtual snowball fights or gun battles.

[0422] Furthermore, by incorporating features such as radar or detection dog-like capabilities to locate the source of a scent, it can be used in games such as treasure hunts.

[0423] Furthermore, by linking with the user's physical information such as facial expressions and pulse, and incorporating a function to detect stress levels and express them as scents, it can be used, for example, in games like Werewolf.

[0424] Furthermore, by incorporating a function that visualizes the history of scents using a water flow-like representation, it can be used for tracking prey in hunting games or to attract customers by representing the scent emanating from food.

[0425] Furthermore, a feature could be implemented that rewards users with virtual currency or other rewards for using a designated scent. For example, rewards could be linked to the number of times a scent is used, or to actions such as walking around the virtual space and spreading the scent. This would allow the system to be used as an advertising medium, for instance, by rewarding users for carrying yakisoba bought from a food stall and spreading the scent as they pass other avatars, or for walking around wearing a newly released perfume.

[0426] Furthermore, by creating a map that records (visualizes) the history of scents, it is possible to predict personality by linking it with data analyzing human preference trends. For example, information on what kinds of people with certain scents gather around buildings or people with a particular scent can be collected and analyzed. This information can then be linked to customer information associated with the scent, and used for targeted advertising (it can also be used to find influencers based on the spread of scents).

[0427] Furthermore, it may have the function of creating and emitting scents that represent phenomena or things that do not exist in real space, or concepts that do not have scents, such as the scent of time, the scent of seasons, the scent of light, or the scent of a change in dimension. This allows for the emission of special scents when characters or spaces are transformed from 3D to 2D within the same game, or when magic is cast by characters.

[0428] Furthermore, it can also be used as an advertisement, for example, by releasing the smell of pizza at noon and displaying a link to pizza delivery services.

[0429] (Sixth Embodiment)

[0430] Figure 34 is a conceptual diagram showing an overview of the sixth embodiment.

[0431] According to the sixth embodiment, the scent-providing server 5000, upon receiving an image containing an object (for example, ramen), recognizes the object and outputs corresponding scent information (for example, ramen scent information).

[0432] Here, it is believed that when humans are blindfolded, their ability to perceive smells (resolution and sensitivity) decreases, suggesting that human smell perception is aided by vision. Therefore, in the transmission of smells, it is common to provide images and smells together as a set.

[0433] Therefore, we will explain an example where an input image is used with artificial intelligence (AI) (for example, a classifier generated by machine learning) to output the corresponding scent.

[0434] For example, based on the color, shape, etc., of an object placed in real or virtual space, the AI ​​recognizes the object and automatically generates a scent for that object.

[0435] In this embodiment, an example of estimating the odor information of an object is described, but a configuration that estimates and reproduces the taste information of an object may also be used.

[0436] Furthermore, the hardware configuration of the server, devices, etc. shown in Figure 34 is the same as the hardware configuration shown in Figure 4, so its explanation is omitted.

[0437] The odor-providing server 5000 according to the sixth embodiment is an information processing device that reproduces odors based on image information.

[0438] Furthermore, in Figure 34, the management server 3000 provides the scent provision server 5000 with training data to generate a "trained model" for estimating scent codes from image information. Authentication information (digital signatures) requesting their use as training data (permissioning their use by the scent provision server 5000) is sent to the management server 3000 from the terminals 2200.1 to 2200.N of the owners of each scent code and the corresponding image data. This authentication information approval can be configured to be performed based on NFTs managed by the blockchain BC, as shown in Figures 31A and 31B.

[0439] Furthermore, the CPU of the scent provisioning server 5000 is also equipped with an information processing module (MD), which, when operating, includes functional blocks such as a learning data acquisition module (learning data acquisition MD), an image recognition module (image recognition MD), a scent code learning processing module (scent code learning processing MD), and a scent estimation module (scent estimation MD).

[0440] The learning data acquisition MD obtains image information containing the authenticated predetermined object and a scent code from the management server 3000. This scent code may also be configured in a way that, similar to the configuration described in Figures 31A and 31B, limits the "number of uses" and "usable time" for playback processing after the artificial intelligence has learned using the scent code, and this information may be managed by a blockchain.

[0441] Image recognition MD recognizes the type of odor-causing object in an image based on image information. The process of classifying the type of object in an image from image data is not particularly limited, but for example, it can be done by generating a trained model for classification by performing supervised learning on an artificial intelligence model using a convolutional neural network beforehand. The classification results can be configured to output a probability for each classification result, for example.

[0442] The odor code learning process (MD) generates a trained model that learns and estimates the corresponding odor code, using the recognition result of the image recognition (MD) as training data. Here, although not particularly limited, for example, a trained model for performing classification processing can be generated by performing supervised learning on an artificial intelligence model using a neural network beforehand.

[0443] Odor estimation MD uses a trained model to estimate the odor information of objects corresponding to the type of object in the input image. In this case, the system can be configured to reproduce the odor of the odor code corresponding to the classification result with the highest probability. Also, although not particularly limited, as described above, if the system outputs a probability for each classification result, the system may be configured to synthesize the odors to be reproduced for each classification result as weights for these probabilities.

[0444] Examples of the sixth embodiment include the following:

[0445] For example, in a virtual space, if an object with the color and shape of a violet flower is near an avatar, it is conceivable that the AI ​​will identify it as a violet and allow the avatar's operator (user) to smell the violet. In this case, as explained in Figures 31A and 31B, if the information limiting the "number of uses" and "usable time" for playback processing is managed by the blockchain, it is also possible to configure the system so that the scent provision server 5000 sends a scent usage request to the management server 3000, and once the management server 3000 confirms that the usage conditions are met, the estimated "scent code" is delivered from the scent provision server 5000 to the playback device.

[0446] Furthermore, for example, if an object with the color and shape of curry is near the camera in the real world, the AI ​​will recognize it as curry and release an image of curry and the smell of curry simultaneously on a remote display.

[0447] In other words, even without pre-prepared scent information or its association with specific objects, the server can control the system to emit scents corresponding to objects based on the input image. This allows users viewing content that does not have existing scent information to smell the various objects displayed in the content, thereby enhancing immersion.

[0448] Alternatively, for odor reproduction based on image information, the following processing can be performed.

[0449] i) In a virtual space such as the metaverse, when performing control as shown in Figures 31A and 31B or Figures 33A and 33B, it is also possible to configure the metaverse service provider server 4000 to, at the stage when it has prepared the images to be distributed to terminals 2100 and 2200, predict the scent (or taste) to be reproduced by the playback device in advance using artificial intelligence based on the image information, and distribute the scent code to be distributed to the playback device at a time before the image is distributed, so that the playback device can prepare for scent reproduction. In this case, the playback device can reproduce the scent (or taste) with minimal time lag as soon as it is authenticated in response to the usage request and notified by the management server 3000.

[0450] ii) In addition, when controlling the relay of scent (or taste) in real space, as shown in Figure 1 or Figure 7, it is also possible to configure the system so that when Server 1 has prepared the image to be distributed to the TV, it uses artificial intelligence to predict in advance the scent (or taste) to be reproduced by the playback device based on the image information, and distributes the scent code to be distributed to the playback device at a time before the image is distributed, so that the playback device can prepare for scent reproduction. In this case, the playback device can reproduce the scent (or taste) with minimal time lag as soon as the corresponding relayed image data is distributed. The timing of the distribution of the image corresponding to the scent (or taste) reproduction will be notified by Server 1.

[0451] Figures 35A and 35B show an example of NFT management using IPFS.

[0452] As shown in Figure 35A, for example, when an image on the web is represented as an NFT, it is possible to prove the authenticity (uniqueness) of the image by tracing its history, which is managed by the blockchain BC, through a smart contract.

[0453] However, it is possible to duplicate the image itself.

[0454] Therefore, as shown in Figure 35B, by using IPFS, the image information itself is stored within IPFS, and based on the domain information between terminals in a P2P connection, it becomes possible to control the display of the image on the terminal that made the connection request only when the connection request from a certain terminal is a request from the legitimate owner.

[0455] Similar control methods can also be used for distributing "scent codes."

[0456] (others)

[0457] Furthermore, the series of processes described above can be executed by hardware or by software. In other words, the functional configuration described above is merely illustrative and not particularly limiting. That is, it is sufficient for the information processing system to have the functionality to execute the series of processes described above as a whole, and the type of functional block used to realize this functionality is not particularly limited to the example above. Also, the location of the functional block is not particularly limited and can be arbitrary. For example, the functional block of a server (information processing device) may be transferred to another device, etc. Conversely, the functional block of another device may be transferred to a server, etc. Moreover, a single functional block may be composed of hardware alone, software alone, or a combination of both.

[0458] When a series of processes are executed by software, the programs that make up that software are installed on a computer or other device from a network or storage medium. The computer may be a computer built into dedicated hardware. Alternatively, the computer may be a computer capable of performing various functions by installing various programs, such as a server, a general-purpose smartphone, or a personal computer.

[0459] Such recording media containing programs may consist not only of removable media (not shown) distributed separately from the main device to provide programs to users, but also of recording media provided to users in a state where they are pre-installed in the main device. Since programs can be distributed via a network, the recording media may be installed on or accessible from a computer connected to or capable of connecting to a network.

[0460] In this specification, the step of describing a program to be recorded on a recording medium includes not only processes that are performed chronologically in that order, but also processes that are not necessarily performed chronologically, but are executed in parallel or individually. Furthermore, in this specification, the term "system" refers to an overall system composed of multiple devices, means, etc.

[0461] In other words, the information processing device to which the present invention is applied can take various forms having the following configurations.

[0462] In other words, the information processing device comprises (1) an acquisition device for acquiring receptor response information showing the responses of multiple types of olfactory receptors or gustatory receptors; a storage device for storing the receptor response information; an emission information determination device for determining emission information relating to the emission of multiple types of odor or taste receptors according to the receptor response information; and an emission control device for causing at least one of the multiple types of odor or taste receptor receptors to be emitted based on the emission information.

[0463] This makes it possible to reproduce the target scent in a non-personal manner.

[0464] Furthermore, (2) the receptor response information is a characteristic quantity for odor molecules or tastes in multiple types of receptors, and should be information that shows at least one of the following characteristics: response intensity, area of ​​response intensity, response duration, response rate, peak time, response rise, and number of peaks.

[0465] This allows for the accurate reproduction of the target scent or taste. Since the way fragrances or seasonings spread and the temperature affect how people perceive scents or tastes, including as much of this information as possible is beneficial for accurately reproducing the target scent or taste.

[0466] Furthermore, (3) the memory device has a mapping table for associating receptor response information with release information, and the release information determination device may determine the release information based on the receptor response information and the mapping table.

[0467] This allows the response information to be converted into corresponding release information, enabling the reproduction of a target scent or taste in a non-personal manner.

[0468] Furthermore, (4) the memory device further stores a learning model that has been pre-generated by machine learning using receptor response information and release information corresponding to the receptor response information as training data, and the release information determination device uses the learning model to determine the release information based on the receptor response information acquired by the acquisition device.

[0469] This makes it possible to reproduce the target scent or taste in a non-personal way by preparing mapping data (training data), even when it is difficult to generate the mapping table described above.

[0470] Furthermore, (5) the release information determination device may determine at least one of the release information items for a substance related to the reception of odor or taste, such as release time, release amount, release temperature, number of releases, and release nozzle throttling amount.

[0471] This allows for highly accurate reproduction of the target scent or taste.

[0472] Furthermore, (6) the release information determination device may determine the release information according to the receptor response information and spatial parameters relating to the state of the space in which the substance is released or the positional relationship with the object from which the substance is released.

[0473] This allows for control over spray direction, volume, and concentration based on factors such as distance from the nose, temperature, and humidity, in situations where the position of a person's nose (face) can be determined to some extent, such as in a movie theater (direct spraying). Furthermore, in large spaces like a sports stadium (indirect spraying), the spray direction, volume, and concentration can be controlled based on factors such as the size of the space, airflow, wind direction, temperature, and humidity.

[0474] Furthermore, the cartridge to which the present invention is applied can take various forms having the following configurations.

[0475] In other words, (7) a cartridge for filling with a substance relating to the reception of odor or taste released by the information processing device described above, the cartridge being filled with a composition that selectively responds only to specific receptors.

[0476] Furthermore, the discharge device (odor spraying device 3) to which the present invention is applied can take various forms having the following configurations.

[0477] In other words, (8) a discharge device having a mounting section for attaching the above-mentioned cartridge, and a discharge port for releasing substances related to the reception of odor or taste based on discharge control by a discharge control device.

[0478] This allows for the reproduction of a target scent or taste through appropriate release.

[0479] Furthermore, the manufacturing method to which the present invention is applied can take various forms having the following configurations.

[0480] In other words, (9) a method for creating an odor or taste, comprising the step of releasing a substance relating to the reception of an odor or taste by the aforementioned release device.

[0481] Furthermore, the data structure to which the present invention is applied can take various forms having the following configurations.

[0482] That is, (10) the data structure of receptor response information used in the information processing device described above.

[0483] Furthermore, the production method to which the present invention is applied can take various forms having the following configurations.

[0484] In other words, (11) a method for generating an N-dimensional code having an encoding step of converting receptor response information into an N-dimensional code by performing a predetermined encoding on the receptor response information.

[0485] Furthermore, the production method to which the present invention is applied can take various forms having the following configurations.

[0486] In other words, (12) a method for generating decoded receptor response information, comprising a decoding step of converting an N-dimensional code into receptor response information by performing a predetermined encoding on the receptor response information and then performing a predetermined decoding on the N-dimensional code.

[0487] Furthermore, the control method to which the present invention is applied can take various forms having the following configurations.

[0488] In other words, (13) a control method for an information processing device having an acquisition step of acquiring receptor response information showing the responses of multiple types of olfactory receptors or taste receptors; an emission information determination step of determining emission information relating to the release of odor or taste in multiple types of fragrances or seasonings according to the receptor response information; and an emission control step of releasing at least one of the multiple types of fragrances or seasonings based on the emission information.

[0489] Furthermore, the computer program to which the present invention is applied can take various forms having the following configurations.

[0490] In other words, (14) a computer program that causes a computer to perform the following steps: an acquisition step of acquiring receptor response information showing the responses of multiple types of olfactory receptors or gustatory receptors; an emission information determination step of determining emission information relating to the release of odor or taste in multiple types of fragrances or seasonings according to the receptor response information; and an emission control step of causing at least one of the multiple types of fragrances or seasonings to be released based on the emission information.

[0491] Furthermore, the information processing device to which the present invention is applied can take various forms having the following configurations. In other words, (2) an information processing device that performs blockchain management of smell information or taste information, A receiving device that receives requests from owners of NFTs related to predetermined scent or taste information managed on a blockchain to use the scent or taste information, A verification device that authenticates NFTs related to scent or taste information to prove the uniqueness of scent or taste information or to verify the integrity of transaction history, It is an information processing device.

[0492] Furthermore, the information processing device to which the present invention is applied can take various forms having the following configurations. In other words, (3) an information processing device that performs device operation control based on NFT, A receiving device that receives requests from owners of NFTs related to predetermined scent or taste information managed on a blockchain to use the scent or taste information, An authentication device that authenticates NFTs related to scent information or taste information, A judgment device that determines whether or not to use odor information or taste information through authentication, When the judgment device determines that odor information or taste information can be used, an operation control device controls the operation of a predetermined odor reproduction device or taste reproduction device. It is an information processing device.

[0493] Furthermore, the information processing device to which the present invention is applied can take various forms having the following configurations. In other words, (4) an information processing device that performs smell reproduction or taste reproduction based on metaverse spatial information, A location information acquisition device that acquires location information of the first user's avatar in a predetermined metaverse space, An environmental information acquisition device that acquires environmental information about the environment surrounding the first user's avatar in the metaverse space, A generating device that generates odor information or taste information corresponding to the smell or taste perceived by the first user's avatar in the metaverse space, based on location information or environmental information, It is an information processing device.

[0494] Furthermore, the information processing device to which the present invention is applied can take various forms having the following configurations. In other words, (5) an information processing device that performs smell reproduction or taste reproduction based on image information, An acquisition device that acquires image information including a predetermined object, A recognition device that recognizes the type of object based on image information, An estimation device that estimates odor information or taste information of an object corresponding to a type, It is an information processing device.

[0495] Furthermore, the following configuration is also possible. A system that performs smell or taste reproduction based on information in the metaverse space in a service in the metaverse space, In peer-to-peer communication, multiple computers corresponding to each of the multiple nodes that make up the blockchain, A system capable of issuing transactions to a blockchain, and comprising a management device for registering non-fungible tokens on the blockchain in response to an issuance request from the original owner of scent information or taste information, and verifying the legitimacy of the non-fungible tokens based on ownership information, Non-fungible tokens are associated with coded data of scent or taste information. The blockchain records changes in ownership information of non-fungible tokens as code data is transferred from the original owner to the first user, and returns the result of verification of the legitimacy of using the scent or taste information based on the non-fungible token. Using code data, and unlike the first user, a second user who uses the service in the metaverse space is further provided with a first playback device for performing odor or taste reproduction processing corresponding to odor or taste information. A system in which, as a usage request from the first user's device, a usage request containing authentication information identifying the first user and the second playback device is sent to the blockchain, and the first playback device executes the playback process according to the verification result based on ownership information of non-fungible tokens in the blockchain.

[0496] In such a system, the first playback device controls the playback process according to spatial information relating to an avatar corresponding to a second user in the metaverse space, and the spatial information includes settings for virtual temperature, humidity, or wind speed that are set as the environment for the avatar in the metaverse space.

[0497] Alternatively, in such a system, the first user's device is a server device for distributing images and sounds from a virtual space to the second user, and in response to the images distributed from the server device, it sends usage requests to the management device, causing it to execute playback processing linked to the first playback device.

[0498] Alternatively, such a system may further include a server device for distributing images and sounds from the metaverse space to the devices of a first user and a second user, wherein when the first user's avatar in the metaverse space approaches the second user's avatar in the metaverse space within a predetermined distance, the server device sends a usage request to a management device, causing it to execute playback processing linked to the first playback device.

[0499] Alternatively, in such a system, a second playback device is provided for a first user using a service in the metaverse space, which uses code data to perform a playback process of scent or taste corresponding to scent or taste information, and when the avatar of the second user in the metaverse space approaches the avatar of the first user in the metaverse space within a predetermined distance, the server device sends a usage request to the management device, causing the second playback device to perform a playback process in conjunction with the second playback device.

[0500] Alternatively, in such a system, the first regeneration device controls the regeneration process according to usage conditions corresponding to the second user in the metaverse space, and the usage condition information includes an upper limit for the regeneration process of recorded smell or taste, and the management device does not send a confirmation result to the regeneration device that permits regeneration, even if the legitimacy of the usage request from the first user's device exceeds the upper limit if at least one of the number of times the legitimacy is confirmed or the regeneration time is confirmed.

[0501] Alternatively, in such a system, the management device initiates a transaction to change the ownership information of a non-fungible token when the code data is transferred from the original owner to the user.

[0502] Alternatively, in such a system, the management device, upon request, verifies that the user is the owner of the non-fungible token based on ownership information of the non-fungible token held within the blockchain.

[0503] Alternatively, in such a system, the control device transmits code data to the first regeneration device, in response to its legitimacy being verified, for the first regeneration device to perform a regeneration process using substances related to the reception of multiple types of smells or tastes.

[0504] Alternatively, the following configuration is also possible.

[0505] A management device for managing smell or taste reproduction based on information in the metaverse space in a service in the metaverse space, comprising an interface for performing communication via a network, and a computing device for issuing transactions to a blockchain via the interface and controlling the operation of a reproduction device that performs smell or taste reproduction, wherein the computing device registers a non-fungible token on the blockchain in response to an issuance request from the original owner of the smell or taste information, the non-fungible token is associated with code data of the smell or taste information, and changes in the ownership information of the non-fungible token are recorded on the blockchain in response to the transfer of the code data from the original owner to a first user, a usage request including authentication information identifying the first user and the reproduction device is sent to the blockchain as a usage request from the first user's device, the code data is distributed to the reproduction device in response to the verification result based on the ownership information of the non-fungible token in the blockchain, and the code data is for the reproduction device to perform smell or taste reproduction processing corresponding to the smell or taste information for a second user who uses the service in the metaverse space, different from the first user. [Explanation of symbols]

[0506] 1: Server 2: Receptor information determination device 3: Odor spraying device 11:CPU 18:Storage section 19:Communication section 31: Response information acquisition unit 32: Image acquisition unit 33: Model information acquisition unit 34: Spray information determination unit 35: Spray control unit 36: Display control unit 41: Response Information DB 42: Model Information DB 43: Mapping DB CO: Odor capture device CA: Cartridge NO: Nozzle RE: Content playback device TV: Display device

Claims

1. An information processing device that performs smell or taste reproduction based on metaverse spatial information, A location information acquisition means for acquiring the location information of the first user's avatar in a predetermined metaverse space, An environmental information acquisition means for acquiring environmental information surrounding the first user's avatar in the metaverse space, An information processing apparatus comprising: generation means for generating odor information corresponding to the smell or taste perceived by the first user's avatar in the metaverse space, based on the location information or the environment information.

2. The information processing device according to claim 1, wherein the position information includes at least one of the coordinates of the first user's avatar in the predetermined metaverse space and the relative positional relationship between the first user's avatar and the second user's avatar in the metaverse space.

3. The information processing apparatus according to claim 1, wherein the environmental information includes at least one of a virtual temperature, humidity, wind speed, size of space, odor diffusion rate, volume of enclosed space, and ventilation rate set around the first user's avatar.

4. The information processing apparatus according to any one of claims 1 to 3, wherein the generation means generates the odor information based on correspondence information which associates spatial information including the location information and the environmental information with the odor information regeneration condition data.

5. The information processing apparatus according to claim 4, wherein the generation means generates odor information including information indicating the intensity of the odor associated with the second user's avatar, according to the distance between the first user's avatar and the second user's avatar in the metaverse space.

6. The information processing apparatus according to claim 5, wherein the generation means generates odor information including information indicating the temporal change of odor perceived by the first user's avatar, based on a setting value relating to a virtual diffusion rate or decay that is different from the propagation rate or decay rate of odor in real space, which is included in the environmental information.

7. The information processing apparatus according to claim 5, wherein the generation means generates the odor information by correcting the intensity or emission amount of the odor included in the odor information based on at least one of the cumulative amount of odor in the metaverse space and the cumulative value of the emission amount in an odor emitter that operates based on the odor information.

8. The system further comprises image information acquisition means for acquiring image information in the aforementioned metaverse space, The information processing apparatus according to claim 7, wherein the generation means predicts the scent perceived by the first user's avatar based on the image information using artificial intelligence, and generates the scent information corresponding to the predicted scent before the timing of distribution of the image information.

Images