WO2021100515A1

WO2021100515A1 - Information processing device and information processing method

Info

Publication number: WO2021100515A1
Application number: PCT/JP2020/041733
Authority: WO
Inventors: 彩藤田; 修二藤田; 直子石塚
Original assignee: ソニーグループ株式会社
Priority date: 2019-11-22
Filing date: 2020-11-09
Publication date: 2021-05-27
Also published as: JPWO2021100515A1

Abstract

The present invention pertains to an information processing device and an information processing method which enable provision of assistance to users by means of fragrance. Provided is an information processing device equipped with a control unit which, by using a determination model generated by machine learning through usage of personal data of each user, controls discharging of a perfume for providing assistance to a user with respect to a target inferred from inputted sensor data. The present invention is applicable to, for example, an aromatic assist system for providing assistance to a user's behavior by means of fragrance.

Description

Information processing device and information processing method

The present technology relates to an information processing device and an information processing method, and more particularly to an information processing device and an information processing method capable of supporting a user by fragrance.

In recent years, not only the user experience by sight and hearing according to images and sounds, but also devices that generate scents and appeal to the user's sense of smell have been attracting attention (see, for example, Patent Document 1).

International Publication No. 2018/016153

By the way, the sense of smell is directly linked to the emotions of the user, and a technique for supporting the user's behavior by the scent has been required.

This technology was made in view of such a situation, and enables the user to be assisted by the scent.

The information processing device of one aspect of the present technology uses a judgment model generated by machine learning using personal data for each user, and discharges a fragrance to support the user with respect to a target estimated from input sensor data. It is an information processing device provided with a control unit for controlling the above.

In the information processing method of one aspect of the present technology, the information processing device uses a judgment model generated by machine learning using personal data for each user to support the user with respect to a target estimated from input sensor data. This is an information processing method that controls the discharge of fragrance for the purpose.

In the information processing device and the information processing method of one aspect of the present technology, the judgment model generated by machine learning using personal data for each user is used to support the user with respect to the target estimated from the input sensor data. The discharge of fragrance is controlled.

The information processing device on one aspect of the present technology may be an independent device or an internal block constituting one device.

It is a figure which shows the example of the structure of one Embodiment of the fragrance support system to which this technique is applied. It is a figure which shows the example of the configuration of a terminal device. It is a figure which shows the example of the functional configuration of a terminal device. It is a figure which shows the example of the configuration of a server. It is a figure which shows the example of the functional configuration of a server. It is a flowchart explaining the 1st example of the fragrance support processing of a terminal apparatus. It is a flowchart explaining the 1st example of the fragrance support processing of a terminal apparatus. It is a figure which shows the example of the positional relationship between a user and a similar person. It is a flowchart explaining the 1st example of the learning process of a server. It is a flowchart explaining an example of a scent customization process of a server. It is a flowchart explaining the 2nd example of the fragrance support processing of a terminal apparatus. It is a flowchart explaining the 3rd example of the fragrance support processing of a terminal apparatus. It is a flowchart explaining the 2nd example of the learning process of a server. It is a figure which shows another example of the functional configuration of a server. It is a flowchart explaining an example of a matching service process between a plurality of terminal devices and a server. It is a flowchart explaining an example of a matching service process between a plurality of terminal devices and a server. It is a figure which shows another example of the structure of one Embodiment of the fragrance support system to which this technique is applied.

<1. First Embodiment>

(Structure of fragrance support system)
FIG. 1 shows an example of the configuration of an embodiment of an fragrance support system to which the present technology is applied.

The fragrance support system 1 is a system that provides scent support to the user. The fragrance support system 1 is composed of terminal devices 10-1 to 10-N (an integer of N: 1 or more) and a server 20, and is connected to each other via a network 50.

The terminal device 10-1 is configured as a wearable terminal such as a spectacle-type device having a transmissive display.

In this spectacle-type device, a pair of transmissive displays for the left eye and the right eye are arranged at the position of the lens attached to the frame in ordinary spectacles, and are worn around the user's eyes. Therefore, in the spectacle-type device, various information can be drawn in the field of view by using AR (Augmented Reality) technology or the like without separating the user's field of view from the real space.

The terminal device 10-1 performs a determination process using a learned determination model provided from the server 20 via the network 50, sensor data acquired by the camera unit and the sensor unit, and the like, and based on the determination result. , Control the discharge of fragrance to assist the user.

The terminal device 10-1 is not limited to a spectacle-type device, and may be, for example, a wearable terminal in the shape of a pin batch, a contact lens, a kuroko, or the like. Further, the wearable terminal can include, for example, a device such as an electronic tattoo that is attached to a substance such as human skin or clothing.

The terminal devices 10-2 to 10-N are configured as wearable terminals such as eyeglass-type devices, respectively, like the terminal device 10-1. In the following description, when it is not necessary to distinguish the terminal devices 10-1 to 10-N, they are referred to as the terminal device 10.

The server 20 is composed of one or a plurality of servers that provide various services to the terminal device 10 via the network 50.

For example, the server 20 performs a learning process using the learning data to generate a determination model and provides it to the terminal device 10. Further, for example, the server 20 performs a matching process based on data or the like transmitted from the terminal device 10, and provides the matching process result to the terminal device 10.

Network 50 includes communication networks such as the Internet, mobile phone networks, and intranets. That is, in the fragrance support system 1 of FIG. 1, as communication, TCP / IP (Transmission Control Protocol / Internet Protocol) communication via the Internet, cellular mobile communication such as LTE-Advanced and 5G, and an access point are used. Communication via wireless LAN (Local Area Network) is adopted.

(Configuration of terminal device)
FIG. 2 shows an example of the configuration of the terminal device 10 of FIG.

As shown in FIG. 2, in the terminal device 10, the CPU (Central Processing Unit) 101, the ROM (Read Only Memory) 102, and the RAM (Random Access Memory) 103 are connected to each other by the bus 104.

The CPU 101 controls the operation of each part of the terminal device 10 by executing the program recorded in the ROM 102. Various data are appropriately recorded in the RAM 103.

The input / output interface 110 is also connected to the bus 104. An input unit 105, an output unit 106, a storage unit 107, a communication unit 108, and a short-range wireless communication unit 109 are connected to the input / output interface 110.

The input unit 105 supplies various input data to each unit including the CPU 101 via the input / output interface 110. For example, the input unit 105 has an operation unit 111, a camera unit 112, and a sensor unit 113.

The operation unit 111 is operated by the user and supplies the operation data corresponding to the operation to the CPU 101. The operation unit 111 is composed of physical buttons and the like.

The camera unit 112 generates captured image data and outputs it as sensor data by photoelectrically converting the light from the subject incident therein and performing predetermined signal processing on the electric signal obtained as a result. The camera unit 112 is composed of an image sensor, a signal processing unit, and the like.

The sensor unit 113 senses spatial information, time information, etc., and outputs sensor data obtained as a result of the sensing.

The sensor unit 113 includes an inertial measurement unit (IMU: Inertial Measurement Unit) that measures three-dimensional angular velocity and acceleration. The inertial measurement unit (IMU) can obtain three-dimensional angular velocity and acceleration by using a three-axis gyroscope and a three-way accelerometer.

Further, the sensor unit 113 includes a biological sensor that measures information such as the heart rate, body temperature, or posture of a living body, a proximity sensor that measures a proximity object, a magnetic sensor that measures the magnitude and direction of a magnetic field (magnetic field), and the like. Various sensors can be included.

The output unit 106 outputs various information and substances (fragrances, etc.) according to the control from the CPU 101 via the input / output interface 110. For example, the output unit 106 has a display unit 121, a sound output unit 122, and a fragrance discharge unit 123.

The display unit 121 displays an image or the like according to the image data according to the control from the CPU 101. For example, when the terminal device 10 is a spectacle-type device, the display unit 121 is configured as a pair of transmissive displays for the left eye and the right eye.

The sound output unit 122 outputs a sound according to the sound data according to the control from the CPU 101. For example, when the terminal device 10 is a spectacle-type device, the sound output unit 122 is configured as small headphones arranged at positions close to the left and right ears of the user.

The fragrance discharge unit 123 discharges various fragrances prepared in advance according to the control from the CPU 101.

For example, the fragrance discharge unit 123 has a fragrance holding structure filled with a liquid fragrance, and air is flowed through a holding space provided in the fragrance holding structure to be held by the fragrance holding body arranged in the holding space. It is released by vaporizing the liquid fragrance.

Liquid fragrances include various liquids that can generate scents by vaporizing. For example, the liquid fragrance may include a perfume, a liquid seasoning, or the like. When a plurality of types of liquid fragrances are used, a plurality of holding spaces are provided in the fragrance holding structure, and the liquid fragrance held in the fragrance holding body of the holding space selected from the plurality of holding spaces is vaporized and released. do it.

The fragrance discharge unit 123 may be built in the terminal device 10 or may be provided in an external housing of the terminal device 10 so as to be controlled by the terminal device 10.

The storage unit 107 records various data and programs according to the control from the CPU 101. The CPU 101 reads various data from the storage unit 107, processes the data, and executes a program.

The storage unit 107 is configured as an auxiliary storage device for a semiconductor memory or the like. The storage unit 107 may be configured as an internal storage, or may be an external storage such as a memory card.

The communication unit 108 communicates with other devices via the network 50 according to the control from the CPU 101. The communication unit 108 is configured as a communication module that supports cellular communication (for example, LTE-Advanced, 5G, etc.), wireless communication such as wireless LAN, or wired communication.

The short-range wireless communication unit 109 performs wireless communication based on short-range wireless communication standards such as Bluetooth (registered trademark) and NFC (Near Field Communication), and exchanges various data.

FIG. 3 shows an example of the functional configuration of the control unit 100 included in the terminal device 10. The function of the control unit 100 is realized by executing a program by the CPU 101.

In FIG. 3, the control unit 100 includes a sensor data acquisition unit 151, a determination model application unit 152, an emotion data acquisition unit 153, a situation analysis unit 154, and a fragrance discharge control unit 155.

The sensor data acquisition unit 151 acquires the sensor data detected by the camera unit 112 or the sensor unit 113 and supplies the sensor data to the determination model application unit 152 and the situation analysis unit 154. The sensor data includes captured image data.

The determination model application unit 152 can use the learned determination model provided from the server 20 via the network 50. The determination model application unit 152 applies the determination model to the captured image data supplied from the sensor data acquisition unit 151, and supplies the determination result data to the situation analysis unit 154.

The emotion data acquisition unit 153 acquires emotion data related to a person's emotions and supplies it to the situation analysis unit 154.

For example, this emotion data is data related to emotions toward the target user, such as sensor data detected by a wearable terminal worn by the target partner, sensor data detected by the terminal device 10, and the like. Includes data for.

The situation analysis unit 154 is supplied with sensor data from the sensor data acquisition unit 151, determination result data from the determination model application unit 152, and emotion data from the emotion data acquisition unit 153, respectively.

The situation analysis unit 154 analyzes various situations (for example, the situation around the user and the emotions of the target partner) based on the data supplied therein. The situation analysis unit 154 supplies the data of the analysis result to the fragrance discharge control unit 155.

The fragrance discharge control unit 155 controls the fragrance discharge unit 123 based on the analysis result data supplied from the situation analysis unit 154 to discharge various fragrances.

(Server configuration)
FIG. 4 shows an example of the configuration of the server 20 of FIG.

As shown in FIG. 4, in the server 20, the CPU 201, ROM 202, and RAM 203 are connected to each other by the bus 204.

The CPU 201 controls the operation of each part of the server 20 by executing the program recorded in the ROM 202. Various data are appropriately recorded in the RAM 203.

The input / output interface 211 is also connected to the bus 204. An input unit 205, an output unit 206, a storage unit 207, a communication unit 208, and a drive 209 are connected to the input / output interface 211.

The input unit 205 supplies various input data to each unit including the CPU 201 via the input / output interface 210. For example, the input unit 205 includes a keyboard, a mouse, a microphone, and the like.

The output unit 206 outputs various information according to the control from the CPU 101 via the input / output interface 110. For example, the output unit 206 has a display unit 221 and a sound output unit 222.

The display unit 221 displays an image or the like according to the image data according to the control from the CPU 201. The display unit 221 is composed of a liquid crystal panel, an OLED (Organic Light Emitting Diode) panel, a signal processing unit, and the like.

The sound output unit 222 outputs a sound according to the sound data according to the control from the CPU 201. The sound output unit 222 is composed of a speaker or the like.

The storage unit 207 records various data and programs according to the control from the CPU 201. The CPU 201 reads various data from the storage unit 207, processes the data, and executes a program.

The storage unit 207 is configured as an auxiliary storage device such as a semiconductor memory or an HDD (Hard Disk Drive). The storage unit 207 may be configured as an internal storage or may be an external storage.

The communication unit 208 communicates with other devices via the network 50 according to the control from the CPU 201. The communication unit 208 is configured as a communication module corresponding to cellular communication (for example, LTE-Advanced, 5G, etc.), wireless communication such as wireless LAN, or wired communication such as Ethernet (registered trademark).

A removable recording medium such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory is appropriately mounted on the drive 209, and the removable recording medium is driven according to the control from the CPU 201. The CPU 201 can control the drive 209 to read the data written in the driven removable recording medium.

FIG. 5 shows an example of the functional configuration of the control unit 200 included in the server 20. The function of the control unit 200 is realized by executing a program by the CPU 201.

In FIG. 5, the control unit 200 has a learning data acquisition unit 251, a learning DB 252, a learning unit 253, and a providing unit 254. The learning DB 252 is recorded in the storage unit 207.

The learning data acquisition unit 251 acquires personal data for each user and stores it in the learning DB 252 as learning data.

This personal data includes general information about the individual user, such as data on the compatibility of the user with other people, biometric data, social data, life logs (including behavior patterns and location information), and schedules. In addition, the data set used as personal data can include data in any format such as text data, image data, moving image data, and audio data.

The learning unit 253 performs learning by machine learning using personal data stored in the learning DB 252, and generates a determination model. This learned determination model is supplied to the providing unit 254.

When a request or the like is made from the terminal device 10, the providing unit 254 controls the communication unit 208 to provide the learned determination model supplied from the learning unit 253 to the terminal device 10 via the network 50. To do.

The configuration of the fragrance support system 1 has been explained above.

Next, the details of the processing executed by each device of the fragrance support system 1 will be described with reference to FIGS. 6 to 16.

(Flow of fragrance support processing)
First, a first example of the fragrance support process executed by the control unit 100 of the terminal device 10 will be described with reference to the flowcharts of FIGS. 6 and 7.

When executing this fragrance support process, the terminal device 10 worn by the user is provided with a determined determination model learned from the server 20 using personal data such as image data of a person the user likes, and is controlled. It is made available by the unit 100.

In step S101, the sensor data acquisition unit 151 acquires captured image data captured in real time by the camera unit 112 provided in the terminal device 10 such as a spectacle-type device. At this time, it can be said that the camera unit 112 is operating as a surveillance camera that monitors the surroundings of the user, so to speak.

In step S102, the determination model application unit 152 applies the learned determination model to the acquired captured image data.

In step S103, the situation analysis unit 154 is similar to a person who likes the user from the surrounding people within a radius of 10 m, centered on the user, based on the judgment result data of the judgment model, the captured image data, and the like. Determine if a person has been detected.

When a user detects a person similar to a favorite person, the personal data used as the learning data in the learning process executed by the control unit 200 (learning unit 253) of the server 20 is added to the personal data of occupation, annual income, and marriage. By including information such as presence / absence, address, hobby, age, DNA (Deoxyribonucleic Acid) information, similar people according to the desired conditions set by the user are detected using the learned judgment model. You may do so.

For example, when a desired condition is set by the user, the situation analysis unit 154 sets the desired condition with respect to the surrounding people within a radius of 10 m centering on the user, together with the similarity with the person who likes the user. The score value can be obtained by performing a predetermined arithmetic process in consideration of the above, and the person with the highest score value among the surrounding people can be estimated as a person similar to the person the user likes.

Further, when detecting a surrounding person within a predetermined range such as within a radius of 10 m, in addition to performing detection processing of a person within a certain distance using captured image data, for example, the user's terminal device 10 and its surroundings Collate the position data (for example, the position data by GPS (Global Positioning System)) acquired by each device owned by the person, or capture the radio wave by short-range wireless communication such as Bluetooth (registered trademark). You may.

If it is determined in the determination process of step S103 that a similar person has not been detected, the process returns to step S101, and the processes of steps S101 to S103 are repeated.

If it is determined in the determination process of step S103 that a similar person has been detected, the process proceeds to step S104. In step S104, the situation analysis unit 154 analyzes the direction in which a person similar to the person the user likes is facing, based on the determination result data of the determination model, the photographed image data, and the like.

In step S105, the situation analysis unit 154 determines whether or not a person who is similar to the person who likes the user is looking in the direction of the user based on the analysis result of the direction in which the similar person is facing.

If it is determined in the determination process of step S105 that a similar person is looking in the direction of the user, the process proceeds to step S106. In step S106, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to discharge a calming scent to the user.

Here, since the impression of the scent is different for each user, for example, the user is made to evaluate the impression of the scent from the fragrance set prepared in advance, and the library of various scents of each user and the impression of the scent. You just have to build and keep it.

This allows the user to set what kind of emotion he wants for the result of smelling. This library may be held by the terminal device 10 or may be managed by the server 20 and provided to the terminal device 10 as needed.

For example, in addition to the above-mentioned "calm", the impressions of the fragrance to be evaluated include "excitement", "blessing", "encouragement", "awakening", "passionate", and "refusal". Various adjective expressions such as "clean" can be used, and various scents of the fragrance set are assigned to each adjective expression and stored in the library. Further, as the evaluation of the impression of the scent, an evaluation method such as a three-stage or five-level evaluation or a visual evaluation scale (VAS: Visual Analog Scale) can be used.

In this way, when a person who is similar to the person you like is looking at you, a calming scent is emitted, so the user can calm down by the scent and take the next action. it can.

On the other hand, if it is determined in the determination process of step S105 that a similar person is not looking in the direction of the user, the process proceeds to step S107. In step S107, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to discharge the scent that excites the user.

In this way, when a person who is similar to the person you like is not looking at you, an exciting scent is emitted, and the user is excited by the scent and gains momentum. Can take action.

That is, the control unit 100 controls the discharge of the fragrance based on the behavior information regarding the behavior of the target (a person similar to the person who likes the user) with respect to the user obtained from the sensor data. Further, the control unit 100 changes the type of fragrance depending on whether or not the target is looking in the direction of the user.

When the process of step S106 or S107 is completed, the process proceeds to step S108 of FIG.

In step S108, the situation analysis unit 154 determines whether or not the distance to a similar person has approached within 3 m based on the determination result data of the determination model, the captured image data, and the like.

In the determination process of step S108, the process proceeds to step S109 after waiting for the distance to a similar person to approach within 3 m. In step S109, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to enhance the scent to be discharged.

FIG. 8 shows the positional relationship between a user who wears the terminal device 10 as a spectacle-type device (hereinafter, also referred to as user U1) and a person who is similar to the person who likes the user (hereinafter, also referred to as target T1). An example is shown.

In FIG. 8, the target T1 has entered the circular region A, which is an region within a radius of 3 m centered on the position of the user U1.

At this time, when the target T1 is looking at the user U1, the amount of the calming scent that has been discharged increases, and the scent becomes stronger. On the other hand, when the target T1 does not look at the user U1, the discharge amount of the excited scent that has been discharged increases, and the scent becomes stronger.

In this way, as the target T1 approaches the user U1, the discharge amount of the discharged scent is increased, so that the user U1 can be supported with a more emphasized scent.

That is, the control unit 100 controls the discharge of the fragrance based on the distance information regarding the distance between the user and the target obtained from the sensor data. Further, in the control unit 100, when the value indicated by the distance information is less than a predetermined threshold value, the discharge amount of the fragrance is increased.

Returning to the description of FIG. 7, when the process of step S109 is completed, the process proceeds to step S110.

In step S110, the emotion data acquisition unit 153 acquires emotion data of a person similar to the person the user likes.

The emotion data is data related to the emotions of the target T1 (FIG. 8) for the user U1 (FIG. 8). For example, emotional data includes sensor data detected by a wearable terminal worn by target T1 (for example, data related to pulse, brain wave, sweating, body temperature, iris, voice pitch, breathing, etc.) and user U1. It includes data such as sensor data (for example, captured image data obtained by photographing the target T1) detected by the terminal device 10 attached to the device.

In step S111, the situation analysis unit 154 analyzes the emotions of the similar person by estimating the emotions of a person similar to the person the user likes based on the acquired emotion data.

Note that the emotion analysis process of a person who is similar to the person who likes the user may be executed by the server 20 on the cloud.

That is, the wearable terminal worn by the target T1 (FIG. 8) transmits emotion data including the sensor data detected by itself to the server 20 via the network 50. Further, the terminal device 10 worn by the user U1 (FIG. 8) transmits emotion data including the sensor data detected by the user U1 (FIG. 8) to the server 20 via the network 50.

The server 20 analyzes the emotion of the target T1 by estimating the emotion of the target T1 based on the emotion data transmitted from the wearable terminal and the terminal device 10. The server 20 transmits the analysis result data to the terminal device 10 via the network 50. As a result, the terminal device 10 can acquire the data of the emotion analysis result of the target T1 transmitted from the server 20.

In step S112, the situation analysis unit 154 determines whether or not the reaction of the similar person is a good reaction based on the data of the analysis result of the emotion of the person similar to the person the user likes.

If it is determined in the determination process of step S112 that the reaction of a similar person is a good reaction (positive emotion), the process proceeds to step S113. In step S113, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to discharge the scent of blessing.

In this way, when a person who is similar to the person you like approaches us, if the person who is similar to you is responsive, the scent that congratulates the user is emitted, so that the user can use it. , The scent can make you happy.

On the other hand, if it is determined in the determination process of step S112 that the reaction of a similar person is not a good reaction (negative emotion), the process proceeds to step S114. In step S114, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to discharge the scent of encouragement.

In this way, if a person who is similar to the person you like approaches you, but the reaction of the similar person is not good, the scent of encouragement will be emitted, so the user will The scent can minimize depression.

That is, the control unit 100 controls the discharge of the fragrance based on the emotional data regarding the emotions of the surrounding people who are the target. In addition, the control unit 100 changes the type of fragrance according to the compatibility with the user regarding the surrounding person who is the target.

When the process of step S113 or S114 is completed, the process is completed.

The flow of the first example of the aroma support treatment has been explained above. In the first example of this fragrance support processing, the control unit 100 of the terminal device 10 such as a spectacle-type device uses a determination model generated by machine learning using personal data for each user, and estimates from the input sensor data. The discharge of fragrance to assist the user with respect to the targeted target is controlled.

As a result, when the user around the user who wears the terminal device 10 such as a spectacle-type device searches for a person who best suits his / her taste, the scent assists the user's feelings. It will be easier to approach the person who suits your taste.

(Flow of learning process)
FIG. 9 is a flowchart illustrating a first example of learning processing executed by the control unit 200 of the server 20.

This learning process is executed prior to the above-mentioned fragrance support process (FIGS. 6 and 7), and the learned determination model generated here is provided to the control unit 100 of the terminal device 10.

In step S201, the learning data acquisition unit 251 acquires personal data such as image data of a person the user likes.

For example, the image data of a person that the user likes can be selected from stock photos, libraries synthesized using artificial intelligence (AI), and the like. In addition, the user himself / herself may operate the device to add an image of his / her favorite person (for example, a celebrity) (or an image of a person he / she dislikes) to the library.

In addition, personal data can include general information about individual users, such as biological data, social data, life logs, and schedules.

In step S202, the learning DB 252 accumulates personal data such as acquired image data as learning data.

In step S203, the learning unit 253 performs learning processing using the learning data accumulated in the learning DB 252, and generates a determination model.

Machine learning methods used in this learning process include, for example, neural networks (NN: neural networks), deep learning, support vector machines (SVMs), and self-organizing maps (SOM:). Self-organizing maps) or k-means clustering can be used.

For example, when image data of a person that the user likes is used as the learning data, the learning unit 253 performs pattern extraction by image recognition using the above-mentioned extraction determination algorithm such as deep learning as the learning process.

In step S204, the providing unit 254 provides the generated learned determination model to the control unit 100 of the terminal device 10.

When the process of step S204 is completed, the process is completed.

The flow of the first example of the learning process has been explained above. In the first example of this learning process, a determination model required for the control unit 100 to execute the fragrance support process (FIGS. 6 and 7) is generated and provided to the terminal device 10.

(Flow of scent customization process)
FIG. 10 is a flowchart illustrating an example of the scent customization process executed by the control unit 200 of the server 20.

In step S231, the learning data acquisition unit 251 acquires emotional data transmitted from the wearable terminal and the terminal device 10. This emotion data is stored in the learning DB 252 as learning data.

In step S232, the learning unit 253 performs a learning process using the emotion data accumulated in the learning DB 252, and customizes the scent to be emitted when the user next meets a favorite person.

For example, in this learning process, as learning data accumulated in the learning DB 252, learning is performed including emotion data as well as data related to a library of various scents and impressions of each user. Then, for example, when emotion data regarding emotions (positive emotions or negative emotions) for the user U1 (FIG. 8) by the target T1 (FIG. 8) is input to this trained determination model, information on the customized fragrance is output. Will be done.

In step S233, the providing unit 254 provides the information regarding the customized scent to the control unit 100 of the terminal device 10. As a result, for example, in the terminal device 10, the scent is discharged according to the direction in which a person similar to the user likes the scent based on the customized scent information (discharged by the processing of S106 and S107 in FIG. 6). The scent to be produced) can be changed to a more appropriate scent.

That is, the control unit 100 of the terminal device 10 feeds back the emotion data and controls the discharge of the fragrance customized according to the fed-back emotion data.

When the process of step S233 is completed, the process is completed.

The flow of an example of scent customization processing has been explained above. In this scent customization process, the scent discharged by the terminal device 10 is changed according to the reaction (positive emotion or negative emotion) of the other party up to the previous time, so that the user's feelings can be supported with a better scent. Can be done.

<2. Second Embodiment>

(Flow of fragrance support processing)
Next, a second example of the fragrance support process executed by the control unit 100 of the terminal device 10 will be described with reference to the flowchart of FIG.

In steps S131 to S135, as in steps S101 to S105 of FIG. 6, when the determination model is applied to the captured image data and a person similar to the person who likes the user is detected from the people around the user. In addition, it is determined whether or not the similar person is looking in the direction of the user.

If it is determined in the determination process of step S135 that a similar person is looking in the direction of the user, the process proceeds to step S136. In step S136, the fragrance discharge unit 123 is controlled by the fragrance discharge control unit 155 as in the process of step S106, and the fragrance that calms the user is discharged.

On the other hand, if it is determined in the determination process of step S135 that a similar person does not look in the direction of the user, the process proceeds to step S137.

In step S137, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to discharge the scent that excites the user. In addition, at the same time as emitting an exciting scent, the appearance of the user is changed to clothes, hairstyle, makeup, eye size and color according to the preference of the target person (a person similar to the person who likes the user). To be done.

Specifically, assuming that the target party also wears the terminal device 10 as a spectacle-type device like the user, the target partner is the spectacle-type device worn by the target partner, and the AR technology is used. Information such as clothes and hairstyle may be drawn so that the appearance of the user viewed through the transparent display can be changed by using the above.

Alternatively, for example, contact lenses can be used to change the color of the user's eyes, or underwear that can change the shape of a part of the user's body can be used to emphasize the shape of a part of the body. You may change the appearance of the user in the real space.

Information about the preference of the target person can be estimated using emotional data transmitted from the wearable terminal worn by the person, or information about the person published on the Internet (for example, social media). Information) can be used for estimation. Alternatively, the server 20 may manage information on the preference of the target partner in the database, or may include information on the preference of the target partner in the learning data when performing the learning process.

That is, the control unit 100 of the terminal device 10 worn by the target partner changes the appearance of the user when viewed from the target so that the target pays attention when the target does not look in the direction of the user. doing.

When the processing of steps S136 or S137 is completed, the subsequent processing is executed, but since it is the same as the processing of steps S108 to S114 of FIG. 7, the description thereof will be omitted.

The flow of the second example of the aroma support treatment has been explained above. In the second example of this fragrance support process, when the user searches for a person who best suits his / her taste from the people around the user who wears the terminal device 10 such as a spectacle-type device, the user uses the scent. It is possible to support the feelings of the user and change the user into a person who is preferable to the other party.

<3. Third Embodiment>

(Flow of fragrance support processing)
Next, a third example of the fragrance support process executed by the control unit 100 of the terminal device 10 will be described with reference to the flowchart of FIG.

When executing this fragrance support process, the terminal device 10 worn by the user is provided with a determination model learned from the server 20 using personal data such as image data of a person who is not good at the user, and is provided with a control unit. It is available by 100.

In step S161, the sensor data acquisition unit 151 acquires captured image data captured in real time by the camera unit 112.

In step S162, the determination model application unit 152 applies the learned determination model to the acquired captured image data.

In step S163, the situation analysis unit 154 detected a person who is not good at the user from the surrounding people within a radius of 10 m, centered on the user, based on the judgment result data of the judgment model, the photographed image data, and the like. Determine if.

If it is determined in the determination process of step S163 that a person who is not good at it has not been detected, the process returns to step S161, and the processes of steps S161 to S163 are repeated.

If it is determined in the determination process of step S163 that a person who is not good at it is detected, the process proceeds to step S164. In step S164, the situation analysis unit 154 analyzes the direction in which the person who is not good at the user is facing, based on the determination result data of the determination model and the captured image data.

In step S165, the situation analysis unit 154 determines whether or not the person who is not good at the user is looking in the direction of the user based on the analysis result of the direction in which the person who is not good at it is facing.

If it is determined in the determination process of step S165 that a person who is not good at it is looking in the direction of the user, the process proceeds to step S166. In step S166, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to discharge a calming scent to the user.

In this way, when a person who is not good at himself / herself is looking at this, a calming scent is emitted, so that the user can calm down by the scent and take the next action.

On the other hand, if it is determined in the determination process of step S165 that a person who is not good at it is not looking in the direction of the user, the process proceeds to step S167. In step S167, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to discharge the awakening scent that encourages quick action.

In this way, when a person who is not good at himself is not looking at this, the scent of awakening that encourages quick action is emitted, so that the user moves quickly by the scent and immediately the person who is not good at himself. You can move to a place away from. For example, as the scent of awakening, the scent of mint or the like can be discharged based on the information stored in the library.

When the process of steps S166 or S167 is completed, the process proceeds to step S168.

In step S168, the situation analysis unit 154 determines whether or not the distance to the person who is not good is within 3 m based on the determination result data of the determination model, the captured image data, and the like.

In the determination process of step S168, the process proceeds to step S169 after waiting for the distance to the person who is not good at approaching within 3 m. In step S169, the fragrance discharge control unit 155 controls the fragrance discharge unit 123 to enhance the scent to be discharged.

In this way, the closer a person who is not good at the user gets to the user, the more the amount of the scent that is discharged can be increased, and the user can be supported with a more emphasized scent.

When the process of step S169 is completed, the process is completed.

The flow of the third example of the aroma support treatment has been explained above. In the third example of this fragrance support process, when searching for a person who is not good at the user from the people around the user who wears the terminal device 10 such as a spectacle-type device, the scent supports the user's feelings. At the same time, it is possible to avoid encountering the person who is not good at it.

(Flow of learning process)
FIG. 13 is a flowchart illustrating a second example of the learning process executed by the control unit 200 of the server 20.

This learning process is executed prior to the above-mentioned fragrance support process (FIG. 12), and the learned determination model generated here is provided to the control unit 100 of the terminal device 10.

In step S261, the learning data acquisition unit 251 acquires personal data such as image data of a person who is not good at the user.

In step S262, the learning unit 253 performs learning using personal data such as acquired image data, and generates a determination model.

In step S263, the providing unit 254 provides the generated learned determination model to the control unit 100 of the terminal device 10.

When the process of step S263 is completed, the process is completed.

The flow of the second example of the learning process has been explained above. In the second example of this learning process, a determination model required for the control unit 100 to execute the fragrance support process (FIG. 12) is generated and provided to the terminal device 10.

<4. Fourth Embodiment>

(Server configuration)
FIG. 14 shows another example of the functional configuration of the control unit 200 included in the server 20.

In FIG. 14, the server 20 has a target data acquisition unit 261, a matching DB 262, a matching processing unit 263, and a matching result providing unit 264.

The target data acquisition unit 261 controls the communication unit 208 to acquire the target data transmitted from the terminal device 10 and supplies it to the matching processing unit 263.

This target data includes data about a person who is similar to a person who likes a user.

The matching DB 262 stores the data required for the matching process. This necessary data includes, for example, data for analyzing compatibility for each user.

The matching processing unit 263 refers to the data stored in the matching DB 262 and performs matching processing using the target data supplied from the target data acquisition unit. The matching processing unit 263 supplies the matching processing result data to the matching result providing unit 264.

The matching result providing unit 264 controls the communication unit 208 to provide the matching processing result data supplied from the matching processing unit 263 to the terminal device 10.

(Flow of matching service processing)
Next, an example of matching service processing executed between the plurality of terminal devices 10 and the server 20 will be described with reference to the flowcharts of FIGS. 15 and 16.

In this matching service process, a process for matching a favorite person among users wearing the terminal device 10 is performed.

15 and 16 show the processes executed by the terminal device 10-1 worn by the user and the terminal devices 10-2 and 10-3 worn by the user's favorite persons A and B, respectively. Has been done.

Further, when executing the matching service process, each of the terminal devices 10-1 to 10-3 is determined to have been learned by using personal data such as image data of a person who likes the user who uses each terminal device 10. A model is provided and made available by the control unit 100 of each terminal device 10.

In the terminal device 10-1 worn by the user, the processes of steps S301 to S304 of FIG. 15 are executed.

That is, in the terminal device 10-1, by applying the learned determination model to the captured image data captured in real time (S301, S302), the people around the user are similar to the person who likes the user. It is determined whether or not the person has been detected (S303). Then, when the terminal device 10-1 detects a person similar to the person the user likes, data about the similar person is transmitted to the server 20 as target data (S304).

In the terminal device 10-2 worn by the user's favorite person A, the processes of steps S311 to S314 of FIG. 15 are executed.

That is, in the terminal device 10-2, by applying the trained determination model to the captured image data captured in real time (S311, S312), the person A around the favorite person A can be referred to as the favorite person A. It is determined whether or not a person similar to the person who likes is detected (S313). Then, when the favorite person A detects a person similar to the favorite person in the terminal device 10-2, the data about the similar person is transmitted to the server 20 as the target data (S314).

In the terminal device 10-3 worn by the user's favorite person B, the processes of steps S321 to S324 of FIG. 15 are executed.

That is, in the terminal device 10-3, by applying the trained determination model to the captured image data captured in real time (S321, S322), the person B around the favorite person B can be referred to. It is determined whether or not a person similar to the person who likes is detected (S323). Then, when the favorite person B detects a person similar to the favorite person in the terminal device 10-3, the data about the similar person is transmitted to the server 20 as the target data (S324).

The server 20 that receives the target data transmitted from the terminal devices 10-1 to 10-3 executes the processes of steps S331 to S333 of FIG.

In step S331, the target data acquisition unit 261 acquires the target data transmitted from the terminal devices 10-1 to 10-3.

In step S332, the matching processing unit 263 refers to the data stored in the matching DB 262 and performs a matching process using the acquired target data.

In this matching process, for example, the ranking of superiority or inferiority of each user is calculated based on information such as the distance between users at that time and the compatibility of each user, and the person whose calculated superiority or inferiority ranking is the most superior. , Determined as a matching partner. As the compatibility here, for example, the degree of mutual preference of the images, the degree of agreement of tastes, the degree of agreement (or disagreement) of DNA information, and the like can be included.

That is, in the matching unit 200, the user with the highest degree of matching can be determined as the matching partner based on the compatibility and the distance between the matching users at that time.

In step S333, the matching result providing unit 264 transmits the matching result data obtained in the matching process to the terminal device 10 according to the matching result. For example, when the user and the favorite person A are matched by the matching process, the matching result data is transmitted to the terminal device 10-1 and the terminal device 10-2 used by the matched person, respectively. ..

The processing of steps S305 to S308 of FIG. 16 is executed in each of the terminal device 10-1 and the terminal device 10-2 that receive the matching result data transmitted from the server 20.

That is, in the terminal device 10-1 and the terminal device 10-2, the fragrance discharge unit 123 is controlled by each fragrance discharge control unit 155, so that the scent of blessing is discharged (S305). The scent of this blessing is controlled by each fragrance discharge control unit 155 so that the scent becomes stronger as the distance between the user and the favorite person A becomes closer (S305).

Further, in the terminal device 10-1 and the terminal device 10-2, each situation analysis unit 154 has a feeling of strangeness in either the user or the favorite person A based on the data such as emotion data. Whether or not it is determined (S306).

Note that the process of determining whether or not there is a sense of discomfort may be executed by the server 20 by the server 20 acquiring data such as emotional data. In this case, the terminal device 10-1 and the terminal device 10-2 receive the data of the determination result regarding the discomfort, which is transmitted from the server 20.

If it is determined in the determination process of step S306 that one of the two persons does not feel uncomfortable, that is, it is determined that neither of the two persons feels uncomfortable, the process proceeds to step S307. Then, in the terminal device 10-1 and the terminal device 10-2, when the distance between the two people is within a radius of 1 m, each fragrance discharge control unit 155 controls each fragrance discharge unit 123. A passionate scent is discharged (S307).

Also here, when detecting the other person within a predetermined range such as within a radius of 1 m, the detection process of the person within a certain distance using the captured image data is performed, and for example, the terminal device 10- The position data (for example, the position data by GPS) acquired by each of 1 and the terminal device 10-2 may be collated, or radio waves may be captured by short-range wireless communication such as Bluetooth (registered trademark).

On the other hand, if it is determined in the determination process of step S306 that one of the two persons feels uncomfortable, the process proceeds to step S308. Then, in the terminal device 10-1 and the terminal device 10-2, the fragrance discharge unit 123 is controlled by each fragrance discharge control unit 155, so that the refused scent is discharged (S308).

In this way, when two people to be matched are satisfied with the matching result, the feelings of the two people can be positively supported by the scent of blessing and the scent of passion. On the other hand, even if at least one of the two matching targets has a feeling of strangeness in the matching result, the scent of refusal can support the feelings of at least the person who has a feeling of strangeness.

That is, the control unit 200 acquires target data related to the target transmitted from the terminal device 10 of each user, and matches according to the compatibility of each user based on the target data for each user.

Further, the control unit 100 controls the discharge of the fragrance based on the distance information regarding the distance between the matched users obtained from the sensor data of the terminal device 10 of the matched users. Further, the control unit 100 increases the discharge amount of a predetermined type of fragrance as the distance between the matched users becomes closer. Further, the control unit 100 discharges a predetermined type of fragrance when the value indicated by the distance information is less than a predetermined threshold value.

Further, the control unit 100 discharges a predetermined type of fragrance when at least one of the matched users feels uncomfortable based on the emotion data regarding the emotions of the matched user toward the other party.

When the process of step S307 or S308 is completed, the process is completed.

The flow of matching service processing will be explained above. In this matching service process, when matching between users using the target data transmitted from the terminal device 10 worn by each user, the feelings of the two matched users are supported by the scent. be able to. And, with the support of this scent, it is expected that the probability of successful matching will be improved and, by extension, the problem of declining birthrate will be solved.

<5. Modification example>

(Other configurations of fragrance support system)
FIG. 17 shows another example of the configuration of one embodiment of the fragrance support system to which the present technology is applied.

In FIG. 17, the fragrance support system 1 is provided with an information device 30 and a fragrance discharge device 40 in addition to the terminal device 10 and the server 20. The terminal device 10, the information device 30, and the fragrance discharging device 40 are possessed by one user.

The information device 30 is configured as, for example, a smartphone, a tablet terminal, a portable music player, a game machine, or the like. The information device 30 has a communication function, can be connected to the network 50, and can communicate with the terminal device 10 by short-range wireless communication such as Bluetooth (registered trademark).

The fragrance discharge device 40 has a stick-like shape such as a round bar or a square bar, and has the same function as the fragrance discharge unit 123 (FIG. 2). Therefore, in the configuration of the terminal device 10 shown in FIG. 2, the fragrance discharge unit 123 (FIG. 2) is removed.

That is, the fragrance discharge device 40 has a fragrance holding structure filled with a liquid fragrance, and air is flowed through a holding space provided in the fragrance holding structure to be held by the fragrance holding body arranged in the holding space. It is released by vaporizing the liquid fragrance.

The fragrance discharge device 40 also has a communication function and can communicate with the terminal device 10 by short-range wireless communication such as Bluetooth (registered trademark).

In the example of the configuration of FIG. 17, the terminal device 10 exchanges data with the server 20 on the network 50 via the information device 30 to perform the above-mentioned fragrance support process (FIGS. 6, 7, etc.). Execute. Further, when the terminal device 10 discharges various scents when executing the fragrance support process (S106, S107 in FIG. 6, S113, S114 in FIG. 7, etc.), the fragrance discharge control unit 155 (FIG. 3) determines. By controlling the fragrance discharge device 40, the scent is discharged.

As described above, in the fragrance support system 1, the device that executes the fragrance support process and the device that discharges the fragrance do not necessarily have to be the same device. In addition, in the example of the configuration of FIG. 17, the configuration in which the information device 30 such as a smartphone is provided is shown, but the terminal device 10 directly communicates with the server 20 on the network 50 without providing the information device 30. Of course, it is also possible to exchange.

In the above description, the control unit 100 of FIG. 3 is included in the terminal device 10, and the control unit 200 of FIG. 5 is included in the server 20, but all or one of the functions of the control unit 100 of FIG. The unit may be included in the server 20, or all or part of the functions of the control unit 200 of FIG. 5 may be included in the terminal device 10.

For example, the determination model application unit 152 of FIG. 3 and the emotion data acquisition unit 153 may be provided in the server 20 (control unit 200). In this case, the terminal device 10 transmits the data to which the determination model is applied to the server 20 via the network 50, so that the terminal device 10 receives the data of the determination result of the learned determination model from the server 20. ..

Further, the scent customization process shown in FIG. 10 may be executed by the control unit 100 of the terminal device 10 worn by each user. That is, each process of the above-mentioned flowchart is executed by the control unit 100 of the terminal device 10 or the control unit 200 of the server 20, or is executed by the cooperation of the control unit 100 and the control unit 200.

<6. Computer configuration>

The series of processes of the terminal device 10 or the server 20 described above can be executed by hardware or software. When a series of processes are executed by software, the programs constituting the software are installed on the computer of each device.

In the computer of each device, the CPU loads the program recorded in the ROM or the storage unit into the RAM and executes it, so that the above-mentioned series of processes is performed.

A program executed by a computer (CPU) can be recorded and provided on a removable recording medium such as a package medium. The program can also be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcasting.

On a computer, the program can be installed in the storage unit by attaching a removable recording medium to the drive. Further, the program can be received by the communication unit and installed in the storage unit via a wired or wireless transmission medium. In addition, the program can be installed in advance in the ROM or storage unit.

Here, in the present specification, the processing performed by the computer according to the program does not necessarily have to be performed in chronological order in the order described as the flowchart. That is, the processing performed by the computer according to the program also includes processing executed in parallel or individually (for example, parallel processing or processing by an object).

Further, the program may be processed by one computer (processor) or may be distributed processed by a plurality of computers. In addition, the program may be transferred to a distant computer for execution.

Further, in the present specification, the system means a set of a plurality of components (devices, modules (parts), etc.), and it does not matter whether all the components are in the same housing. Therefore, a plurality of devices housed in separate housings and connected via a network, and a device in which a plurality of modules are housed in one housing are both systems. ..

The embodiment of the present technology is not limited to the above-described embodiment, and various changes can be made without departing from the gist of the present technology. For example, the present technology can have a cloud computing configuration in which one function is shared and jointly processed by a plurality of devices via a network.

In addition, each step described in the above flowchart can be executed by one device or shared by a plurality of devices. Further, when a plurality of processes are included in one step, the plurality of processes included in the one step can be executed by one device or shared by a plurality of devices.

Further, the effects described in the present specification are merely examples and are not limited, and other effects may be obtained.

Note that this technology can have the following configuration.

(1)
An information processing device including a control unit that controls the discharge of a fragrance to support the user with respect to a target estimated from input sensor data using a judgment model generated by machine learning using personal data for each user.
(2)
The personal data includes data on the compatibility of the user with others.
The sensor data includes captured image data around the user.
The control unit uses the determination model to control the discharge of the fragrance to the user who acts by targeting the surrounding people according to the compatibility, which is estimated from the input captured image data. The information processing device according to (1) above.
(3)
The information processing device according to (2), wherein the control unit controls the discharge of the fragrance based on the behavior information regarding the behavior of the target with respect to the user obtained from the sensor data.
(4)
The information processing device according to (3), wherein the control unit changes the type of the fragrance depending on whether or not the target is looking in the direction of the user.
(5)
The information processing according to (4) above, wherein the control unit changes the appearance of the user when viewed from the target so that the target is noticed by the target when the target is not looking in the direction of the user. apparatus.
(6)
The control unit controls the discharge of the fragrance based on the distance information regarding the distance between the user and the target obtained from the sensor data according to any one of (2) to (5). Information processing device.
(7)
The information processing device according to (6) above, wherein the control unit increases the discharge amount of the fragrance when the value indicated by the distance information is less than a predetermined threshold value.
(8)
The information processing device according to any one of (2) to (7), wherein the control unit controls the discharge of the fragrance based on emotional data regarding emotions toward the user by a person around the target.
(9)
The information processing device according to (8), wherein the control unit changes the type of the fragrance according to the compatibility of the target surrounding person with the user.
(10)
The control unit
Feed back the emotional data
The information processing device according to (8) or (9), which controls the discharge of the fragrance customized according to the fed-back emotion data.
(11)
The information processing device according to any one of (1) to (10), wherein the personal data includes a desired condition of the user when estimating the target.
(12)
The control unit
Acquire the target data related to the target transmitted from each user's terminal, and
The information processing device according to (2) above, which performs matching according to the compatibility of each user based on the target data for each user.
(13)
The information processing device according to (12), wherein the control unit controls the discharge of the fragrance based on the distance information regarding the distance between the matched users obtained from the sensor data of the terminal of the matched user. ..
(14)
The information processing device according to (13), wherein the control unit increases the discharge amount of a predetermined type of fragrance as the distance between the matched users becomes closer.
(15)
The information processing device according to (13) or (14), wherein the control unit discharges a predetermined type of fragrance when the value indicated by the distance information is less than a predetermined threshold value.
(16)
The control unit discharges a predetermined type of fragrance when at least one of the matched users feels uncomfortable based on emotional data regarding the emotions of the matched user with respect to the other party (12) to (15). The information processing device according to any one.
(17)
At the time of matching, the control unit determines the user with the highest degree of matching as the matching partner based on the compatibility and the distance between the matching users at that time. Information processing device described in Crab.
(18)
The information processing device according to any one of (1) to (11) above, which is configured as a wearable terminal having a device for detecting the sensor data.
(19)
The information processing device according to any one of (12) to (17) above, which is configured as a wearable terminal having a device for detecting the sensor data and a server connected via a network.
(20)
Information processing device
An information processing method that uses a judgment model generated by machine learning using personal data for each user to control the discharge of fragrance to support the user with respect to a target estimated from input sensor data.

1 Fragrance support system, 10, 10-1 to 10-N terminal device, 20 servers, 50 networks, 100 control units, 101 CPU, 102 ROM, 103 RAM, 105 input unit, 106 output unit, 107 storage unit, 108 communication Unit, 109 short-range wireless communication unit, 111 operation unit, 112 camera unit, 113 sensor unit, 121 display unit, 122 sound output unit, 123 fragrance discharge unit, 151 sensor data acquisition unit, 152 judgment model application unit, 153 emotion data Acquisition unit, 154 situation analysis unit, 155 fragrance discharge control unit, 200 control unit, 201 CPU, 202 ROM, 203 RAM, 205 input unit, 206 output unit, 207 storage unit, 208 communication unit, 209 drive, 251 learning data acquisition Department, 252 learning DB, 253 learning department, 254 providing department, 261 target data acquisition department, 262 matching DB, 263 matching processing department, 264 matching result providing department

Claims

An information processing device including a control unit that controls the discharge of a fragrance to support the user with respect to a target estimated from input sensor data using a judgment model generated by machine learning using personal data for each user.
The personal data includes data on the compatibility of the user with others.
The sensor data includes captured image data around the user.
Using the determination model, the control unit controls the discharge of the fragrance to the user who acts by targeting the surrounding people according to the compatibility, which is estimated from the input captured image data. The information processing device according to claim 1.
The information processing device according to claim 2, wherein the control unit controls the discharge of the fragrance based on the behavior information regarding the behavior of the target with respect to the user obtained from the sensor data.
The information processing device according to claim 3, wherein the control unit changes the type of the fragrance depending on whether or not the target is looking in the direction of the user.
The information processing apparatus according to claim 4, wherein the control unit changes the appearance of the user when viewed from the target so that the target is noticed by the target when the target is not looking in the direction of the user. ..
The information processing device according to claim 2, wherein the control unit controls the discharge of the fragrance based on the distance information regarding the distance between the user and the target obtained from the sensor data.
The information processing device according to claim 6, wherein the control unit increases the discharge amount of the fragrance when the value indicated by the distance information is less than a predetermined threshold value.
The information processing device according to claim 2, wherein the control unit controls the discharge of the fragrance based on emotional data regarding emotions toward the user by a person around the target.
The information processing device according to claim 8, wherein the control unit changes the type of the fragrance according to the compatibility of the target surrounding person with the user.
The control unit
Feed back the emotional data
The information processing device according to claim 8, which controls the discharge of the fragrance customized according to the fed-back emotion data.
The information processing device according to claim 1, wherein the personal data includes a desired condition of the user when estimating the target.
The control unit
Acquire the target data related to the target transmitted from each user's terminal, and
The information processing device according to claim 2, wherein matching is performed according to the compatibility of each user based on the target data for each user.
The information processing device according to claim 12, wherein the control unit controls the discharge of the fragrance based on the distance information regarding the distance between the matched users obtained from the sensor data of the terminal of the matched user.
The information processing device according to claim 13, wherein the control unit increases the discharge amount of a predetermined type of fragrance as the distance between the matched users becomes closer.
The information processing device according to claim 13, wherein the control unit discharges a predetermined type of fragrance when the value indicated by the distance information is less than a predetermined threshold value.
The information processing device according to claim 12, wherein the control unit discharges a predetermined type of fragrance when at least one of the matched users feels uncomfortable based on emotional data regarding the emotions of the matched user. ..
The information processing device according to claim 12, wherein the control unit determines the user with the highest degree of matching as the matching partner based on the compatibility and the distance between the matching users at that time.
The information processing device according to claim 1, which is configured as a wearable terminal having a device for detecting the sensor data.
The information processing device according to claim 12, wherein a wearable terminal having a device for detecting the sensor data and a server connected via a network are configured.
Information processing device
An information processing method that uses a judgment model generated by machine learning using personal data for each user to control the discharge of fragrance to support the user with respect to a target estimated from input sensor data.